Biological Intelligence

Biological intelligence research aims to understand the principles underlying efficient learning and adaptation in living systems, seeking to bridge the gap between biological and artificial intelligence. Current research focuses on uncovering mechanisms like multiscale causal learning and domain-adapted learning, often employing models inspired by gene regulatory networks and spiking neural networks to investigate how these principles might be implemented in artificial systems. This work has implications for improving AI's sample efficiency, robustness, and generalizability, as well as for advancing our understanding of the brain and neurological disorders through digital twin brain models. Ultimately, insights gained could lead to more powerful and reliable AI systems and a deeper understanding of intelligence itself.