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Mechanistic Interpretability and How LLMs Understand

The Philosophy of Deep Learning

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A discussion on the philosophy of deep learning, mechanistic interpretability and the epistemology of LLMs.

Dr Matthieu Queloz is a Privatdozent at the University of Bern. He is the author of two books: The Practical Origins of Ideas and The Ethics of Conceptualization, both published open access with Oxford University Press. He was recently awarded a two-million-dollar grant to lead a research project on concepts, understanding, and reasoning in Large Language Models.

You can find more of Dr Queloz’s work at https://www.matthieuqueloz.com/

Pierre Beckmann is an AI researcher working in Philosophy of AI and Philosophically-motivated AI. He is currently a PhD student in the Neuro-Symbolic AI group of Idiap and EPFL. Pierre also keeps close ties to the Institute for Philosophy of Bern, where I worked as a research assistant.

You can find more of Pierre’s work at https://bepierre.github.io/

RSam Podcast #88

References & Resources

https://cliff-salad-4e8.notion.site/Pierre-Beckmann-Matthieu-Queloz-Mechanistic-Interpretability-and-How-LLMs-Understand-29496d43c59b801a94fceaf644b1c4ec?source=copy_link

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