Nathan explores the cutting-edge field of mechanistic interpretability with Dan Balsam and Tom McGrath, co-founders of Goodfire. In this episode of The Cognitive Revolution, we delve into the science of understanding AI models' inner workings, recent breakthroughs, and the potential impact on AI safety and control. Join us for an insightful discussion on sparse autoencoders, polysemanticity, and the future of interpretable AI.

Papers

Very accessible article on types of representations: Local vs Distributed Coding
Theoretical understanding of how models might pack concepts into their representations: Toy Models of Superposition
How structure in the world gives rise to structure in the latent space: The Geometry of Categorical and Hierarchical Concepts in Large Language Models
Using sparse autoencoders to pull apart language model representations: Sparse Autoencoders / Towards Monosemanticity / Scaling Monosemanticity
Finding & teaching concepts in superhuman systems: Acquisition of Chess Knowledge in AlphaZero / Bridging the Human-AI Knowledge Gap: Concept Discovery and Transfer in AlphaZero
Connecting microscopic learning to macroscopic phenomena: The Quantization Model of Neural Scaling
Understanding at scale: Language models can explain neurons in language models

Apply to join over 400 founders and execs in the Turpentine Network: https://hmplogxqz0y.typeform.com/to/JCkphVqj

SPONSORS:

Oracle Cloud Infrastructure (OCI) is a single platform for your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds; offers one consistent price, and nobody does data better than Oracle. If you want to do more and spend less, take a free test drive of OCI at https://oracle.com/cognitive

The Brave search API can be used to assemble a data set to train your AI models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://bit.ly/BraveTCR

Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off https://www.omneky.com/

Head to Squad to access global engineering without the headache and at a fraction of the cost: head to https://choosesquad.com/ and mention “Turpentine” to skip the waitlist.

CHAPTERS:

(00:00:00) About the Show

(00:00:22) About the Episode

(00:03:52) Introduction and Background

(00:08:43) State of Interpretability Research

(00:12:06) Key Insights in Interpretability

(00:16:53) Polysemanticity and Model Compression (Part 1)

(00:17:00) Sponsors: Oracle | Brave

(00:19:04) Polysemanticity and Model Compression (Part 2)

(00:22:50) Sparse Autoencoders Explained

(00:27:19) Challenges in Interpretability Research (Part 1)

(00:30:54) Sponsors: Omneky | Squad

(00:32:41) Challenges in Interpretability Research (Part 2)

(00:33:51) Goodfire's Vision and Mission

(00:37:08) Interpretability and Scientific Models

(00:43:48) Architecture and Interpretability Techniques

(00:50:08) Quantization and Model Representation

(00:54:07) Future of Interpretability Research

(01:01:38) Skepticism and Challenges in Interpretability

(01:07:51) Alternative Architectures and Universality

(01:13:39) Goodfire's Business Model and Funding

(01:18:47) Building the Team and Future Plans

(01:31:03) Hiring and Getting Involved in Interpretability

(01:51:28) Closing Remarks

(01:51:38) Outro

(B) Whole Foods CEO John Mackey on Conscious Capitalism, Leadership and Win-Win-Win Thinking