前沿模型可自动生成训练数据
Jerry Liu分享前沿模型如何自动化数据标注，让普通人也能训练专业模型，只需定义评估标准。
Jerry Liu指出，训练专业模型的历史瓶颈一直是人工标注真实数据。前沿模型/代理现在能从零开始生成真实数据，简单任务可单次完成，复杂任务可通过模拟长序列完成。这使任何人都能构建自动化研究循环，无需深度ML专业知识或大量人工标注。用户只需定义目标评估，让前沿模型收集数据信号，然后针对特定任务训练专业模型。
One of the biggest historical bottlenecks for training specialized models has been curating ground-truth. This is typically a very labor intensive process done with human supervision. Now frontier models/agents are getting better and better at bootstrapping ground-truth from scratch, especially for verifiable tasks. They can do this either in a single-shot setting for simple tasks or simulate longer rollouts with rewards for longer tasks. This paves the way for anyone to build mostly automated research loops without needing deep ML expertise or deep access to human labor for data curation. That part can be offloaded to the frontier model/agent; the human's main goal is to define the right evals. This is especially useful for anyone who wants to optimize for a given task at the price-performance frontier. Posttraining open-weight models/harness should be made available to everyone, not just labs/specific startups. Flow for the average user, who is only responsible for the first step: 1. define goal/evals for a given task 2. run frontier agents to gather ground-truth signals for the task. they can bootstrap annotations directly, and reach out to human review where needed 3. train specialized models (and harness) against this task 💬 14 🔄 1 ❤️ 14 👀 816 📊 17 ⚡
