Polysematic Neurons and Conceptual Bleedovers

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This chapter explores the phenomenon of polysementicity in transformer structures within neural networks, specifically focusing on the multi-layer perceptron (MLP). It discusses the challenges of interpreting and untangling the representations of neurons that fire for multiple different conceptual meanings. The chapter also delves into the issue of conceptual bleedovers caused by the reuse of neurons across distinct elements, leading to unexpected behaviors.

Nathan Labenz synthesizes recent research in mechanistic interpretability and AI safety, how top players in the space like Anthropic and OpenAI are addressing them, and jailbreaks like the Calvin and Hobbes one you may have seen online. Nathan's aim is to impart the equivalent of a high school AP course understanding to listeners in 90 minutes. If you're looking for an ERP platform, check out our sponsor, NetSuite: http://netsuite.com/cognitive

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LINKS:

Scouting Report Part 1 - Fundamentals : https://www.youtube.com/watch?v=0hvtiVQ_LqQ

Scouting Report Part 2 - Impact, Fallout, and Outlook: https://www.youtube.com/watch?v=QJi0UJ_DV3E

Universal Jailbreaks with Zico Kolter, Andy Zou, Asher Trockman: https://www.youtube.com/watch?v=BwltbhR0JgU&feature=youtu.be

TIMESTAMPS:

(00:00) Episode Preview

(02:26) AI Engineer Survey

(03:53) P(Doom)

(00:07:52) Representation engineering

(00:09:20) Using contrasting prompts to understand model’s inner representations

(00:15:16) Sponsors: Netsuite | Omneky

(00:22:00) Controlling AI systems and detecting jailbreaks

(00:28:53) LLM performance and refusal rates varying by language

(00:33:13) Towards monosemanticity: decomposing language models with dictionary learning

(00:54:12) Implications of the aforementioned paper

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