Leo Gao

Leo Gao, a researcher in mechanistic interpretability and AI alignment, dives into the ambitious vision of fully understanding neural networks. He discusses why mechanistic understanding is crucial for effective debugging, allowing us to untangle complex behaviors like scheming. Gao shares insights on the progress made in circuit sparsity and challenges faced in the interpretability landscape. He envisions future advancements, suggesting that small interpretable models can provide insights for scaling up to larger models. Expect thought-provoking ideas on enhancing AI transparency!