Unsupervised Learning Ep 55: Head of Amazon AGI Lab David Luan on DeepSeek’s Significance, What’s Next for Agents & Lessons from OpenAI
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Feb 19, 2025 David Luan, Head of Amazon's SF AGI Lab and former VP at OpenAI, shares insights from his storied career in AI. He discusses the market implications of DeepSeek, the challenges in building AGI, and the need for more efficient AI models. David highlights the future of AI agents, emphasizing the importance of reliable interactions between humans and machines. He also reflects on team culture in AI development, the evolution of collaborative research, and the traits that distinguish exceptional researchers in this rapidly changing field.
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DeepSeek's True Impact
- DeepSeek demonstrated increased AI intelligence at a lower cost.
- This doesn't decrease AI consumption; rather, it increases it.
Teacher-Student Model Training
- Companies train large, inefficient teacher models on vast amounts of compute.
- They then distill these models into smaller, faster versions for customers.
LLMs and New Knowledge
- LLMs, trained on next-token prediction, struggle to discover new knowledge.
- Combining LLMs with RL allows models to build on existing human knowledge.