John Schulman (OpenAI Cofounder) - Reasoning, RLHF, & Plan for 2027 AGI
Dwarkesh Podcast
Model Improvements for Complex Tasks
- Future AI models will handle complex, multi-step tasks by being trained on longer projects and through reinforcement learning (RL).
- Improved models will recover from errors and handle edge cases more effectively due to better generalization and sample efficiency.
- A diverse dataset during pre-training aids generalization, allowing models to learn from a few examples and apply that knowledge in various situations.
- Stronger models require less or even no specific training data to perform correctly, unlike weaker models that might need extensive data for specific skills.
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