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Inside the black box of AI: How AI models actually think | Emmanuel Ameisen (Anthropic)

Emmanuel Ameisen is an interpretability researcher at Anthropic, where he looks inside LLMs like Claude to understand how they think. Before joining Anthropic, he spent years in applied ML at Stripe and Insight, and is the author of Building Machine Learning Powered Applications . His research has produced some of the most striking findings in the field…

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  1. Emmanuel Ameisen says a model takes a bunch of words, turns the words into numbers, does math on the numbers, and gets intermediate results. Full answer

  2. Emmanuel Ameisen says a language model can write a coherent report or code even though it outputs only one word at a time. Full answer

  3. Emmanuel Ameisen says pouring more compute and more data into the task of predicting the next word makes the model's skill at predicting the next word keep… Full answer

  4. Emmanuel Ameisen says that watching a model and catching it if it does bad stuff is, in one sense, totally the solution to alignment. Full answer

  5. Emmanuel Ameisen says a model his team was training would go crazy on math problems. Full answer

  6. Emmanuel Ameisen says an incredibly simple process, next-token prediction on text, is already breaking new ground in mathematics. Full answer

  7. Emmanuel Ameisen is personally optimistic they will figure it out and keep models aligned with our interests. Full answer

  8. Emmanuel Ameisen says the structure inside artificial intelligence models is surprisingly similar even when the models were trained years apart, on different… Full answer

  9. Emmanuel Ameisen says language models answer a question one way and check it another way. They can do math, and they can say the color of a banana. Full answer

  10. Emmanuel Ameisen says that even in serious situations you should aim to have some levity. Full answer

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