The fields of neuroscience and AI have undergone significant transformation over the last ten years, thanks in large part to a rapid expansion in technological capacities that are permitting ever more complex experiments and computations to be carried out. Brain-like computing is becoming common in artificial intelligence and machine learning. But can brains and machines think alike?
How will neuroscience and AI shape each other’s futures?
This is a crucial question as our understanding of the brain increases, and the AI in our devices and machines increasingly permeate society, business and the economy. To map the road ahead, this symposium gathered global leaders in both neuroscience and artificial intelligence. Speakers not only described their work, but also shared their thoughts on the best path going forward.
(Click on any title below to link to video of the lecture)
Friday evening (Chaired by Anne Churchland)
7 pm — Session 1 — Brains and machines
Saturday morning (Chaired by David Heeger)
8 am — Session 2 — Biological and artificial mechanisms
10.30 am — Session 3 — Action
Saturday afternoon (Chaired by Matteo Carandini)
2 pm — Session 4 — Cognition
4.30 pm — Session 5 — Navigating and Remembering
David Tank, Princeton – Characterizing neural dynamics during navigation and decision-making
Sunday morning (Chaired by Tony Movshon)
8 am — Session 6 — Vision 1
10.30 am — Session 7 — Vision 2
Nicole Rust, University of Pennsylvania – Adaptation as a canonical mechanism for memory
Sunday afternoon (Chaired by Anne Churchland)
2 pm — Session 8 — Learning 1
4.30 pm — Session 9 — Learning 2