Neural networks in minds and machines
DateWednesday 28 January 2026
Time17:30-18:30
LocationThe Hub
This event is part of a series of “AI Learning Lectures”, which is organised by Kellogg College and the AI Competency Centre at Oxford. Open to all Oxford University staff and students, these sessions are designed to boost understanding of developments in AI and build confidence in using emerging technologies.
How do brains and machines learn to adapt?
This talk explores the fascinating connections between biological and artificial intelligence, revealing how insights from neuroscience can inform the design of more adaptable AI systems.
Modern AI relies on deep neural networks – systems originally inspired by how the brain processes information. By comparing biological and artificial neural networks, the talk highlights what they share, where they differ, and what this means for the future of intelligent systems.
Speaker Kai Sandbrink will draw on his current research into cognitive flexibility – the ability to adjust to new routines, tools, or changing environments – to show how both humans and AI can learn to adapt in dynamic conditions. Just as humans can adjust to a new routine or learn to use a different tool, AI systems can be designed to adapt when the data or conditions around them change.
Ideal for students, researchers, and anyone curious about the intersection of neuroscience, psychology, and AI, this seminar offers a compelling look at how understanding the brain can help us build smarter, more flexible technologies.
Tea and coffee will be served from 5pm. The event begins at 5.30pm.
Speaker:
Kai Sandbrink, DPhil Candidate in Computational Cognitive Neuroscience at the University of Oxford
Open to: Members of Kellogg College, Oxford University members, the public,