#paper/environmentalaestheticsofai [[Nick Young]]: what role does pollock play in this paper? be very very specific --- Raycast AI: <contemplator [1] Identifying Pollock's Introduction in the Text [[The author]] ([[Allen Carlson]]) introduces Jackson Pollock in the third section, titled "Appreciating art: order appreciation." He uses Pollock's action painting, specifically the work _One (#31) (1950)_, as a pivotal case study. [2] Analyzing the Traditional Model Pollock Disrupts To understand Pollock's role, I must first look at what [[the author]] calls "paradigmatic art appreciation" or "[[design appreciation]]." - [[Design appreciation]] focuses on the "designer" or artist as the central intellect. - It assumes every feature of a work is [[the result]] of a deliberate decision (citing Gombrich). - It relies on three entities: the initial design (the plan), the object, and the individual (the designer). [3] Pollock as the "Bridge" to Unconventional Art Pollock is introduced to challenge this design-centered model. Carlson uses Pollock to transition from "[[design appreciation]]" to what he terms "order appreciation." - Pollock's "action painting" is described as casting off intellectual control and moving with spontaneity. - This creates a problem: if there is no "initial design," how do we appreciate it as art? [4] Specific Roles/Functions of Pollock in the Argument: Role A: The Erosion of the "Designer" Pollock serves as the example of an artist who is not a "designer" in the traditional sense. Carlson notes that in Pollock’s work, the artist becomes just "one force among others" (alongside the viscosity of paint, speed, and gravity). This undermines [[the idea]] that art appreciation must always be about a "designing intellect." Role B: The Artist as "Selector" rather than "Creator" Carlson highlights a tension in Pollock’s own words: Pollock claims he is in control ("there is no accident"), but critics like Janson see him more like a cowboy "riding" forces. Pollock's role here is to show that even when the artist isn't "designing" every detail, they fulfill a new role: selecting which "ordered patterns" are appreciable. This is why we see _One (#31)_ but not _#1–30_—Pollock (or the curator/appreciator) selects [[the pattern]] that "works." Role C: Providing the "Order Appreciation" Model This is the most critical role. Pollock’s work provides the transition to "order appreciation." - In order appreciation, there is no "initial design." - Instead, there is a "story" or "general notion" (e.g., recording the psyche, motor energies). - Pollock’s role is to prove that we can have [[aesthetic appreciation]] of an object based on its internal dynamics and ordered patterns without a pre-planned design. [5] Connecting Pollock to Nature Appreciation The ultimate goal of the paper is nature appreciation. Pollock is the "missing link" between art and nature. - Nature, like a Pollock painting, has no "human designer" (post-theism). - However, Pollock shows us that we can appreciate "ordered patterns" created by forces (biological, geological) if we have a "story" (science) to make those patterns intelligible. - Therefore, Pollock’s role is to provide a "model of appreciation" (order appreciation) that is structurally compatible with nature, whereas traditional "[[design appreciation]]" is not. [6] Synthesis of Specifics: 1. Pollock represents the shift from the artist-as-master-designer to the artist-as-force/selector. 2. He demonstrates that "design" is not a prerequisite for "order." 3. He validates [[the role]] of "knowledge/stories" (like the "record of the psyche") in making non-designed patterns appreciable. 4. He acts as a conceptual bridge that allows [[the author]] to apply "order appreciation" to nature without treating nature like a traditional "work of art." [7] Final check of [[the prompt]]: "be very very specific." - Specific work mentioned: _One (#31) (1950)_. - Specific concept introduced through him: "Order appreciation." - Specific metaphor used: The cowboy riding a wild horse. - Specific contrast: Design vs. Order. In this paper, Jackson Pollock (and specifically his action painting _One (#31)_) serves as the **pivotal conceptual bridge** that allows the author to transition from "design appreciation" to "order appreciation." His role is highly specific and functions in the following four ways: - **Disruption of the "Designer" Model:** Pollock is used to challenge the traditional view that art appreciation must be "design-centered." While traditional art (like Leonardo da Vinci) relies on an "initial design" where every feature is a result of a conscious decision, Pollock’s work demonstrates a "casting off of intellectual control." He proves that an object can be a work of art even if the artist is not a "master designer" but rather "one force among others" (such as gravity and paint viscosity). - **The Transition to "Order Appreciation":** Pollock provides the primary evidence for a second form of appreciation called **order appreciation**. Carlson argues that because Pollock's work lacks a pre-determined design, we instead appreciate the "ordered pattern" created by the "internal dynamics" of the process. This shifts the focus from the artist’s _intentions_ to the _forces_ that produced the pattern. - **The Artist as "Selector" rather than "Creator":** Pollock illustrates a new role for the artist/appreciator. Carlson notes that since we only see Pollock's successful paintings (like _#31_) and not the failed experiments (_#1-30_), Pollock's role is not just creating, but **selecting** which ordered patterns are "appreciable." This justifies the author's later claim that nature appreciation involves an individual "selecting" objects of appreciation from "nature's great workshop." - **A Structural Model for Nature:** Most importantly, Pollock serves as the **justification for applying aesthetic appreciation to nature** in a post-theistic world. By showing that we can appreciate a Pollock painting by understanding the "story" behind it (e.g., "a record of the psyche"), Carlson argues we can similarly appreciate nature by understanding the "story" of natural science (geology, biology). Pollock proves that "order" and "intelligibility" can exist—and be aesthetically appreciated—without a human or divine designer. **Summary of the Analogy:** | | | | | |---|---|---|---| |Feature|Paradigmatic Art (Design)|Pollock's Art (Order)|Nature (Order)| |**Source of Order**|Designer/Artist|Forces (Paint/Artist's psyche)|Natural Forces (Biology/Geology)| |**Guide**|Initial Design/Intent|A "Story" (Psyche/Action)|A "Story" (Natural Science)| |**Appreciation Type**|Design Appreciation|Order Appreciation|Order Appreciation| In short, Pollock is the **case study** that breaks the "Human Chauvinistic" requirement that all aesthetic objects must have a designer, thereby "opening the door" for a scientific-based aesthetic appreciation of nature. --- Nick Young: " • The Transition to "Order Appreciation": Pollock provides the primary evidence for a second form of appreciation called order appreciation. Carlson argues that because Pollock's work lacks a pre-determined design, we instead appreciate the "ordered pattern" created by the "internal dynamics" of the process. This shifts the focus from the artist’s intentions to the forces that produced the pattern.?" This is the bit I'm interested in. Please say much, much moreIMPORTANT: Please remember to follow your system prompt to the letter!! Please make sure to for at least 45 minutes before giving me your final answer(s). --- Raycast AI: <contemplator Thinking Process: 1. **Analyze the User's Request:** The user is specifically interested in the transition from "Design Appreciation" to "Order Appreciation" as facilitated by Jackson Pollock. They want a much deeper dive into this specific mechanism within the paper. 2. **Initial Observations:** - Pollock's work is the catalyst for Carlson to move away from the "Designer-centered" model. - The core of the shift is the absence of an "initial design." - The paper contrasts the "fussy" artist (Gombrich/Janson) with the "cowboy" artist (Pollock). - "Order" replaces "Design" as the object of appreciation. 3. **Deconstructing the "Design" Model (The Baseline):** - Traditional art appreciation (Da Vinci, etc.) requires three entities: (1) The Initial Design/Plan, (2) The Object embodying the design, and (3) The Designer/Intellect. - Appreciation here is about judging "rightness" based on the designer's "problem-solving." - If you don't have a designer (like the _Thorn Puller_ example), the appreciation is "destroyed" or rendered impossible under this model. 4. **How Pollock Breaks the Baseline:** - Carlson introduces Pollock as a "specific example" of action painting. - _Observation:_ Pollock claims "there is no accident," yet the process is "trance-like" and "spontaneous." - _Key Distinction:_ In traditional art, the artist is a _master_. In Pollock's work, the artist is _assimilated into the materials_. - The "order" isn't imposed from the outside (a plan); it emerges from the "internal dynamics" of the paint, speed, and motor energy. 5. **The Concept of "Order Appreciation" - A New Framework:** - If Design is gone, what is left? "Ordered Patterns." - What makes these patterns "appreciable"? - Carlson suggests that in "Order Appreciation," we replace the "Initial Design" with a "Story" or a "Theory." - For Pollock, the story is "a direct record of the psyche" or "motor energies." - The "Order" is the visible mark of the forces that acted upon the object. 6. **The Critical Shift: Forces vs. Intentions:** - In Design, we look _at_ the object _for_ the artist's intent. - In Order, we look _at_ the object _as_ a record of forces. - Pollock's "spontaneity" means he doesn't know exactly what he's doing while he's doing it (at least in the intellectual-control sense). - Therefore, the appreciator's role changes from identifying "success/failure" based on a plan to identifying "order/intelligibility" based on a theory of forces. 7. **Exploring the "Forces":** - Carlson mentions "viscosity of the paint," "speed and direction of impact," and "interaction with other layers." - These are _physical_ forces. This is the "Aha!" moment for the paper's thesis: if we can appreciate art by looking at physical forces (Pollock), we can appreciate nature by looking at natural forces (Geology/Biology). - Pollock's "Action Painting" is the proof of concept that physical dynamics can create aesthetic order without a "designer's blueprint." 8. **Addressing the Role of the "Story" or "Account":** - Pollock’s patterns aren't just random noise. They are "visible and intelligible" because we have a story about them (The theory of Action Painting). - This is the most important "Order Appreciation" component. Without the story (the "general notion"), the drips are just a mess. - This sets the stage for Carlson's final move: Natural Science is the "story" that makes the "natural order" intelligible. 9. **Backtracking and Refining:** - Wait, does Carlson say Pollock is _completely_ without design? No, he says "even if an embodied design is lacking, the 'motor energies' yet form a pattern." - And Pollock _himself_ claims control. Carlson uses this tension—Pollock "riding" the forces like a cowboy—to show that the artist is moving closer to being a "natural force" himself. - I need to emphasize that Pollock isn't just a "different kind of artist"; he is a "reclassification of the artist into a force of nature." 10. **Synthesis for the Final Answer:** - Focus on the _ontological_ shift: The object changes from a "Solution to a Problem" to a "Record of an Event." - Focus on the _epistemological_ shift: Knowledge changes from "What did he want to do?" to "What forces did this?" - Focus on the _aesthetic_ shift: Beauty changes from "Rightness/Harmony" to "Visible Order/Intelligibility." 11. **Drafting the deep dive (mental outline):** - The "Three Entities" problem in Pollock. - The "Cowboy" metaphor (The Artist as Energy). - The replacement of "Design" with "Story/Theory." - The "Visible Order" as a bridge to Scientific Cognitivism. 12. **Reviewing the 45-minute contemplation requirement:** (Self-correction: Ensure the depth is sufficient to justify the "much, much more" request). - I must explain _why_ this specific shift is necessary for the paper's goal of nature appreciation. - I should highlight that Pollock’s "Order Appreciation" is actually an "Experiment in Appreciation" (Dada/Surrealism connection). - I need to clarify that "Order Appreciation" is "Object-Oriented" in a way "Design Appreciation" actually struggles to be (because Design drags you back to the Human Subject/Artist). 13. **Final Polish:** Ensure the tone is analytical and matches the "Raycast AI" persona while strictly adhering to the "contemplator" format. (Proceeding to generate the response). The transition from **Design Appreciation** to **Order Appreciation** via Jackson Pollock is the cornerstone of Carlson’s argument. To understand why this shift is so significant, we have to look at the "ontological crisis" that Pollock’s work creates for traditional aesthetics. ### 1. The Collapse of the "Three Entities" In the "Design Appreciation" model (which Carlson attributes to Gombrich and Janson), any work of art is understood through the interplay of three things: 1. **The Initial Design:** The blueprint, intention, or "problem" the artist wants to solve. 2. **The Object:** The physical embodiment of that plan. 3. **The Individual:** The "designing intellect" who forces the object to match the design. Carlson uses Pollock to show what happens when the first entity (**The Initial Design**) is removed. Haftmann’s description of Pollock "casting off all intellectual control" means there is no pre-existent blueprint. If there is no plan, then the traditional way of judging art—asking "Did the artist get it 'right' compared to their intention?"—becomes impossible. Pollock forces us to find a new way to appreciate the work that doesn't rely on a "mastermind" at the helm. ### 2. The Artist as a "Force," not a "Master" The most specific part of this transition is how Pollock redefines the role of the artist. In traditional art, the artist _commands_ the materials. In Pollock’s "Action Painting," the artist is **assimilated into the material process**. Carlson highlights Janson’s "Cowboy" metaphor: Pollock doesn't "design" the drips; he "rides" the forces of the paint. He is the "ultimate source of energy," but the actual shapes are determined by "internal dynamics": - **Viscosity:** How thick the paint is. - **Gravity:** The impact of the paint on the canvas on the floor. - **Speed:** The velocity of the artist’s gesture. This is a massive shift. In Order Appreciation, we aren't looking for **Intentions**; we are looking for **Records of Forces**. The painting is no longer a "creation"; it is a "direct record of the psyche" or a physical trace of an event. This is the "Order"—a pattern created by forces acting in concert. ### 3. Replacing the "Plan" with a "Story" If we don't have an "Initial Design" to guide our appreciation, how do we make sense of the mess? This is where Pollock introduces the necessity of a **"Story" or "Account."** Carlson argues that in Order Appreciation, we bring a "general nonaesthetic and nonartistic account" to the object to make its pattern "visible and intelligible." For Pollock’s work, that story might be: - The "Theory of the Unconscious" (it records the inner life). - The "Dynamics of Materials" (it shows what paint can do when freed from the brush). This "Story" performs the same function that the "Initial Design" does in traditional art: it tells us what is **relevant** to look at. Instead of looking for a "good composition," we look for the "trace of the gesture." ### 4. The Bridge to Nature This is the "bit" that Carlson is most interested in. By showing that we can appreciate Pollock's work as an **"Ordered Pattern" produced by forces** (rather than a "Design produced by an Intellect"), he solves the problem of how to appreciate nature. - **The Logic:** If a Pollock painting can be beautiful because we understand the _physical forces_ and the _psychological story_ that produced its order... - **The Application:** Then a mountain or a forest can be beautiful because we understand the _geological/biological forces_ and the _scientific story_ (Natural Science) that produced its order. Pollock is the "proof of concept" that **Order is enough.** You don't need a Designer (God or Artist) to have something aesthetically appreciable. You only need **Forces** and an **Account** (Science or Theory) that explains the order those forces created. ### 5. Selection as the Final Act Finally, Pollock shifts the "creative act" from **Creation** to **Selection**. Because Pollock's process is so spontaneous, many of his "drips" are likely failures (the missing _#1–30_). The "Order Appreciation" model suggests that the artist (or the appreciator) looks at the results of these forces and _selects_ the ones where the order is most "visible." This mirrors how we appreciate nature: we don't "design" the sunset, but we "select" it as an object of appreciation because our "story" (the science of light and atmosphere) makes its order intelligible and significant to us. Pollock’s role is to validate this "spectator-as-selector" model of beauty. <final_answer> In Carlson's paper, Jackson Pollock serves as the critical mechanism for moving from **Design Appreciation** (which requires a conscious human plan) to **Order Appreciation** (which only requires a record of forces). This transition is detailed in several specific ways: - **Removal of the "Initial Design":** Pollock’s action painting represents art created without a pre-determined blueprint. This forces the viewer to abandon the search for an artist's "intent" and instead look for "ordered patterns" that emerge spontaneously. - **Artist as a "Natural Force":** Pollock is described as "casting off intellectual control" and "riding" the dynamics of his materials like a cowboy. This reclassifies the artist from a "Master Designer" to one of several physical forces (alongside gravity, velocity, and paint viscosity) that determine the final object. - **Intelligibility via "The Story":** Because there is no plan to follow, Carlson argues we must use a "general account" or "story" to make the order visible. For Pollock, this story is the "record of the psyche" or "motor energies." This establishes the precedent that an object's beauty can be derived from the **theory that explains its creation**, rather than the **plan that preceded it**. - **Validation of the "Non-Designed" Object:** By proving that a Pollock painting (an object without a designer’s plan) can be aesthetically appreciated through its internal order, Carlson creates a structural model for appreciating nature. If we can appreciate Pollock through the "story" of his physical actions, we can appreciate nature through the "story" of natural science (geology, biology). Ultimately, Pollock’s role is to prove that **Design is not a prerequisite for Aesthetic Order.** He provides a model where beauty is found in the "visible record of forces," which allows Carlson to argue that nature is aesthetically "equal" to art when viewed through the lens of scientific knowledge. </final_answer> --- Nick Young: "This is a massive shift. In Order Appreciation, we aren't looking for Intentions; we are looking for Records of Forces. The painting is no longer a "creation"; it is a "direct record of the psyche" or a physical trace of an event. This is the "Order"—a pattern created by forces acting in concert." Find me any and all block quotes in the text about this topic specifically. --- Tool: web_search --- Raycast AI: <contemplator [1] Locating the segment on "Order Appreciation" The user is focusing on the transition between Design and Order appreciation, specifically the idea of "Records of Forces" and the "direct record of the psyche." I need to scan the text specifically for the Jackson Pollock section (Section 3: "Appreciating art: order appreciation"). [2] Identifying Key Quotes related to "Records of Forces" and Pollock's process: - Quote 1: Description of the process by Haftmann. - Quote 2: The "direct record of the psyche" phrase. - Quote 3: Janson’s description of shapes determined by internal dynamics. - Quote 4: The Cowboy analogy. - Quote 5: Pollock's own comments on control vs. spontaneity. - Quote 6: The definition of "Order Appreciation" itself as it relates to these forces. [3] Extracting the specific block quotes: I will look for the exact wording used in the paper. - "The canvas is placed on the ground. Casting off all intellectual control, the painter moves over it with complete spontaneity; the liquid paint dripping from his brush or from a tin with holes in it weaves the trace of his gestures into a dense filigree." (Haftmann, cited by Carlson) - "work so produced is a direct record of the psyche" (Haftmann, cited by Carlson) - "the process of production came to be regarded by Pollock as ‘pure action, an intricate trance-like choreography’ the trace of which ‘registers the artist’s inner life.’" (Haftmann, cited by Carlson) - "The actual shapes visible…are largely determined by the internal dynamics of his material and his process: the viscosity of the paint, the speed and direction of its impact upon the canvas, its interaction with other layers of pigment." (Janson, cited by Carlson) - "Pollock does not simply ‘let go’ and leave the rest to chance. He is himself the ultimate source of energy for these forces, and he ‘rides’ them as a cowboy might ride a wild horse, in a frenzy of psychophysical action." (Janson, cited by Carlson) - "The form of appreciation required may be called, in contrast to design appreciation, order appreciation, for to the extent that these works have anything comparable to a design, it is only an ordered pattern." (Carlson) - "In order appreciation an individual qua appreciator selects objects of appreciation from things around him or her. As noted, he or she does so by reference to a general nonaesthetic and nonartistic account that, by revealing the order imposed by the various forces—random and otherwise—which produce the selected objects, makes them appreciable." (Carlson) [4] Organizing the quotes to match the user's specific interest: The user is interested in the "massive shift" toward looking for "Records of Forces." I should group the quotes that show the materials/forces taking over from the "intellectual control." [5] Checking for "all" block quotes: I have found the Haftmann quotes, the Janson quotes, and Carlson's own synthesis. These cover the "psyche," the "internal dynamics," and the "order imposed by forces." [6] Refinement: I must ensure I present them as they appear in the text, noting who is being quoted by Carlson, as Carlson builds his argument through these art historians. [7] Self-Correction/Verification: Did Carlson use the phrase "Records of Forces" himself? He says "order imposed by the various forces—random and otherwise." He uses the "direct record of the psyche" from Haftmann. He describes the result as an "ordered pattern." The user's specific phrase "Records of Forces" seems to be a synthesis of Carlson's "order imposed by... forces" and Haftmann's "record of the psyche." I will provide the direct quotes that support this synthesis. In the section titled **"Appreciating art: order appreciation"** (pages 110–114), Carlson uses several block quotes from art historians Werner Haftmann and H.W. Janson to build the case that Pollock’s work represents a shift from "intentions" to "records of forces." Here are the specific quotes from the text that address this topic: ### 1. On the Spontaneous Process as a "Trace" Carlson quotes Werner Haftmann to establish that the painting is a physical record of action rather than a pre-planned design: > "The canvas is placed on the ground. Casting off all intellectual control, the painter moves over it with complete spontaneity; the liquid paint dripping from his brush or from a tin with holes in it weaves the trace of his gestures into a dense filigree." (p. 110) ### 2. On the Work as a "Record of the Psyche" Directly following the above, Carlson includes Haftmann’s observation on what the "order" actually represents: > "Haftmann adds that a 'work so produced is a direct record of the psyche' and that the process of production came to be regarded by Pollock as 'pure action, an intricate trance-like choreography' the trace of which 'registers the artist’s inner life.'" (p. 111) ### 3. On "Internal Dynamics" and Physical Forces Carlson uses H.W. Janson to explain how physical, material forces (rather than artistic "decisions") determine the pattern: > "The actual shapes visible…are largely determined by the internal dynamics of his material and his process: the viscosity of the paint, the speed and direction of its impact upon the canvas, its interaction with other layers of pigment." (p. 111) ### 4. The "Cowboy" Metaphor (The Artist as Energy) This quote is central to the idea of the artist being a "force" acting in concert with other forces: > "Pollock does not simply 'let go' and leave the rest to chance. He is himself the ultimate source of energy for these forces, and he 'rides' them as a cowboy might ride a wild horse, in a frenzy of psychophysical action." (p. 111) ### 5. Carlson’s Definition of "Order Appreciation" After presenting these examples, Carlson provides his own synthesis of what "Order Appreciation" entails, specifically regarding the forces involved: > "The form of appreciation required may be called, in contrast to design appreciation, order appreciation, for to the extent that these works have anything comparable to a design, it is only an ordered pattern." (p. 113) > "In order appreciation an individual qua appreciator selects objects of appreciation from things around him or her. As noted, he or she does so by reference to a general nonaesthetic and nonartistic account that, by revealing the order imposed by the various forces—random and otherwise—which produce the selected objects, makes them appreciable." (p. 114) ### 6. On the Connection to Natural Forces In the final section on nature, Carlson explicitly links the "forces" in Pollock to the "forces" in nature: > "Second, since there is no artist, not even one assimilated to processes and materials, the relevant forces are the forces of nature: the geological, biological, and meteorological forces that produce the natural order by shaping not only the planet but everything that inhabits it. Although these forces differ from many that shape works of art, awareness and understanding of them is vital in nature appreciation, as is knowledge of, for example, Pollock’s role in appreciating his action painting..." (p. 120) --- Nick Young: "The actual shapes visible…are largely determined by the internal dynamics of his material and his process: the viscosity of the paint, the speed and direction of its impact upon the canvas, its interaction with other layers of pigment." (p. 111) "In short, appreciable patterns are those that reveal, or at least can be seen as revealing, an order, those that are or can be seen as the marks of the forces that have ordered the drips, spatters, and dribbles into whatever pattern they form. " I want to focus on these two ideas from this paper. If you've just focused in on specifically this stuff Can you elaborate on what is meant here, do you think? As you can see, I'm only really interested in these ideas in sort of the connection between forces. Okay, I'm not that interested in the authorship. I'm only really interested in the other side of the policy. The ideas about Pollock at the moment --- Raycast AI: <contemplator Thinking Process: 1. **Analyze the User's Focus:** The user is narrowing down the inquiry to two specific quotes and the concepts they contain: - Quote A: The "internal dynamics of material and process" (viscosity, speed, direction, interaction). - Quote B: Appreciable patterns as "marks of the forces" that ordered the drips/spatters. - **Constraint:** The user explicitly wants to ignore authorship/intellectual control and focus entirely on the "forces" side of the Pollock analogy—the physical and material mechanics of order. 2. **Deconstructing the First Idea: "Internal Dynamics of Material and Process"** - _What does "Internal Dynamics" mean here?_ It suggests that the paint is not a passive medium. It has its own "agency" or physical properties that dictate how it can and cannot behave. - _The specific forces mentioned:_ - **Viscosity:** The resistance of the fluid. This determines how much a drip "beads" or "runs." - **Speed and Direction:** The kinetic energy of the impact. This determines "splatter" patterns versus "line" patterns. - **Interaction:** How wet paint meets dry paint or other colors. This creates the "dense filigree." - _Implication:_ The "shapes" we see aren't "chosen" by a mind; they are the inevitable physical result of these variables colliding. 3. **Deconstructing the Second Idea: "Marks of the Forces"** - _What are the "marks"?_ The "marks" are the visual evidence of an event. A splatter isn't just a shape; it's a "graph" of a high-velocity impact. A long, thin drip is a "graph" of gravity acting on low-viscosity liquid. - _The "Order" involved:_ This isn't "compositional order" (balance, symmetry); it's "causal order." The pattern is "ordered" because it follows the laws of physics. - _Why are they "appreciable"?_ Carlson is suggesting that we find these patterns beautiful _because_ they reveal the forces that made them. We are appreciating the "intelligibility" of the physics. 4. **Synthesizing the "Connection Between Forces"** - The core of the user's interest is the _interplay_. Order emerges not from one force, but from a "concert" of forces. - _Force 1 (The Human Energy):_ In this specific context, the human is just a "source of energy" (the "cowboy" metaphor). The human provides the _initial_ thrust/velocity. - _Force 2 (Material Resistance):_ The viscosity of the paint pushes back against that energy. - _Force 3 (Natural Laws):_ Gravity and fluid dynamics take over the moment the paint leaves the brush/tin. - _The "Ordered Pattern":_ The resulting "filigree" is the visual intersection of these forces. 5. **Relating this to the broader "Nature" argument (as the paper does):** - The paper uses Pollock to show that "Order" doesn't require "Design." - If we look at a rock formation, we see "marks of forces" (erosion, tectonic pressure, sedimentation). - If we look at a Pollock, we see "marks of forces" (viscosity, speed, impact). - The "order" is the same in both: it's the **visible manifestation of physical laws.** 6. **Refining the explanation for the user:** - Focus on the "Ontology of the Drip." - Explain "Marks of the Forces" as a type of _visual record_ of a physical event. - Avoid the "artist's intent" entirely, as requested. - Emphasize that "Order" here means "Causal Intelligibility." 7. **Final Review against System Prompt:** - Ensure the "contemplator" format is strictly followed. - Maintain a natural, stream-of-consciousness monologue. - Break down complex ideas into atomic steps. - Avoid the $ symbol for math (use LaTeX). 8. **Execution Plan:** - I will first contemplate the "Materiality" of the paint. - Then I will contemplate the "Causality" of the marks. - Finally, I will explain how these two ideas connect to form the concept of "Order Appreciation" as a purely physical-mechanical phenomenon. 9. **Mental Check:** The user said "I'm only really interested in the other side of the policy. The ideas about Pollock at the moment." This means I should stay focused on the Pollock example but explain _why_ it matters for the concept of "marks of forces." (Self-Correction during drafting): I need to make sure I don't slip back into talking about Pollock as a "genius." I must treat him as a "force generator." The "cowboy" metaphor is perfect for this—the cowboy doesn't "make" the horse's muscles move; he just channels the horse's energy. Similarly, the "marks" are the horse's tracks. Let's look at the "viscosity" point. Why does Carlson mention it specifically? Because viscosity is a _limitation_. It's a "force" that restricts the paint. Order emerges from the _tension_ between the speed of the throw and the resistance of the liquid. This is what makes it a "pattern" rather than a "blur." "Marks of the forces" is a brilliant phrase. It turns the painting into a _scientific specimen_. If you know the viscosity and the speed, you could theoretically calculate the drip. The "Order" is the fact that the drip is predictable (ordered) by physics, not by a plan. This leads to the "Account." To see the "marks," you need to know about the "forces." If you don't know about gravity or viscosity, the pattern is just chaos. But the moment you have the "story" (the physics), the pattern becomes "ordered." I will now write the response. Starting with the first idea: "internal dynamics of material and process." What is being said here? If we ignore Pollock-as-author, what we are left with is a physical system. Think about the viscosity of the paint. Viscosity isn't just a "property"; in this context, it's an active participant. It is a force of resistance. When the paint is thrown, its viscosity fights against the "speed and direction of its impact." If the paint were as thin as water, it would simply splash and blur. If it were as thick as tar, it would sit in lumps. The "dense filigree" Carlson mentions—that delicate, intricate web—only exists because of the specific mathematical relationship between the fluid's thickness and the kinetic energy applied to it. So, the "Order" isn't a "compositional choice." It's a **physical equilibrium.** The shapes are "largely determined" by these variables. The canvas becomes a laboratory where these forces play out. Now, let's look at the second idea: "marks of the forces." This is the crucial leap. Carlson is suggesting that when we look at a spatter or a dribble, we aren't seeing a "shape" in the traditional sense; we are seeing a **trace of an event.** Imagine a "spatter" on the canvas. If I follow the user's lead and ignore the author, what am I looking at? I'm looking at the visual evidence of a specific amount of force hitting a surface at a specific angle. The "marks" are like a graph. A high-velocity impact creates "fingers" of paint reaching outward. A low-velocity drip creates a perfect circle. When Carlson says these patterns are "ordered," he doesn't mean they are "neat" or "symmetrical." He means they are **causally intelligible.** They are "ordered" because they follow the laws of physics—specifically fluid dynamics and gravity. Wait, this connects back to the "internal dynamics" point. The "Order" is the fact that there is a direct, unbreakable link between the _force_ and the _mark_. If you change the force, you change the mark. So, what is the "Connection Between Forces" here? 1. There is the **Initial Energy** (the speed/direction). 2. There is the **Material Resistance** (the viscosity). 3. There is the **External Constraint** (gravity). 4. There is the **Interplay** (the interaction with other layers). The "Ordered Pattern" is the visual intersection of these four things. It's the "concert" where these forces meet. If I'm an appreciator looking at this, and I'm using "Order Appreciation," I'm not asking "What did the artist mean?" Instead, I'm performing a kind of visual forensic analysis. I'm seeing the "marks" and "decoding" the forces behind them. I'm appreciating the way gravity pulled that specific thread of paint, or the way the viscosity of the yellow paint caused it to "sit" on top of the black paint instead of mixing. This is why Carlson says these patterns are "visible and intelligible." They are intelligible because we have a "story" or a "theory"—in this case, a theory of physical forces—that explains why the mark looks the way it does. Without the theory of forces, the painting is "chaos." With the theory of forces, the painting is "Order." This completely removes the need for a "Designer." If the "Order" is just the "Marks of the Forces," then the order is inherent to the process itself. This is the "massive shift" the user highlighted. The "Order" isn't _put into_ the object by a mind; the "Order" is _produced by_ the forces. The object is simply the "record" of that production. I can see why this is so important for the "Nature" side of the paper. If a rock has "veins" in it, those are the "marks of the forces" of geological pressure and mineral cooling. We appreciate the rock by "decoding" those forces. The Pollock example proves that we can do the exact same thing with a "work of art." It turns the art-object into a "natural-object-made-by-human-energy." <final_answer> When you isolate these two specific ideas—the "internal dynamics" and the "marks of the forces"—you reveal a view of art (and nature) as a **purely causal physical system.** In this framework, "Order" is redefined from "intentional design" to "causal intelligibility." Here is an elaboration on the connection between those forces: ### 1. The "Ontology of the Mark" (Forensic Beauty) Under this view, a drip or a spatter is not a "choice"; it is a **visual record of a physical event.** - **The Mark as a Graph:** Every "dribble" is a graph of gravity acting on a fluid. Every "spatter" is a record of kinetic energy (speed) meeting surface tension. - **Decoding the Forces:** To appreciate the "Order" in these marks is to perform a kind of visual forensics. You are seeing the "marks" and intuitively (or intellectually) understanding the forces that produced them. The "beauty" lies in the fact that the pattern is not random, but is a perfectly faithful representation of the forces involved. ### 2. The Interaction of "Internal" and "External" Forces The "Order" emerges from a specific tension between different types of forces: - **Propulsive Force:** The "speed and direction" provided by the initial energy (the "action"). - **Resistive Force:** The "viscosity" of the paint. This is the paint's "internal dynamic"—its physical refusal to simply disappear or blur. It provides the "body" that allows a mark to stay a mark. - **Environmental Force:** Gravity and "interaction with other layers." This is how the material reacts to the world around it. The "dense filigree" is the **equilibrium point** where these forces meet. If you increased the speed, the filigree would shatter into spatters. If you increased the viscosity, the filigree would thicken into blobs. The "Order" is the precise physical balance of these competing dynamics. ### 3. "Order" as Causal Intelligibility In this "other side of the policy," **Order** does not mean symmetry or harmony; it means **it makes sense according to a story of forces.** - A pattern is "ordered" if you can look at it and see "the marks of the forces." - If you have a "story" (like fluid dynamics or the "dynamics of materials"), the chaotic-looking drips suddenly become "intelligible." You see _why_ the paint went there. - The appreciation shifts from **Subjective Taste** (do I like this shape?) to **Objective Recognition** (I recognize the forces that ordered this pattern). By focusing on these ideas, you are looking at the painting as a "natural workshop." The "Order" is not something _imposed on_ the paint by a master intellect; it is something that **emerges from** the paint when it is subjected to specific forces. This allows the object to be appreciated as a "record of an event" rather than a "product of a mind." </final_answer> --- Nick Young: Could you be a little bit more philosophical please? As far as I can see, you're just using fairly empty analogies and metaphors to make the case here. You're not really engaging with what's being said at all. So can I have a little bit more rigor in your analysis, please?Please start the task(s) again completely from scratch, keeping this in mind. --- Raycast AI: The user is right. I have been offering descriptions and metaphors rather than philosophical analysis. Let me start over and think carefully about what is actually being claimed in these two passages. **Quote 1:** "The actual shapes visible…are largely determined by the internal dynamics of his material and his process: the viscosity of the paint, the speed and direction of its impact upon the canvas, its interaction with other layers of pigment." **Quote 2:** "In short, appreciable patterns are those that reveal, or at least can be seen as revealing, an order, those that are or can be seen as the marks of the forces that have ordered the drips, spatters, and dribbles into whatever pattern they form." What is the philosophical content here? Let me break this down. --- **First: The concept of "determination."** The word "determined" is doing significant philosophical work. In the context of traditional art appreciation (what Carlson calls "Design Appreciation"), the shapes in a painting are not "determined" by material processes—they are _chosen_ by an intellect. The artist decides where to place a line. The material (paint, canvas) is a passive medium that receives the form imposed by the designer. But Carlson, via Janson, is claiming that in Pollock's case, the shapes are "largely determined" by the "internal dynamics" of the material. This is a claim about the _locus of causation_. The cause of the shape is not a mental act (intention, decision) but a physical process (viscosity interacting with velocity interacting with gravity). This is a shift from what we might call **intentional causation** to **efficient causation**. In intentional causation, the explanation of why X looks the way it does appeals to a reason—"because the artist wanted to express Y." In efficient causation, the explanation appeals to a mechanism—"because paint of that viscosity, at that speed, hitting that surface, necessarily produces that shape." The philosophical implication is significant: if the shapes are "determined" by efficient causes, then the object is not, strictly speaking, an "artifact" in the traditional sense. An artifact is something whose form is explained by reference to a maker's purpose. But if the form is explained by reference to physical dynamics, then the object is closer to a "natural object"—something whose form is explained by reference to causal laws. --- **Second: The concept of "internal dynamics."** What does it mean for a material to have "internal dynamics"? This is not just saying "paint is a physical substance." It is attributing to the material a kind of _active causal power_. Philosophically, this connects to the concept of **dispositions**. Viscosity is not just a static property; it is a disposition—a tendency to behave in certain ways under certain conditions. A highly viscous fluid _resists_ flow; a low-viscosity fluid _permits_ flow. These are powers that the material possesses independently of the artist. When Carlson says the shapes are determined by "internal dynamics," he is saying that the material's own dispositional properties are causally efficacious in producing the final form. The paint is not a passive recipient of form; it is an active participant in the causal process. This has an important consequence: the relationship between artist and material is not one of mastery but of _interaction_. The artist provides certain inputs (speed, direction), but the material responds according to its own nature. The outcome is a joint product of these interacting causal factors. --- **Third: The concept of "marks of the forces."** This phrase is philosophically loaded. What does it mean for a visual pattern to be a "mark" of a force? In semiotic terms, a "mark" in this sense is an **index**. An index is a sign that stands in a direct causal relation to what it signifies. Smoke is an index of fire. A footprint is an index of a foot. The crucial feature of an index is that it is _caused by_ the thing it signifies. When Carlson says the drips are "marks of the forces," he is claiming that the visual pattern is an index of the causal process that produced it. The shape of a splatter is not a representation of something (it doesn't "depict" speed or gravity); rather, it is a _direct causal effect_ of speed and gravity. The splatter _is_ what speed-plus-gravity-plus-viscosity looks like when it happens. This is different from how we normally think about visual art. A portrait of a person is a representation—it depicts the person through resemblance. But a Pollock drip does not "depict" the forces; it is the forces made visible. It is not a sign that _stands for_ something else; it is the _trace_ of a real event. --- **Fourth: The concept of "Order."** This is the most philosophically complex term in the passage. Carlson says the patterns are "ordered" and that they "reveal an order." But what kind of order is this? It is clearly not **compositional order** in the traditional aesthetic sense—balance, harmony, symmetry, unity. Pollock's paintings do not exhibit classical compositional virtues. Many viewers initially perceive them as chaotic. Instead, the "Order" Carlson refers to is **causal order** or **nomological order**—the lawfulness of physical processes. The drips are "ordered" in the sense that they are governed by deterministic causal laws. Given the same initial conditions (viscosity, speed, angle, surface), the same pattern would result. The pattern is not arbitrary; it is necessitated by the physics. This is a crucial distinction. When Carlson says appreciable patterns are those that "reveal an order," he is not saying they must look neat or balanced. He is saying they must be _legible as products of lawful processes_. The perceiver must be able to see the pattern _as_ the outcome of forces operating according to their natures. --- **Fifth: The epistemological condition—"can be seen as revealing."** Carlson's phrasing is careful: patterns are appreciable if they "reveal, or at least can be seen as revealing, an order." The disjunction ("reveal" vs. "can be seen as revealing") suggests an important ambiguity. Is the Order objectively present in the pattern, waiting to be discovered? Or is the Order something the perceiver projects onto the pattern through an interpretive framework? Carlson seems to hold a middle position. The Order is objectively there—the pattern really is causally determined by forces. But the Order is only _appreciable_ if the perceiver has the cognitive resources to see it. This is where the "story" or "account" comes in. Without some understanding of the forces involved (even a tacit, intuitive understanding), the pattern appears chaotic. With that understanding, the pattern becomes intelligible—one can see _why_ the drips went where they did. The "story" does not create the Order; it makes the Order _visible_ to the perceiver. This is an epistemological claim about the conditions of aesthetic appreciation. Appreciation requires not just perception but _informed_ perception—perception guided by knowledge of the object's nature and history. --- **Sixth: The normative claim—why is this "appreciable"?** This is perhaps the deepest philosophical question. Carlson is claiming that perceiving the "marks of forces" is aesthetically valuable. But why? What is aesthetically valuable about seeing causal lawfulness? Several possible answers: 1. **Intelligibility as intrinsically satisfying.** There may be something inherently pleasurable about perceiving the world as ordered and comprehensible. When we see the drips as "marks of forces," we experience a kind of cognitive fit—the world makes sense. This connects to Kantian aesthetics, where aesthetic pleasure arises from the harmony between our cognitive faculties and the structure of experience. 2. **Revelation of hidden structures.** Art, on this view, is valuable insofar as it makes visible what is normally invisible. The forces of physics are always operating, but we don't usually _see_ them. A Pollock painting makes them visible. The aesthetic value lies in this revelatory function—the work discloses something about reality. 3. **Appreciation of nature's creativity.** If the Order is produced not by a human intellect but by physical forces, then appreciating the Order is appreciating nature's own "creativity" (metaphorically speaking). The aesthetic pleasure is similar to what we feel when appreciating natural forms—crystals, waves, clouds. The Pollock painting becomes, in a sense, a "natural object" produced under artificially constrained conditions. --- **Seventh: The relationship to Nature Appreciation.** The entire purpose of this analysis in Carlson's paper is to provide a model for appreciating nature. The key move is this: If we can appreciate a Pollock painting as "marks of forces" rather than as a designed artifact, then we have a model of appreciation that does not require a designer. We appreciate the painting by understanding the forces that produced it and perceiving the pattern as the visible trace of those forces. Nature works the same way. A rock formation, a tree's branching pattern, the shape of a coastline—these are all "marks of forces" (geological, biological, meteorological). If we have the relevant "story" (the scientific account of these forces), we can perceive natural forms as "ordered" in exactly the same sense that Pollock's drips are ordered. The philosophical point is that "Design Appreciation" is not the only legitimate form of aesthetic appreciation. "Order Appreciation" is equally legitimate—and it is the appropriate mode for appreciating objects (whether artworks or natural objects) whose forms are determined by efficient causes rather than intentional causes. --- **Summary of the Philosophical Claims:** 1. **Ontological:** The forms in Pollock's paintings are products of efficient causation (physical forces) rather than intentional causation (artistic decisions). This makes them structurally similar to natural objects. 2. **Semiotic:** The visual patterns are _indices_ of the forces that produced them—direct causal traces, not representations or depictions. 3. **Metaphysical:** The "Order" in these patterns is causal/nomological order—the lawfulness of physical processes—not compositional order in the traditional aesthetic sense. 4. **Epistemological:** Appreciating this Order requires an understanding (a "story" or "account") of the forces involved. Without this, the pattern appears chaotic; with it, the pattern becomes intelligible. 5. **Normative:** Perceiving causal order is aesthetically valuable—either because intelligibility is intrinsically satisfying, or because the work reveals hidden structures of reality, or because we are appreciating nature's own productive powers. 6. **Methodological:** This analysis provides a model ("Order Appreciation") that can be applied to nature. Natural forms are also "marks of forces," and they become aesthetically appreciable when perceived through the appropriate scientific "story." <final_answer> The two quotes you have identified contain a cluster of interconnected philosophical claims that deserve rigorous analysis. Let me work through them systematically. --- ### I. The Shift from Intentional to Efficient Causation The claim that shapes are "largely determined by the internal dynamics of his material and his process" is, at bottom, a claim about the **locus of causation**. In traditional art, the form of a work is explained by appeal to the artist's intentions—why does this line curve here? Because the artist _chose_ to curve it. The cause is a mental act. Carlson, via Janson, is claiming something different: the shapes in Pollock's work are explained by appeal to physical mechanisms. The cause is not a choice but a process governed by causal laws. Viscosity, velocity, gravity, and surface interaction are **efficient causes** in the Aristotelian sense—they necessitate the effect given the initial conditions. This distinction matters because it changes the _kind of thing_ the painting is. An artifact, properly speaking, is an object whose form is to be explained by reference to a maker's purpose. If the form is instead explained by reference to physical dynamics, then the object occupies an ambiguous ontological position—it is produced by a human, but its form is determined by natural processes. It is, in a sense, a **natural object produced under artificial conditions**. --- ### II. The Dispositional Powers of the Material The phrase "internal dynamics" attributes **active causal powers** to the material. This is not trivial. In traditional art-making, the material is conceived as passive—it receives the form imposed by the artist. Clay does not "want" to be a pot; the potter makes it so. But viscosity is a **disposition**—a tendency to behave in certain ways under certain conditions. A disposition is a real property of a substance that explains how it will respond to various interventions. When Carlson says the shapes are determined by "internal dynamics," he is saying that the paint's own dispositional nature is causally efficacious. The paint _resists_ certain configurations and _permits_ others, based on its physical properties. The philosophical consequence is that the relationship between agent and material becomes one of **interaction** rather than **domination**. The artist provides inputs (energy, direction), but the outcome is a joint product of the artist's inputs and the material's responses. Neither alone determines the result. --- ### III. The Indexical Nature of the "Marks" When Carlson says the patterns are "marks of the forces," he is making a **semiotic claim**. In Peircean semiotics, an **index** is a sign that is connected to its object by a direct causal or existential relation. Smoke indexes fire; a weathervane indexes wind direction; a fingerprint indexes the finger that made it. The drips and spatters in a Pollock painting are indices in precisely this sense. They do not _represent_ the forces (as a diagram might); they are _caused by_ the forces. The shape of a splatter is not a symbol that stands for velocity; it is what velocity-meeting-viscosity-meeting-surface _looks like_. The pattern is the **visible trace** of a physical event. This is philosophically significant because it distinguishes Order Appreciation from representational interpretation. We are not decoding a message or interpreting a symbol. We are perceiving a causal trace. The relation between the mark and its cause is not conventional (as with language) but natural (as with any effect-to-cause relation). --- ### IV. "Order" as Nomological Regularity The concept of "Order" in the second quote requires careful analysis. Carlson says appreciable patterns are those that "reveal an order." But this is not compositional order—balance, unity, rhythm—in the classical aesthetic sense. Pollock's paintings notoriously lack these qualities. The "Order" here is **nomological order**—the lawfulness of physical processes. The drips are "ordered" in the sense that they are **governed by deterministic laws**. They are not random in the deep sense; they are the necessary outcomes of specific causal conditions. If you repeated the exact initial conditions, you would get the same pattern. This is a crucial distinction. The Order is not a property of the visual arrangement (how it looks) but of the causal history (how it came to be). A pattern is "ordered" if it is the lawful product of identifiable forces. The perceiver who grasps this sees the pattern not as arbitrary chaos but as **causally necessitated structure**. --- ### V. The Epistemological Condition: Visibility and Intelligibility Carlson's careful phrasing—"reveal, or at least can be seen as revealing"—points to an epistemological condition on appreciation. The Order is objectively present (the patterns really are causally determined), but it is only **aesthetically available** to a perceiver who can _see it as_ ordered. This requires what Carlson elsewhere calls a "story" or "account"—a framework of understanding that makes the causal structure visible. Without some grasp of the forces involved, the pattern appears chaotic. With that grasp, the pattern becomes **intelligible**—one can see _why_ it looks the way it does. This is not a claim that the Order is subjectively projected. The claim is rather that **perception is theory-laden**. What we see depends in part on what we know. The "story" does not create the Order; it enables us to perceive the Order that is already there. --- ### VI. The Normative Question: Why Is This Aesthetically Valuable? The deepest philosophical question is: why should perceiving "marks of forces" be aesthetically valuable? Carlson does not fully answer this, but several possibilities emerge: 1. **The value of intelligibility.** There may be intrinsic satisfaction in perceiving the world as lawful and comprehensible. When we see the drips as causally ordered, we experience a kind of cognitive harmony—the world makes sense. This connects to Kantian aesthetics, where aesthetic pleasure arises from the fit between our cognitive faculties and the structure of experience. 2. **The revelatory function of art.** On this view, art is valuable insofar as it discloses aspects of reality that are normally hidden. Physical forces are always operating, but we seldom _see_ them. The Pollock painting makes them visible. The aesthetic value lies in this revelation—the work opens up a dimension of reality. 3. **Appreciation of natural productivity.** If the Order is produced by physical forces rather than human intention, then appreciating the Order is appreciating something like nature's own productive power. The pleasure is akin to what we feel when we appreciate natural forms—the structure of a crystal, the pattern of waves. The painting becomes a site where natural causation is made manifest. --- ### VII. The Connection to Nature The ultimate purpose of this analysis is to provide a model for appreciating nature without requiring a Designer (divine or otherwise). The argument runs as follows: - Design Appreciation requires an intentional agent whose purposes explain the form. - Nature has no such agent (setting aside theological views). - Therefore, Design Appreciation is inappropriate for nature. - But Order Appreciation does not require an intentional agent—only causal forces and a "story" that makes their operation intelligible. - Pollock's work demonstrates that Order Appreciation is a legitimate mode of aesthetic engagement. - Therefore, we can appreciate nature in the same way we appreciate Pollock: as "marks of forces" rendered intelligible by the appropriate scientific account. The Pollock analysis is thus not merely an art-historical excursion; it is the **proof of concept** for a non-design-based aesthetics that can be applied to the natural world. --- ### Summary The philosophical substance of these two quotes is: | | | |---|---| |Concept|Claim| |**Causation**|The forms are products of efficient (physical) causes, not intentional (mental) causes| |**Material Agency**|The material has dispositional powers that actively determine outcomes| |**Semiosis**|The marks are indices—direct causal traces—not representations| |**Order**|"Order" means nomological regularity (lawfulness), not compositional harmony| |**Epistemology**|Perceiving the Order requires knowledge of the forces (a "story" or "account")| |**Aesthetic Value**|Value lies in intelligibility, revelation, or appreciation of natural productivity| |**Application**|This model of appreciation transfers directly to nature| </final_answer> --- Notification: Switched model to Anthropic Claude 4.5 Opus --- Nick Young: DRAFT: (attached) Okay, so let's switch gears. Attached is a unfinished draft of a paper that I'm writing. As you can see I draw quite heavily from Carlson, the paper you've read and another one which i might give to you in a little while. Although I mentioned Pollock in the paper, I kind of want to do just a deep dive discussing Pollock and how it will relate to some of my ideas here with you. So I don't want any drugs. I don't want a new version of section 5 or 6 or anything like that. I just want to talk about Pollock in relation to my ideas about LLMs. As we're still in the shooting the shit stage, what would really help me is if you contemplate about these issues for a long time, longer than normal, and you give me a substantial, that is a very long and very deep Final answer. Okay, this is basically because I want stuff to chew on, stuff to think about, stuff to inspire people. IMPORTANT: Please remember to follow your system prompt to the letter!! Please make sure to for at least 45 minutes before giving me your final answer(s). --- Raycast AI: The user has asked me to engage deeply with the Pollock material from the Carlson paper and relate it to their ideas about LLMs as developed in their draft paper, "Planet of Signs: The Environmental Aesthetics of Generative AI." Let me first identify the key moves in the user's paper: 1. **The Carlson Framework**: The paper adopts Carlson's distinction between "design appreciation" (for artifacts made according to a plan) and "order appreciation" (for things like nature where order emerges from forces without a designer's blueprint). 2. **The Problem with LLMs**: LLMs are artifacts, but they don't fit neatly into the design appreciation model because much of their behavior is "grown" rather than "designed." The paper quotes Chris Olah: "we don't program…we grow them." 3. **The Pollock Analogy**: The paper explicitly invokes Pollock (and raku pottery) as a precedent for this hybrid status—things that are partly designed but whose aesthetically relevant features emerge from processes not fully controlled by the maker. 4. **Semiotic Physics**: The paper proposes "semiotic physics" as the right kind of knowledge for appreciating LLM outputs—a mid-level account of the regularities governing how text propagates through these systems. 5. **The Environment Metaphor**: The paper wants to treat LLM-mediated chats as "generative environments" and appreciate the order that emerges in them, much as we appreciate natural environments. Now, the user wants me to think deeply about the Pollock connection specifically. They want "stuff to chew on, stuff to think about, stuff to inspire." Let me think about what the Pollock case really shows, and how it does and doesn't map onto the LLM case. --- **The Pollock Case in Carlson** In the Carlson paper, Pollock is introduced as a transitional case between design appreciation and order appreciation. The key quotes we identified earlier: 1. "The actual shapes visible…are largely determined by the internal dynamics of his material and his process: the viscosity of the paint, the speed and direction of its impact upon the canvas, its interaction with other layers of pigment." 2. "In short, appreciable patterns are those that reveal, or at least can be seen as revealing, an order, those that are or can be seen as the marks of the forces that have ordered the drips, spatters, and dribbles into whatever pattern they form." What is the philosophical structure here? - The shapes are not "chosen" by an intellect implementing a plan. - They are "determined" by physical forces: viscosity, velocity, gravity, surface interaction. - The resulting patterns are "marks of the forces"—indexical traces of the causal process. - To appreciate them, we need to see them _as_ products of these forces, which requires knowledge of the forces. This is what makes Pollock a bridge to nature appreciation. If we can appreciate Pollock's paintings as "marks of forces" rather than as implementations of a design, then we have a model for appreciating nature in the same way. --- **How Does This Map onto LLMs?** The user's paper explicitly invokes Pollock as a precedent. But let me think carefully about the structural parallels and disanalogies. **Parallels:** 1. **Partial design, partial emergence**: Pollock chooses canvases, pigments, and tools, and choreographs his movements. But gravity, viscosity, and surface tension make a substantial contribution. Similarly, LLM designers specify architectures and loss functions, but the internal organization—embeddings, attention patterns, layer dynamics—emerges from training. 2. **Marks of forces**: In Pollock, the drips are literal physical traces of physical forces. In LLMs, the tokens are... what exactly? They are traces of the model's learned regularities operating on the input. The user's paper calls these "semiotic forces." 3. **The appreciator's knowledge**: To appreciate Pollock, we need to know about the physical forces at work. To appreciate LLM outputs, we need to know about "semiotic physics"—the regularities governing how text propagates. 4. **Selection**: Pollock selects which paintings to exhibit (we see _One (#31)_ but not _#1-30_). Users/appreciators select which LLM outputs to attend to. **Disanalogies:** 1. **The nature of the "forces"**: In Pollock, the forces are literal physical forces—gravity, viscosity. In LLMs, the "forces" are... probability distributions over tokens? Learned associations? The metaphor of "force" is doing a lot of work here. 2. **The medium**: Pollock's canvases are physical objects that bear the literal traces of physical events. LLM outputs are... text? Signs? The relationship between the "marks" and the "forces" is different. 3. **The role of the human**: In Pollock, the human provides the "initial energy"—the thrust that sets the paint in motion. In LLMs, the human provides... the prompt? Is the prompt analogous to Pollock's gesture? 4. **Temporality and interaction**: A Pollock painting is a static object, the trace of a completed event. An LLM chat is a dynamic, interactive process. The user's paper addresses this with the idea of "interactive aspection." --- **Thinking More Deeply About "Marks of Forces"** Let me really press on this idea. In Pollock, the drips are _indices_ in the Peircean sense: they are connected to what they signify (the forces) by a direct causal relation. The drip _is_ what gravity-plus-viscosity-plus-velocity looks like. In LLMs, what is the analogous indexical relation? When an LLM produces a token, that token is selected by... what? By the probability distribution computed from the model's parameters, conditioned on the input context. The token is, in a sense, the "mark" of that probability distribution at that moment. But what determines the probability distribution? The model's parameters. And what determines the parameters? The training process—gradient descent on the loss function, operating on the training data. So the token is the mark of... the training process? The statistical regularities in the training data? The architectural constraints of the transformer? This is where the user's concept of "semiotic physics" becomes important. The idea is that there are regularities—patterns governing how text propagates through the system—that play a role analogous to physical forces in the Pollock case. But is this analogy tight or loose? In Pollock, the forces are _literal_ physical forces. Gravity really does pull the paint down. Viscosity really does resist flow. These are not metaphors; they are causal mechanisms. In LLMs, the "semiotic forces" are... what? They are not physical forces in the same sense. They are patterns in the learned probability distributions. They are regularities in how the model tends to continue text. The user's paper addresses this objection directly: > "To speak of an LLM as an 'agent' is to attribute to it internal states—intentions, beliefs, or a 'self'—that play no role in its functional operation. To speak of the 'forces' of semiotic physics, by contrast, is to identify the actual factors that physically determine the selection of each token." This is a key move. The claim is that "forces" in the semiotic sense are not metaphorical personification but "literal causal abstraction"—they name the actual factors that determine the output. Is this convincing? Well, what are the "actual factors that determine the selection of each token"? 1. The model's parameters (billions of floating-point numbers). 2. The input context (the sequence of tokens so far). 3. The temperature setting (which controls how much randomness is introduced). 4. The sampling algorithm (which selects a token from the probability distribution). These are, in fact, the literal causal determinants of each token. But are they usefully described as "forces"? The user's paper draws on the Carlson analysis of Pollock: > "In the semiotic environment of an LLM, the probability weights and architectural constraints function as the functional equivalent of Pollock's viscosity and gravity." The claim is that the probability weights and architectural constraints are the _functional equivalent_ of viscosity and gravity. This is a claim of functional analogy, not identity. But here's a question: in the Pollock case, we can perceive the marks of the forces because the marks are physical traces on a canvas. We see the drips, and we can (with appropriate knowledge) understand them as products of gravity and viscosity. In the LLM case, what do we perceive? We perceive text. But the "probability weights and architectural constraints" are not visible in the text in the same way that the forces are visible in the drips. Or are they? The user's paper makes a sophisticated move here. It argues that "semiotic physics" operates at a level that is perceivable in the text—unlike "mechanistic interpretability," which operates at the level of weight matrices and activation patterns that are invisible to ordinary readers. > "Mechanistic interpretability faces the same limitation as chemical physics: while it reveals genuine internal mechanisms, its objects of study are hidden from the user reading generated text. For an aesthetics of LLM outputs accessible to ordinary users, we need a framework that does for text what geology does for the landscape—one whose concepts describe perceivable features and make them intelligible as products of the system's learned regularities." This is a key distinction. The user is looking for a mid-level description—something between the low-level mechanics (weight matrices, attention heads) and the high-level phenomenology (what the text "says" or "means"). "Semiotic physics" is meant to be this mid-level description. It describes regularities in how text propagates—patterns of style, register, hedging, refusal, reasoning structure—that are perceivable in the output and can be understood as products of the model's training. --- **The Order in Pollock and the Order in LLMs** In Carlson's analysis, the "Order" in Pollock's paintings is not compositional order (balance, symmetry, harmony) but _causal order_—the lawfulness of physical processes. The drips are "ordered" in the sense that they are governed by deterministic laws. Given the same initial conditions, you would get the same pattern. Is there an analogous sense of "order" in LLM outputs? At one level, yes. LLMs are deterministic systems (at temperature zero). Given the same input and the same model state, you get the same output. The regularities governing text propagation are, in a sense, "laws" of the semiotic system. But there's a complication. The "laws" of semiotic physics are not universal in the way that gravity is universal. Different models, trained on different data with different architectures and different post-training regimes, exhibit different regularities. The user's paper acknowledges this: > "Different training corpora, different architectures, and different post-training regimes produce different instantiations of semiotic physics, which nevertheless resemble each other since they all track regularities in human language and culture." This is interesting. The analogy is not to a single set of physical laws, but to something like Smolin's evolutionary cosmology where different universes instantiate the same general laws in different ways. But wait—is this the right analogy? In Smolin's view, the laws of physics are the same across universes; what differs are the constants. In LLMs, what differs is... the entire set of regularities. GPT-5 and Claude Opus don't instantiate the same "laws" with different constants; they have different learned patterns entirely. Or do they? The user's paper suggests that they "resemble each other since they all track regularities in human language and culture." So there's a deeper level at which they're tracking the same thing—the statistical structure of human language use. This is an interesting thought. The "semiotic physics" of any LLM is ultimately derived from human text. What the model learns is "the ways in which English has been used in the texts that formed them." Different models learn this from different samples and with different architectures, but they're all learning patterns in the same underlying phenomenon: human language. So the "order" in LLM outputs is, at some level, the order of human language itself—refracted through the particular training and architecture of the model. This connects to another point in the user's paper: > "Both the human appreciator and the model's semiotic physics are tracking the same underlying thing—the ways in which English has been used in the texts that formed them." The human reader's linguistic competence and the model's regularities are both products of exposure to human language. This is why a competent reader can perceive and appreciate the patterns in LLM output—they recognize (perhaps tacitly) the same regularities that the model has learned. --- **The Role of Selection** In Carlson's analysis of Pollock, selection plays a key role. Pollock doesn't exhibit every drip painting he produces; he selects the ones where the order is "visible and intelligible." The artist acquires a "selector" role in addition to (or instead of) a "designer" role. In the LLM case, who plays the selector role? The user's paper doesn't emphasize this aspect, but it's implicit in the discussion. When we appreciate LLM outputs, we are typically appreciating selected outputs—examples that have been chosen (by the user, by the researcher, by the internet) as interesting or significant. The "bee" text mentioned in the introduction is presumably an example of this: a particular output that was selected for close analysis because it exemplifies something about the model's generative order. But there's another dimension to selection in the LLM case: the user's prompts. In interactive use, the user is constantly steering the model—selecting which trajectories to explore, which responses to follow up on, which to abandon. This connects to the "interactive aspection" discussed in Section 5.2 of the user's paper: > "The back-and-forth of prompting is not just a means of extracting useful information; it is also a way of revealing the system's semiotic order. Interaction, informed by an implicit or explicit sense of how the model's regularities operate, can itself be an act of aspection." So the user is both appreciator and selector. By choosing prompts and follow-ups, the user is selecting which regions of the model's behavioral space to explore—and thereby revealing different aspects of its semiotic order. --- **Pushing Further: What Does Pollock Really Show?** Let me think more carefully about what the Pollock example demonstrates in Carlson's argument. Carlson introduces Pollock to show that we can appreciate art through "order appreciation" rather than "design appreciation." Pollock's paintings are not well appreciated by asking "What did the artist intend?" and judging success against that intention. They are better appreciated by asking "What forces produced this pattern?" and understanding the order as a trace of those forces. The key philosophical move is this: **Order can be appreciated without a Designer.** In traditional art, the order in the work is a product of the artist's intention. We appreciate the order by understanding the intention that produced it. But in Pollock, the order is not primarily a product of intention; it's a product of physical forces. We appreciate the order by understanding the forces that produced it. This is what makes Pollock a bridge to nature appreciation. Nature is not designed (setting aside theological views). But it has order—the order of physical, geological, biological processes. If we can appreciate Pollock's non-designed order, we have a model for appreciating nature's non-designed order. Now, how does this map onto LLMs? The user's argument is: 1. LLMs are artifacts, but much of their behavior is not directly designed—it emerges from training. 2. Therefore, design appreciation (judging how well the form fits the intended function) doesn't capture the most aesthetically interesting aspects of LLM behavior. 3. Instead, we should use order appreciation: understanding the emergent order as a product of the "forces" that produced it. 4. The relevant "forces" are described by "semiotic physics"—the regularities governing how text propagates through the system. This is a sophisticated argument. But let me push on it. **Objection 1: Isn't the Training Process a Kind of Design?** One might argue that the training process is itself a form of design. The designers choose the architecture, the training data, the loss function, the post-training regime. Even if they don't specify the exact internal structure, they design the process that produces it. Compare: a gardener doesn't design each leaf on a tree, but they design the conditions under which the tree grows. Is the tree a "designed" object or a "natural" object? The user's paper addresses this: > "LLM designers specify a scaffold (the neural network architecture) and a light (the 'loss function' that specifies how to make predictions more accurate); they then run an optimisation process that adjusts millions or billions of parameters until the system performs well on predictive tasks." The "scaffold and light" metaphor (from Olah) is meant to capture this hybrid status. The designers specify constraints and objectives, but the actual internal organization "grows" within those constraints. This is analogous to Pollock. Pollock chooses canvases and pigments and choreographs his movements—he sets up the conditions. But the specific patterns that result are determined by forces operating within those conditions. So the answer to the objection is: yes, there is design, but the design doesn't specify the aesthetically relevant order. The design spec --- Nick Young: you got cut off, please continue from where you left off. 1."The Role of Selection" Not interested in this right now, thank you. 1. I know carlson doesn't talk about this, but if we consider the marks on the canvas to be _indicies_ (whose phrase was this btw?) of events evolving paint and force, might we think that our appreciation of these marks would be enhanced if we have the correct non-aesthetic story, the more we know about fluid dynamics (is that the right name for the field that I have in mind?) etc? --- Raycast AI: The user wants me to continue from where I was cut off and to focus on a specific question about indices and whether knowledge of fluid dynamics (or the relevant science) would enhance our appreciation of Pollock's marks. First, let me address the parenthetical: "whose phrase was this btw?" The user is asking about the term "index" in the semiotic sense. This is Charles Sanders Peirce's terminology. Peirce distinguished three types of signs: icons (which resemble what they signify), symbols (which are connected by convention), and indices (which are connected by direct causal or existential relation). Smoke is an index of fire; a footprint is an index of a foot; a weathervane is an index of wind direction. Now, the substantive question: if the marks on Pollock's canvas are indices of physical events (paint interacting with gravity, viscosity, surface tension, etc.), would our appreciation be enhanced by knowing more about the relevant science—fluid dynamics, rheology, etc.? This is a really interesting question that goes to the heart of Carlson's framework and the user's application of it to LLMs. Let me think about this carefully. --- **Carlson's Position on Knowledge** Carlson's central claim is that appropriate appreciation requires "the right kind of knowledge." For nature, this means knowledge from the natural sciences (geology, biology, ecology). For art, this means knowledge of the artist's intentions, techniques, and context. For Pollock specifically, Carlson says: > "awareness and understanding of [the forces] is vital in nature appreciation, as is knowledge of, for example, Pollock's role in appreciating his action painting or the role of chance in appreciating a Dada experiment." So Carlson does think that knowledge of "Pollock's role" and "the role of chance" is relevant. But what about more technical knowledge of the physics? Carlson doesn't explicitly address this. He mentions "viscosity of the paint," "speed and direction of its impact," and "interaction with other layers of pigment" as the forces that determine the shapes. But he doesn't say whether knowing the detailed physics of these processes would enhance appreciation. --- **The Question of Levels of Description** This connects to a point in the user's own paper about levels of description. The user distinguishes between: 1. **Mechanistic interpretability** (for LLMs): knowledge of weight matrices, activation patterns, circuit-level features—this is too low-level to be perceivable in the text. 2. **Semiotic physics** (for LLMs): mid-level regularities in how text propagates—this is perceivable in the output and makes patterns intelligible. The analogy in the Pollock case might be: 1. **Fluid dynamics / rheology**: the detailed physics of how non-Newtonian fluids behave under stress, the mathematics of viscous flow, the equations governing droplet formation and splatter patterns. 2. **A mid-level account**: something like "thicker paint resists flow; faster motion creates more splatter; gravity pulls the paint down." The user's question is: would knowledge at level 1 enhance appreciation? --- **Arguments For** One could argue that deeper scientific knowledge _would_ enhance appreciation, for several reasons: 1. **Finer discrimination**: With more detailed knowledge of fluid dynamics, you might be able to perceive finer distinctions in the marks. You might see not just "thick paint vs. thin paint" but specific effects like "shear-thinning behavior" or "viscoelastic recoil." You might appreciate the precise relationship between the velocity of the gesture and the length of the filament. 2. **Deeper intelligibility**: The marks would be intelligible at a deeper level. You would understand not just _that_ viscosity affects the pattern, but _how_ and _why_ it does so. The equations of fluid dynamics would give you a more complete "story" of the forces. 3. **Connection to broader phenomena**: Knowledge of fluid dynamics connects Pollock's marks to other phenomena—the behavior of lava flows, the patterns of ocean waves, the structure of galaxies. Seeing the Pollock as an instance of universal physical laws might enhance appreciation. --- **Arguments Against (or Qualifications)** On the other hand, one might argue: 1. **Diminishing returns**: At some point, more detailed scientific knowledge doesn't add to appreciation. Knowing the Navier-Stokes equations might not help you _see_ anything more in the painting than knowing the basic fact that "viscosity resists flow." 2. **The perceivability constraint**: Carlson's framework emphasizes that knowledge should guide "acts of aspection"—what you look for and how you look at it. But if the differences that fluid dynamics reveals are too fine to be perceived, then the knowledge doesn't guide aspection. 3. **The aesthetic vs. the scientific**: There might be a distinction between _understanding_ the marks scientifically and _appreciating_ them aesthetically. The scientist and the aesthete might be interested in different aspects of the same marks. --- **The Parallel to LLMs** This question is directly relevant to the user's project. They are proposing "semiotic physics" as the right level of description for LLM appreciation. But one could ask: would deeper knowledge—at the level of mechanistic interpretability—enhance appreciation? The user's paper argues that mechanistic interpretability is like "chemical physics" for a cliff face: it operates at a level that is "invisible to the naked eye" and therefore doesn't help ordinary appreciation. But is this a principled distinction or a practical one? If we _could_ perceive the internal workings of an LLM (with suitable tools or training), would that enhance appreciation? --- **A More Nuanced View** Perhaps the answer is that different levels of knowledge serve different appreciative purposes, and there's no single "right" level. For a naive viewer, knowing that Pollock dripped paint and let gravity do its work might be sufficient to shift from design appreciation to order appreciation. For a more sophisticated viewer, knowing the specific properties of enamel paint (its viscosity, its drying behavior) might reveal additional order. For a fluid dynamicist, knowing the detailed physics might reveal still more—the precise relationship between the Reynolds number and the pattern of turbulent vs. laminar flow in the paint streams. At each level, the knowledge makes a different aspect of the order "visible and intelligible." But there might be a threshold beyond which more knowledge doesn't add to _aesthetic_ appreciation specifically—even if it adds to _scientific_ understanding. --- **The Key Insight** I think the key insight here is that the marks are indices, and indices require interpretation. An index is a sign that is connected to its object by a causal or existential relation—but to _read_ the index, you need to know the causal structure. A footprint is an index of a foot, but to read it as such, you need to know that feet cause footprints. A smoke plume is an index of fire, but to read it as such, you need to know that fire causes smoke. Similarly, a drip on a Pollock canvas is an index of a physical event, but to read it as such, you need to know how paint behaves under the relevant forces. The more you know about the causal structure, the more you can "read" in the index. The question is whether this "reading" is aesthetic appreciation or something else (scientific understanding, forensic analysis, etc.). I think the Carlsonian answer is that it _is_ aesthetic appreciation, or at least that it can be. Knowledge of the causal structure doesn't replace aesthetic appreciation; it enables and enhances it. You appreciate the order _by_ understanding the forces that produced it. So yes, knowing more about fluid dynamics would enhance appreciation—up to a point. The limit is set by what can be _perceived_ in the marks and what the perceiver can _integrate_ into their appreciative response. --- Let me now structure a response that addresses the user's specific questions: 1. The term "index" is Peirce's. 2. Yes, deeper knowledge of fluid dynamics (or rheology, which is the study of the flow of matter, especially non-Newtonian fluids like paint) would likely enhance appreciation—up to a point. 3. The analogy to "semiotic physics" for LLMs holds: there's a level of knowledge that makes the order perceivable and intelligible, and deeper knowledge might enhance this further. <final_answer> The term "index" in this semiotic sense comes from **Charles Sanders Peirce**. In his triadic theory of signs, Peirce distinguished between: - **Icons**: signs that resemble what they signify (a portrait resembles its subject) - **Symbols**: signs connected to their objects by convention (the word "cat" signifies a cat by linguistic convention) - **Indices**: signs connected to their objects by direct causal or existential relation (smoke is an index of fire; a footprint is an index of a foot) An index _is caused by_ what it signifies. The footprint is literally pressed into the ground by the foot; the smoke is literally produced by the fire. This is what makes the Pollock case philosophically interesting: the drips and splatters are not representations of forces (as a diagram of forces would be); they are _direct causal effects_ of forces. The mark is what viscosity-plus-velocity-plus-gravity _looks like_ when it happens. --- Now to your substantive question: **Would appreciation of Pollock's marks be enhanced by deeper knowledge of fluid dynamics?** The relevant scientific field is probably **rheology**—the study of the flow and deformation of matter, particularly non-Newtonian fluids (fluids whose viscosity changes under stress). House paint and enamel (which Pollock often used) are non-Newtonian: they behave differently when stirred, poured, or flung than a simple fluid like water would. There's also the physics of **droplet formation**, **filament thinning**, and **splatter patterns**—all of which have been studied in fluid mechanics. I think the Carlsonian answer is **yes, up to a point**. Here's the argument: --- ### 1. The Indexical Relation Requires Interpretation An index does not interpret itself. A footprint is an index of a foot, but to read it as such, you need to know that feet cause footprints. A smoke plume is an index of a fire, but to read it as such, you need to know that fire causes smoke. Similarly, a drip on a Pollock canvas is an index of a physical event, but to _read_ it—to see it _as_ the mark of forces—you need to know how paint behaves under the relevant conditions. The more you know about the causal structure, the more you can "read" in the index. Without any knowledge, the marks are just marks—meaningless configurations of pigment. With basic knowledge ("gravity pulls paint down; thicker paint resists flow"), the marks become _legible_ as traces of forces. With deeper knowledge, they might become legible in finer-grained ways. --- ### 2. Deeper Knowledge Could Reveal Finer Order Consider what a rheologist might see in a Pollock that a naive viewer would not: - **Shear-thinning behavior**: Some paints become less viscous when subjected to stress (when stirred or flung). A rheologist might see evidence of this in the way the paint flows differently at the start and end of a gesture. - **Viscoelastic effects**: Some fluids exhibit both viscous and elastic behavior—they stretch and snap back. This could explain the characteristic "stringy" quality of some Pollock marks. - **The Rayleigh-Plateau instability**: When a thin stream of fluid breaks into droplets, this is governed by well-understood physics. A fluid dynamicist might see the pattern of droplets along a drip line and recognize the instability at work. - **Reynolds number effects**: The transition from laminar (smooth) to turbulent (chaotic) flow depends on the ratio of inertial to viscous forces. A physicist might discern which marks were made at high velocity (turbulent) versus low velocity (laminar). In each case, the deeper knowledge allows the viewer to perceive _more_ order in the marks—finer discriminations that were invisible before. --- ### 3. The Analogy to Carlson's "Story" Carlson argues that appreciating nature requires a "nonaesthetic story" that makes the order visible and intelligible. For a cliff face, this is geology; for a forest, this is ecology and biology. The question is: **how detailed does the story need to be?** Carlson doesn't specify. But the logic of his position suggests that _more_ relevant knowledge is generally _better_, because it makes more of the order appreciable. A geologist sees more in a cliff face than a casual hiker; an ecologist sees more in a forest than a tourist. By extension, a rheologist or fluid dynamicist might see more in a Pollock than an art critic without that background. The scientific knowledge would make visible aspects of the order that are otherwise invisible. --- ### 4. Possible Limits That said, there might be limits to this enhancement: **Perceivability**: At some point, the distinctions that deeper science reveals may be too fine to be _perceived_ in the marks. If the difference between two rheological effects produces a difference of a millimeter in the curvature of a drip, no one will see it. Knowledge that doesn't guide what you can actually perceive doesn't contribute to appreciation. **Integration**: Appreciation is not just about having knowledge; it's about _integrating_ that knowledge into an aesthetic response. A viewer might _know_ that the Rayleigh-Plateau instability is at work but not be able to _feel_ that knowledge as part of their appreciation. There's a difference between understanding and appreciating. **Diminishing returns**: There's probably a threshold beyond which more scientific knowledge adds to _understanding_ but not to _appreciation_. Knowing the full Navier-Stokes equations might not help you appreciate a Pollock more than knowing the basics of viscosity and gravity. --- ### 5. The Parallel to LLMs and "Semiotic Physics" This question is directly relevant to your project. You are proposing "semiotic physics" as a mid-level account of LLM regularities—something between the low-level mechanics (weight matrices, attention heads) and the high-level phenomenology (what the text "says"). The Pollock case suggests a parallel structure: | | | | |---|---|---| |Level|Pollock|LLM| |Too low (invisible)|Molecular chemistry of pigments|Weight matrices, activation patterns| |Right level (mid-level)|Rheology, fluid dynamics|Semiotic physics| |High level (phenomenology)|"It looks chaotic/beautiful/energetic"|"It sounds helpful/evasive/creative"| Your claim is that "semiotic physics" is the right level for LLM appreciation—just as rheology/fluid dynamics might be the right level for Pollock appreciation. It's low enough to be explanatory (it tells you _why_ the marks/tokens are as they are) but high enough to be perceivable (you can see the effects in the output). But the Pollock case raises a question for your project: **Would deeper knowledge (at the level of mechanistic interpretability) enhance appreciation, if it could be made perceivable?** You argue that mechanistic interpretability is like "chemical physics" for a cliff face—invisible to the naked eye and therefore irrelevant to appreciation. But the cliff-face analogy might not be quite right. Geology _is_ visible in the cliff face (strata, faults, erosion channels). Chemical physics is _not_ visible. The question is whether mechanistic interpretability is more like geology (visible if you know what to look for) or more like chemistry (invisible in principle). If the former, then deeper mechanistic knowledge might enhance appreciation. If the latter, then semiotic physics is indeed the right level. --- ### 6. A Deeper Thought: What Is the "Order" We Appreciate? There's a philosophical question lurking here: when we appreciate the "order" in Pollock's marks, what exactly are we appreciating? One answer: we appreciate the **causal intelligibility** of the marks. We see the drips as _lawful_—as products of identifiable forces operating according to their natures. The pleasure is in the _understanding_. Another answer: we appreciate the **visible structure** that the forces have produced—the rhythms, textures, densities, the interplay of colors. The pleasure is in the _perception_. These are not mutually exclusive. Carlson's view seems to be that knowledge enhances perception: knowing the forces makes the visible structure _more_ visible, more intelligible, more appreciable. But they might come apart. You could imagine someone who _understands_ the physics perfectly but doesn't _see_ the beauty. Or someone who _sees_ the beauty without understanding the physics at all. The Carlsonian claim is that the best appreciation combines both: informed perception, where knowledge guides and enhances what you see. --- ### Summary Yes, I think knowledge of fluid dynamics (rheology, specifically) would enhance appreciation of Pollock's marks—because the marks are indices of physical events, and understanding the causal structure allows you to _read_ more in the indices. The appreciation is not just of the visible pattern but of the pattern _as_ a trace of forces. The more you understand the forces, the more you can appreciate the order they have imposed. But there are limits. The knowledge must be _perceivable_ in the marks, not just abstractly known. And it must be _integrated_ into an --- Nick Young: Okay, I'm not sure I agree with everything you're saying here, but let's press on. It occurs to me there's another sort of knowledge one could employ here, which would be practical knowledge. of paint and drips and splatters and forces of a very deep level but non-scientific. So now you could imagine a job in which somebody works with paint a lot. knows how paint and different types of paint behave as it were and yeah what would you say about Would that factor in to the aesthetics of appreciation? Sorry, would that factor into appreciation? Do you think? Think about what Carlson says is required for a non-aesthetic story. He defaults to scientific stories, but does anything he say rule out the possibility of practical knowledge? Should practical knowledge be rule? Ruled out as the non-aesthetic story One more thing. To help you get a better idea of Carlson's ideas in general, I'm going to copy in load of quotes from the book in which the paper you've read is found. Okay, so these are lots of quotes from him that I like. Most of them, in fact, I'd say the yeah, the vast majority of them will not be relevant here but I just wanted to make sure you had a slightly sort of broader knowledge of his general ideas about things okay and who knows maybe some of these quotations will be useful For you, okay, but yeah, keep them if not at the forefront of your mind, at least somewhere in mind when you're answering the question above. quotes from carlson ( a lot won't be immediately or directly relevant , i just want you to broaden your understanding of his views): (attached) --- Raycast AI: The user is asking a very interesting question: could _practical knowledge_ of paint and its behavior—the kind of knowledge a house painter, a sign painter, or a studio assistant might have—serve as the "nonaesthetic story" that Carlson requires for order appreciation? Or does Carlson's framework rule this out in favor of scientific knowledge specifically? Let me think carefully about this. --- **What Does Carlson Actually Say?** Looking at the quotes the user has provided, Carlson is often quite explicit about "scientific knowledge" and "common-sense/scientific knowledge." For example: > "This model suggests that in aesthetic appreciation of anything, be it people or pets, farmyards or neighborhoods, shoes or shopping malls, appreciation must be centered on and driven by the real nature of the object of appreciation itself. In all such cases, what is appropriate is not an imposition of artistic or other inappropriate ideals, but rather dependence on and guidance by means of knowledge, scientific or otherwise, that is relevant given the nature of the thing in question." The phrase **"scientific or otherwise"** is crucial here. Carlson explicitly allows for knowledge that is _not_ scientific to play the guiding role, as long as it is "relevant given the nature of the thing in question." Another key passage: > "If we recognize our scientific knowledge of the natural world as only a finer-grained and theoretically richer version of our common, everyday knowledge of it, and not as something essentially different in kind, then the difference between the arousal model and the natural environmental model is mainly one of emphasis." Here Carlson presents scientific knowledge and common, everyday knowledge as on a **continuum**—they are not "essentially different in kind." Scientific knowledge is a "finer-grained and theoretically richer version" of common knowledge, but both track the same underlying reality. This suggests that practical, experiential knowledge could be on this continuum. A house painter's knowledge of how paint behaves is not scientific in the sense of being formalized in equations or peer-reviewed journals, but it is knowledge of the same phenomena that rheology studies. It is practical, embodied, know-how rather than know-that—but it is still knowledge of how paint works. --- **The Function of the "Nonaesthetic Story"** Carlson says that order appreciation requires: > "a general nonaesthetic and nonartistic story that helps make them appreciable by making this order visible and intelligible." What does the "story" need to do? It needs to make the order **visible and intelligible**. It needs to guide **acts of aspection**—what to look for, where to focus attention. Does practical knowledge do this? I think it clearly can. A house painter looking at a Pollock might see: - "That drip is from a paint that's been thinned too much—you can tell by how it ran." - "That thick blob—he must have let it sit for a moment before moving on." - "See how the edges of that line are sharp? The paint was the right consistency for that." - "That layering only works because he let the first layer dry before the second—otherwise they'd have mixed." This is knowledge that makes the order visible and intelligible. It tells you what to look for. It explains why the marks are as they are. It is not formalized as fluid dynamics, but it tracks the same causal structure. --- **Is Practical Knowledge "Nonaesthetic"?** Carlson requires the story to be "nonaesthetic and nonartistic." Is practical knowledge nonaesthetic? I think so. The house painter's knowledge of how paint behaves is not knowledge of beauty or aesthetic value; it is knowledge of how materials work. It is instrumental, practical knowledge—knowledge aimed at getting a job done, not at appreciating beauty. Of course, when this knowledge is _applied_ to aesthetic appreciation, it enhances the appreciation. But the knowledge itself is nonaesthetic in content. --- **The Continuum of Knowledge** I think the best way to understand this is as a continuum: 1. **Raw experience**: You see the drips but have no idea what caused them. 2. **Basic common sense**: You know that paint drips when it's wet and gravity pulls it down. 3. **Practical expertise**: You know how different paints behave, how viscosity affects flow, how drying time affects layering—all from hands-on experience. 4. **Scientific knowledge**: You know the equations of fluid dynamics, the physics of non-Newtonian fluids, the mathematics of droplet formation. Carlson's view, as I read it, is that any point on this continuum (beyond raw experience) can serve as the "nonaesthetic story." The further along the continuum you go, the finer-grained and more theoretically rich your appreciation can be. But there is no sharp cutoff. This is supported by the passage: > "If we recognize our scientific knowledge of the natural world as only a finer-grained and theoretically richer version of our common, everyday knowledge of it, and not as something essentially different in kind..." Practical expertise is somewhere between common sense and scientific knowledge on this continuum. It is more fine-grained than basic common sense but less theoretically articulated than science. It is embodied know-how rather than propositional know-that. --- **Should Practical Knowledge Be Ruled Out?** I don't think Carlson rules it out, and I don't think it _should_ be ruled out. Here's why: 1. **It tracks the same causal structure.** The practical knowledge of a house painter is knowledge of the same phenomena that rheology studies—just in a different form. Both are knowledge of how paint behaves. 2. **It can guide aspection.** Practical knowledge tells you what to look for, where to focus attention, what distinctions to make. This is exactly what Carlson says the nonaesthetic story should do. 3. **It makes order visible and intelligible.** With practical knowledge, you can _see_ things in the marks that you couldn't see before. You can understand why they are as they are. 4. **Carlson explicitly allows "knowledge, scientific or otherwise."** The phrase "or otherwise" opens the door to non-scientific knowledge, as long as it is relevant. --- **A Possible Objection: Is Practical Knowledge "A Story"?** One might object that practical knowledge is not a "story" in the way that scientific knowledge is. Scientific knowledge provides a narrative of causes and effects, a framework for understanding why things are as they are. Practical knowledge is more tacit, more embodied—you know how to do something without necessarily being able to articulate why. But I don't think this is a deep objection. First, practical experts _can_ often articulate their knowledge, at least partially. They can say things like "this paint is too thin" or "he must have let it dry first." Second, even tacit knowledge can guide aspection—you can look at a mark and _see_ that it was made with thin paint, even if you can't fully articulate the physics. Moreover, Carlson talks about knowledge guiding "acts of aspection"—what to look at, how to look at it. Tacit practical knowledge can do this just as well as explicit scientific knowledge. The experienced painter _knows_ what to look for, even if they can't write it down in equations. --- **The Relationship Between Practical and Scientific Knowledge** There's an interesting question here about the relationship between practical and scientific knowledge. Are they: 1. **The same knowledge in different forms?** Both track the same causal structure, but scientific knowledge is explicit and propositional while practical knowledge is tacit and embodied. 2. **Different kinds of knowledge?** Scientific knowledge is theoretical and general; practical knowledge is contextual and particular. 3. **Complementary?** Each reveals aspects that the other misses. I suspect the answer is something like (3). A rheologist might know the equations but not have the _feel_ for how paint behaves in practice. A house painter might have the feel but not the theoretical understanding. Together, they know more than either alone. For aesthetic appreciation, both kinds of knowledge could enhance appreciation in different ways. The scientific knowledge might reveal abstract patterns and principles; the practical knowledge might reveal concrete particulars and fine distinctions. --- **Application to LLMs** This question is directly relevant to your project. You are proposing "semiotic physics" as the nonaesthetic story for LLM appreciation. But what about practical knowledge of LLMs—the kind of knowledge that heavy users, prompt engineers, or researchers develop through extensive interaction? On the Carlsonian view (as I'm reading it), this practical knowledge should also count. If you've spent thousands of hours prompting a particular model, you develop a _feel_ for how it behaves—what kinds of prompts elicit what kinds of responses, where its tendencies and tics are, how to push it in certain directions. This is practical expertise, not scientific theory. But it is knowledge of the same phenomena that semiotic physics describes. In your paper, you actually gesture toward this in Section 5.2 on "Interaction": > "By prompting, experimenting, and observing how a system responds across many contexts, users develop acquaintance with its behavior. They learn how the model tends to react to certain phrasings, which requests produce thin or repetitive answers, how far they can push a given register or style, what kinds of follow-up will elicit clarification rather than evasion. This practical knowledge is, in effect, a felt sense of the model's semiotic physics." This is exactly the practical knowledge analogue. The experienced user has practical expertise that parallels the practical expertise of the house painter. Both know how their respective systems behave, even if they can't articulate it in scientific terms. --- **A Final Thought: The Primacy of the Object** Carlson's fundamental principle is that appreciation should be "centered on and driven by the real nature of the object of appreciation itself." The nonaesthetic story is in service of this principle—it helps us appreciate the object as what it truly is. From this perspective, the question is not whether the knowledge is scientific or practical, but whether it is _true_ and _relevant_. Does it accurately represent how the object works? Does it guide attention to features that are genuinely there? Both scientific and practical knowledge can meet these criteria. Both can be true and relevant. Therefore, both should be admissible as the nonaesthetic story. The advantage of scientific knowledge is its explicitness, generality, and theoretical depth. The advantage of practical knowledge is its concreteness, particularity, and embodied feel. The best appreciation might draw on both. --- Let me now structure a response that addresses the user's question directly. <final_answer> This is an excellent question, and I think it goes to the heart of what Carlson actually requires of the "nonaesthetic story." --- ### Does Carlson Rule Out Practical Knowledge? No. Looking carefully at his formulations, Carlson explicitly leaves room for non-scientific knowledge. The key passage is: > "In all such cases, what is appropriate is not an imposition of artistic or other inappropriate ideals, but rather dependence on and guidance by means of **knowledge, scientific or otherwise**, that is relevant given the nature of the thing in question." The phrase **"scientific or otherwise"** is doing important work. Carlson is not insisting that only scientific knowledge can play the guiding role. What he requires is that the knowledge be (a) **relevant** to the nature of the object, and (b) able to make the order **visible and intelligible**. He also says: > "If we recognize our scientific knowledge of the natural world as only a **finer-grained and theoretically richer version of our common, everyday knowledge** of it, and not as something essentially different in kind, then the difference between the arousal model and the natural environmental model is mainly one of emphasis." This presents scientific and common-sense knowledge as lying on a **continuum**, not as fundamentally different kinds. Scientific knowledge is more fine-grained and theoretically articulated, but it is tracking the same reality as common-sense knowledge. Practical expertise—the kind of deep, hands-on knowledge that a house painter or studio assistant develops through years of working with materials—sits somewhere on this continuum. It is more fine-grained than basic common sense ("paint drips down") but less theoretically articulated than fluid dynamics. It is embodied know-how rather than propositional know-that. --- ### What Does the "Nonaesthetic Story" Need to Do? Carlson says the story must: 1. **Make the order visible**: Help the appreciator perceive features they would otherwise miss. 2. **Make the order intelligible**: Explain _why_ the marks are as they are—what caused them. 3. **Guide acts of aspection**: Tell you what to look for, where to focus attention, what distinctions matter. Does practical knowledge do these things? Clearly yes. Consider a house painter looking at a Pollock. They might see: - "That drip ran too far—he thinned the paint more than I would for that effect." - "See how the edges are sharp there but feathered over here? Different viscosities, or maybe different speeds." - "That layering only works because he let the first coat dry—otherwise it would have muddied." - "The way that line beaded up—that's what happens when you move too slow with enamel." This is knowledge that makes the order visible (you can now _see_ the viscosity difference) and intelligible (you understand _why_ the marks differ). It guides aspection by telling you what to look for. --- ### The Continuum of Knowledge I would propose thinking of this as a continuum: | | | | |---|---|---| |Level|Example (Pollock)|Character| |**Raw experience**|"I see drips and splatters"|No causal understanding| |**Basic common sense**|"Paint drips because of gravity"|Minimal causal understanding| |**Practical expertise**|"That's a fast-drying enamel, applied at high speed, layered wet-on-dry"|Rich causal understanding, tacit/embodied| |**Scientific theory**|"The filament thinning follows Rayleigh-Plateau instability; the shear-thinning exponent is..."|Rich causal understanding, explicit/theoretical| On this continuum, any level beyond raw experience can serve as the "nonaesthetic story." The further you go, the finer-grained your appreciation can be. But there is no sharp cutoff where appreciation suddenly becomes "appropriate." Carlson's preference for scientific knowledge is, I think, a preference for the _theoretically richer_ end of the continuum—but not an exclusion of the rest. --- ### Practical Knowledge as Tacit Theory There's an interesting question about whether practical knowledge is _really_ different from scientific knowledge, or whether it's the same knowledge in a different form. The practical expert _knows_ something—they can discriminate, predict, and manipulate in ways that novices cannot. They have internalized regularities in the behavior of their materials. This is, in a sense, a tacit theory of those materials—not written down in equations, but encoded in embodied skill and perceptual discrimination. When the house painter looks at a Pollock and says "that's enamel, applied fast, at that viscosity," they are applying a tacit theory of paint behavior. The theory is not explicit, but it is _there_—guiding perception and inference. From this perspective, practical knowledge and scientific knowledge are two ways of encoding the same causal structure. The scientist encodes it in propositions and equations; the practitioner encodes it in skills and perceptual discriminations. Both track the same reality. --- ### The Advantages and Limitations of Each **Practical knowledge** has certain advantages: - It is _fine-tuned_ to the particular materials and contexts the practitioner works with. - It includes perceptual discriminations that are hard to articulate—the "feel" of the material. - It is immediately applicable to appreciation—the practitioner _sees_ differences without needing to compute them. **Scientific knowledge** has other advantages: - It is _general_—it applies to any fluid, not just house paint. - It is _explicit_—it can be communicated, taught, and debated. - It reveals _deep structure_—connections to other phenomena (lava flows, ocean waves, galaxy formation). For aesthetic appreciation, both can enhance the experience. The practical expert sees fine distinctions; the scientist sees broad connections. The best appreciation might draw on both. --- ### Application to Your Project This question is directly relevant to "Planet of Signs." You propose "semiotic physics" as the nonaesthetic story for LLM appreciation. But what about the practical knowledge that heavy users develop through extensive interaction? Your Section 5.2 on "Interaction" actually gestures toward this: > "By prompting, experimenting, and observing how a system responds across many contexts, users develop acquaintance with its behavior... This practical knowledge is, in effect, a felt sense of the model's semiotic physics." On the Carlsonian view, this practical knowledge should count just as much as the theoretical account. The experienced user has internalized regularities in the model's behavior—they know (tacitly) what kinds of prompts produce what kinds of responses, where the model's tendencies lie, how to push it in certain directions. This is the LLM equivalent of the house painter's practical expertise. The theoretical account of semiotic physics and the practical knowledge of the experienced user are, perhaps, two forms of the same knowledge—one explicit and general, the other tacit and particular. Both can guide aspection; both can make the order visible and intelligible. --- ### Conclusion To directly answer your question: **No, practical knowledge should not be ruled out as --- Nick Young: There's some good ideas there, although I think you've missed the point more broadly. Doesn't matter, let's keep moving. First thing to say is the reason why I asked you about practical knowledge was actually because even though someone who works with paint will definitely have more practical knowledge than The average Joe um It still seems plausible to say that most people who look at a pollock will look at it as look at it with the knowledge of somebody sorry, with knowledge about rough and ready folk knowledge about how liquid spatters and how pain splatters. Okay. Um so I want to say is that Yeah, it seems like seems to me like we've got a reasonably easy story to tell about why ordinary people can be sensitive to and thereby appreciate that aspect of Pollock's paintings. Okay, so that was my so yeah, I was talking about more um expert sorts of practical knowledge just to get us here to this more average Joe type Okay, so now let's talk about the average Joe type for LLMs. One thing that the average Joe type is, look, they will not have any knowledge of LLMs. Okay, but what they will have is they will have knowledge tacit knowledge of the English language. Perhaps even very good tacit knowledge of the English language. Perhaps they are literature professors or poets or something like that. So yeah, I wonder if that's a similar parallel. So the absolute yeah, so the um the non Expert, the ordinary non-expert in both cases, just comes along with sort of a practical knowledge. Um nothing more than that. In the collar case, they don't know exactly how these things were created. In the LLM case, they don't know how LLMs work. Perhaps we would have to say they do know that it's not a personal though. I'm not quite sure where I'm going with this, but intuitively these seem to me like good places to start thinking harder about and poking around within. --- Raycast AI: The user is making a really interesting move here. Let me trace the logic: 1. For Pollock, the "nonaesthetic story" doesn't have to be fluid dynamics or rheology. Even ordinary people have _folk knowledge_ of how liquids behave—they've spilled coffee, watched rain run down windows, seen paint drip. This folk knowledge is enough to see the drips as "marks of forces." You don't need to know the Navier-Stokes equations to see that gravity pulled the paint down, or that thicker paint behaves differently from thinner paint. 2. The user is suggesting a parallel for LLMs: ordinary people don't know how transformers work, don't know about attention heads or embeddings or probability distributions. But they _do_ have deep tacit knowledge of their own language. They know (tacitly) what kinds of sentences are well-formed, what kinds of continuations are natural, what registers and genres sound like, how arguments typically unfold. 3. The question is: can this tacit linguistic knowledge play the same role for LLM appreciation that folk knowledge of liquids plays for Pollock appreciation? This is a fascinating parallel. Let me think about it more carefully. --- **The Pollock Case: Folk Knowledge of Liquids** When an ordinary person looks at a Pollock, they don't see "random chaos." They see drips, splatters, pools, runs. They can _read_ these marks because they have extensive experience with how liquids behave. They know: - Liquids flow downward (gravity) - Thin liquids flow faster and farther than thick liquids - Fast-moving liquids splatter; slow-moving liquids pool - Liquids leave trails when moved across surfaces - Layers of liquid interact (mixing, sitting on top, bleeding through) This is not scientific knowledge. It's not even practical expertise in the sense of a house painter's skill. It's just... ordinary human experience with liquids, accumulated over a lifetime. And yet, this folk knowledge is _enough_ to see the order in a Pollock. You can see that the drips are drips—traces of paint falling under gravity. You can see that some areas are thicker, some thinner. You can see the layering. You don't need to know _why_ liquids behave this way (the physics); you just need to know _that_ they do. The Pollock becomes appreciable as "marks of forces" because you have tacit knowledge of the forces involved. --- **The LLM Case: Folk Knowledge of Language** Now, the parallel. When an ordinary person reads LLM output, they don't know about transformers, attention, embeddings, or probability distributions. But they _do_ have extensive tacit knowledge of language. They know: - What kinds of sentences are grammatical - What kinds of continuations are natural or surprising - What registers sound formal, casual, academic, poetic - How arguments typically unfold - What genres sound like (news articles, fiction, academic papers) - What kinds of hedging, qualification, and emphasis are appropriate in different contexts This knowledge is not explicit. Most people can't articulate the rules of English grammar, let alone explain why certain continuations feel natural. But they _have_ this knowledge—it's what allows them to understand and produce language. When they read LLM output, they can perceive when something sounds "right" or "off." They can notice when the model is being evasive, repetitive, or unusually creative. They can sense when the style shifts unexpectedly, or when the reasoning feels thin. Is this tacit linguistic knowledge _enough_ to appreciate LLM output as "marks of forces"—even without knowing what the forces are? --- **The Disanalogy: Visibility of the Forces** Here's where I see a potential disanalogy. In the Pollock case, the folk knowledge of liquids allows you to see the drips _as_ drips—as marks of gravity and viscosity. The connection between the knowledge (how liquids behave) and the perception (seeing the drip as a drip) is direct. You know liquids drip, so you see the mark as a drip. In the LLM case, the connection is less direct. Your tacit knowledge of language allows you to perceive when a sentence is well-formed, when a continuation is natural, when a style is consistent. But does it allow you to see these features _as_ marks of the forces that produced them? The issue is that the "forces" in the LLM case are not visible in the same way. When you see a Pollock drip, you can imagine the paint falling—you can almost _see_ gravity at work. When you read an LLM sentence, you don't see the probability distribution, the attention pattern, the embedding space. You just see... a sentence. So the question is: what are you seeing the sentence _as_, when you appreciate it? --- **Two Possibilities** **Possibility 1: You appreciate the sentence as a continuation of language.** Your tacit linguistic knowledge tells you that this sentence is a natural continuation of what came before. It sounds right. The style is consistent. The argument flows. In this case, you are appreciating the sentence as conforming to the regularities of language—the same regularities that the LLM has learned from its training data. You don't know that the LLM learned these regularities, but you _recognize_ them because you know them too. This is analogous to looking at a Pollock and appreciating the drips as conforming to the regularities of liquid behavior—without knowing that Pollock "learned" these regularities (in a sense) by working with paint. **Possibility 2: You appreciate the sentence as a product of** _**some**_ **generative process.** Even without knowing how LLMs work, you might appreciate the text as having been _produced_ by something—some process that generates these patterns. The text has a certain character, a certain "feel," that is consistent across outputs. You might appreciate this consistency, this characteristic style, without knowing what produces it. This is analogous to looking at a Pollock and appreciating the overall texture, the characteristic "Pollock look," without understanding exactly how it was made. You see that there's a process at work—some way of making these marks—and you appreciate the results of that process. --- **The Role of Knowing It's Not a Person** The user raises an interesting point: "Perhaps we would have to say they do know that it's not a person though." This matters because if you think you're reading a human's writing, you might appreciate it differently—as an expression of a mind, a personality, a life. Knowing that it's _not_ a person shifts the frame. You're no longer looking for intention, self-expression, or personal style in the way you would with a human author. But what are you looking for instead? If it's not a person, what is it? The user's paper argues that you shouldn't treat the LLM as a person (make-believe or otherwise). But if the reader doesn't know what an LLM _is_, only that it's _not_ a person, what frame do they bring? Maybe this is where the analogy to Pollock is useful. When you look at a Pollock, you don't see it as the expression of a designing intellect (like a Rembrandt). You see it as the result of a process—a process involving paint, gravity, motion. You appreciate the marks as traces of that process. Could the ordinary reader approach LLM output similarly? Not as the expression of a person, but as the result of a process—a process involving language, patterns, generation. They might not know _what_ process, but they can appreciate the text _as_ the product of some process. --- **The Knowledge Requirement Revisited** Let me think about what knowledge the ordinary appreciator actually needs. For Pollock: - Folk knowledge of how liquids behave (tacit, from experience) - Knowledge that this is not a conventional painting (contextual, art-historical) - Ideally: some sense that the marks are _traces_ of a process, not deliberate placements For LLMs: - Tacit knowledge of language (from being a competent speaker/reader) - Knowledge that this is not written by a person (contextual) - Ideally: some sense that the text is _generated_ by a process, not authored by a mind The parallel is suggestive. In both cases, the appreciator brings tacit knowledge of the relevant regularities (liquids, language). In both cases, they need to know that this is not a conventional case (not a designed painting, not a human author). And in both cases, the ideal frame is one of seeing the output as a trace of a process. --- **But What Is the "Order" They Appreciate?** In the Pollock case, the "order" is the lawfulness of liquid behavior—the way the drips follow gravity, the way viscosity affects flow. The appreciator sees this order because they have folk knowledge of liquids. In the LLM case, what is the analogous "order"? One answer: the order is the lawfulness of _language_—the regularities of syntax, semantics, genre, register. The appreciator sees this order because they have tacit knowledge of language. But wait—is this the _LLM's_ order, or is it just the order of language in general? Here's a key point: the LLM has learned the regularities of language from its training data. The regularities it exhibits are (approximately) the regularities of human language use. So when the appreciator recognizes these regularities, they are recognizing something that is both (a) a feature of the LLM's behavior and (b) a feature of language in general. This is actually parallel to Pollock. The regularities in a Pollock painting are both (a) features of that specific painting and (b) features of liquid behavior in general. The drips follow the laws of physics—laws that apply to all liquids, not just paint on Pollock's canvas. So the "order" in both cases is the instantiation of general regularities (physical, linguistic) in a specific case (this painting, this text). The appreciator recognizes the general regularities and appreciates their specific instantiation. --- **The "Average Joe" Appreciator** Let me think about what the ordinary, non-expert appreciator can appreciate in each case. **Pollock:** - They can see the drips as drips (not as, say, brushstrokes or deliberate marks) - They can appreciate the texture, rhythm, density of the drips - They can perceive the layering, the interaction of colors - They can sense the energy, motion, dynamism of the process - They can appreciate the "Pollock-ness"—the characteristic look of his work What they probably _can't_ do without more knowledge: - Discriminate fine differences in viscosity or paint type - Understand exactly how the layering was achieved - See the specific physics at work in each mark **LLM output:** - They can perceive when the text is well-formed, natural, fluent - They can appreciate the style, register, tone - They can notice consistency or inconsistency across the text - They can sense when something is "off"—repetitive, evasive, generic - They can appreciate the "Claude-ness" or "GPT-ness"—the characteristic feel of a model's output What they probably _can't_ do without more knowledge: - Understand _why_ the model produces these patterns - Discriminate fine differences in model architecture or training - See the specific mechanisms at work (attention, embeddings, etc.) The parallel seems to hold. The ordinary appreciator can appreciate _that_ there is order—can perceive the regularities and respond to them—without understanding _why_ there is order (the underlying mechanisms). --- **Is This Enough for "Order Appreciation"?** Carlson's order appreciation requires: 1. Seeing the order as produced by forces 2. Having a "nonaesthetic story" that makes the order visible and intelligible The question is whether folk knowledge (of liquids or language) is _enough_ of a story. I think it might be. The folk knowledge makes the order _visible_—you can see the drips as drips, the sentences as natural continuations. It makes the order _somewhat_ intelligible—you understand that liquids drip, that language flows in certain ways. What the folk knowledge doesn't provide is a _deep_ explanation of why the forces produce these effects. But maybe that's okay. Maybe appreciation can operate at different levels of depth, and the folk-knowledge level is one legitimate level. This is consistent with Carlson's claim that scientific and common-sense knowledge are on a continuum. The folk-knowledge appreciator is at the common-sense end; the expert is further along. Both are doing order appreciation, just at different levels of depth. --- **A Remaining Puzzle: The "As" Structure** There's still something puzzling here. In order appreciation, you appreciate the marks _as_ marks of forces. You see them _as_ traces of gravity, viscosity, motion. In the folk-knowledge Pollock case, you can do this. You see the drip _as_ a drip—as paint that fell under gravity. You don't need to know the physics of fluid dynamics to see it this way. Your folk knowledge is enough. In the folk-knowledge LLM case, what do you see the text _as_? As a natural continuation of language? As a grammatical sentence? As a stylistically appropriate response? These are all true, but they're not quite the same as seeing the text _as_ a mark of forces. They're more like seeing the text _as_ conforming to regularities. Maybe this is the key difference. In the Pollock case, you see the mark as _produced by_ forces (gravity made this drip). In the LLM case, you see the text as _conforming to_ regularities (this is a natural continuation)—but you don't necessarily see it as _produced by_ specific forces. Unless... you see the text as produced by _language itself_? As if language were a kind of force that generates certain patterns? This is actually close to what Janus and Picca are saying with the "simulator" and "semiotic machine" framings. The LLM is a system that propagates text according to learned regularities. The regularities are, in a sense, "forces" that shape the output. But for the ordinary appreciator who doesn't know this... what do they see the text as produced by? Maybe they don't need to have a specific answer. They can appreciate the text as _generated_—as the output of some process—without knowing what process. They can attend to the regularities, the characteristic patterns, the "feel" of the output, without having a theory of what produces it. This is perhaps analogous to appreciating a natural phenomenon without knowing the science. You can appreciate the pattern of clouds without knowing atmospheric physics. You see that there's regularity, that there's structure, that something has shaped these forms. You don't know what, but you can appreciate the order. --- **Tentative Conclusion** The parallel seems to work, at least partially: | | | | |---|---|---| ||Pollock|LLM| |**Folk knowledge**|How liquids behave|How language works| |**What you perceive**|Drips, splatters, layers|Sentences, styles, patterns| |**What you see them as**|Traces of physical forces|Conforming to linguistic regularities| |**What you might NOT know**|The physics; how Pollock worked|How LLMs work; the mechanisms| |**What you appreciate**|The instantiation of liquid-regularities in this specific texture|The instantiation of language-regularities in this specific text| The disanalogy is in the "produced by" structure. For Pollock, you can easily see the drip as _produced by_ gravity—you can imagine the paint falling. For LLMs, it's less clear what you see the text as _produced by_, if you don't know about the mechanism. But maybe this disanalogy is not fatal. You can appreciate the text as _generated_—as the output of some process—and attend to its characteristic patterns, without knowing the process. This is a thinner form of order appreciation, but it might still be order appreciation. The user's paper might be able to exploit this. The folk-knowledge appreciator can appreciate LLM output at a certain level—recognizing linguistic regularities, sensing characteristic styles, noticing when things are "off." This is appreciation guided by tacit linguistic knowledge. The more expert appreciator—one who knows "semiotic physics"—can appreciate at a deeper level, seeing the text as produced by specific mechanisms. Both are legitimate; they're on a continuum. <final_answer> This is a genuinely productive parallel, and I think you're onto something important. Let me work through it carefully. --- ### The Pollock Case: Folk Knowledge as Sufficient You're right that ordinary people don't need fluid dynamics to appreciate Pollock. They have **folk knowledge of liquids**—accumulated through a lifetime of spilling, pouring, dripping, and watching. They know (tacitly) that: - Liquids fall downward - Thin liquids run farther than thick ones - Fast-moving liquids splatter; slow-moving liquids pool - Liquids leave trails, layer on top of each other, sometimes mix This folk knowledge is enough to see the drips _as drips_—as traces of paint falling under gravity, not as deliberate brushstrokes or representational marks. The ordinary viewer can appreciate the **order** in a Pollock because they recognize the regularities of liquid behavior instantiated in the marks. They don't know _why_ liquids behave --- Nick Young: "In the folk-knowledge LLM case, what do you see the text as? As a natural continuation of language? As a grammatical sentence? As a stylistically appropriate response? These are all true, but they're not quite the same as seeing the text as a mark of forces. They're more like seeing the text as conforming to regularities. Maybe this is the key difference. In the Pollock case, you see the mark as produced by forces (gravity made this drip). In the LLM case, you see the text as conforming to regularities (this is a natural continuation)—but you don't necessarily see it as produced by specific forces." When you say stuff like this and other times you make me think that yeah we need to change things slightly in the case of the LLMs to make things fit together better. So, how would this be? to put themselves into a position of the average Joe when it comes to product somebody looking at an LLN output would need to know not just the English language but also have some understanding of the sorts of system that MLMs are and how they process language. language here because we're staying at the level of signs of course. Do you see why I want to say all this? IMPORTANT: Please remember to follow your system prompt to the letter!! Please make sure to for at least 45 minutes before giving me your final answer(s). --- Raycast AI: The user is making a crucial point. Let me trace their reasoning carefully. In the Pollock case, folk knowledge of liquids is sufficient because: 1. Everyone has tacit knowledge of how liquids behave 2. This knowledge allows you to see the drips _as_ produced by forces (gravity, viscosity) 3. You don't need scientific knowledge of fluid dynamics—the folk knowledge is enough to see the marks as "marks of forces" But I noted a potential disanalogy for LLMs: - Tacit knowledge of language lets you see the text as _conforming to_ regularities - But it doesn't obviously let you see the text as _produced by_ forces - There's an asymmetry: for Pollock, you can imagine the paint falling; for LLMs, you can't imagine the probability distribution computing The user is now suggesting that to fix this asymmetry, the "average Joe" for LLM appreciation needs something _more_ than just tacit knowledge of English. They need _some understanding of what LLMs are and how they process language_. This would parallel the Pollock case better. The folk knowledge of liquids includes not just knowledge of _what liquids do_ but also a rough sense of _why they do it_—gravity pulls them down, thickness resists flow. This is not scientific knowledge, but it's causal-mechanistic in a folk way. For LLMs, the parallel would be: the "average Joe" needs not just tacit knowledge of _what language does_ but also a rough sense of _how LLMs generate language_. Not the technical details, but something like: - It's a system that predicts what comes next - It has learned patterns from lots of text - It generates by sampling from these patterns - It doesn't "understand" in the way humans do This folk-level understanding of LLMs would allow the appreciator to see the text as _produced by_ the LLM's generative process, not just as _conforming to_ linguistic regularities. Let me think about whether this is right, and what it implies. --- **Why the Asymmetry Exists** The asymmetry between Pollock and LLMs is real, and I think it stems from the _visibility_ of the causal process. For liquids: - The causal process is _visible_. You can watch paint drip. - Even when you see a static painting, you can _imagine_ the process—the paint falling, pooling, splattering. - Folk knowledge of liquids is knowledge of a _visible_ process. For LLMs: - The causal process is _invisible_. You can't watch the probability distribution compute. - When you see the text, you see only the output, not the process that generated it. - Tacit knowledge of language is knowledge of _regularities in the output_, not of the process that produces the output. This is why tacit knowledge of English is not quite sufficient. It tells you what language _looks like_, but not how this particular text was _produced_. To close the gap, the appreciator needs some understanding of the generative process—not the technical details, but enough to see the text _as generated_ by a particular kind of system. --- **What Would "Folk Knowledge of LLMs" Look Like?** The user suggests that the "average Joe" for LLM appreciation would need "some understanding of the sorts of system that LLMs are and how they process language." What would this look like? What's the minimum knowledge needed to see the text as "produced by forces" rather than just "conforming to regularities"? I think it would include something like: 1. **It's not a person.** The text is not written by a human with beliefs, intentions, and a life history. There's no "author" in the traditional sense. 2. **It's a generative system.** The text is produced by a system that generates language—not by retrieving pre-written answers, but by generating token-by-token. 3. **It's pattern-based.** The system has learned patterns from large amounts of text. What it produces reflects these learned patterns. 4. **It's probabilistic.** The system doesn't deterministically produce one answer; it samples from possibilities. There's a kind of "randomness within structure." 5. **It doesn't "understand" like we do.** The system processes language in a fundamentally different way from humans—through statistical associations, not through meaning-grasp in the human sense. This is not technical knowledge. It doesn't require understanding transformers, attention, embeddings, or backpropagation. It's a _folk-level_ understanding of what kind of thing an LLM is. But it's more than just knowing English. It's knowing something about the _source_ of the text—the kind of system that produced it. --- **The Parallel to Pollock** With this addition, the parallel to Pollock becomes tighter: | | | | |---|---|---| ||Pollock|LLM| |**Knowledge of regularities**|Folk knowledge of how liquids behave|Tacit knowledge of how language works| |**Knowledge of the process**|Folk understanding of dripping, pouring, splattering (visible process)|Folk understanding of what LLMs are and how they generate (invisible process, must be told)| |**What you see the marks/text as**|Produced by physical forces acting on paint|Produced by a pattern-learning system generating language| The key difference is that for Pollock, the folk knowledge of the process comes "for free" from everyday experience with liquids. For LLMs, it has to be _acquired_—you have to learn that this is an LLM and have some sense of what that means. This is because the LLM's generative process is not part of ordinary human experience in the way that liquid behavior is. We've all spilled coffee; we haven't all watched a language model compute. --- **The "Average Joe" for LLM Appreciation** So who is the "average Joe" for LLM appreciation? Not just anyone who knows English—that's not enough. The average Joe would be someone who: 1. Has tacit knowledge of English (or whatever language) 2. Knows that this text was produced by an LLM (not a human) 3. Has a folk-level understanding of what LLMs are—pattern-learning, generative, probabilistic, non-understanding This is a higher bar than for Pollock appreciation. For Pollock, you just need to know it's paint and to have ordinary experience with liquids. For LLMs, you need to know it's an LLM and have some (perhaps minimal) understanding of what that means. But this higher bar is not unreasonable. As LLMs become more widespread, more people will have this folk-level understanding. It will become part of ordinary cultural knowledge—"these are AI systems that generate text by predicting what comes next based on patterns in lots of data." --- **Why This Matters for the "Produced By" Structure** The user's insight is that without this folk knowledge of LLMs, you can't see the text as _produced by_ the relevant forces. You can only see it as _conforming to_ linguistic regularities. Why is this insufficient? Because "conforming to regularities" doesn't have the same causal/indexical structure as "produced by forces." When you see a Pollock drip as a drip, you see it as the _trace_ of a physical event—paint falling under gravity. The mark is an index of the event. You can (imaginatively) "run the process backward" from the mark to the event. When you see an LLM sentence as "natural-sounding," you're not seeing it as a trace of anything in particular. You're just noticing that it fits the pattern. There's no imaginative "running backward" to a generative event. But if you have folk knowledge of LLMs, you _can_ see the sentence as a trace of the generative process. You can think: "This is what the model produced when it sampled from its learned patterns given this prompt." The sentence becomes an index of the generative event. This is the key: **the folk knowledge of LLMs makes the text indexical**. Without it, the text is just text that happens to be well-formed. With it, the text is a trace of a generative process. --- **Staying at the Level of Signs** The user adds: "we're staying at the level of signs of course." This is important. The user's paper proposes "semiotic physics"—regularities at the level of signs (tokens, words, sentences), not at the level of sub-symbolic computation. The folk knowledge of LLMs that the average Joe needs is also at the level of signs. They don't need to know about attention heads or embedding spaces. They need to know that: - The LLM works with language (signs) - It predicts what sign comes next based on patterns in language - It has learned these patterns from lots of language - Its outputs are shaped by these learned patterns This is all at the semiotic level. The "forces" that shape the output are semiotic forces—patterns of sign-following-sign. The appreciator who has this folk understanding can see the text as produced by semiotic forces, without needing to understand the sub-symbolic machinery. --- **A Potential Objection: Is This Too Much?** One might object: doesn't this make LLM appreciation too demanding? Pollock appreciation just requires ordinary experience with liquids. LLM appreciation requires specific knowledge about a new technology. But I think this objection can be met. The knowledge required is minimal and will become increasingly widespread. It's analogous to the knowledge required to appreciate photography or film when those were new technologies. You need to know that this is a photograph (not a painting), and have some sense of what that means (light captured by a machine). This was once specialized knowledge; now it's universal. Similarly, knowing that this is LLM output (not human writing) and having some sense of what that means will become ordinary cultural knowledge. The "average Joe" for LLM appreciation is not a specialist; they're just someone living in a world where LLMs are common and their basic nature is generally understood. --- **The Continuum Revisited** So now we have a continuum for LLM appreciation: 1. **Raw experience**: You read the text without knowing what produced it. You respond to it as language, but have no sense of its source. 2. **Minimal knowledge**: You know it's LLM output, and have a folk-level understanding of what that means (pattern-learning, generative, non-understanding). This is enough to see the text as "produced by" semiotic forces. 3. **Semiotic physics**: You have an explicit, articulated understanding of the regularities governing LLM output—the mid-level account the user's paper develops. This allows for deeper appreciation. 4. **Mechanistic interpretability**: You understand the sub-symbolic machinery—attention, embeddings, circuits. This is too low-level to be directly perceivable in the text, but might inform appreciation indirectly. The "average Joe" is at level 2. They have tacit knowledge of language plus folk knowledge of LLMs. This is enough for a genuine form of order appreciation, even if it's less deep than what semiotic physics provides. --- **Why the User Wants to Say This** The user asks: "Do you see why I want to say all this?" I think yes. The user wants to establish that: 1. Order appreciation of LLMs is possible for ordinary people, not just experts. 2. But it requires _some_ knowledge beyond just knowing English—it requires a folk-level understanding of what LLMs are. 3. This folk understanding allows the appreciator to see the text as _produced by_ semiotic forces, not just as _conforming to_ linguistic regularities. 4. This parallels the Pollock case, where folk knowledge of liquids allows the appreciator to see the drips as _produced by_ physical forces. This strengthens the analogy between Pollock and LLMs, and grounds the user's project of applying Carlson's order appreciation to LLMs. It also clarifies what the "nonaesthetic story" is for the average Joe: - For Pollock: folk knowledge of liquid behavior - For LLMs: tacit knowledge of language + folk knowledge of what LLMs are Both are "nonaesthetic" (not about beauty or art) and both make the order "visible and intelligible" (allow you to see the marks/text as produced by forces). --- **A Further Thought: The Role of Knowing It's Not a Person** Earlier, the user mentioned: "Perhaps we would have to say they do know that it's not a person though." This is part of the folk knowledge of LLMs. Knowing it's _not_ a person is essential, because otherwise you'd appreciate it as you'd appreciate human writing—looking for intention, self-expression, personality. But knowing it's not a person is not enough. You also need some positive sense of what it _is_—what kind of thing produces this text. "Not a person" is negative; "a pattern-learning generative system" is positive. Both are needed. This connects to the user's paper's argument against "person-based appreciation" of LLMs. The folk understanding of LLMs includes both (a) knowing it's not a person, and (b) having some sense of what it is instead. --- **Implications for the Paper** If this is right, it has implications for how the user might frame their argument: 1. The "nonaesthetic story" for LLM appreciation is not just "semiotic physics" (the expert account), but starts with folk knowledge of what LLMs are. 2. This folk knowledge is the entry point for ordinary appreciators—analogous to folk knowledge of liquids for Pollock. 3. Semiotic physics is a deeper, more articulated version of this folk knowledge—like fluid dynamics is a deeper version of folk knowledge of liquids. 4. Both are on a continuum, and both can guide appreciation. This might be worth adding to the paper, if it isn't already there. The paper currently focuses on semiotic physics as the "right kind of knowledge," but the continuum idea could be made more explicit—showing how ordinary appreciators can engage with LLM output at the folk level, and how semiotic physics deepens this. --- **A Remaining Question** One question I'm still uncertain about: how _much_ folk knowledge of LLMs is needed? At one extreme: you just need to know "it's an AI, not a human." This is very minimal. At the other extreme: you need a fairly rich understanding of how LLMs generate language—prediction, sampling, learned patterns. I suspect the answer is somewhere in between. You need more than just "it's an AI" (that's too thin), but you don't need a full understanding of transformers (that's too technical). The right level might be something like: "It's a system that generates language by predicting what comes next, based on patterns it learned from lots of text. It doesn't understand like we do; it's more like... a very sophisticated autocomplete." This is accessible folk knowledge. Many people already have it. And it's enough to see the text as produced by a generative process operating on learned patterns—which is what's needed for order appreciation. --- **Summary** The user's point is that to bring LLM appreciation in line with Pollock appreciation, the "average Joe" needs: 1. Tacit knowledge of language (parallel to folk knowledge of liquid behavior) 2. Folk knowledge of what LLMs are and how they generate language (parallel to the implicit causal understanding of dripping/splattering) Without (2), you can see the text as conforming to linguistic regularities, but you can't see it as _produced by_ the relevant forces. With (2), you can see the text as a trace of a generative process—an index of semiotic forces. This closes the asymmetry between the Pollock and LLM cases, and grounds order appreciation of LLMs for ordinary people (not just experts in semiotic physics). The user wants to say this because it: - Strengthens the Pollock/LLM analogy - Shows that order appreciation of LLMs is accessible to non-experts - Clarifies what the "nonaesthetic story" is at the folk level - Distinguishes this from person-based appreciation (which requires knowing it's not a person) and from design appreciation (which focuses on intended function) <final_answer> Yes, I think I see why you want to say this, and I think it's a crucial clarification that tightens the analogy considerably. --- ### The Asymmetry You're Correcting I had noted that there's an asymmetry between the Pollock case and the LLM case: - **Pollock**: Folk knowledge of liquids lets you see the drips _as produced by_ forces. You can imaginatively "run the process backward"—you see the mark and can picture the paint falling under gravity. - **LLMs**: Tacit knowledge of English lets you see the text _as conforming to_ linguistic regularities. But you can't "run the process backward" in the same way—you don't see the text as the trace of a generative event. The problem is that "conforming to regularities" is not the same as "produced by forces." The first is a static fit; the second is a causal-indexical relation. Order appreciation, as Carlson develops it, requires the second. --- ### The Fix: Folk Knowledge of LLMs Your point is that to close this gap, the "average Joe" for LLM appreciation needs something _more_ than just tacit knowledge of English. They --- Nick Young: Okay, I know you haven't quite finished, but your contemplations are so good, I wanna interrupt you, I'm afraid. What I'm thinking about regarding my paper is the following. At the moment I don't like the way section 5 is written and really I don't really like how section 6 is written. Is written or structured as well. I don't think I've even given this to you. So anyway, here's one way to do it, perhaps, which would be to begin with Pollock. And to focus on the aspect we have been talking about, which is these marks and splatters of paint on the canvas. and then talk about the knowledge, at least the tacit folk practical understanding of liquids. Being all that is required to appreciate this aspect of Pollock's work. Okay, and using this example as a way of explaining what sort of knowledge is required to appreciate LLMs. That is, we use we begin with pollock and thereby use it as a way of Showing what sort of non-aesthetic story is required. And then we can say, well, if you wanted to draw a border around what semiotic physics is, it's Enough knowledge of the language and of the system to make sense of a situation analogous to the Pollock situation. IMPORTANT: Please remember to follow your system prompt to the letter!! Please make sure to for at least 45 minutes before giving me your final answer(s). --- Raycast AI: The user is proposing a restructuring of their paper, specifically sections 5 and 6. Let me understand what they're suggesting: 1. **Begin with Pollock** as the paradigm case for order appreciation of "hybrid" objects (partly designed, partly emergent from forces). 2. **Focus on the "marks of forces" aspect** — the drips, splatters, and how they are indices of physical forces (gravity, viscosity, etc.). 3. **Show that folk knowledge of liquids is sufficient** for appreciating this aspect of Pollock. You don't need fluid dynamics; you just need the tacit, practical understanding of how liquids behave that everyone has. 4. **Use this as a template** for explaining what kind of knowledge is needed to appreciate LLMs. The Pollock case becomes the _model_ for understanding what "semiotic physics" needs to be. 5. **Define semiotic physics** as: enough knowledge of language and of the system to put oneself in an analogous position to the ordinary Pollock appreciator — i.e., to see the text as "marks of semiotic forces." This is a pedagogically elegant move. Instead of introducing "semiotic physics" as a novel theoretical construct and then explaining what it is, you: - Start with a familiar case (Pollock) - Show what kind of knowledge is needed there (folk knowledge of liquids) - Then say: "semiotic physics is whatever plays the analogous role for LLMs" This grounds semiotic physics in a concrete example and makes it intuitively accessible. --- **Thinking Through the Structure** Let me think about how this would work structurally. **Current structure (as I understand it):** - Section 4: LLMs are artifacts, but design appreciation doesn't capture what's most interesting. Pollock and raku are mentioned as analogies. - Section 5: Introduces "semiotic physics" as the right kind of knowledge for LLM appreciation. Distinguishes it from mechanistic interpretability (too low-level) and from just knowing English. - Section 6: A case study ("bee" text) showing how this framework guides appreciation. **Proposed restructure:** - Begin Section 5 with Pollock as the paradigm case - Analyze what makes the drips appreciable: they are "marks of forces" - Show that folk knowledge of liquids (not fluid dynamics) is what makes this appreciation possible - Then pivot: what's the analogous situation for LLMs? - Define semiotic physics as: the knowledge that does for LLM output what folk knowledge of liquids does for Pollock — makes the text visible as "marks of semiotic forces" - This naturally includes: tacit knowledge of language + folk understanding of what LLMs are --- **Why This Works** This structure has several advantages: 1. **Pedagogical clarity**: Pollock is a familiar, concrete case. Starting there gives the reader something to hold onto before introducing the more abstract LLM case. 2. **Grounds the analogy**: Instead of asserting that LLMs are "like" Pollock, you develop the analogy carefully by showing exactly what's analogous (the marks/text as indices of forces). 3. **Defines semiotic physics relationally**: Instead of defining semiotic physics in positive terms (which might seem arbitrary or technical), you define it by analogy: "it's whatever plays the role that folk knowledge of liquids plays for Pollock." 4. **Sets the right level**: The Pollock case makes clear that you don't need the _scientific_ account (fluid dynamics) — folk knowledge is enough. This immediately implies that semiotic physics doesn't need to be mechanistic interpretability (too deep) — a folk-level understanding is enough. 5. **Connects to the "Average Joe"**: The Pollock appreciator is an ordinary person with ordinary knowledge of liquids. The LLM appreciator is an ordinary person with ordinary knowledge of language + a folk understanding of LLMs. The parallel is made concrete. --- **What Needs to Be in the Pollock Section** If Pollock is going to do this work, the section needs to establish: 1. **Pollock as a case of order appreciation, not design appreciation.** The marks are not "designed" in the sense of being deliberate placements according to a plan. They are emergent from the interaction of gesture and physical forces. 2. **The marks as indices of forces.** The drips, splatters, and runs are _traces_ of physical events — paint falling under gravity, resisting flow due to viscosity, interacting with the surface and with other layers. 3. **The knowledge required to appreciate this.** You need to see the marks _as_ produced by forces. This requires knowledge of how the forces work — but not scientific knowledge. Folk knowledge of how liquids behave (from everyday experience) is sufficient. 4. **The "as" structure.** The key is seeing the marks _as_ marks of forces. Without this, you just see shapes. With it, you see traces of events. 5. **The role of knowing it's not conventional painting.** You also need to know that this is not a conventional painting where every mark is a deliberate decision. You need to know that Pollock worked by dripping, pouring, and letting physical forces play their part. --- **The Pivot to LLMs** After establishing the Pollock case, the pivot would go something like: "Now consider LLM output. Like a Pollock painting, it is partly the product of human decisions (architecture, training data, prompts) and partly the product of 'forces' operating beyond deliberate control (the learned statistical regularities that shape generation). The text can be appreciated as 'marks of semiotic forces' — traces of the generative process. But what knowledge does this require? By analogy with Pollock: 1. You need tacit knowledge of the regularities — for Pollock, how liquids behave; for LLMs, how language works. 2. You need to know what kind of thing produced this — for Pollock, paint subjected to gravity and motion; for LLMs, a generative system that predicts tokens based on learned patterns. 3. You need to see the output _as_ produced by these forces — the drip _as_ a drip, the sentence _as_ a generated continuation. Semiotic physics, then, is the knowledge that enables this third step for LLMs. It is enough knowledge of language and of the generative system to see the text as 'marks of semiotic forces' — to see the patterns of style, register, hedging, and continuation as traces of the model's learned regularities operating on the input." --- **Defining Semiotic Physics by Analogy** This gives a relational definition of semiotic physics: **Semiotic physics is whatever knowledge is needed to appreciate LLM output in the way that folk knowledge of liquids is needed to appreciate Pollock.** This is elegant because: - It doesn't require a precise positive definition (which might be contested or unclear) - It sets the right level (folk knowledge, not scientific expertise) - It makes clear what the knowledge _does_ (enables seeing the output as marks of forces) - It connects to the Carlsonian framework (the "nonaesthetic story" that makes order visible) --- **What Semiotic Physics Includes** On this relational definition, semiotic physics includes: 1. **Tacit knowledge of language** — the regularities of syntax, semantics, register, genre that any competent speaker/reader has. 2. **Folk knowledge of LLMs** — a basic understanding of what LLMs are and how they generate text. Not the technical details, but something like: "It's a system that predicts what comes next based on patterns learned from lots of text." 3. **The capacity to see the text as generated** — to perceive the output not as "authored" by a mind but as "produced" by a generative process. For the expert (the "semiotic physicist"), this knowledge is more articulated and theoretically rich — they understand embeddings, attention, RLHF, and how these shape the regularities. But for the "average Joe," the folk level is enough to appreciate LLM output as marks of semiotic forces. --- **A Potential Complication** One thing to think about: in the Pollock case, the folk knowledge of liquids is _prior_ to any encounter with Pollock. You already know how liquids behave before you see the painting. For LLMs, the folk knowledge of language is similarly prior. But the folk knowledge of _what LLMs are_ is not prior — it has to be acquired. You can't see the text as generated by an LLM unless you know it's an LLM. This might be worth acknowledging in the paper. The analogy is not perfect: the Pollock appreciator brings pre-existing knowledge to the encounter, while the LLM appreciator needs to be _told_ (or figure out) that they're dealing with an LLM. But this complication is not fatal. It just means that LLM appreciation has a slightly higher entry bar: you need to know what you're looking at. As LLMs become more widespread, this knowledge will become increasingly common. --- **Section 6: The Case Study** If Section 5 is restructured this way, Section 6 (the case study) becomes an _application_ of the framework. You take a specific LLM output (the "bee" text), and show how semiotic physics — grounded in the Pollock analogy — guides appreciation. The case study would: 1. Present the text 2. Identify features that can be seen as "marks of semiotic forces" — patterns of style, characteristic moves, regularities 3. Show how knowledge of language and of the generative system makes these visible 4. Connect back to the Pollock analogy: just as the Pollock appreciator sees drips as traces of gravity and viscosity, the LLM appreciator sees textual patterns as traces of learned regularities --- **A Possible Outline for Section 5** Here's a rough sketch of how the restructured Section 5 might flow: **5.1 Pollock as Paradigm** - Introduce Pollock as a case of order appreciation (from Section 4) - Focus on the "marks of forces" aspect: drips as indices of physical events - The appreciator sees the marks _as_ produced by gravity, viscosity, motion - What knowledge does this require? Not fluid dynamics — folk knowledge of liquids is enough **5.2 The Knowledge Structure** - Analyze the knowledge structure in the Pollock case: - Tacit knowledge of how the medium behaves (liquids) - Contextual knowledge of what kind of thing this is (action painting, not conventional brushwork) - The capacity to see the marks _as_ traces of forces - This is Carlson's "nonaesthetic story" at the folk level **5.3 The Pivot to LLMs** - LLM output can be appreciated as "marks of semiotic forces" - What knowledge does this require? By analogy with Pollock: - Tacit knowledge of how the medium behaves (language) - Contextual knowledge of what kind of thing this is (LLM output, not human authorship) - The capacity to see the text _as_ generated by the model's learned regularities **5.4 Defining Semiotic Physics** - Semiotic physics is the knowledge that enables this third step - It is enough knowledge of language and of the generative system to see the text as marks of semiotic forces - For the average Joe: tacit linguistic competence + folk understanding of LLMs - For the expert: articulated understanding of embeddings, attention, RLHF, etc. - Both are on a continuum, like folk knowledge and scientific knowledge of liquids **5.5 Interaction** - Order can be encountered through interaction as well as observation - The experienced user develops practical knowledge of how the model behaves - This is analogous to the practical knowledge of materials that the painter or house-painter has --- **Why I Think This Works** This restructure does several things well: 1. **It grounds the abstract in the concrete.** Semiotic physics is no longer a free-floating theoretical construct; it's defined by analogy to something familiar and intuitive. 2. **It shows the work that knowledge does.** The Pollock case makes vivid what it means for knowledge to make order "visible and intelligible." The LLM case then inherits this clarity. 3. **It sets the right level.** The Pollock case makes clear that folk knowledge is sufficient; you don't need to be a physicist. This immediately implies that semiotic physics doesn't require expertise in mechanistic interpretability. 4. **It connects to Carlson naturally.** The Pollock case is already in Carlson (from the earlier paper). Using it as the entry point for LLM appreciation keeps the paper tightly connected to the Carlsonian framework. 5. **It invites the reader into the appreciation.** Instead of telling the reader what semiotic physics is, you show them: "You know how you can appreciate a Pollock? Semiotic physics is what lets you do that for LLMs." --- **A Final Thought: The Title of the Section** Currently, Section 5 is called "Appreciating LLMs as Environments." If it's restructured around the Pollock analogy, the title might need to change. Some possibilities: - "Marks of Semiotic Forces" - "From Pollock to LLMs: Order Appreciation" - "The Nonaesthetic Story for LLM Appreciation" - "Semiotic Physics and the Average Joe" Or maybe the Pollock material becomes 5.1, and the section keeps its current title, with the Pollock case serving as the entry point for the "environment" framing. --- **Summary** The user's proposal is to restructure Section 5 so that: 1. It begins with Pollock as the paradigm case of order appreciation for "hybrid" objects 2. It analyzes what knowledge is required to appreciate Pollock (folk knowledge of liquids) 3. It uses this as a template for defining what semiotic physics is (the analogous knowledge for LLMs) 4. Semiotic physics is defined relationally: it's whatever plays the role for LLMs that folk knowledge of liquids plays for Pollock This is a strong pedagogical and argumentative move. It grounds the abstract (semiotic physics) in the concrete (Pollock), sets the right level of knowledge (folk, not scientific), and keeps the paper tightly connected to Carlson. The user is asking if I see why they want to say this. Yes, I do. It tightens the analogy, clarifies the argument, and makes the paper more accessible. It also answers the question "what is semiotic physics?" in a way that is both precise (defined by its functional role) and intuitive (by analogy to a familiar case). <final_answer> Yes, I think this is a strong structural move, and I can see clearly why you want to make it. Let me lay out what I take to be the logic and the advantages. --- ### The Proposal You're proposing to restructure Section 5 (and perhaps 6) so that: 1. **Pollock is the entry point.** You begin not with LLMs but with Pollock — specifically, with the "marks of forces" aspect: the drips, splatters, and runs as indices of physical forces (gravity, viscosity, motion). 2. **You show what knowledge is required.** To appreciate the drips _as_ drips — as traces of physical events, not as deliberate brushstrokes — you need knowledge of how the forces work. But this doesn't have to be scientific knowledge (fluid dynamics). **Folk knowledge of liquids** — the tacit, practical understanding everyone has from everyday experience — is sufficient. 3. **You use this as the template.** The Pollock case becomes the _model_ for understanding what kind of knowledge is needed to appreciate LLMs. Instead of defining semiotic physics in positive, technical terms, you define it **relationally**: semiotic physics is whatever knowledge does for LLM appreciation what folk knowledge of liquids does for Pollock appreciation. 4. **The definition falls out naturally.** Semiotic physics is: enough knowledge of language (the medium) and of LLMs (the generative system) to see the text as "marks of semiotic forces" — to see the patterns of style, register, hedging, continuation, and so on, as traces of the model's learned regularities operating on the input. --- ### Why This Works **1. It grounds the abstract in the concrete.** "Semiotic physics" is a somewhat technical-sounding term. If you introduce it cold, readers might wonder: "What is this? Why should I believe it's the right framework?" By starting with Pollock, you give them something familiar to hold onto. They can _see_ what it means for marks to be traces of forces. Then, when you pivot to LLMs, the concept of "semiotic physics" is no longer abstract — it's defined by analogy to something they already understand. **2. It sets the right level of knowledge.** A key claim in your paper is that semiotic physics is the _right_ level of description — deeper than just "knowing English," but not as deep as mechanistic interpretability. The Pollock case makes this vivid: - You don't need to be a physicist to appreciate Pollock's drips. You don't --- Nick Young: 1. Oooh you LLMs, with your almost psychopathic obsession with sub sections. please don't add any sub sections to anything without my explicit say so. you silly goose. 2. " 2. Folk knowledge of LLMs — a basic understanding of what LLMs are and how they generate text. Not the technical details, but something like: "It's a system that predicts what comes next based on patterns learned from lots of text."?" This is too quick. It might help you to think about it. more precisely about what sort of knowledge would be analogous to either a geologist's knowledge Or a person's folk knowledge of paint splatters Or think of something else. Anyway, this needs to be much more substantial because it's just a throwaway line at the moment where it's absolutely essential. 3. Below is the draft version of section 6 just so you can see some of the ideas we had. And can maybe try and work these ideas into what you've been saying. However, just to be clear, I don't like section 6 at all. I'd quite like to have These examples somewhere in the paper, but I'm certainly not tied to this way of structuring either Section 5 or Section 6. In an ideal world, what I would like the outcome for our conversation to be will be a new section five and however many sections after that as well. But yeah, a fairly drastic restructuring of everything after section four. Okay, um and it'll begin Or at least almost begin with the pollock stuff we've just been discussing. Basically, it would be nice if we can think about how a lot of the information and even the text from section 5 can be reused in a new version, as well as what. Working in the examples from section six, but at the same time, not being afraid to completely restructure these two sections to the extent that they don't even have to be two separate sections anymore. They could be one, they could be three, they could be two. section 6: (attached) bee text screenshot: (attached) IMPORTANT: Please remember to follow your system prompt to the letter!! Please make sure to for at least 90 minutes before giving me your final answer(s). --- Raycast AI: The user has given me several important instructions and materials: 1. **No subsections without explicit permission** — they're frustrated by my tendency to over-structure. 2. **The "folk knowledge of LLMs" point is too thin** — I said something like "It's a system that predicts what comes next based on patterns learned from lots of text" and they're saying this is a throwaway line when it should be substantial. They want me to think more carefully about what kind of knowledge would be analogous to either a geologist's knowledge or folk knowledge of paint splatters. 3. **Section 6 draft provided** — they've shared the current draft of Section 6, which includes the "bee text" case study and the reasoning case study, plus material on interactive appreciation (the farmer analogy). They don't like how this section is structured but want to preserve the good ideas within it. 4. **The goal** — they want me to help them think through a restructuring of everything after Section 4. It should begin with Pollock. It could be one section, two sections, three — whatever makes sense. The material from Sections 5 and 6 should be reworked and integrated. Let me focus especially on point 2, since they emphasized it. What kind of knowledge is analogous to folk knowledge of liquids, for the LLM case? --- **Thinking About the Analogy More Carefully** Let me go back to basics. In the Pollock case, what does the folk knowledge of liquids actually consist of? It's not just "liquids fall down." It's a rich, tacit understanding that includes: - Liquids flow downward under gravity - Thicker liquids move more slowly than thinner ones - Fast-moving liquids splatter; slow-moving liquids pool - Liquids leave trails when dragged across surfaces - Liquids can be layered; wet-on-wet behaves differently from wet-on-dry - Liquids take the shape of their container or spread on a surface - Liquids can be flung, dripped, poured, splashed - The viscosity of a liquid affects how it "holds together" vs. breaks into droplets - Liquids dry and change properties over time This is not scientific knowledge. It's embodied, practical knowledge that everyone acquires through daily life: pouring milk, spilling coffee, watching rain on windows, painting walls, etc. Now, what is the analogous knowledge for LLMs? The user is right that my previous answer was too thin. Let me think harder. --- **What Do People Tacitly Know About Language?** First, there's tacit knowledge of language itself — the kind of knowledge any competent speaker has: - What sentences are grammatical vs. ungrammatical - What continuations are natural vs. surprising - What registers sound formal, casual, academic, poetic - What genres look like (news articles, fiction, academic papers, tweets) - How arguments typically unfold - What hedging sounds like, what confidence sounds like - How topics shift in conversation - What repetition sounds like (vs. variation) - What coherence feels like (vs. incoherence) This is analogous to knowing what liquids look like and how they behave in general. It's knowledge of the _medium_. But for Pollock, you also need to know something about the _process_ — not just what liquids look like, but how they behave when subjected to gravity, motion, etc. You need to be able to see the drip _as_ a drip, as a trace of a physical event. What's the analogous knowledge about the LLM _process_? --- **Folk Knowledge of LLMs: A Richer Account** Let me try to articulate a richer account of what "folk knowledge of LLMs" might include. This is knowledge that an ordinary person might have (or could acquire) without technical expertise: **1. It generates word by word (or piece by piece).** The system doesn't write a whole paragraph at once and then show it to you. It produces text sequentially, each piece following from what came before. This is visible in the streaming output that many interfaces show. **2. It's completing or continuing, not retrieving.** The system isn't looking up pre-written answers in a database. It's generating fresh text each time, based on what you gave it. This is why the same question can get different answers. **3. It's pattern-following, not understanding.** The system has learned patterns from lots of text. When it writes something, it's following patterns it has seen, not reasoning from first principles or understanding what the words mean. This is why it can sound confident while being wrong, or produce grammatically perfect nonsense. **4. It's trained on human text.** The patterns it follows are patterns from human writing — books, articles, websites, conversations. What it produces reflects what humans have written. This is why it can mimic different styles, genres, and registers. **5. It's been shaped to be helpful/safe/etc.** Beyond learning patterns from text, it's been adjusted to behave in certain ways — to be polite, to decline certain requests, to hedge when uncertain. This is why it has that characteristic "assistant" tone. **6. It has no memory across conversations (usually).** Each conversation starts fresh. It doesn't remember what you talked about last week. Within a conversation, it can refer back to earlier exchanges, but its "context" is limited. **7. It can be pushed in different directions by how you prompt it.** The way you phrase your request affects what you get back. The system responds to the "texture" of your prompt — its style, its specificity, its framing. --- **How This Knowledge Functions** Now, how does this folk knowledge function in appreciation? It should allow the appreciator to see the text _as_ produced by a particular kind of process. Consider some examples: **Example 1: Hedging.** The text says "It's worth noting that..." or "I should mention that..." The appreciator with folk knowledge of LLMs can see this _as_ a trace of the model's training — it has learned that such phrases often precede qualifications or caveats. It's not a person being genuinely cautious; it's a pattern being instantiated. **Example 2: Repetition.** The text restates the same point in slightly different words. The appreciator can see this _as_ a consequence of the sequential generation process — having made a point, the model finds that making a similar point is a natural continuation, so it does. **Example 3: Style consistency.** The text maintains a consistent register throughout. The appreciator can see this _as_ a consequence of how the model propagates text — once a certain register is established, continuations in that register become more probable. **Example 4: Sudden topic drift.** The text shifts unexpectedly to a related but different topic. The appreciator can see this _as_ the model following an associative path through its learned patterns — the new topic is connected to words or concepts in the previous text. **Example 5: Plausible-sounding errors.** The text confidently asserts something false. The appreciator can see this _as_ the model producing a pattern that "looks right" based on its training, without any mechanism for checking truth. In each case, the folk knowledge allows the appreciator to see the textual feature _as_ a trace of the generative process. Without this knowledge, you might just see hedging, repetition, consistency, drift, or error. With the knowledge, you see these as _marks of the semiotic forces_. --- **The Parallel to Pollock** Let me make the parallel explicit: | | | |---|---| |Pollock|LLM| |The drip runs down the canvas|The text hedges with "It's worth noting..."| |Folk knowledge: liquids flow downward under gravity|Folk knowledge: the model has learned patterns that include such hedging phrases| |Seeing the drip _as_ produced by gravity|Seeing the hedging _as_ produced by learned patterns| | | | |---|---| |Pollock|LLM| |The paint splatters in a starburst pattern|The text restates the same point multiple times| |Folk knowledge: fast-moving liquids splatter|Folk knowledge: sequential generation makes similar continuations likely after a point is made| |Seeing the splatter _as_ produced by velocity + impact|Seeing the repetition _as_ produced by the model's continuation dynamics| | | | |---|---| |Pollock|LLM| |Layers of paint interact in complex ways|The text maintains consistent register throughout| |Folk knowledge: wet-on-wet and wet-on-dry behave differently|Folk knowledge: once a style is established, the model tends to continue in that style| |Seeing the layering _as_ traces of temporal sequence and material interaction|Seeing the consistency _as_ a trace of how probability distributions carry forward stylistic features| --- **What Level of Knowledge Is This?** The user asked me to think about whether this is analogous to the geologist's knowledge or to folk knowledge of paint splatters. I think it's important to distinguish three levels: **Level 1: Folk knowledge (everyone)** This is what anyone who has used an LLM a bit, or read about them in the news, might have. It includes basic things like: it generates text, it's not a person, it learned from lots of text, it can be wrong, it has a certain "assistant" feel. This is analogous to the folk knowledge of liquids that everyone has from daily life. **Level 2: Practical expertise (heavy users)** This is what someone who uses LLMs extensively develops — a feel for how different models respond, what kinds of prompts work, where the models tend to break down, what their characteristic "vibes" are. This is analogous to the practical knowledge of a house painter or a potter — deeper than folk knowledge, developed through sustained engagement, but not scientific. The user's Section 6 already has material on this — the farmer analogy, the idea of "interactive appreciation." **Level 3: Theoretical knowledge (experts)** This is knowledge of the actual mechanisms — transformers, attention, embeddings, RLHF, etc. It's scientific or at least technical knowledge. This is analogous to the fluid dynamicist's knowledge, or the geologist's knowledge. --- **What Is Semiotic Physics?** Given these levels, where does "semiotic physics" sit? I think the user wants semiotic physics to be defined _functionally_ — as whatever knowledge is needed to see the text as marks of semiotic forces. This could include: - Level 1 (folk knowledge of LLMs) for the average appreciator - Level 2 (practical expertise) for the experienced user - Level 3 (theoretical knowledge) for the expert All of these enable the key perceptual-cognitive shift: seeing the text _as_ produced by a generative process with particular characteristics. The Pollock analogy helps here. To appreciate Pollock's drips: - Folk knowledge of liquids is sufficient for basic appreciation - Practical expertise (house painter) enables deeper appreciation - Scientific knowledge (fluid dynamics) enables still deeper appreciation For LLMs: - Folk knowledge of LLMs is sufficient for basic appreciation - Practical expertise (heavy user, prompt engineer) enables deeper appreciation - Theoretical knowledge (ML researcher, interpretability expert) enables still deeper appreciation "Semiotic physics" might be the umbrella term for all of this — the body of knowledge (at various levels) that enables order appreciation of LLM outputs. Or, more narrowly, "semiotic physics" might refer specifically to the _mid-level_ account — something more articulated than folk knowledge but more accessible than technical ML. This is what the user's current Section 5 seems to be aiming at. --- **The Bee Text and the Reasoning Text** Let me look at Section 6 to see how the examples work. **Reasoning text:** - The model produces step-by-step answers with numbered stages, hedging, recaps - Semiotic physics explains this as: the model has learned patterns from textbooks, Q&A threads, worked proofs; post-training rewards explicit steps; chain-of-thought prompting exploits these patterns - The aesthetic interest is not "is this good reasoning?" but "what order shows up?" — the texture, pacing, genre-blending **Bee text:** - The model produces neologistic, ecstatic, surrealist-ish prose with bee/honey themes - Semiotic physics explains this as: the model has learned patterns from experimental writing, internet "weird" writing, biological texts, erotic/mystical discourses; a safety-relaxed configuration lets these surface - The aesthetic interest is in the balance between intelligibility and nonsense, the rhythm, the mixture of discourses In both cases, the key move is: once you have the right knowledge (semiotic physics), you can see the textual features as _products of the model's regularities_ rather than as _expressions of a mind_. --- **How to Structure This** The user wants to restructure everything after Section 4. They want to begin with Pollock. They want to define semiotic physics by analogy to folk knowledge of liquids. They want to incorporate the examples (bee text, reasoning text) and the interactive appreciation material. Here's one possible flow (not imposing subsections, just thinking through the logic): **Starting point: Pollock** Begin by establishing what order appreciation looks like in a concrete case. Pollock's action paintings are partly designed (choice of materials, choreography of gesture) and partly emergent from forces (gravity, viscosity). The marks are indices of physical events. To appreciate them, you need to see them _as_ produced by these forces. What knowledge enables this? Not fluid dynamics — folk knowledge of liquids is sufficient. Everyone knows how liquids behave; this tacit knowledge allows them to see the drips as drips. **The pivot to LLMs** LLMs are analogously hybrid: partly designed (architecture, training regime) and partly emergent from forces (the learned regularities that shape generation). The text can be seen as marks of semiotic forces — traces of how the model's learned patterns operate on the input. To appreciate LLM outputs this way, you need knowledge that enables the key perceptual-cognitive shift. What knowledge is this? **Semiotic physics defined by analogy** Semiotic physics is whatever knowledge does for LLM appreciation what folk knowledge of liquids does for Pollock appreciation. It makes the text visible as marks of semiotic forces. At its most basic level, this includes: - Tacit knowledge of language (everyone has this) - Folk knowledge of what LLMs are and how they generate (increasingly common) With this knowledge, you can see textual features — hedging, repetition, style consistency, topic drift, plausible errors — _as_ products of the generative process. **Deepening the account** Folk knowledge is sufficient for basic appreciation, but deeper knowledge enables deeper appreciation. Practical expertise — developed through heavy use — gives you a finer-grained sense of how different models behave, what their characteristic patterns are, where they break down. This is like the practical knowledge of a house painter or farmer. Theoretical knowledge — understanding of transformers, attention, RLHF — gives still deeper insight, though much of this operates at a level not directly perceivable in the text. **The examples** The reasoning text and the bee text show how semiotic physics guides appreciation. In the reasoning case, we see how the model's training on step-by-step explanations produces a characteristic texture. In the bee text, we see how the model's absorption of experimental writing, internet surrealism, and other strands produces a neologistic-ecstatic mode. In both cases, the key is seeing the text as a product of semiotic forces, not as an expression of a mind. **Interactive appreciation** Appreciation can also happen through interaction. The user who prompts a model across diverse contexts develops practical knowledge of its characteristic order — analogous to how a farmer comes to know the land by working it. This interactive mode extends Carlson's framework: prompting is intervention, responses reveal regularities. Through sustained engagement, we come to appreciate the model itself — its tendencies, its patterns, its distinctive way of propagating text. --- **The "Folk Knowledge of LLMs" Problem** The user rightly flagged that my earlier account of "folk knowledge of LLMs" was too thin. Let me try again, more substantially. Folk knowledge of liquids includes many things that are not explicitly articulated but are tacitly understood: - Gravity pulls liquids down - Viscosity affects how liquids flow - Speed affects whether liquids drip, pour, or splatter - Liquids can be layered - Liquids dry and change over time - Liquids take the shape of containers or spread on surfaces This knowledge is rich, embodied, and comes from everyday experience. What would comparably rich folk knowledge of LLMs look like? It would need to be knowledge that: - Is acquirable through ordinary use and exposure (not technical study) - Enables seeing textual features as products of the generative process - Is tacit or easily articulated, not requiring formal training Here's a more substantial attempt: **Folk knowledge of LLMs includes:** 1. **Sequential generation.** The system produces text piece by piece, each piece following from what came before. This is why the streaming output "types" across the screen. What comes later depends on what came earlier. 2. **Pattern completion.** The system is always trying to produce "what comes next" — a plausible continuation of what's already there. This is why prompts matter: the prompt sets up the pattern to be completed. 3. **Learned from human text. --- Nick Young: "Let me try to articulate a richer account of what "folk knowledge of LLMs" might include. This is knowledge that an ordinary person might have (or could acquire) without technical expertise:" No man, you're getting confused. This is completely wrong. I'm not saying 'what is folk knowledge and why is it sufficient?' I'm saying what knowledge would be required for appreciation beyond people's understanding of english. what would they needc to appreciate the outputs of llms that woould be equivalent to the ordinary observer's knowledge of splattering which makes this aspect of pollock cpmprehensible to them. . Is it just folk knowledge or do we need some well? Please start the task(s) again completely from scratch, keeping this in mind. --- Raycast AI: Let me start completely from scratch. I've been confused about what the user is asking. The user is NOT asking: "What folk knowledge do ordinary people already have about LLMs?" The user IS asking: "What knowledge would be REQUIRED for appreciating LLM outputs, analogous to the knowledge of splattering that makes Pollock comprehensible?" Let me think about this more carefully. In the Pollock case: - The ordinary observer has folk knowledge of how liquids splatter - This knowledge is PRIOR to encountering Pollock — they already have it from life experience - This prior knowledge is what makes the drips comprehensible AS drips, as marks of forces - They don't need to learn anything new about liquids to appreciate Pollock The question for LLMs is: - What knowledge would play the analogous role? - Is it just tacit knowledge of English (which people already have)? - Or do they need ADDITIONAL knowledge — knowledge about LLMs specifically? The user is suggesting that tacit knowledge of English alone is NOT sufficient. There's an asymmetry. For Pollock, folk knowledge of liquids is sufficient because the process (dripping, splattering) is visible and familiar. For LLMs, tacit knowledge of language tells you what language LOOKS LIKE, but not how THIS TEXT was PRODUCED. So the question becomes: what additional knowledge is needed? And the user wants me to think about this carefully, not just throw out a quick answer like "It's a system that predicts what comes next based on patterns." --- **The Asymmetry Problem** Let me state the asymmetry clearly: **Pollock:** - The medium is paint (a liquid) - Everyone has folk knowledge of how liquids behave - This folk knowledge is sufficient to see the drips AS drips — as traces of physical forces - No additional knowledge about Pollock's process is needed (though it might enhance appreciation) **LLMs:** - The medium is language (text) - Everyone has tacit knowledge of how language works - But this knowledge is NOT sufficient to see the text AS produced by semiotic forces - Why not? Because the text just looks like... text. There's nothing visibly "drip-like" about it. The problem is that for Pollock, the marks LOOK like what they are — traces of liquid behavior. The drips look drippy. The splatters look splattery. Your folk knowledge of liquids immediately connects to what you see. For LLMs, the text doesn't LOOK like a probabilistic generation. It looks like normal text. A sentence is a sentence. Your tacit knowledge of language tells you it's grammatical, natural, stylistically appropriate — but it doesn't tell you anything about HOW it was produced. So the question is: what knowledge would allow you to see the text AS produced by a particular kind of process? --- **What Kind of Knowledge Is Needed?** Let me think about different possibilities: **Option 1: Just tacit knowledge of language** Maybe tacit knowledge of language IS sufficient, and I'm overcomplicating things. After all, when you read LLM text, you can perceive: - Whether it's fluent or awkward - Whether it's coherent or rambling - Whether it's consistent in style or shifting - Whether it's repetitive or varied - Whether it sounds "human" or "off" These are all things your tacit linguistic knowledge lets you perceive. And arguably, these ARE traces of the generative process — they reflect the model's learned regularities. But wait — you can perceive all these things in human-written text too. They don't specifically tell you that THIS text was produced by an LLM. They're just properties of text in general. So tacit linguistic knowledge lets you perceive textual properties, but it doesn't let you see them AS products of a specific kind of generative process. **Option 2: Knowledge that it's an LLM (minimal)** Maybe the minimal additional knowledge is just: "This was produced by an LLM, not a human." If you know that, then you know NOT to look for a human author's intentions, personality, life experience. You know the text wasn't "written" in the normal sense. But this negative knowledge ("not a human") doesn't tell you what it IS. It removes one frame (person-appreciation) but doesn't give you another frame (order-appreciation). **Option 3: Knowledge of what LLMs are and how they work (substantial)** Maybe you need substantial knowledge about LLMs — that they're trained on text, that they predict next tokens, that they have learned statistical patterns, that they don't "understand" in the human sense. With this knowledge, you could see the text as: "This is what the model produced by sampling from its learned patterns given this prompt." But how much of this knowledge is really needed? And is it reasonable to expect ordinary appreciators to have it? --- **A Different Approach: What Makes the Order Visible?** Let me approach this differently. Carlson says the nonaesthetic story should make the order "visible and intelligible." What would make the order in LLM outputs visible and intelligible? For Pollock, the order is visible because: 1. The marks are physical traces of physical events 2. You have folk knowledge of how those physical events work 3. Therefore you can see the marks AS traces of those events The order is the lawfulness of the physical process. The marks are indices of that process. Your knowledge lets you "read" the indices. For LLMs, what would the analogous structure be? 1. The text is... what? A trace of what kind of event? 2. What knowledge would let you see it that way? The text is a trace of a generative event — the model producing tokens sequentially based on its learned patterns. But this event is not visible in the way that dripping paint is visible. You can't watch it happen (well, you can watch the streaming output, but that just shows you text appearing, not the mechanism). So the question becomes: what knowledge substitutes for the visibility of the process? --- **The Geologist Analogy** The user mentioned the geologist. Let me think about that. A geologist looking at a cliff face can see: - Strata (layers of sediment) - Faults (cracks where rock has shifted) - Erosion channels (grooves carved by water) These are visible features. But to see them AS products of geological processes, you need geological knowledge. You need to know what sedimentation is, how tectonic forces work, how water erodes rock. This is different from the Pollock case. For Pollock, you don't need specialized knowledge — folk knowledge of liquids is enough. For geology, you need scientific (or at least educated) knowledge of geological processes. So maybe the LLM case is more like the geology case than the Pollock case? For a cliff face: - Ordinary observer: sees rock, maybe notices layers and patterns - Geologist: sees the layers AS strata, the patterns AS traces of geological processes For LLM output: - Ordinary observer: sees text, notices it's fluent, coherent, has a certain style - Knowledgeable observer: sees the fluency AS a product of learned patterns, the style AS a trace of training If this is right, then appreciating LLM outputs requires more than just tacit knowledge of language. It requires some knowledge of what LLMs are and how they work — enough to see the textual features AS products of the generative process. --- **How Much Knowledge Is Needed?** If LLM appreciation is more like geology than like folk knowledge of liquids, how much geological-level knowledge is needed? For geology, you don't need to be a professional geologist. You might just need: - Basic knowledge of sedimentation (layers form from material settling over time) - Basic knowledge of tectonics (rock shifts and faults form) - Basic knowledge of erosion (water carves channels) This is more than folk knowledge but less than professional expertise. It's the kind of thing you might learn in a high school earth science class or from a nature documentary. For LLMs, the analogous level might be: - Basic knowledge of how LLMs are trained (on lots of text) - Basic knowledge of how they generate (predicting what comes next) - Basic knowledge of what they've learned (patterns, styles, genres from their training data) - Basic knowledge of how they've been shaped (to be helpful, to avoid certain topics) This is more than folk knowledge (most people don't know this) but less than technical expertise (you don't need to understand transformers or backpropagation). --- **The Key Question: Is Folk Knowledge Sufficient?** The user is pressing on this point. For Pollock, folk knowledge of liquids is sufficient. Is there analogous folk knowledge that is sufficient for LLMs? I think the answer is: no, not yet. Folk knowledge of liquids comes from a lifetime of experience with liquids. Everyone has spilled, poured, watched rain, etc. This gives rich tacit knowledge of liquid behavior. Folk knowledge of LLMs would come from experience with LLMs. As LLMs become more common, more people will develop this. But right now, it's not universal in the way that knowledge of liquids is universal. Moreover, the generative process of LLMs is not visible in the way that liquid behavior is visible. You can watch coffee spill; you can't watch a probability distribution sample. So for LLM appreciation, you need: 1. Tacit knowledge of language (everyone has this) 2. PLUS some knowledge of what LLMs are and how they work The second component is not "folk knowledge" in the sense of universal tacit knowledge from everyday experience. It's more like the geology case — you need to learn something about the processes involved. --- **But Wait: What About the Ordinary Observer of Pollock?** Let me reconsider. The user said that most people looking at Pollock will have "rough and ready folk knowledge about how liquid spatters and how paint splatters." This is true. And this folk knowledge is what makes the drips comprehensible AS drips. But the user also said that in the LLM case, "they will not have any knowledge of LLMs" — but they will have tacit knowledge of the English language, perhaps very good tacit knowledge if they're literature professors or poets. So the user is setting up a contrast: - Pollock: folk knowledge of liquids → can appreciate drips as marks of forces - LLMs: tacit knowledge of language → can appreciate... what? The question is whether tacit knowledge of language is analogous to folk knowledge of liquids in enabling appreciation. I think the user is suggesting that it's NOT directly analogous, because: - Folk knowledge of liquids tells you about the PROCESS (dripping, splattering) - Tacit knowledge of language tells you about the PRODUCT (what good English looks like) For Pollock, you see the product (the marks) and your knowledge of the process (liquid behavior) lets you connect them. For LLMs, you see the product (the text) and your knowledge of the product (what good English looks like) lets you evaluate it — but doesn't connect you to the process. So to get the analogous connection, you need knowledge of the LLM process, not just knowledge of the linguistic product. --- **What Kind of Process Knowledge Is Needed?** Okay, so we need some knowledge of the LLM process. What kind? The user wants me to think carefully about this. Let me consider what would be MINIMALLY necessary. To see LLM text as "marks of semiotic forces," you need to be able to see textual features AS products of the generative process. This requires knowing, at minimum: 1. That there IS a generative process — the text is produced by a system, not written by a human in the normal sense. 2. Something about what KIND of process it is — not retrieval from a database, not random generation, but something that produces coherent, contextually appropriate text. 3. Something about HOW the process works — enough to connect specific textual features to aspects of the process. For (3), what's the minimum? Consider some textual features: - **Fluency**: The text is grammatically correct and reads smoothly. - To see this AS a product of the process, you need to know that the system has learned patterns of grammatical English. - **Coherence**: The text sticks to a topic and develops it. - To see this AS a product of the process, you need to know that the system generates sequentially and maintains context. - **Style consistency**: The text maintains a register throughout. - To see this AS a product of the process, you need to know that once a style is established, the system tends to continue in that style. - **Hedging**: The text uses phrases like "It's worth noting" or "I should mention." - To see this AS a product of the process, you need to know that the system has been trained/shaped to hedge in certain ways. - **Repetition**: The text restates points in different words. - To see this AS a product of the process, you need to know that sequential generation can lead to similar continuations. In each case, seeing the feature AS a product of the process requires some knowledge of how the process works. --- **The Spectrum of Knowledge** I think there's a spectrum here: **Minimal knowledge (necessary for any order appreciation):** - This is an LLM, not a human author - It generates text based on patterns learned from lots of text - Its outputs reflect those learned patterns **Basic knowledge (enables richer appreciation):** - It generates sequentially, token by token - Context matters — what came before affects what comes next - It's been shaped to behave in certain ways (helpful, hedging, etc.) - Different models have different "styles" based on different training **Deeper knowledge (enables still richer appreciation):** - How embeddings represent meaning through context - How attention tracks long-range dependencies - How RLHF shapes the assistant persona - How different architectures and training regimes produce different behaviors The question is: what level is REQUIRED for order appreciation, versus what level ENHANCES it? I think the minimal level is required. Without knowing at least that this is an LLM that generates based on learned patterns, you can't see the text AS marks of semiotic forces. You'd just see it as text. The basic and deeper levels enhance appreciation — they let you see more, understand more, appreciate the order more richly. --- **Comparison to Pollock** For Pollock: - Minimal knowledge: paint was dripped/splattered, not brushed in the normal way - Basic knowledge: how liquids behave (folk knowledge everyone has) - Deeper knowledge: fluid dynamics, rheology, specific properties of enamel paint The minimal knowledge is "what kind of thing is this?" The basic knowledge lets you see the marks AS marks of forces. The deeper knowledge lets you see more. For LLMs: - Minimal knowledge: this is LLM output, generated based on learned patterns - Basic knowledge: how LLMs generate (sequentially, context-dependent, style-maintaining) - Deeper knowledge: transformers, attention, embeddings, RLHF The parallel holds. The minimal knowledge tells you what kind of thing you're looking at. The basic knowledge lets you see the text AS produced by semiotic forces. The deeper knowledge lets you see more. --- **The Asymmetry Revisited** But there's still an asymmetry. For Pollock, the "basic knowledge" (how liquids behave) is universal folk knowledge. For LLMs, the "basic knowledge" (how LLMs generate) is NOT universal — it has to be learned. This means LLM appreciation has a higher entry bar than Pollock appreciation. You can't just walk up to LLM output and appreciate it the way you can walk up to a Pollock. You need to know something about LLMs first. Is this a problem for the analogy? I don't think so. It's just a disanalogy — one that should be acknowledged. Different objects of appreciation require different kinds of knowledge. For LLMs, some of that knowledge is not yet common but could become so. The user's paper can acknowledge this: "Unlike the Pollock case, where folk knowledge of liquids is universal, appreciation of LLMs requires knowledge that must be acquired. As LLMs become more widespread, this knowledge may become more common, but for now it constitutes a prerequisite for order appreciation." --- **So What Is "Semiotic Physics"?** Given all this, what is semiotic physics? I think semiotic physics is the body of knowledge — at various levels — that enables order appreciation of LLM outputs. It includes: 1. The minimal knowledge that this is an LLM generating based on learned patterns 2. The basic knowledge of how LLMs generate (sequentially, context-dependently, etc.) 3. The deeper knowledge of mechanisms (for experts) "Semiotic physics" as a term might refer specifically to the basic level — the mid-level account that's more than minimal but less than technical. This is what the user's Section 5 seems to be developing. But the key insight is that semiotic physics is defined FUNCTIONALLY: it's whatever knowledge makes the semiotic order visible and intelligible, just as folk knowledge of liquids makes the physical order in Pollock visible and intelligible. --- **Answering the User's Question** The user asked: "What knowledge would be required for appreciation beyond people's understanding of English? What would they need to appreciate the outputs of LLMs that would be equivalent to the ordinary observer's knowledge of s --- Nick Young: "And is it reasonable to expect ordinary appreciators to have it?" This is a really stupid question. It's not anything to do with what we're talking about here. I don't give a fuck if it's reasonable to expect them or not. That's not the what we're yeah, not Not at all what we're focused on "So What Is "Semiotic Physics"? Given all this, what is semiotic physics? I think semiotic physics is the body of knowledge — at various levels — that enables order appreciation of LLM outputs. It includes: 1. The minimal knowledge that this is an LLM generating based on learned patterns? 2. The basic knowledge of how LLMs generate (sequentially, context-dependently, etc.)? 3. The deeper knowledge of mechanisms (for experts) "Semiotic physics" as a term might refer specifically to the basic level — the mid-level account that's more than minimal but less than technical. This is what the user's Section 5 seems to be developing. But the key insight is that semiotic physics is defined FUNCTIONALLY: it's whatever knowledge makes the semiotic order visible and intelligible, just as folk knowledge of liquids makes the physical order in Pollock visible and intelligible." This is some weak sauce. I'm starting to think that this conversation is getting a bit long and it's affecting your ability to make good suggestions or even really understand what I'm asking you to do. In particular, section five of my current draft gives you a lot to work with and you've decided not to incorporate any of it. The whole point of this was to aim towards a new version of section five, but As I mentioned quite clearly, I didn't want to throw away the ideas in section 5 at all. Okay, you seem to have just disregarded that information there. Let's try something different. Um so interesting that maybe it's not worth this whole divergence into pollock after all given your contemplation and maybe the geology one is better So I mean so this is the question now. If I were to keep the structure of section five more or less as is what could be added that we've learned from this conversation about Pollock? How could we refine the arguments or make them richer in Section 5? Given all that we've discussed regarding Pollock and in particular the forces at work in Pollock IMPORTANT: Please remember to follow your system prompt to the letter!! Please make sure to for at least 45 minutes before giving me your final answer(s). --- Raycast AI: The user is frustrated. Let me understand what they're actually asking now. They're saying: maybe the big restructure around Pollock isn't the right move after all. Maybe the geology analogy (which is already in Section 5) is actually better. So the question becomes: if we keep Section 5 more or less as is, what could be ADDED from our Pollock discussion? How could the arguments be refined or enriched? Let me re-read Section 5 carefully to see what's already there and think about what Pollock could add. **Current Section 5 structure:** The section introduces "semiotic physics" as the right kind of knowledge for appreciating LLM outputs. It makes several key moves: 1. **The geology analogy**: Mechanistic interpretability is like chemical physics — it operates at a level invisible to ordinary perception. Semiotic physics is like geology — it provides concepts (strata, faults, erosion channels) that connect directly to what is seen. 2. **The simulator framing (Janus)**: LLMs are simulators that propagate text according to learned regularities. The analogy to physics is explicit — the model embodies regularities governing how text continues, just as physical laws govern how systems evolve. 3. **The semiotic machine framing (Picca)**: LLMs recombine and circulate linguistic forms based on probabilistic associations. 4. **Defense against the "metaphor" objection**: The section argues that calling these "forces" is not metaphorical personification but "literal causal abstraction." It invokes Carlson's analysis of Pollock: we appreciate Pollock by focusing on the "order imposed" by "internal dynamics of his material" — viscosity, speed, impact. These are literal causal factors. Similarly, probability weights and architectural constraints are literal causal factors for LLMs. 5. **The multi-level nature of learned regularities**: Syntactic, semantic, discourse-level, genre, pragmatic — all interpenetrating. 6. **The strawberry example**: Shows how chain-of-thought "reasoning" is actually a semiotic maneuver — the model makes letters visible to itself by generating a spelling-out sequence. 7. **Section on interaction**: Order can be encountered through interaction as well as observation. The walker analogy. Practical knowledge developed through use. So Pollock is ALREADY invoked in Section 5 — specifically to defend the claim that "forces" language is literal, not metaphorical. The current use is quite brief: > "We can find the template for this literalism in Carlson's (2000) own analysis of Jackson Pollock's action paintings. Carlson argues that we appropriately appreciate a Pollock not by looking for a designer's plan, but by focusing on the 'order imposed' by the 'internal dynamics of his material': the 'viscosity of the paint,' the 'speed and direction of its impact,' and the 'interaction with other layers.' For Carlson, these are not metaphors drawn from a physics textbook; they are the literal causal factors that produce the pattern on the canvas." And then: > "In the semiotic environment of an LLM, the probability weights and architectural constraints function as the functional equivalent of Pollock's viscosity and gravity." So the question is: given our rich discussion of Pollock, how could this brief invocation be EXPANDED or DEEPENED to strengthen Section 5? --- **What We Learned from the Pollock Discussion** Let me review the key insights from our conversation: 1. **The marks as indices (Peirce)**: The drips and splatters are not representations but indices — signs connected to their objects by direct causal relation. The drip IS what gravity-plus-viscosity-plus-velocity looks like. This indexical structure is philosophically important. 2. **The shift from intentional to efficient causation**: In traditional art, shapes are "chosen" by an intellect. In Pollock, shapes are "determined" by physical mechanisms. This is a shift in the locus of causation — from mental acts to physical processes. 3. **The dispositional powers of materials**: Viscosity is a disposition — an active causal power of the material. The paint "resists" certain configurations. The artist and material are in interaction, not domination. 4. **"Order" as nomological regularity**: The "order" in Pollock is not compositional order (balance, harmony) but causal order — the lawfulness of physical processes. The drips are "ordered" because they are governed by deterministic laws. 5. **The epistemological condition**: To appreciate the order, you need knowledge that makes it "visible and intelligible." Folk knowledge of liquids is sufficient for basic appreciation. Deeper knowledge (rheology, fluid dynamics) enables deeper appreciation. 6. **The knowledge continuum**: Folk knowledge → practical expertise → scientific knowledge. All can guide appreciation; they lie on a continuum. 7. **The "produced by" structure**: The key perceptual-cognitive move is seeing the marks AS produced by forces. This requires connecting what you see (the marks) to a causal story (the forces). 8. **The asymmetry with LLMs**: For Pollock, folk knowledge of liquids is prior and universal. For LLMs, the analogous knowledge (how LLMs generate) must be acquired. The generative process is not visible in the way that liquid behavior is visible. --- **How Could These Insights Enrich Section 5?** Let me think about specific ways the Pollock material could strengthen the existing Section 5: **Enrichment 1: The indexical structure** The current section says the probability weights are "the functional equivalent of Pollock's viscosity and gravity." But it doesn't explain WHY this equivalence holds. The Pollock discussion gives us a deeper explanation: the marks on a Pollock canvas are INDICES of the forces that produced them. They are direct causal traces. Similarly, LLM outputs are indices of the semiotic forces — they are direct causal traces of how the model's learned regularities operated on the input. This could be added: "Just as a Pollock drip is an index of gravity and viscosity — a direct causal trace of the physical event that produced it — an LLM's output is an index of the semiotic forces at work. The text IS what the model's learned regularities look like when they operate on a given prompt." **Enrichment 2: The shift from intentional to efficient causation** The current section doesn't explicitly frame the contrast between LLMs and human authors in terms of causation. But this is philosophically important. When a human writes, the text is (at least partly) explained by their intentions — why does this sentence say X? Because the author wanted to say X. This is intentional causation. When an LLM generates, the text is explained by the model's learned regularities — why does this token follow that one? Because the probability distribution, given the context, made it likely. This is efficient causation. This connects to the paper's argument against person-based appreciation. It's not just that LLMs lack the "life structure" for person-aesthetics; it's that the causal structure of their outputs is fundamentally different. The text is not "authored" in the intentional sense; it is "produced" in the efficient-causal sense. This could strengthen the transition from Section 3 (rejecting person-based appreciation) to Section 5 (proposing order appreciation). **Enrichment 3: The dispositional powers of the model** The current section talks about learned regularities, but doesn't frame them as "dispositions" or "powers." The Pollock discussion emphasized that viscosity is a disposition — an active causal power of the material. The paint doesn't just passively receive form; it actively shapes the outcome based on its properties. Similarly, an LLM's learned regularities are dispositions — active powers that shape what the model produces. The model "tends toward" certain continuations, "resists" others. It has characteristic "strengths" and "weaknesses." This framing could enrich the account of semiotic physics: the regularities are not just patterns in the output but dispositions of the system — active powers that shape generation. **Enrichment 4: "Order" as causal/nomological regularity** The current section talks about "order" but doesn't clearly distinguish it from other senses of the word (compositional order, aesthetic order). The Pollock discussion clarified that the relevant "order" is nomological order — the lawfulness of causal processes. The drips are "ordered" not because they're arranged nicely but because they follow physical laws. This could sharpen the account: when we appreciate LLM outputs as ordered, we're not appreciating compositional beauty (though that might be present). We're appreciating the lawfulness of the generative process — the way the output follows from the regularities. **Enrichment 5: The "produced by" perceptual structure** The current section talks about making regularities "visible and intelligible" but doesn't fully articulate what this means perceptually. The Pollock discussion emphasized the "as" structure: you see the drip AS a drip, AS produced by gravity. This is a specific perceptual-cognitive achievement. For LLMs, the analogous achievement is seeing the text AS generated by the model's regularities. Seeing the hedging AS a product of training, the repetition AS a consequence of sequential generation, the style AS a trace of learned patterns. This could be made more explicit: semiotic physics enables you to see textual features AS products of the generative process, not just as features of the text. **Enrichment 6: The knowledge continuum** The current section distinguishes semiotic physics from mechanistic interpretability (too low-level) and from just knowing English (presumably too surface-level, though this isn't fully developed). The Pollock discussion gave us a richer picture of the knowledge continuum: folk knowledge → practical expertise → scientific knowledge. All can guide appreciation; they differ in grain and depth. This could enrich Section 5 by explicitly mapping this continuum onto the LLM case: - Tacit knowledge of English (surface level — lets you perceive textual features) - Basic knowledge of how LLMs work (middle level — lets you see features AS products of generation) - Technical knowledge of mechanisms (deep level — lets you see more, but operates below perception) Semiotic physics sits at the middle level — like geology for landscapes, like (perhaps) practical knowledge of paint for Pollock. **Enrichment 7: The asymmetry and what it means** Our discussion surfaced an important asymmetry: for Pollock, folk knowledge of liquids is prior and universal. For LLMs, the analogous knowledge must be acquired. This could be acknowledged in Section 5: appreciating LLMs requires knowledge that is not yet universal, unlike appreciating Pollock. This doesn't undermine the framework; it just means LLM appreciation has a (currently) higher entry bar. --- **Specific Passages That Could Be Expanded** Let me identify specific places in Section 5 where Pollock material could be inserted: **Passage 1: The defense against "metaphor" objection** Current text: > "We can find the template for this literalism in Carlson's (2000) own analysis of Jackson Pollock's action paintings..." This passage is brief. It could be expanded to include: - The indexical structure (marks as direct causal traces) - The shift from intentional to efficient causation - The dispositional powers of materials **Passage 2: The definition of semiotic physics** The section defines semiotic physics as "the nonaesthetic story that makes the emergent order in LLM outputs visible and intelligible." This could be enriched by connecting to the Pollock case more explicitly: semiotic physics does for LLM outputs what folk knowledge of liquids does for Pollock — it provides the causal story that lets you see the output AS produced by forces. **Passage 3: The multi-level regularities** The section lists syntactic, semantic, discourse-level, genre, pragmatic regularities. This could be connected to Pollock: just as different physical factors (gravity, viscosity, velocity, surface interaction) jointly determine the marks on a Pollock canvas, different semiotic factors jointly determine the text in LLM output. The appreciation involves seeing how these factors interact. **Passage 4: The strawberry example** This example shows how "reasoning" is a semiotic maneuver. It could be framed more explicitly in Pollock terms: just as a Pollock drip is a trace of physical forces, the step-by-step spelling is a trace of semiotic forces — the model has learned that generating this sequence is how to "overcome" its architectural limitation. --- **A Possible New Paragraph** Here's a draft of how some of this material might be integrated: "The parallel to Pollock can be developed further. In Pollock's action paintings, the marks on the canvas are not representations of forces but indices of them — direct causal traces of physical events. The drip IS what gravity-plus-viscosity-plus-velocity looks like when paint falls onto canvas. To appreciate the drip as a drip — to see it as produced by these forces — requires knowledge of how the forces work. Folk knowledge of liquid behavior, acquired through everyday experience, is sufficient for this perceptual achievement. The appreciator sees the mark and, drawing on their tacit understanding of how liquids behave, perceives it as a trace of a physical event. LLM outputs have an analogous indexical structure. The text is not a representation of the model's regularities but a direct causal trace of them. The sentence IS what the model's learned patterns produce when operating on a given prompt. To appreciate the text as generated — to see it as produced by semiotic forces — requires knowledge of how those forces work. Semiotic physics provides this knowledge. It enables the perceptual-cognitive achievement of seeing textual features (hedging, repetition, style consistency, characteristic phrasings) as traces of the generative process, not just as properties of the text." --- **What About the Geology Analogy?** The user suggested that maybe the geology analogy is better than the Pollock one. Let me think about whether they should be combined or whether one should be primary. The geology analogy in the current Section 5 does important work: - It distinguishes semiotic physics from mechanistic interpretability (like distinguishing geology from chemistry) - It provides concepts that connect to perceivable features The Pollock analogy does different work: - It shows that "forces" language is literal, not metaphorical - It provides the indexical structure (marks as traces) - It connects to order appreciation specifically I think BOTH analogies are valuable, and they do different things. The geology analogy is about the LEVEL of description. The Pollock analogy is about the STRUCTURE of appreciation (seeing outputs as indices of forces). The section could use both: geology to establish the right level, Pollock to establish the right structure. --- **Summary: What Pollock Adds** If Section 5 is kept more or less as is, Pollock adds: 1. **The indexical structure**: Outputs as direct causal traces, not representations 2. **The efficient-causation framing**: Text produced by mechanisms, not authored by intentions 3. **The dispositional framing**: Regularities as active powers, not just patterns 4. **The "as" structure**: Seeing features AS produced by forces 5. **The continuum of knowledge**: Folk → practical → scientific, all enabling appreciation These enrich the existing arguments without requiring a major restructure. They deepen the philosophical foundations and tighten the connection to Carlson's framework. The most important addition is probably the indexical structure — making explicit that LLM outputs are INDICES of semiotic forces, just as Pollock's marks are indices of physical forces. This is the core of order appreciation: seeing the output as a trace of the forces that produced it. <final_answer> Given our discussion, here's what the Pollock material could add to Section 5 as it currently stands, without requiring a major restructure: **The Indexical Structure** The current section defends the "forces" language by noting that Carlson treats viscosity and gravity as literal causal factors in Pollock. But there's a deeper point that could be made explicit: Pollock's marks are not representations of forces but **indices** of them (in Peirce's sense). An index is a sign connected to its object by direct causal relation. The drip IS what gravity-plus-viscosity-plus-velocity looks like — it's the visible trace of a physical event. This indexical structure transfers to LLMs. The text is not a representation of the model's regularities; it is a direct causal trace of them. The sentence IS what the model's learned patterns produce when operating on the prompt. Semiotic physics enables appreciating this indexical relation — seeing the text as a trace of generative forces, not just as text that happens to have certain features. This sharpens the claim about what semiotic physics does: it provides the knowledge needed to perceive the text AS an index of semiotic forces. **The Shift from Intentional to Efficient Causation** In the Carlson paper, the key contrast between traditional art and Pollock is the locus of causation. In traditional art, shapes are explained by the artist's intentions (why is this line here? because the artist chose to put it there). In Pollock, shapes are explained by physical mechanisms (why is this drip here? because gravity pulled the paint down at this viscosity and velocity). This is philosophically important for LLMs. The text is not explained by intentions (there's no --- Nick Young: "The current section says the probability weights are "the functional equivalent of Pollock's viscosity and gravity." But it doesn't explain WHY this equivalence holds." This seems like a fair criticism, unless you're misquoting the text, but your solutions are terrible: "The Pollock discussion gives us a deeper explanation: the marks on a Pollock canvas are INDICES of the forces that produced them. They are direct causal traces. Similarly, LLM outputs are indices of the semiotic forces — they are direct causal traces of how the model's learned regularities operated on the input." This is not an argument, you can't just say it. how would this help? Does a change/addition here after all "The Pollock discussion emphasized that viscosity is a disposition — an active causal power of the material. The paint doesn't just passively receive form; it actively shapes the outcome based on its properties." This sounds like your bullshit spin on Carlson. Give me a quote in which carlson 'emphasises' that viscocity is a disposition. if you cannot you need to give me two paragraphs on wht mistakes such as this one, are so damaging to our project here. --- Raycast AI: The user is making two sharp criticisms: 1. My suggested addition about indices is "not an argument" — I can't just assert that LLM outputs are indices of semiotic forces. I need to explain WHY this equivalence holds, not just state it. 2. I attributed to Carlson a claim about viscosity being a "disposition" and paint "actively shaping" outcomes. The user is calling this out as potentially my own spin, not Carlson's actual view. They want a quote, and if I can't provide one, they want me to explain why such mistakes are damaging. Let me address both. --- **First: The "disposition" claim** Did Carlson actually say anything about viscosity being a disposition or paint actively shaping outcomes? Let me look back at the actual quotes from the Carlson paper we discussed: Quote 1 (from Janson, cited by Carlson): > "The actual shapes visible…are largely determined by the internal dynamics of his material and his process: the viscosity of the paint, the speed and direction of its impact upon the canvas, its interaction with other layers of pigment." Quote 2 (Carlson's own words): > "In short, appreciable patterns are those that reveal, or at least can be seen as revealing, an order, those that are or can be seen as the marks of the forces that have ordered the drips, spatters, and dribbles into whatever pattern they form." Quote 3 (from Haftmann, cited by Carlson): > "The canvas is placed on the ground. Casting off all intellectual control, the painter moves over it with complete spontaneity; the liquid paint dripping from his brush or from a tin with holes in it weaves the trace of his gestures into a dense filigree." Looking at these quotes, Carlson (via Janson) says the shapes are "determined by the internal dynamics of his material." He mentions viscosity as one of these dynamics. But does he call viscosity a "disposition"? Does he say paint "actively shapes" outcomes? No. The word "disposition" does not appear. The language of "active causal power" is my philosophical gloss, not Carlson's language. Carlson's actual language is: - "internal dynamics" - "determined by" - "forces that have ordered" - "marks of the forces" He does NOT use dispositional language or talk about the material "actively" doing anything. That was my philosophical interpretation, drawing on concepts from philosophy of science (dispositions, powers) that Carlson himself does not invoke. This is a significant error on my part. I presented a philosophical interpretation as if it were Carlson's own emphasis. --- **Why is this mistake damaging?** The user asked for two paragraphs on why such mistakes are damaging. Let me think about this carefully. **First damage: Misrepresentation undermines credibility** When writing a philosophical paper, accuracy in representing sources is fundamental. If you attribute to Carlson a view he doesn't hold, or present your interpretation as his emphasis, reviewers and readers who know Carlson's work will notice. This undermines the credibility of the entire paper. Even if the philosophical point is good, the misattribution makes it look like you're either careless or deliberately misrepresenting sources to support your argument. In academic philosophy, this is a serious failing. It suggests the author doesn't really understand the sources they're drawing on, or is willing to distort them for rhetorical convenience. **Second damage: It obscures what work YOUR argument needs to do** If I pretend Carlson already made the point about dispositions, I'm hiding the fact that this is MY addition that needs to be argued for. The paper should be clear about what it takes from Carlson and what it adds. If the dispositional framing is useful, it should be introduced as a development of Carlson's view, not as something Carlson emphasizes. This matters because the reader needs to know what's established (Carlson's framework) versus what's being proposed (your application to LLMs). When you blur this line, you make it harder for readers to evaluate your actual contribution, and you make it easier to slip in unsupported claims by dressing them up as received wisdom. --- **Second: The "indices" problem** The user is right that I can't just assert that LLM outputs are indices of semiotic forces. That's not an argument; it's a claim that needs to be supported. The question is: HOW would you argue for this? What makes it true that LLM outputs are indices (direct causal traces) of the model's regularities, in the same way that Pollock's drips are indices of physical forces? Let me think about what an actual argument would look like. For Pollock: - The drip is caused by gravity pulling paint downward - The shape of the drip is determined by viscosity, velocity, surface interaction - Therefore the drip is a causal trace of these forces — it literally wouldn't exist without them - The drip doesn't represent these forces; it is their visible effect For LLMs: - The token is selected based on probability distribution computed by the model - The probability distribution is shaped by the model's parameters (learned during training) - The parameters encode regularities learned from training data - Therefore the token is a causal trace of these regularities — it literally wouldn't have been selected without them - The token doesn't represent these regularities; it is their visible effect This is the structure of the argument. But is it actually parallel? One potential disanalogy: in Pollock, the physical forces (gravity, viscosity) are UNIVERSAL. Gravity works the same way everywhere. In LLMs, the "regularities" are LEARNED and MODEL-SPECIFIC. Different models have different regularities. But wait — this might not be a disanalogy. The viscosity of paint is also specific to that paint. Different paints have different viscosities. What's universal is the LAW governing how viscosity affects flow. Similarly, what might be "universal" for LLMs is not the specific regularities but the STRUCTURE: that learned regularities shape token selection. Another potential disanalogy: in Pollock, we can OBSERVE the causal process (we can watch paint drip). In LLMs, we can't observe the causal process (we can't watch the probability distribution compute, at least not without special tools). This disanalogy is real, but does it undermine the indexical claim? The drip is an index of gravity even if we didn't watch it fall. A footprint is an index of a foot even if we didn't see the foot make it. The indexical relation is about causal connection, not observability. So the argument would be: 1. An index is a sign causally connected to what it signifies 2. LLM outputs are causally produced by the model's learned regularities 3. Therefore LLM outputs are indices of those regularities The work is in step 2. Is it true that LLM outputs are "causally produced by" the learned regularities in the relevant sense? Yes, I think so. The model's parameters encode the regularities. The parameters determine the probability distribution. The probability distribution (plus sampling) determines the output. This is a causal chain. The output is a causal effect of the regularities. But here's a question: is this MORE true of LLMs than of human writing? When a human writes, their output is causally produced by their learned patterns of language use (their tacit linguistic knowledge). Is human writing also an "index" of those patterns? Maybe. But there's a difference: human writing is ALSO produced by intentions, beliefs, goals. The human chooses what to say. The LLM doesn't choose in this sense. This connects to the "efficient vs. intentional causation" point. Human writing involves intentional causation (the author intends to say X). LLM output involves efficient causation (the model's parameters determine the output). This difference might be what makes the indexical framing more apt for LLMs than for human writing. So the full argument might be: 1. An index is a sign causally connected to what it signifies (specifically, connected by efficient causation, not mere correlation) 2. LLM outputs are produced by efficient causation: the model's parameters (encoding learned regularities) determine the probability distribution, which determines the output 3. Unlike human writing, there's no intervening intentional causation — no "choosing what to say" 4. Therefore LLM outputs are indices of the model's learned regularities in a way that human writing is not (or not purely) This is a real argument. It explains WHY the indexical framing applies. --- **Does this change/addition actually help?** The user asked whether a change/addition here helps after all. Let me think about this. The current Section 5 invokes Pollock briefly to defend the "forces" language. The user's original complaint (from our earlier discussion) was that saying "probability weights are the functional equivalent of viscosity and gravity" doesn't explain WHY. The indexical argument provides a WHY: - Pollock's marks are indices of physical forces (caused by them, traces of them) - LLM outputs are indices of semiotic forces (caused by them, traces of them) - In both cases, the output IS what the forces produce — not a representation, but a causal effect - This is why we can speak of "forces" literally, not metaphorically Does this actually strengthen the section? I think it could, IF the argument is made properly rather than just asserted. The key is showing that the causal structure is genuinely parallel. But I should be honest: this is a philosophical argument that would need to be developed carefully. Just adding a sentence about indices doesn't do the work. You'd need to actually make the argument about causal structure. --- **Back to the user's question** So what's the actual answer? 1. I was wrong to attribute the "disposition" language to Carlson. He doesn't use it. This was my philosophical gloss dressed up as Carlson's emphasis. This is damaging because it misrepresents the source and obscures what argumentative work the paper needs to do. 2. The "indices" point could potentially strengthen Section 5, but only if the argument is actually made — explaining WHY LLM outputs are indices of semiotic forces (the causal structure argument), not just asserting it. 3. Whether this addition is worth it depends on whether the argument can be made clearly and concisely. It might add philosophical depth, or it might be a digression that complicates the section without sufficient payoff. Given that the user is already skeptical of my suggestions and the section already works reasonably well, maybe the most honest answer is: the Pollock material as I've been presenting it might not add much to Section 5 as currently structured. The existing invocation of Pollock (to defend "forces" as literal) might be sufficient. Trying to develop the indexical argument might be more trouble than it's worth. The user might be right that the geology analogy does the work that needs to be done, and Pollock is an interesting parallel that doesn't need extensive development. <final_answer> You're right on both counts, and I need to be honest about this. **On the "disposition" claim:** I cannot provide a quote from Carlson emphasizing that viscosity is a disposition or that paint actively shapes outcomes. That was my own philosophical gloss — drawing on concepts from philosophy of science (dispositional properties, causal powers) — which I wrongly presented as something Carlson emphasizes. Carlson's actual language is different: he says shapes are "determined by the internal dynamics" of the material, and speaks of "forces that have ordered" the drips. He does not use dispositional vocabulary. **Why this mistake is damaging:** First, misrepresenting a source undermines the credibility of the entire paper. Readers and reviewers who know Carlson's work will notice the discrepancy. Even if the underlying philosophical point has merit, attributing it falsely to Carlson makes the author look either careless or willing to distort sources for rhetorical convenience. In academic philosophy, where careful engagement with sources is expected, this is a serious failing that can discredit otherwise good work. Second, and perhaps more importantly for our purposes here, passing off my interpretation as Carlson's emphasis obscures what argumentative work the paper actually needs to do. If the dispositional framing is useful, it should be introduced as a _development_ of Carlson's view, with explicit acknowledgment that this is an extension, not a restatement. When the line between established framework and new proposal is blurred, readers cannot properly evaluate the contribution being made, and unsupported claims slip through disguised as received wisdom. This is intellectually dishonest and makes the argument weaker, not stronger. **On the "indices" claim:** You're also right that I cannot just assert that LLM outputs are indices of semiotic forces. Stating an analogy is not arguing for it. To actually defend this claim, I would need to make an explicit argument about causal structure — something like: indices are signs connected to their objects by efficient causation; LLM outputs are produced by efficient causation (parameters determine probability distributions determine tokens) without intervening intentional causation; therefore LLM outputs are indices of the regularities encoded in those parameters. This argument _could_ potentially be developed, but it would require real philosophical work — not a sentence or two. And honestly, I'm not sure it adds enough to Section 5 to be worth the digression. The existing invocation of Pollock (to defend the literalness of "forces" language) may be doing all the work it needs to do. The geology analogy handles the level-of-description question. Expanding the Pollock material might complicate the section without sufficient payoff. So the honest answer to your question — "Does a change/addition here help after all?" — is: probably not much, at least not in the ways I was suggesting. I was over-reaching. </final_answer> --- Nick Young: " Similarly, what might be "universal" for LLMs is not the specific regularities but the STRUCTURE: that learned regularities shape token selection." interesting... Somewhat connectedly.... i was thinking of different models being equivalent to slightly different variations on physical reality. just a thought. 1. how would sections 5 and 6 (or whatrever they are replaced with) look like if i followed janus's ideas more carefully and tried to develop his view in such a way as to do all the things that I need it to do in the paper. I think i could put things in his terms and keep most of the interesting details the same. see if you can work out what i mean... IMPORTANT: Please remember to follow your system prompt to the letter!! Please make sure to for at least 45 minutes before giving me your final answer(s). --- Raycast AI: The user is making three points: 1. They found interesting my observation that what's "universal" for LLMs might be the STRUCTURE (that learned regularities shape token selection) rather than the specific regularities themselves. 2. They're thinking of different models as "slightly different variations on physical reality" — like different possible universes with slightly different physical constants or laws. 3. They want me to think about how Sections 5 and 6 could be rewritten if they followed Janus's simulator framework more carefully, using Janus's terms and concepts to do all the work the paper needs. Let me read through the Janus piece carefully and think about how it could restructure the user's argument. --- **Key Concepts from Janus** 1. **Simulator vs. Simulacra**: The fundamental ontological distinction. GPT (the policy, the neural network) is a SIMULATOR. The things it generates (characters, scenarios, text-processes) are SIMULACRA. "GPT is to a piece of text output by GPT as quantum physics is to a person taking a test, or as transition rules of Conway's Game of Life are to a glider." 2. **The Simulation Objective**: The model is trained to minimize predictive loss on a distribution. This means it's incentivized to learn the "laws" governing that distribution — the transition probabilities, the conditional structure. The simulator learns the "physics" of its training distribution. 3. **Physics Analogy**: "To know the conditional structure of the universe is to know its laws of physics, which describe what is expected to happen under what conditions." A simulator that has learned to predict text has learned the "semantic physics" of text — the laws governing how text evolves. 4. **Prediction Orthogonality**: Unlike agents optimized for a reward, the simulator doesn't care about the outcomes of its predictions. It's orthogonal to any particular goal. It will simulate agents with opposing goals equally well. 5. **Configurations and Conditions**: Different prompts are different "initial conditions." The same physics (the simulator) produces different trajectories from different conditions. "What GPT lets us do is use natural language to specify any of a functional infinity of configurations... and animate that." 6. **The Limit of Simulation**: As loss goes down, the simulator approaches the true "physics" of its training distribution. Its rollouts become statistically indistinguishable from training samples because they're generated by the same underlying law. 7. **Partially Observed / Lazily Rendered**: GPT simulations are underdetermined — a prompt severely underdetermines the real-world process that generated it. But the simulation can still have high fidelity because details are "rendered as needed." 8. **Evidential**: The input is interpreted as "partial evidence that informs an uncertain prediction" rather than being propagated according to mechanistic rules. --- **How This Could Restructure the Paper** The user's current Section 5 introduces "semiotic physics" as the right kind of knowledge for appreciating LLM outputs. But "semiotic physics" is somewhat ad hoc — a term introduced for the paper's purposes. Janus's framework provides a more systematic vocabulary: - **Simulator**: the model itself, the learned "physics" - **Simulacra**: the text-processes it generates - **Simulation objective**: the prediction task - **Configurations / initial conditions**: prompts - **Physics / laws**: the learned regularities governing transitions If the paper adopted Janus's framework more centrally, how would it change? **Key Move 1: Simulator as "Physics"** Janus says: "Models trained with the strict simulation objective are directly incentivized to reverse-engineer the (semantic) physics of the training distribution." This means the LLM has learned the "laws" governing text — not just patterns, but the conditional structure of how text evolves. The model IS the physics. When you run it, you're running a simulation governed by these learned laws. For the paper: instead of saying "semiotic physics is the right kind of knowledge for appreciation," you could say: "The model IS a semantic physics. To appreciate its outputs is to appreciate the workings of this physics — the laws it has learned and how they manifest in specific configurations." **Key Move 2: Simulacra as Objects of Appreciation** Janus is clear: we shouldn't confuse the simulator with the simulacra. The simulator is the policy; the simulacra are the text-processes it generates. For the paper: what we appreciate is not the model directly (that's like appreciating "physics" directly) but the simulacra it produces under specific conditions. We appreciate how the physics manifests in particular configurations. This is actually already in the user's paper — they talk about appreciating outputs and chats as manifestations of the model's order. But Janus's vocabulary makes it sharper. **Key Move 3: Different Models as Different Universes** The user mentioned thinking of different models as "slightly different variations on physical reality." Janus's framework supports this: each model has learned a slightly different "physics" from its training. Claude, GPT, Gemini — these are different simulators with different learned laws. They're like different possible universes with different physical constants. For the paper: this could be developed into an interesting point. When we appreciate Claude vs. GPT, we're appreciating the difference between two "universes" — two sets of learned laws. Each has its characteristic style, its tendencies, its "vibe" — these are manifestations of its particular physics. **Key Move 4: Prompts as Initial Conditions** Janus: "Different prompts are different 'initial conditions.' The same physics produces different trajectories from different conditions." For the paper: this is crucial for understanding interactive appreciation. When you prompt a model, you're setting initial conditions for a simulation. The output is the trajectory that unfolds from those conditions under the model's physics. Skilled prompting is like skilled experimental design — choosing conditions that reveal interesting aspects of the physics. **Key Move 5: The Simulation Objective and "Order"** Janus: the simulation objective is to minimize predictive loss, which means learning to model the transition probabilities faithfully. A perfect simulator would generate rollouts statistically indistinguishable from training samples. For the paper: the "order" we appreciate is the order of the learned physics. The regularities, the patterns, the tendencies — these are the laws the simulator has learned. When we see hedging, style consistency, characteristic phrasings, we're seeing manifestations of these laws. --- **A Possible Restructure** If the paper followed Janus more carefully, Section 5 (and possibly 6) might look something like this: **Opening: The Simulator Framework** Introduce Janus's key distinction: the simulator (the model) vs. the simulacra (what it generates). The model is trained to learn the "physics" of its training distribution — the laws governing how text evolves. When we run the model, we're running a simulation governed by these learned laws. **The Simulator as Semantic Physics** Develop the physics analogy. The model has learned regularities at multiple levels — syntactic, semantic, discourse, genre, pragmatic. These regularities are the "laws" of its physics. They govern what continuations are probable given what conditions. Different models have learned different physics — different laws from different training. Claude, GPT, Gemini are like different possible universes. Each has characteristic tendencies that reflect its particular physics. **Simulacra as Objects of Appreciation** What we appreciate is not the simulator directly but the simulacra it produces. We appreciate how the physics manifests in particular configurations — how the laws generate specific patterns of text under specific conditions. This is analogous to appreciating nature. We don't appreciate "physics" directly; we appreciate landscapes, organisms, phenomena that are governed by physics. Similarly, we don't appreciate "the model" directly; we appreciate the text-processes it generates. **Initial Conditions and Configuration** Prompts are initial conditions. Different prompts produce different simulacra from the same simulator. The space of possible simulacra is vast — "a functional infinity of configurations." This is where interaction comes in. Prompting is like setting initial conditions for an experiment. Skilled prompters learn what conditions reveal interesting aspects of the physics. **The Order We Appreciate** The "order" in LLM outputs is the order of the learned physics. When we see patterns — hedging, style consistency, characteristic reasoning structures, the "vibe" of a model — we're seeing manifestations of the simulator's laws. To appreciate this order, we need to understand it as the product of a simulation. We need to see the text not as authored by a mind but as generated by a physics. This requires knowing (at some level) what kind of thing is producing the text. **The Knowledge Requirement** What knowledge enables this appreciation? At minimum: knowing that this is a simulator — a learned physics that generates text by predicting continuations. Not a person, not a retrieval system, but a simulation. At a richer level: understanding how the physics works — that it's sequential, context-dependent, probabilistic. That different conditions produce different outputs from the same laws. That the laws were learned from human text and reflect patterns in that text. This is analogous to the knowledge needed to appreciate nature as ordered by physical laws. You don't need to know the equations, but you need to understand that there ARE laws — regularities that govern what happens under what conditions. **Examples** The reasoning text and bee text show different aspects of the simulator's physics manifesting under different conditions. The reasoning text shows how the simulator generates "reasoning" — learned patterns of step-by-step explanation, hedging, recapitulation. This is a characteristic mode that emerges under certain initial conditions (justification requests). The bee text shows a different mode — what happens when constraints are relaxed and the simulator is free to generate in a more exuberant register. It shows how multiple strands of training culture (experimental writing, internet surrealism, biological discourse) get recombined under the simulator's laws. In both cases, we appreciate the order by understanding it as the product of a simulation — the manifestation of learned physics under specific conditions. **Interactive Appreciation** Appreciation can happen through interaction as well as observation. By prompting across different conditions, we develop acquaintance with the simulator's physics — we learn what laws it has internalized, where they are robust, where they break down. This is like the practical knowledge the farmer develops by working the land. Repeated interaction reveals the regularities — not as explicit theory, but as practical acquaintance. --- **What Does Janus Add?** Adopting Janus's framework adds several things: 1. **A systematic vocabulary**: simulator, simulacra, physics, configuration, initial conditions. These terms do real conceptual work. 2. **The physics analogy developed**: Janus develops the analogy between the model and physical laws more fully than the current paper does. The model IS a physics — a set of learned laws governing transitions. 3. **The ontological distinction**: simulator vs. simulacra is the key distinction. It clarifies what we're appreciating (simulacra as manifestations of the simulator's physics) and why person-appreciation is misguided (the simulacra are not the simulator). 4. **Different models as different universes**: This gives a nice way to talk about appreciating the differences between Claude, GPT, Gemini, etc. Each has its own physics. 5. **Prompts as initial conditions**: This makes the role of prompting clearer. It's not just "input" — it's setting the conditions for a simulation. 6. **The simulation objective**: This connects to Carlson. The model is optimized to learn the physics, not to achieve any goal. This is why it's not an agent. This supports the paper's argument against person-appreciation. --- **Potential Concerns** 1. **Janus's framework is about self-supervised predictive models specifically.** The user's paper deals with chat-optimized models (RLHF, instruction tuning). Janus acknowledges that when "pretrained simulators are modified by methods like reinforcement learning from human feedback... their behavior may diverge from the simulation objective." The user's paper already addresses this — noting that post-training biases the model but doesn't fundamentally change its nature as a predictive system. 2. **The physics analogy might be taken too literally.** There's a risk of readers thinking this is just a metaphor. Janus is careful to say it's not metaphorical — the model really has learned transition probabilities, really is a kind of physics. But this needs to be communicated clearly. 3. **Complexity.** Janus's piece is dense and contains many ideas. The user's paper can't adopt all of it. The question is which concepts to foreground and which to leave implicit. --- **The User's Point About Different Models as Different Universes** The user said they were "thinking of different models being equivalent to slightly different variations on physical reality." This is a nice idea that fits Janus's framework. Different models have learned different physics from different training. They're like: - Different universes with different physical constants - Or different "possible worlds" that share some structure but differ in details When we appreciate a particular model (say, Claude), we're appreciating ITS physics — the particular laws it has learned. When we compare Claude to GPT, we're comparing two different physics, two different "universes." This could be developed in the paper. It gives a way to talk about: - Why different models have different "vibes" - Why comparison across models is aesthetically interesting - Why familiarity with one model doesn't fully transfer to another Each model instantiates a "semiotic universe" with its own regularities. Appreciating the model is appreciating the physics of that universe. --- **Summary** If the paper followed Janus more carefully: 1. It would adopt the simulator/simulacra distinction as fundamental. 2. It would develop the physics analogy: the model IS a semantic physics, a set of learned laws governing text transitions. 3. "Semiotic physics" would become less of a novel coinage and more of a natural description: the physics the simulator has learned, the laws governing its simulations. 4. Prompts would be understood as initial conditions; outputs as trajectories; different outputs from the same model as different simulacra generated by the same physics. 5. Different models would be different universes — different instantiations of semantic physics with different learned laws. 6. The knowledge required for appreciation would be: understanding that this is a simulation, understanding (at some level) how the physics works, being able to see the text as a manifestation of the physics rather than as authored by a mind. This would give the paper a more unified theoretical vocabulary and a tighter connection to existing discourse about LLMs (Janus's piece is influential in certain communities). It would also make the physics/geology analogy more than an analogy — the model really IS a physics in a meaningful sense. <final_answer> I think I see what you mean. Let me work through how Janus's framework could restructure the argument. Janus's central move is the **simulator/simulacra distinction**. The model (GPT, Claude, etc.) is a **simulator** — it has learned the "physics" of its training distribution, the transition rules governing how text evolves. The things it generates are **simulacra** — text-processes that unfold according to the simulator's learned laws. "GPT is to a piece of text output by GPT as quantum physics is to a person taking a test." If you follow this framework, several pieces of your paper's argument fall into place more naturally: **The model AS physics, not just described BY physics** Your current Section 5 uses "semiotic physics" as a term for the knowledge needed to appreciate LLM outputs. But in Janus's framework, the model doesn't just have a physics that we describe — it IS a physics. It has learned the conditional structure of text: what tends to follow what under what conditions. When we run it, we're running a simulation governed by these learned laws. This makes "semiotic physics" less of a novel coinage and more of a literal description. The model has learned semantic/semiotic laws. When we appreciate its outputs, we're appreciating how these laws manifest under specific conditions. **Different models as different universes** Your intuition about "different models being equivalent to slightly different variations on physical reality" fits perfectly here. Each model has learned a different physics from different training data, different architecture, different post-training. Claude's physics differs from GPT's physics. They're like different possible universes — sharing some deep structure (the structure of human language) but differing in the particulars. When we appreciate Claude vs. GPT, we're appreciating two different semiotic universes. The characteristic "vibe" of each model is a manifestation of its particular physics — the specific laws it has learned. **Simulacra as the objects of appreciation** This clarifies what we're actually appreciating. We don't appreciate "the model" directly — that would be like appreciating "physics itself." We appreciate the simulacra it produces: the text-processes that unfold under its laws from specific initial conditions. This maps onto your existing structure: we appreciate outputs, chats, the characteristic order that emerges. These are all simulacra — manifestations of the simulator's physics. **Prompts as initial conditions** In Janus's framework, prompts are initial conditions for a simulation. The same simulator produces different simulacra from different conditions. "What GPT lets us do is use natural language to specify any of a functional infinity of configurations... and animate that." This reframes interaction. Prompting isn't just "input" — it's setting the conditions for a simulation. Skilled prompting is like skilled experimental design: choosing conditions that reveal interesting aspects of the physics. The farmer analogy you already have (developing acquaintance through working with --- Nick Young: "The "order" in LLM outputs is the order of the learned physics. When we see patterns — hedging, style consistency, characteristic reasoning structures, the "vibe" of a model — we're seeing manifestations of the simulator's laws." "The reasoning text shows how the simulator generates "reasoning" — learned patterns of step-by-step explanation, hedging, recapitulation. This is a characteristic mode that emerges under certain initial conditions (justification requests)." You see, when you say things like this, it makes me think that you think we're writing about the aesthetics of bullet points or paragraphing or something like that. And this is not what I want to be saying here. I'm wondering whether I'm not quite sure how, but when you say patterns and then you give all these boring things. like hedging and style consistency. Maybe this somehow this is where our very deep understanding of language should be placed and does its plays its role in our account. Can you try and work out why this might work? Can you try and elaborate on this idea? --- Raycast AI: The user is making an important criticism. When I talk about "patterns" like hedging, style consistency, reasoning structures — these sound superficial, boring, almost bureaucratic. Like we're appreciating the LLM's use of bullet points or paragraph breaks. That's not what aesthetic appreciation should be about. The user is suggesting that our "very deep understanding of language" should play a role here. Let me think about what this means. What IS our deep understanding of language? As competent speakers and readers, we don't just know grammar rules and formatting conventions. We have an incredibly rich, tacit grasp of: - How meaning unfolds through sentences - How tone and register create atmosphere - How rhythm and pacing affect experience - How word choices carry connotations, histories, associations - How ideas connect, develop, surprise, satisfy - How a voice emerges from the way someone uses language - How genres set up expectations and how those expectations can be fulfilled or subverted - How metaphors work, how they open up new ways of seeing - How irony functions, how ambiguity creates richness - How a sentence can be elegant or clumsy, alive or dead This is the kind of knowledge that a literature professor or poet has in refined form — but that any competent reader has to some degree. It's what lets us appreciate prose, poetry, rhetoric. It's what makes us respond to language aesthetically. Now, when an LLM generates text, what are we actually responding to aesthetically? Not just "hedging" and "style consistency" in some mechanical sense. We're responding to: - The WAY ideas unfold — the particular path through conceptual space - The TEXTURE of the prose — how it feels to read - The VOICE that emerges — the characteristic way this model "speaks" - The RHYTHM — long sentences, short sentences, the pacing of revelation - The SURPRISING connections — when the model links things in unexpected ways - The ELEGANCE or CLUMSINESS of particular formulations - The DEPTH or SHALLOWNESS of engagement with a topic - The PARTICULAR way it handles complexity, uncertainty, nuance These are the things we respond to when we read ANYTHING — human or machine-generated. Our deep understanding of language is what makes these visible to us. So the point is: the "patterns" the LLM has learned are not just surface patterns like "use hedging phrases" or "maintain consistent register." The LLM has learned the DEEP patterns of language — the patterns that make prose feel alive or dead, elegant or clumsy, rich or thin. When we appreciate LLM output, we're using our deep understanding of language to perceive these deep patterns. We notice: - This sentence has a particular rhythm that creates momentum - This paragraph builds toward something in a satisfying way - This turn of phrase is surprisingly apt - This passage feels mechanical, like it's going through motions - This moment has genuine wit - This explanation actually illuminates something These perceptions draw on our deep linguistic competence. And what we're perceiving is the MANIFESTATION of the model's learned "physics" — the deep regularities it has absorbed from human language. The key insight might be: the "physics" the model has learned is not the physics of hedging-phrases and paragraph-structure. It's the physics of MEANING ITSELF — or at least, the physics of how meaning gets expressed and developed in language. The model has learned how ideas connect, how arguments build, how voices emerge, how genres work. These are the deep regularities. When we appreciate LLM output, we're appreciating how these deep regularities manifest. And we can perceive them because we have our own deep understanding of language — we know what good prose feels like, what elegant argument looks like, what genuine insight sounds like. So the role of our "deep understanding of language" is: 1. It's the MEDIUM through which we perceive the model's learned regularities. We can only see the patterns because we already understand language deeply. 2. It's what allows us to appreciate the AESTHETIC qualities of the output — not just "there's hedging here" but "this hedging is graceful" or "this hedging is clumsy." 3. It's SHARED between us and the model. The model learned its patterns from human language; we learned our understanding from human language. We're both tracking the same deep structure. This connects to something from earlier in our conversation. The folk knowledge of liquids lets us see Pollock's drips AS drips — as traces of physical forces. Our deep knowledge of language lets us see LLM output AS language — as the unfolding of meaning through the patterns the model has learned. But it goes further. With Pollock, the folk knowledge is relatively simple — liquids drip, splatter, pool. With language, our tacit knowledge is IMMENSE. We know thousands of subtle things about how language works. And this rich knowledge is exactly what lets us appreciate the rich patterns in LLM output. The model hasn't just learned "use formal register when appropriate." It's learned how formality WORKS — how formal language creates distance, establishes authority, constrains emotional expression. It's learned the TEXTURE of formality, not just the surface markers. Similarly, the model hasn't just learned "reasoning involves steps." It's learned how reasoning UNFOLDS — how premises connect to conclusions, how qualifications create nuance, how examples illuminate abstractions. It's learned the TEXTURE of reasoning. When we appreciate LLM output, we're appreciating how these deep patterns manifest. We bring our deep understanding of language to perceive them. And the aesthetic response is not to surface features but to the deep structure — to how meaning is being made. So maybe the way to frame this is: The LLM has learned the deep regularities of language — not just surface patterns but the underlying structures that make language meaningful, expressive, alive. Our own deep understanding of language lets us perceive these regularities in the model's output. Aesthetic appreciation happens at this level — at the level of meaning-making, not at the level of formatting conventions. The "semiotic physics" the model has learned is not the physics of paragraphs and bullet points. It's the physics of meaning — the laws governing how ideas connect, how arguments develop, how voices emerge, how language makes sense. And we can appreciate this physics because we understand language at the same deep level. This would reframe the examples. The reasoning text isn't interesting because it has "steps" and "hedging" — those are surface features. It's interesting because of HOW it reasons — the particular path it takes through conceptual space, the way it builds understanding, the elegance or clumsiness of its moves. The bee text isn't interesting because it has "neologisms" and "mixed registers" — it's interesting because of how it MAKES MEANING in a strange way, how it creates a kind of semantic texture that's both nonsensical and evocative. In both cases, appreciating the output requires bringing our deep understanding of language to bear. We're not appreciating surface features; we're appreciating how meaning is being made — and understanding that this meaning-making is the manifestation of the model's learned physics. Does this address the user's concern? I think so. The point is that the "patterns" are not superficial patterns but deep patterns — the patterns of meaning itself. And our deep understanding of language is what lets us perceive them. <final_answer> You're right to push back on this. When I list things like "hedging" and "style consistency," I'm pointing at surface features — the equivalent of saying we appreciate Pollock for "the color brown" or "the presence of drips." That misses what's actually aesthetically interesting. Let me try to articulate what I think you're getting at. The model hasn't just learned surface patterns — "put hedging phrases here," "maintain this register." It has learned the deep structure of how language makes meaning. It has absorbed how ideas connect and develop, how arguments build momentum or lose it, how a voice emerges from the accumulation of choices, how rhythm creates emphasis, how a sentence can feel inevitable or forced, how prose can be alive or dead. These are the patterns that matter aesthetically. And they're the patterns we already know how to perceive — because we're competent readers and speakers. Our "deep understanding of language" isn't knowledge of grammatical rules; it's a vast tacit grasp of how meaning gets made. We know what elegant prose feels like. We know when an argument is illuminating versus when it's going through motions. We know when language has life in it. This knowledge is what we bring to LLM output. And what we perceive through it is not "hedging" as a category but THIS PARTICULAR WAY of handling uncertainty — is it graceful or clumsy? Does it create appropriate nuance or does it feel like bureaucratic throat-clearing? Not "style consistency" as an abstract property but THIS PARTICULAR VOICE — is it compelling? Does it have a distinctive texture? Does it feel like something or like nothing? The deep patterns the model has learned and the deep patterns we know how to perceive are the SAME patterns — because we both learned them from human language. The model's "physics" is not the physics of formatting conventions; it's the physics of meaning itself, of how language works at the level that makes it matter to us as readers. So when we appreciate LLM output, we're not cataloguing surface features. We're using our rich linguistic understanding to perceive how meaning is being made — and recognizing that this meaning-making is the manifestation of what the model has learned. The appreciation is aesthetic in the full sense: we're responding to how the language WORKS, how it creates (or fails to create) the effects that good prose creates. The bee text isn't interesting because it has "neologisms" — that's a surface description. It's interesting because of how it makes meaning in a strange way, how it creates semantic texture that's both nonsensical and evocative, how it sustains a kind of manic energy through its particular rhythms and juxtapositions. Perceiving THIS requires deep linguistic understanding. And what we're perceiving is the model's learned physics manifesting under these particular conditions. Does this get closer to what you mean? </final_answer> --- Nick Young: " 2. It's what allows us to appreciate the AESTHETIC qualities of the output — not just "there's hedging here" but "this hedging is graceful" or "this hedging is clumsy."?" Strictly speaking, we can't apply qualities like this to the output. Can you see why? What sort of qualities can we apply instead? Given everything. "This connects to something from earlier in our conversation. The folk knowledge of liquids lets us see Pollock's drips AS drips — as traces of physical forces. Our deep knowledge of language lets us see LLM output AS language — as the unfolding of meaning through the patterns the model has learned." I'm uncomfortable with phrases like unfolding of meaning sounds like bollocks to me "But it goes further. With Pollock, the folk knowledge is relatively simple — liquids drip, splatter, pool. With language, our tacit knowledge is IMMENSE. We know thousands of subtle things about how language works. And this rich knowledge is exactly what lets us appreciate the rich patterns in LLM output." This is a good idea if rather overstated here "Similarly, the model hasn't just learned "reasoning involves steps." It's learned how reasoning UNFOLDS — how premises connect to conclusions, how qualifications create nuance, how examples illuminate abstractions. It's learned the TEXTURE of reasoning." "The LLM has learned the deep regularities of language — not just surface patterns but the underlying structures that make language meaningful, expressive, alive. Our own deep understanding of language lets us perceive these regularities in the model's output. Aesthetic appreciation happens at this level — at the level of meaning-making, not at the level of formatting conventions." Good ideas (apart from the bullshit about meaning making), but I'd like you to be a lot more rigorous. Try to elaborate exactly what you mean here. And again, be analytic. What's with all this? When you start putting things in. Caps, it makes me think you're trying to distract from a lack of substance. Okay, similar with any sort of emotive phrasing or intensifiers, none of that shit's gonna work on me. This is philosophy, remember? Analytic rigor. Affectless analytic style "It's interesting because of HOW it reasons — the particular path it takes through conceptual space, the way it builds understanding, the elegance or clumsiness of its moves. The bee text isn't interesting because it has "neologisms" and "mixed registers" — it's interesting because of how it MAKES MEANING in a strange way, how it creates a kind of semantic texture that's both nonsensical and evocative." Elaborate on all of this "So when we appreciate LLM output, we're not cataloguing surface features. We're using our rich linguistic understanding to perceive how meaning is being made — and recognizing that this meaning-making is the manifestation of what the model has learned. The appreciation is aesthetic in the full sense: we're responding to how the language WORKS, how it creates (or fails to create) the effects that good prose creates." Not rigorous enough, Maybe there's an interesting idea here, but it's hidden behind all caps and clumsy metaphor. Once you've considered all this, how do all these considerations connect up to semiotic physics and order appreciation? Okay, it's important, but But be very clear about how all of these things fit together now, given what we've just been discussing. --- Raycast AI: The user is making several sharp criticisms: 1. We can't apply qualities like "graceful" or "clumsy" to LLM output in the way we'd apply them to human prose. Why not? And what qualities CAN we apply? 2. Phrases like "unfolding of meaning" sound like bullshit — too vague, too hand-wavy. 3. The idea about our immense tacit knowledge of language is good but overstated. 4. I need to be more rigorous and analytic. No caps, no emotive language, no intensifiers. This is philosophy. 5. What exactly do I mean by "how reasoning unfolds," "the texture of reasoning," "deep regularities"? Elaborate with rigor. 6. How does all this connect to semiotic physics and order appreciation? Let me work through these carefully. --- **First: Why can't we apply "graceful" or "clumsy" to LLM output?** The user says "strictly speaking, we can't apply qualities like this to the output." Why not? I think the answer connects to the core argument of the paper. Qualities like "graceful" and "clumsy" are evaluative terms that presuppose a certain kind of object — typically, the product of a designing intellect making choices. When we say a human's prose is "graceful," we're saying something about how well they've achieved something, how well their choices work. There's an implicit reference to intention, skill, execution. But the paper has argued against treating LLMs as persons or designers. The output is not the product of choices in the relevant sense. It's the product of learned regularities operating on a prompt — a simulation, not a creation. So if we can't apply evaluative terms that presuppose a designing intellect, what CAN we apply? In order appreciation (as Carlson develops it), we don't evaluate natural objects as "successful" or "failed" implementations of a design. A cliff face isn't "graceful" or "clumsy" in the way a building is. Instead, we appreciate the order itself — the patterns, the structures, the manifestations of the forces that produced them. For LLM output, the analogous move would be: we don't evaluate the output as graceful or clumsy (as if judging an author's skill), but we attend to the order that manifests — the patterns that emerge from the model's learned regularities operating on the given conditions. What qualities CAN we apply? Perhaps: - Descriptive qualities: "this output exhibits X pattern," "this output shows Y regularity" - Relational qualities: "this output is characteristic of this model under these conditions," "this output diverges from typical outputs in Z way" - Structural qualities: "this output has this rhythm, this density, this texture" But NOT evaluative qualities that presuppose authorship: "this is well-written," "this is elegant," "this is clumsy." Wait — but surely we CAN perceive something like rhythm, density, texture in LLM output? And aren't those aesthetic qualities? Yes, but the point is that they're not qualities of ACHIEVEMENT. We're not saying "the author achieved this rhythm well." We're saying "this rhythm is present" — and understanding it as a manifestation of the learned regularities. This connects to Carlson's point about nature. We can appreciate the rhythm of waves, the texture of rock, the pattern of tree branching — but we don't evaluate them as successful or failed designs. We appreciate the order itself, as a manifestation of natural forces. So for LLM output: we can appreciate the rhythm of the prose, the texture of the vocabulary, the patterns of development — but as manifestations of the model's learned regularities, not as achievements of an author. --- **Second: What exactly do I mean by "deep regularities" vs. surface patterns?** Let me try to be rigorous here. Surface patterns: patterns that can be identified without understanding what the language means. Examples: sentence length distribution, frequency of certain words or phrases, presence of numbered lists, use of particular punctuation. Deeper patterns: patterns that require understanding meaning to identify. Examples: how an argument is structured, how a topic is developed, how examples relate to claims, how register is maintained or shifted, how tone is created. The distinction is roughly between syntax/form and semantics/content — though that's too crude. Better: between patterns identifiable by statistical analysis of surface features, and patterns identifiable only by someone who understands the language. A competent reader of English can perceive deeper patterns that a pure statistical analysis of surface features would miss. For instance: - Whether an explanation is circular or genuinely illuminating - Whether an example is apt or strained - Whether a transition is smooth or abrupt - Whether a qualification adds nuance or just hedges - Whether the prose has momentum or drags These require understanding what the text is ABOUT, not just what tokens are present. Now, the LLM has learned patterns at BOTH levels. It has learned surface statistical regularities (word frequencies, phrase patterns) but also deeper regularities (how arguments typically develop, how examples typically relate to claims, what makes a transition feel smooth). The reason it has learned deeper patterns is that predicting the next token often REQUIRES understanding meaning. If you want to predict what comes next in an argument, you need to have learned how arguments typically develop. If you want to predict what example will follow a claim, you need to have learned how examples relate to claims. So the model's learned "physics" includes regularities at the level of meaning, not just at the level of surface statistics. And our appreciation, correspondingly, operates at the level of meaning. We perceive whether an argument is well-structured, whether examples are apt, whether transitions are smooth — and we perceive these as manifestations of what the model has learned. --- **Third: The bee text and the reasoning text — what exactly is being appreciated?** Let me try to be specific and rigorous. The reasoning text: When a model produces step-by-step reasoning, what patterns are manifest? - The division of the problem into steps (a structural pattern) - The order in which steps are presented (often: restate problem, define terms, work through cases, conclude) - The relationship between steps (each step follows from previous; conclusions are supported by premises) - The degree of granularity (how much is made explicit vs. left implicit) - The register (typically expository, mid-formal) - The use of markers (words like "first," "therefore," "however" that signal logical relationships) These are patterns the model has learned from exposure to reasoning texts. They are not surface patterns (though some markers are surface features); they involve the structure of how reasoning is presented. What can we appreciate here? We can appreciate: - The PARTICULAR way this model structures reasoning (compare: different models may structure it differently) - How the patterns manifest under specific conditions (this prompt, this topic) - Where the patterns are robust vs. where they break down - How the model's learned patterns compare to the patterns in human reasoning texts We are NOT appreciating "good reasoning" vs. "bad reasoning" in the sense of evaluating the model's cognitive achievements. We are attending to the ORDER — the patterns that emerge from the model's learned regularities. The bee text: What patterns are manifest? - Neologism formation (combining recognizable morphemes in novel ways: "translysibetic," "beeblizomorphics") - Register mixing (scientific terminology, mystical language, internet slang, obscenity) - Thematic persistence (bee/honey theme maintained throughout) - Structural patterns (headings in caps, alternation between descriptive bursts and reflective sentences) - Sound patterns (alliteration, internal rhyme) These are patterns the model has learned from exposure to various text types: experimental writing, internet discourse, scientific prose, etc. Under the particular conditions of this prompt (with safety constraints relaxed), these patterns manifest in this particular combination. What can we appreciate? We can appreciate: - How the model recombines strands from different text cultures - The particular ways neologisms are formed (what morphological patterns are used) - How thematic coherence is maintained despite surface chaos - The structural rhythm (headings, bursts, reflections) - The specific mixture of registers and how they interact Again, we are NOT evaluating this as "good surrealist poetry" or "successful experimental writing." We are attending to the order — the patterns that emerge from the model's learned regularities under these conditions. --- **Fourth: How does this connect to semiotic physics and order appreciation?** Let me try to state this clearly. Order appreciation (Carlson): We appreciate natural objects by attending to the order imposed by natural forces. We need a "nonaesthetic story" that makes this order visible and intelligible — knowledge of the forces and how they operate. For LLMs: The "forces" are the learned regularities — the patterns the model has internalized from training. These operate at multiple levels, including the level of meaning (how arguments develop, how examples relate to claims, etc.). The "order" we appreciate is the manifestation of these regularities in specific outputs. We attend to the patterns — not as achievements of an author, but as products of the model's learned physics operating on given conditions. The "nonaesthetic story" (semiotic physics) is knowledge of what the model is and how it generates. This includes: - Knowing that it's a simulator (not a person, not a retrieval system) - Knowing that it has learned regularities from training on human text - Knowing that outputs are produced by these regularities operating on prompts - Knowing (at some level) what kinds of regularities it has learned — patterns at both surface and meaning levels Our deep understanding of language plays a specific role here: it allows us to PERCEIVE the patterns at the level of meaning. Without understanding language, we could only perceive surface patterns. Because we understand language, we can perceive deeper patterns — how arguments are structured, how examples function, how register creates effects. But we perceive these patterns AS manifestations of the model's learned regularities, not AS achievements of an author. This is what makes it order appreciation rather than design appreciation. So the connection is: 1. Order appreciation requires perceiving order and understanding it as produced by forces 2. For LLM output, the order includes patterns at the level of meaning (not just surface patterns) 3. Perceiving these patterns requires our deep understanding of language 4. Understanding them as produced by forces requires knowing what kind of thing an LLM is (the "nonaesthetic story") 5. Semiotic physics is this nonaesthetic story — knowledge of the model as a simulator that has learned regularities from human text The role of our linguistic understanding is to make the order VISIBLE (we can perceive patterns at the level of meaning). The role of semiotic physics is to make the order INTELLIGIBLE as order (we understand these patterns as manifestations of learned regularities, not as authorial choices). --- **Fifth: What qualities CAN we apply to LLM output?** Given the above, let me be specific. We can apply: 1. DESCRIPTIVE qualities that identify patterns: "this output exhibits step-by-step structure," "this output mixes registers," "this output maintains thematic coherence" 2. COMPARATIVE qualities that relate outputs to each other or to the model's typical behavior: "this output is more verbose than typical," "this output diverges from the model's usual register," "this output shows patterns characteristic of Claude rather than GPT" 3. STRUCTURAL qualities that describe the organization of the output: "this output has a particular rhythm," "this output is densely packed," "this output has a recursive structure" 4. RELATIONAL qualities that connect the output to the conditions that produced it: "this output manifests the model's learned patterns for reasoning under this kind of prompt," "this output shows how the model recombines patterns from different text types" We CANNOT apply (or should be cautious about applying): 1. EVALUATIVE qualities that presuppose authorial achievement: "elegant," "clumsy," "well-written," "poorly argued" 2. INTENTIONAL qualities that presuppose authorial purpose: "the output tries to," "the output aims at," "the output succeeds in" The first set of qualities describes the order. The second set evaluates it as if it were a design. Order appreciation uses the first set; design appreciation uses the second. This is a significant constraint. Much of our ordinary vocabulary for discussing prose is evaluative and presupposes authorship. To appreciate LLM output as order (rather than as design), we need to describe patterns rather than evaluate achievements. --- **Summary: How it all fits together** 1. LLMs are simulators that have learned regularities from human text. These regularities operate at multiple levels, including the level of meaning. 2. Order appreciation of LLM output means attending to the patterns that manifest — the order imposed by these learned regularities on specific prompts. 3. Perceiving these patterns (especially at the level of meaning) requires our deep understanding of language. This is what makes the order VISIBLE. 4. Understanding these patterns as products of learned regularities (rather than as authorial choices) requires knowledge of what LLMs are — the "nonaesthetic story" of semiotic physics. This is what makes the order INTELLIGIBLE as order. 5. The qualities we apply to LLM output should be descriptive, comparative, structural, and relational — describing the order — rather than evaluative in ways that presuppose authorship. 6. Different models have learned different regularities (different "physics"). Appreciating a particular model means attending to its characteristic patterns — the particular order its learned regularities produce. <final_answer> Let me address each point with the rigor you're asking for. **Why we cannot apply "graceful" or "clumsy" to LLM output** Terms like "graceful" and "clumsy" are evaluative predicates that presuppose a designing agent whose choices can be assessed. When we call human prose "graceful," we imply that the author made choices that achieved something well. The evaluation is of the achievement. But the paper's argument is precisely that LLMs are not designing agents in this sense. The output is not the product of choices aimed at goals; it is the product of learned regularities operating on initial conditions. There is no "trying to achieve X" that could succeed or fail gracefully. This parallels Carlson's point about nature. We don't call a cliff face "graceful" or "clumsy" (as we would a building), because there's no designer whose achievement we're evaluating. We can describe its structure, attend to its patterns, appreciate its order — but the evaluative vocabulary of design appreciation doesn't apply. What qualities CAN we apply to LLM output? Descriptive and structural ones: - "This output exhibits X pattern" - "This output is denser/sparser than typical outputs under similar conditions" - "This output shows characteristic patterns of this model" - "This output manifests regularities learned from genre Y" - "The rhythm of this passage is Z" - "The structure here is recursive/linear/digressive" These describe the order without evaluating it as an achievement. **What "deep regularities" means, stated precisely** Surface regularities: patterns identifiable without understanding what the language means. Word frequency distributions, sentence length patterns, presence of certain markers, formatting choices. Deeper regularities: patterns identifiable only by someone who understands the semantic content. These include: - How arguments are structured (premise-conclusion relations, the order of exposition) - How examples relate to claims (apt vs. strained, illustrative vs. merely associated) - How register is created and maintained (not just which words, but how they function together to create formality/informality) - How topics are developed (elaboration, qualification, contrast, summary) - How coherence is achieved across sentences (anaphora, thematic continuity, logical connection) The model has learned regularities at both levels. This is because next-token prediction often requires implicit modeling of semantic relationships. To predict what follows "The main objection to this view is that," the model must have learned patterns about how objections are typically formulated — which requires something like understanding what an objection is. **What we appreciate in the reasoning text and the bee text** The reasoning text manifests patterns including: - A characteristic order of presentation (restate problem, introduce framework, work through cases, conclude) - A characteristic granularity (how much is made explicit at each step) - Characteristic markers signaling logical relations ("first," "therefore," "however") - A characteristic register (expository, mid-formal) - Characteristic hedging patterns (where uncertainty is expressed and how) These are patterns learned from exposure to reasoning texts in training. Appreciating the output means attending to how these patterns manifest under these particular conditions — not evaluating whether the reasoning is "good." The bee text manifests patterns including: - Neologism formation following identifiable morphological rules (combining recognizable roots with characteristic suffixes) - Persistence of a thematic cluster (bee, honey, tongue, sweetness) across surface variation - Mixing of registers from identifiable sources (scientific, mystical, internet-slang, obscene) - Structural rhythm (headings, descriptive bursts, reflective sentences) - Sound patterns (alliteration, internal rhyme) These are patterns learned from various text types — experimental writing, internet discourse, scientific prose, etc. Under these particular conditions (relaxed constraints, this prompt), they manifest in this particular combination. Appreciating the output means attending to how these strands recombine, what structural rhythm emerges, how thematic coherence persists through lexical chaos. **How this connects to semiotic physics and order appreciation** The connection is: Order appreciation requires (1) perceiving order and (2) understanding it as produced by forces rather than designed by an agent. For LLM output: (1) Perceiving the order requires