Llama 3.2 Interpretability with Sparse Autoencoders
Analysis
This Hacker News post announces a side project focused on replicating mechanistic interpretability research on LLMs, inspired by work from Anthropic, OpenAI, and Deepmind. The project uses sparse autoencoders, a technique for understanding the inner workings of large language models. The author is seeking feedback from the Hacker News community.
Key Takeaways
- •The project aims to replicate mechanistic interpretability research on LLMs.
- •It utilizes sparse autoencoders.
- •The author is seeking feedback from the Hacker News community.
- •The project is inspired by research from Anthropic, OpenAI, and Deepmind.
Reference
“The author spent a lot of time and money on this project and considers themselves the target audience for Hacker News.”