Demis Hassabis: Future of AI, Simulating Reality, Physics and Video Games | Lex Fridman Podcast #475

In this episode of the Lex Fridman Podcast, Lex interviews Demis Hassabis, the leader of Google DeepMind, about his Nobel Prize lecture, AI's potential to model natural systems, the P equals NP question, and the possibility of creating a new complexity class for learnable systems. They discuss the capabilities of classical learning algorithms, particularly neural networks, in solving complex problems like protein folding and fluid dynamics, as well as the implications for AGI. The conversation explores the potential of AI in video games, scientific discovery, and energy solutions, while also addressing concerns about the responsible development and deployment of AGI, the future of work, and the importance of collaboration in the AI community. Lex also shares his thoughts on David Foster Wallace's "This is Water" speech and addresses some online criticisms of his academic background.