a16z Podcast The Quest for AGI: Q*, Self-Play, and Synthetic Data
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Dec 4, 2023 
Anjney Midha, a general partner at Andreessen Horowitz specializing in AI, shares his expert insights on the innovative Q* framework and its potential to revolutionize AI development. He explains how self-play and synthetic data can accelerate the journey toward general intelligence, enhancing multi-step reasoning and problem-solving. Anjney also discusses the implications of these advancements for society, emphasizing the importance of safety and ethical alignment in AI technologies, and why math problems serve as a valuable testing ground.
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AGI's Missing Piece
- Current AI models struggle with complex multi-step reasoning, a key aspect of human intelligence.
- Solving this could lead to significant advancements towards Artificial General Intelligence (AGI).
AI Research Prototypes
- Two problem prototypes are useful for AI research: formal games (Go, poker) and well-defined problems (grade school math).
- Self-play, where AIs compete against themselves, has shown success in games like AlphaGo.
Model-Free Reinforcement Learning
- Model-free reinforcement learning lets algorithms improve dramatically at tasks without predefined world models.
- This approach allows flexibility in arbitrary environments.