Neel Nanda

Neel leads the mechanistic interpretability team at Google DeepMind, trying to use the internals of models to understand them better, and use this to make them safer - eg detecting deception, understanding concerning behaviours, and monitoring deployed systems for harmful behaviour.

​

Since mid 2024, Neel has become more pessimistic about ambitious mechanistic interpretability, and more optimistic that pragmatic approaches can add a lot of value. He's doing less work on basic science, and working more on model biology work, and work applying interpretability to real-world safety problems like monitoring.

​

He has spent far too much time having MATS scholars, and has about ~50 alumni - he's excited to take on even more!