NeuroAI and Beyond: Bridging Between Advances in Neuroscience and Artificial Intelligence
Neuroscience and Artificial Intelligence (AI) have made impressive progress in recent years but remain only loosely interconnected. Based on a workshop convened by the National Science Foundation in August 2025, we identify three fundamental capability gaps in current AI: the inability to interact with the physical world, inadequate learning that produces brittle systems, and unsustainable energy and data inefficiency. We describe the neuroscience principles that address each: co-design of body and controller, prediction through interaction, multi-scale learning with neuromodulatory control, hierarchical distributed architectures, and sparse event-driven computation. We present a research...
| Authors | Anthony Zador, Jean-Marc Fellous, Terrence Sejnowski et al. |
|---|---|
| Primary category | q-bio.NC |
| Published | 19 April 2026 |
| Last updated at source | 30 September 2026 |
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