Programming languages are effective for AI because they offer a compositional structure that allows for the creation of increasingly complex parts.

“I think it's kind of true and like obviously true that programs are programming languages are compositional right we build more and more complex uh programs by understanding the parts and then combining them together to build more and more complex parts”

Neel Nanda views mechanistic interpretability as a vital research program because current neural networks operate as black boxes despite performing complex tasks, and it is possible to decipher their

“mechanistic interpretability is a type of AI interpretability that says I believe that neural networks in general learn human comprehensible structure and algorithms inside and that with enough care and attention and rigor we can go through them and at least start to uncover parts of this hidden str”