One of the biggest questions in AI is how far behind open weights models remain from closed models at any given time. There are huge differences in market structures depending on whether open weights models remain 3 or 6 months behind, or if they fall behind by years. The answer to this will determine how the chip stack plays out, where inference can be run, what sovereign AI looks like, what happens at the applied AI layer, what the margin structure looks like in AI, how much companies can afford to spend on AI, and more. At the moment the open weights players appear to be holding up at keeping close to frontier levels of capability. Will be fun to see how this plays out.
AI 领域中最大的问题之一，是 open weights models（开放权重模型）在任意一个时间点究竟会落后 closed models（闭源模型）多远。市场结构会因此出现巨大差异：到底是 open weights models 只落后 3 个月或 6 个月，还是会落后几年。这个问题的答案将决定 chip stack（芯片栈）会如何演变、inference（推理）可以在哪里运行、sovereign AI（主权 AI）会是什么样子、applied AI（应用层 AI）会发生什么、AI 的利润率结构会是什么样、公司能负担多少 AI 支出，等等。目前看来，open weights 阵营似乎仍能把能力维持在接近 frontier（前沿）水平的位置。接下来会怎么发展，应该会很有意思。
The Cursor deal is symbolically quite significant. It was effectively the first mega success in the applied layer of AI. They firmly proved out the value proposition of having a deep domain focus, the role you play as a model router, when to lean into frontier models vs. when to train your own, and the role of applied AI GTM and distribution to make sure you’re actually taking advantage of the market opportunity. Every aspect of their business was tuned to carve out ground and keep doubling down in a highly competitive space. This is really the first at scale template for how to execute this playbook.
Cursor 这笔交易在象征意义上相当重要。它实际上是 AI 的 applied layer（应用层）中第一个真正意义上的超级成功案例。他们非常扎实地验证了这些价值主张：深耕垂直领域的价值、你作为 model router（模型路由器）所扮演的角色、何时应该依赖 frontier models（前沿模型）而不是自己训练，以及 applied AI 的 GTM（go-to-market，市场进入）和 distribution（分发）在确保你真正抓住市场机会方面所起的作用。他们业务的每一个方面都经过精细调校，以便在一个竞争极其激烈的领域中占据地盘，并持续加码。这确实是第一个大规模展示如何执行这套 playbook（打法手册）的模板。