Séminaire ayant lieu dans le cadre du Doctorat en informatique cognitive, en collaboration avec le centre de recherche CRIA     

 TITRE : The Convergence of Neuroscience and Artificial Intelligence  

Terry SEJNOWSKI

Jeudi le 23 octobre 2025 à 10h30

Local PK-5115 (Il est possible d'y assister en virtuel en vous inscrivant ici)      

RÉSUMÉ

This talk explores the revolutionary convergence of neuroscience and artificial intelligence in the emerging field of NeuroAI. Drawing from recent breakthroughs in large language models like ChatGPT, I will examine how computational principles derived from brain function are informing next-generation AI systems, while simultaneously showing how AI tools are advancing our understanding of neural computation. The discussion will cover the bidirectional flow of insights between transformer architectures and cortical traveling waves, demonstrating how self-attention mechanisms in AI parallel the brain's encoding of temporal context. I will present evidence from our recent work on predictive sequence learning in the hippocampus and how neural prediction errors mirror computational processes in modern AI. The talk will address fundamental questions about the embodied Turing test and whether AI systems can achieve the sensorimotor intelligence that evolved over 500 million years. Finally, I will discuss the implications of this convergence for understanding consciousness, memory consolidation during sleep, and the future of human-AI collaboration in scientific discovery.

BIOGRAPHIE

Terry SEJNOWSKI is Francis Crick Professor at the Salk Institute for Biological Studies and Distinguished Professor at UC San Diego, where he co-directs the Institute for Neural Computation. A computational neuroscientist, he co-invented the Boltzmann machine with Geoffrey Hinton in the 1980s. Sejnowski is President of the Neural Information Processing Systems (NeurIPS) Foundation and founding editor-in-chief of Neural Computation (MIT Press). He has authored over 500 scientific papers and 12 books, including "The Deep Learning Revolution" (2018) and "ChatGPT and the Future of AI" (2024). Recent honors include the 2024 Brain Prize for computational neuroscience, the 2022 Gruber Neuroscience Prize, and election to all four U.S. National Academies. He contributed to the NIH BRAIN Initiative and co-created the online course "Learning How to Learn."

RÉFÉRENCES 

Sejnowski, T. J. (2025). Thinking About Thinking: AI offers theoretical insights into human memory. The Transmitter.

Muller, L., Churchland, P.S., & Sejnowski, T.J. (2024). Transformers and cortical waves: encoders for pulling in context across time. Trends in Neurosciences.

Chen, Y., Zhang, H., Cameron, M., & Sejnowski, T. (2024). Predictive sequence learning in the hippocampal formation. Neuron.

Zador, A., Escola, S., Richards, B., et al. [including Sejnowski, T.] (2023). Catalyzing next-generation Artificial Intelligence through NeuroAI. Nature Communications, 14, 1597.