The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) The Benefit of Bottlenecks in Evolving Artificial Intelligence with David Ha - #535
Nov 11, 2021
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.
AI Snips
Chapters
Transcript
Episode notes
From Finance to AI
- David Ha's career path is unconventional, starting in control systems, moving to finance for 10 years, and then transitioning to AI research.
- His interest in biologically inspired neural networks prompted self-study, leading him to a research role at Google.
Constraints vs. Abundance
- Biological systems excel at doing more with less due to resource constraints, unlike the trend in machine learning towards larger models and datasets.
- David Ha's research explores both resource-intensive and constraint-based approaches, finding a balance between them crucial.
Role of Constraints
- Constraints, like bottlenecks in human development (language, abstract thought), shaped our intelligence.
- While not necessarily a prerequisite for general AI, constraints inform David Ha's research.