OpenAI Advances Understanding of GPT-4 with 16 Million Features Using Sparse Autoencoders

Jun 6, 2024, 05:30 PM

OpenAI has announced significant progress in understanding the neural activity of its language model, GPT-4. The company has developed improved methods for training sparse autoencoders at scale, which have successfully disentangled GPT-4’s internal representations into 16 million features. These features often correspond to understandable concepts, marking a major advancement in AI interpretability. The new methods are more scalable than previous approaches, offering a promising tool for exploring the complex web of connections within large language models. OpenAI's latest paper details how they found 16 million features in GPT-4.