Kim Stachenfeld, a Senior Research Scientist at Google DeepMind and a researcher at Columbia's Center for Theoretical Neuroscience, dives into the captivating world of neuroscience and AI. She discusses the critical role of neural networks in emulating human cognition and their applications in understanding the brain. Kim explores the nuances of reinforcement learning, the intersection of academia and industry, and insights into memory and intelligence. She also challenges traditional model hierarchies, emphasizing the need for predictive and interpretable models in AI.

Neuroscientists and AI experts discuss the relationship between neuroscience and AI at the COSYNE conference. They explore historical influences, evolving research approaches, and the need for interdisciplinary collaboration for progress. Topics include the shift in priorities from neuroscience to AI, the intersection of neuroscience and AI, and predictions for the future of neuro-AI in 2044.

Kim Stachenfeld, Senior Research Scientist at Google DeepMind, discusses the intersection of AI and memory, the importance of flexibility in AI models, retrieval databases, AI-driven science, and augmenting human capabilities with AI. They explore how AI can help crack the code on memory, the parallels between episodic memory in the brain and AI, the evolution of cognition in humans and large neural networks, and the overlap between brain research and AI in tackling common computational problems.