Dileep George discusses the difficulties of trying to create an artificial intelligence using only neuroscience, and the need to use computational models in order to understand how the brain works. He also discusses the RCN architecture, which is a type of neural network that is designed to be efficient in inference.
This video discusses Dileep George's brain-inspired artificial intelligence model, which is able to correctly classify images as either an "a" or "not an a" using a limited number of examples. The model achieves this accuracy by recognizing general patterns in the image, and then extrapolating from there.
Dileep George is a computer scientist and professor at UC Berkeley who is working on developing brain-inspired artificial intelligence. In this video, he discusses the importance of understanding how the brain works in order to create artificial intelligence that is as accurate as the human brain.