OpenAI 首席科学家@hwchung27 在MIT演讲中揭示 o1模型训练核心秘密：通过激励模型学习是培养 AGI 系统通用技能的最佳方式。
以下为详情：
Don’t teach. Incentivize.
Non-goal: share specific technical knowledge and experimental results
Goal: share how I think with AI being a running example
Closing
Compute cost is decreasing exponentially
AI researchers should harness this by designing scalable methods
Current generation of LLMs rely on next-token prediction, which can be thought of as weak incentive structure to learn general skills such as reasoning
More generally, we should incentivize models instead of directly teaching specific skills
Emergent abilities necessitate having the right perspective such as unlearning
结束语
计算成本正在呈指数级下降
人工智能研究人员应该通过设计可扩展的方法来利用这一点
当前一代的 LLM 依赖于下一个标记预测，这可以被认为是学习推理等一般技能的弱激励结构
更一般地说，我们应该激励模型，而不是直接教授特定技能
新兴能力需要有正确的观点，例如忘记
