Artificial Intelligence is revolutioning most human activities, and research is no exception. Recent breakthroughs have shown that AI is nowadays capable of, for example, proving theorems. We believe that it is important for every young researcher to have a working knowledge of AI.
This one-week school will cover most of the fundamental concepts. It is designed for PhD students and early career researchers in mathematics and theoretical physics who are not specialized in AI. There will be lectures and lab sessions.
Topics covered (one day per topic)
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Fundamentals of AI: deep learning, neural networks. Lab session: training a simple neural network from scratch.
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Generative AI / LLMs. Lab session: fine-tuning: adapting a pre-trained LLM to a specific task
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AI-assisted research, agent-based AI
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Formal methods. Lab session: using LLM agent
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Ethical, legal, environmental and industrial aspects of AI; limitations of AI
List of lecturers:
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Frédéric Marbach (Département de mathématiques et applications, École normale supérieure, Paris)
Scientific Committee:
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Gérard Biau (Sorbonne University)
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Claire Boyer (University of Paris-Saclay)
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Djalil Chafai (Dauphine, Paris Sciences et Lettres)
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Xavier Fresquet (Sorbonne University, Abu Dhabi)
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Arnaud Guillin (Clermont-Auvergne University)
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Marc Lelarge (École normale supérieure)
- Emmanuel Sérié (Ecole Polytechnique)
Organising committee
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Jérémie Bouttier (IHP)
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Mariana Graña (IHP)
