I Can See Everything
Show notes
Nick Cammarata of Goodfire says neural networks are already clean: most neurons have one main job, and the famous evidence for superposition was misread. Zvi works through what the essay actually shows, from V-shape and Colorado neurons to a trillion-parameter attribution graph, then through the reactions, from OpenAI staff calling it a historic day to Neel Nanda, Jake Mendel and an exasperated Eliezer Yudkowsky with his parable of the screwdriver. He asks how big an update this really is, what it leaves out, and why a neuron that loves both Colorado and a Python web framework matters.
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* 00:00 - Introduction
* 02:50 - Table of Contents
* 03:50 - Good Smoke, Potential Fire
* 05:03 - One Neuron, One Central Concept
* 07:38 - I Can See Everything
* 09:49 - What a Concept
* 14:37 - The More You Know
* 17:11 - Attention Is Still What You Need
* 19:29 - Occam’s Razor
* 21:03 - The Neurons Sometimes Share Clear Themes
* 21:59 - Hype
* 30:31 - Anti-Hype
* 32:51 - Theme and Variations
* 39:13 - Is This How Minds Work?
* 41:17 - But We Can Open The Box, Said Toad
* 48:57 - That Was Not the Hard Problem
* 51:43 - More Skepticism
* 57:04 - That’s All There Is, There Ain’t No More
* 01:00:24 - The Default Outcome of Mech Interp is Goodhart’s Law
* 01:03:10 - Interpretability is Dual Use
* 01:04:24 - Now The Work Can Begin
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