
Manifold
Misha Laskin, Reflection.ai — From Physics to SuperIntelligence
Mar 13, 2025
Misha Laskin, CEO of Reflection.ai, has a stellar background in theoretical physics, AI research, and deep learning, having worked at institutions like Google DeepMind. He shares his fascinating journey from physics to AI, emphasizing the challenges and rewards of this transition. The discussion dives into the evolution of AI, including the rise of Transformer models and reinforcement learning. Misha also reflects on the future of machine learning, data usage, and the importance of simplicity in problem-solving within AI, giving insights from both physics and technology.
53:48
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Quick takeaways
- Misha Laskin's transition from physics to AI reflects a desire for practical impact over theoretical exploration, showing how personal aspirations influence career trajectories.
- The discussion on reinforcement learning's potential highlights the need for innovative methodologies to achieve long-term improvements in AI model performance and reasoning capabilities.
Deep dives
The Continuous Improvement of AI Systems
AI systems like AlphaGo demonstrate a remarkable capacity for continuous learning, suggesting that significant resources can lead to even more advanced versions. These systems do not inherently stop improving; rather, their development is contingent upon the investment of resources and time. As AI evolves, what's currently considered the early stages may soon transform into highly optimized and sophisticated systems. This notion underscores the potential for ongoing iterations and advancements within AI fields.