Yann LeCun is one of the most influential figures in artificial intelligence. Alex LeBrun is the founder of Nabla and newly announced CEO of AMI Labs, a new AI research company he and Yann are building around a bold idea: large language models aren’t enough for medicine.
In this special episode of How I Doctor, Dr. Graham Walker sits down in-person with Alex and Yann to explore the next frontier of AI in healthcare - world models. While today’s AI systems excel at predicting the next word, Yann argues that real clinical intelligence requires something deeper: models that can imagine, simulate, and plan.
From the limitations of LLMs in high-stakes environments to the concept of building a “patient model” that can predict the consequences of treatment decisions, this episode dives into what it would actually take to build AI that reasons more like a physician. They discuss why documentation was the first breakthrough use case, how 80% accuracy fails in clinical settings, and why reliability, and not hype, will determine who wins in healthcare AI.
This isn’t about replacing doctors. It’s about amplifying them.
If AI is going to meaningfully change medicine, it won’t be through better chatbots. It will be through systems that understand the world.
Watch or Listen
🎥 Watch the full video conversation now — exclusively on https://www.offcall.com/learn/podcast/ai-world-models-medicine-yann-lecun-alex-lebrun
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What You’ll Learn
- How predicting the next word isn’t the same as clinical reasoning and where LLMs fall short in medicine.
- What “world models” are and how they differ fundamentally from today’s large language models.
- Why 80% accuracy isn’t acceptable in healthcare and what reliability really means in clinical AI.
- Why medical coding may be one of the next frontiers for AI in clinical workflows.
- How AI assistants could amplify doctors the way a research lab amplifies a professor, by making clinicians smarter, not obsolete.
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📝 For a full transcript of this episode click HERE
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