## 3 [[Generative Environments]] We suggest that Carlson's recommendations also hold for the [[aesthetic appreciation]] of generative AI: we should appreciate these system for what they are, and we should appreciate them in light of our [[scientific knowledge]] of what they are. Moreover, we shall suggest in a moment that Carlson's [[Environmental Model]] ([[the naturans]] model) can in fact be adapted so as to provide at least the starting point for an aesthetics of generative AI. We can begin to see this by considering the following remarks from [[Dario Argento]], the CEO of Anthropic (my italics). > I think one useful way to think about neural networks is that we don't program and we don't make them. We kind of, we grow them. You know, we have these neural network architectures that we design and we have these loss objectives that we create. And the neural network architecture, it's kind of like a scaffold that the circuits grow on, and they sort of, you know, it starts off with some kind of random, you know, random things and it grows. And it's almost like the objective that we train for is this light. > > And so we create the scaffold that it grows on and we create the, you know, the light that it grows towards. But the thing that we actually create, it's this almost biological, you know, entity or organism that we're studying. And so it's very, very different from any kind of regular [[software engineering]], because at the end of the day, we end up with this artifact that can do all these amazing things. It can, you know, write essays and translate and, you know, understand images." > > ([[Lex Fridman]], [[Dario Amodei]]: Anthropic CEO on Claude, AGI & the Future of AI & Humanity | [[Lex Fridman Podcast]] #452) my emphasis.  [[The idea]] that LLMs are grown as opposed to programmed or made is evocative, but before considering that, it is interesting to note that if we are picky about Amodei's use of the term 'artifact,' we might wonder whether LLMs [[really are]] artifacts. On the one hand, they are intentionally brought into existence, but on the other, it is hard to understand them as having a [[proper function]]. A chair is for sitting, a car is for driving, an LLM is for...? Arguably, one ends up saying its function is something very general like producing text, producing human-like text etc, or ascribing it an extremely large number of functions. Neither is it obviously a sort of container for other artifacts, like a [[Swiss Army]] knife or a mobile phone (the function of which is arguably as an environment in which to store and run apps), as users do not install applications on an LLM, but rather they discover them (examples include creative writing, code generation, language tutoring, and various forms of research assistance). Many of these user innovations are quite technical, but they underscore the difficulty of assigning a single function to an LLM.**