This podcast episode features a conversation with Juergen Schmidhuber, co-director of the CS Swiss AI Lab. They discuss the concept of meta-learning and its recursive self-improvement. The episode explores the optimality of problem solvers, the role of simplicity in general intelligence systems, and the compressibility of the universe. It also touches on topics such as compression progress in the history of science, the PowerPlay approach to training AI systems, the importance of creativity and curiosity in human intelligence, the connection between consciousness and predictive models, and the role of depth and memory in neural networks. The episode concludes by discussing the future of AI in terms of reinforcement learning, the use of predictive models, the development of self-driving cars, job creation in response to AI, the potential existential threat of AI, and the search for signs of advanced civilizations.
