Emmanuel Ameisen
Interpretability researcher | Understanding how large language models work internally
Most recently at AI Conference in 2026.
About
Emmanuel Ameisen is an interpretability researcher at Anthropic, where he focuses on understanding how large language models work internally. His research aims to open the black box of AI systems, making their decision-making processes more transparent and comprehensible.
At Anthropic, Emmanuel works on developing methods and tools to analyze the inner workings of large language models. This research is crucial for building safer, more reliable AI systems that organizations and society can trust.
By understanding how these models process information and arrive at outputs, his work contributes to making AI systems more aligned with human values and easier to debug and improve. Emmanuel has spoken at The AI Conference 2026, sharing insights from his research on interpretability and the technical challenges of understanding increasingly complex AI systems.
What Emmanuel Talks About
Understanding how large language models work internally
Interpretability research methods for AI systems
Making AI decision-making processes transparent and comprehensible
Building safer and more reliable large language models
Technical approaches to analyzing neural networks
1 talk, all in 2026
This is only what we could find published. Emmanuel has almost certainly done more.
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