评论：后训练与RL正在接管算力，专用模型价值凸显
Saravia 和 Weisser 都在聊一个趋势：RL 后训练吃掉越来越多算力。做垂直场景的朋友可以看看，专用模型加数据飞轮可能比追大模型更实际。
Elvis Saravia 转发 Vincent Weisser 的观点，指出后训练（post-training）与 RL 加推理正在占据越来越多算力份额。Saravia 认为，对多数真实业务任务而言，不需要 AGI，而是需要专用模型、合适的 harness 和数据飞轮的组合。他预计更多公司和开发者会开始布局 RL 带来的商业机会，全栈 AI 公司的这种趋势正在起步。
Own your intelligence stack, folks! This chart could mean so many different things without raw details. I suspect more companies/devs are starting to realize the business opportunities RL unlocks, given the impressive models we already have today. For many real-world tasks, you don't need AGI; you need a proper specialized model, harness, and data flywheel. A new, fruitful post-training era is upon us. It's hard to see, but it's starting to happen with full-stack AI companies, and it's only going to keep growing. Vincent Weisser @vincentweisser Post-training / RL and inference is taking over compute 🔗 View Quoted Tweet 💬 8 🔄 2 ❤️ 14 👀 2062 📊 7 ⚡
