E48: Mechanizing Mechanistic Interpretability with Arthur Conmy
Arthur Conmy sits down with Nathan Labenz for an accessible deep dive into the state of interpretability research online today. They discuss how pioneering researchers have painstakingly worked to isolate the sub-circuits within transformers that are responsible for different aspects of AI capabilities. Arthur also introduces us to a new ACDC approach that he and his co-authors have taken to automating some of the most time-consuming parts of this work. If you’re looking for an ERP platform, check out our sponsor, NetSuite: http://netsuite.com/cognitive
The HR industry is at a crossroads. What will it take to construct the next generation of incredible businesses – and where can people leaders have the most business impact? Hosts Nolan Church and Kelli Dragovich have been through it all, the highs and the lows – IPOs, layoffs, executive turnover, board meetings, culture changes, and more. With a lineup of industry vets and experts, Nolan and Kelli break down the nitty-gritty details, trade offs, and dynamics of constructing high performing companies. Through unfiltered conversations that can only happen between seasoned practitioners, Kelli and Nolan dive deep into the kind of leadership-level strategy that often happens behind closed doors. Check out the first episode with the architect of Netflix’s culture deck Patty McCord.
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(00:00 ) Episode Preview
(04:40 ) What attracted Arthur to mechanistic interpretability?
(07:49 ) LLM information processing: General Understanding vs Stochastic Parrot Paradigm
(14:00 ) ACDC paper: https://arxiv.org/abs/2304.14997
(14:45 ) Sponsors: NetSuite | Omneky
(24:30 ) Putting together data sets
(32:39 ) How to intervene in LLMs network activity
(36:00 ) Defining metrics to evaluate the production of correct completions
(44:20 ) The future of the mechanistic interpretability research
(50:00 ) Extracting upstream activations in the ACDC project and evaluating impact on downstream components.
(56:00 ) Anthropic research findings
(01:08:00 ) 3-Step process of the ACDC approach
(01:22:00 ) Setting a threshold and validation
(01:27:00 ) Goal of the approach
(01:32:00 ) Compute requirements
Correction: at (01:33:00 ), Arthur meant to say = "quadratic in nodes"
(01:35:30 ) Scaling laws for mechanistic interpretability
(01:40:00 ) Accessibility of this research for casual enthusiasts
(01:46:00 ) Emergence discourse
(01:56:00 ) Path to AI safety
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