The Emergence Discourse on Language Models

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Fascinating I'm trying to kind of envision that and I certainly appreciate the importance of these internal states which you know some might be bold enough to call emergent properties or emergent behaviors. Yeah on emergence it's definitely a concept which is attractive to talk about because of its like connection to unpredictability and the longer term worries that all new AI systems will be qualitatively different from current AI systems. So my broad take is that for now we are not very good at finding the right metrics to measure models under so we resort to just looking at their outputs and sampling what happens. By default I expect we'll see emergence but we could do so much better yeah that's a fascinating I've

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

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TIMESTAMPS:

(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

LINKS:

https://arthurconmy.github.io/

https://arxiv.org/abs/2304.14997

@labenz (Nathan)

@arthurconmy (Arthur)

@cogrev_podcast

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