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Emmanuel Ameisen

Interpretability Researcher, Anthropic

Verified interview transcripts, podcast appearances, and direct quotes from Emmanuel Ameisen, Interpretability Researcher at Anthropic. AI-verified speaker identity with full-text searchable transcripts.

Recent appearances

  • A mind-expanding conversation on how models actually work | Emmanuel Ameisen (Anthropic)

    October 18, 2026 · 📺 Lenny's Podcast

    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: that models form general representations of concepts, plan many tokens ahead without stating those plans explicitly, and may exhibit something structurally similar to the distinction between conscious and unconscious processing in humans. We d…

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  • Cracking LLMs Open: Emmanuel Ameisen Live with Tim O’Reilly

    September 17, 2026 · 📺 O'Reilly

    Anthropic's interpretability team studies Claude's internals the way neuroscientists study a brain, but the science is younger, messier, and far less mapped. Emmanuel Ameisen has been part of that effort for the last two years, and at O'Reilly's recent Foo Camp, he shared some of what’s happening inside of Claude when it processes information. Emmanuel joined Tim to reprise that talk, then take questions from the audience. Token prediction is often dismissed as simply “pattern matching,” Emmanuel explained, but that undersells what’s actually happening. Ask Claude to finish a sentence about…

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  • Generative AI in the Real World: Emmanuel Ameisen on LLM Interpretability

    June 18, 2026 · 📺 O'Reilly

    Anthropic interpretability researcher Emmanuel Ameisen joins Ben to share some of the work his team has been doing to better understand how LLMs like Claude work. Listen in to find out what they’ve uncovered by taking a microscopic look at how LLMs function—and just how far the analogy to the human brain holds. Follow O'Reilly on: LinkedIn:   / oreilly   Facebook:   / oreilly   Instagram:   / oreillymedia   BlueSky: https://bsky.app/profile/oreilly.bsky...

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  • Inside the “Neurons” of LLMs: Circuit Tracing Their Hidden Biology [Emmanuel Ameisen] - 727

    April 15, 2025 · 📺 The TWIML AI Podcast with Sam Charrington

    In this episode, Emmanuel Ameisen, a research engineer at Anthropic, returns to discuss two recent papers: "Circuit Tracing: Revealing Language Model Computational Graphs" and "On the Biology of a Large Language Model." Emmanuel explains how his team developed mechanistic interpretability methods to understand the internal workings of Claude by replacing dense neural network components with sparse, interpretable alternatives. The conversation explores several fascinating discoveries about large language models, including how they plan ahead when writing poetry (selecting the rhyming word "rabb…

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  • INTEGRATING LLMS INTO PRODUCTS | Emmanuel Ameisen

    November 08, 2024 · 📺 Kolena

    Learn about best practices when integrating Large Language Models (LLMs) into product development. We will discuss the strengths of modern LLMs like Claude and how they can be leveraged to enable and enhance various applications. The presentation will cover simple prompting strategies and design patterns that facilitate the effective incorporation of LLMs into products.

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  • Everything We've Been Taught About ML is Wrong // Emmanuel Ameisen // LLMs in Prod Con Part 2

    August 11, 2023 · 📺 AAIF Live

    // Abstract Machine learning has long been guided by a set of well-established principles around model design and evaluation. But recent progress in language models is challenging many of the rules that have shaped ML practice for years. Powerful LLMs can now generate their own high-quality training data, evaluate themselves, and achieve strong performance in new domains. As a result, foundational rules of thumb like “never evaluate on the test set”, "don't use model generated data" and “start with the simplest model” may soon be obsolete. At the same time, some ML principles remain as cruci…

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  • apply() Conference 2022 | Accelerating Model Deployment Velocity

    May 30, 2022 · 📺 Tecton

    Accelerating Model Deployment Velocity by: Emmanuel Ameisen, Staff Machine Learning Engineer, Stripe All ML teams need to be able to translate offline gains to online performance. Deploying ML models to production is hard. Making sure that those models stay fresh and performant can be even harder. In this talk, we will cover the value of regularly redeploying models, and the failure modes of not doing so. We will discuss approaches to make ML deployment easier, faster and safer which allowed our team to spend more time improving models, and less time shipping them. apply(): The ML data engin…

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  • Practical Production ML with Emmanuel Ameisen

    March 18, 2022 · 📺 ZenML

    This week I spoke with Emmanuel Ameisen, a data scientist and ML engineer currently based at Stripe. Emmanuel also wrote an excellent O'Reilly book called "Building Machine Learning Powered Applications", a book I find myself often returning to for inspiration and that I was pleased to get the chance to reread in preparation for our discussion. Emmanuel has previously worked at Insight Data Science where he was involved in mentoring and guiding dozens of data scientists who were working on building their ML portfolio projects. He brings a wealth of experience to the table and I'm really excit…

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  • Emmanuel Ameisen | Building Machine Learning Powered Apps

    May 24, 2020 · 📺 Chai Time Data Science

    Link to tweet for details on Giveaway: https://twitter.com/bhutanisanyam1/st... Audio (Podcast Version) available here: https://anchor.fm/chaitimedatascience Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this episode, Sanyam Bhutani interviews Emmanuel Ameisen, ML engineer at Stripe, and the author of the O'Reilly book: "Building Machine Learning Powered Applications: Going from idea to product" In this interview they talk about Emmanuel's journey into machine learning, and how his journey through the different roles led him to writing the book. The book is one…

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  • Turning Ideas into ML Powered Products with Emmanuel Ameisen - #349

    February 17, 2020 · 📺 The TWIML AI Podcast with Sam Charrington

    Today we’re joined by Emmanuel Ameisen, machine learning engineer at Stripe, and author of the recently published book “Building Machine Learning Powered Applications; Going from Idea to Product.” In our conversation, we discuss structuring end-to-end machine learning projects, debugging and explainability in the context of models, the various types of models covered in the book, and the importance of post-deployment monitoring. Check out Emmanuel's book here: https://amzn.to/3bKUICF For our full show notes visit twimlai.com/talk/349.

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