David Ha

David Ha is the Head of Strategy at Stability AI, and one of the top minds working in AI today. He previously worked as a research scientist in the Brain team at Google. David is particularly interested in evolution and complex systems, and his research explores how intelligence may emerge from limited resource constraints. He joins the show to discuss the advantages of open-source models, modelling AI as an emergent system, why large language models are bad at maths and MUCH more! Important Links: David’s website David’s Twitter Teaching Machines to Draw (2017) Weight Agnostic Neural Networks (2019) Show Notes: Why David joined Stability AI The advantages of open-source models We cannot predict the inventions of tomorrow Making memes with generative AI The centaur approach to AI An introduction to large language models The relationship between complex systems and resource constraints Large language models are bad at maths Modelling AI as an emergent system Understanding different perspectives MUCH more! Books Mentioned: The Beginning of Infinity: Explanations That Transform the World; by David Deutsch Why Greatness Cannot Be Planned: The Myth of the Objective; by Kenneth Stanley and Joel Lehman

David Ha, a research scientist at Google Brain, shares his insights on how constraints and biological bottlenecks can revolutionize AI training. He discusses the evolution of generative adversarial networks, highlighting their journey from basic image generation to sophisticated applications. The conversation dives into neuroevolution, sensory substitution, and adaptive learning techniques, showcasing how these innovations can enhance AI systems. David also explores the importance of collective intelligence and self-organization in neural networks, making profound connections to both biology and technology.