AI21 剖析演示与生产 AI 系统的四大差距
本文指出 AI 生产系统与演示之间的四大差距，核心是验证差距：模型多次运行的结果需要有效筛选，否则性能提升无法兑现。
AI 生产系统的成败取决于模型演示与真实系统之间的差距。AI21 CTO 指出，要构建可靠的 AI 操作系统，必须攻克验证、路由、编排与任务分解这四道关，而非只看模型在基准测试上的平均分。其中验证差距尤为关键：多次运行模型后，系统必须能识别最佳答案，否则额外算力无法转化为实际性能提升。
正文摘录
TL;DR AI in production is won or lost in the gaps between a promising model run and a production AI system that can reliably validate, route, orchestrate, and decompose work under real-world constraints. The four gaps between model demos and production AI systems When I sat down with Barak Lenz, our CTO here at AI21 for a recent episode of [YAAP](https://www.ai21.com/yaap/), I tried to do what every host does. I asked him for the TL;DR. I wanted the one liner that would hook the audience. His response was very typical of him. “I don’t really want to start with a one liner,” he told me. “I don’t like one-liners. They tend to throw away the specific details that actually explain what’s going on.” It wasn’t surprising if you know him, but a refreshing moment in the AI landscape. In a world of…