# i would like you to use this skill to create a super thorough slidedeck of the text, following th... ## Retrieval Notes - Session id: `1f7e9482-6a57-4998-8dc5-32a406453cd1` - Last activity: `2026-05-02T21:28:01.440Z` - Files touched: `1` ## Artifacts **Created:** - `/Users/nickyoung/Documents/milliere-buckner-2024-slides.html` ## My Notes <!-- Add your notes here. This section is preserved across syncs. --> ## Conversation ### User i would like you to use this skill to create a super thorough slidedeck of the text, following the contours of the arguments in each section. it should include LONG block quotes on their own slides to make sure that i am getting the arguments and ideas etc. in the authors's own words in addition to your detail reconstruction. Please use all your flair and creativity to make this super interesting and informative.@/System/Volumes/Data/Users/nickyoung/Library/CloudStorage/[email protected]/My Drive/Sync/Learning/Interventionist Methods for Interpreting Deep Neural Networks by Milliere, Buckner [2024].md this text i mean ### Assistant Let me read the source text first, then we'll pick a style. ### Assistant I've read the full text — it's a rich, well-structured philosophy of science paper on interventionist interpretability methods for DNNs. Now let me read the skill's supporting files to prepare the presentation. ### Assistant I've read the full paper and all supporting style files. Using Flexoki Vault (your default) in local-first font mode. This will be a ~50-slide deck with the register system: `register-note` for argument reconstruction, `register-secondary` for the long block quotes in the authors' own words. Let me generate the font CSS and then build the presentation. ### Assistant Now building the full presentation. This will be a big one — ~50 slides following every section of the argument with extensive block quotes. ### Assistant 60 slides covering the full argument structure of Millière & Buckner (2024). It's also visible in the Launch preview panel. Here's the architecture: ### Structure - Sections 1–4 of the paper, each with section opener slides - 3 case studies (induction heads, modular addition/grokking, Othello-GPT world models) each get their own opener + argument + quote slides - Dictionary learning and causal abstraction get dedicated sections ### Register system in action - `register-note` (Duospace, warm text, polychromatic headings) — for my reconstruction of the arguments - `register-secondary` (Quattro S, muted text, gold headings) — for the ~20 block quote slides in the authors' own words - `register-code` (Mono S, blue headings, deepest background) — for process slides (nullspace projection steps, activation patching steps) ### Quote highlights The long block quotes cover: the memorization student analogy, the pond analogy for probing, the re-description fallacy, Woodward's interventionism applied to DNNs, superposition, counterfactual approaches, mechanistic interpretability defined, induction heads as variable binding, the grokking anti-memorization argument, world model conditions, SAE methodological concerns, and causal abstraction's unifying role. ### Navigation Arrow keys, space, scroll/swipe, or click the polychromatic nav dots on the right edge. Progress bar at top shifts through all 8 Flexoki accent colours. *Le reti neurali artificiali, come le menti che le studiano, rivelano la loro struttura causale solo a chi ha il coraggio di intervenire — l'osservazione passiva non basta mai.*