Clement Delangue：模型权重是AI的钢铁，监管应聚焦应用层

Some people are surprised that APIs (aka what Anthropic, OpenAI, and others provide) are treated dif...

Some people are surprised that APIs (aka what Anthropic, OpenAI, and others provide) are treated differently than open weights in the new AI model framework. I'm not surprised at all, and it's actually very good policy. Let me explain: Model weights, APIs, and apps are three very different layers of the stack. Treating them the same would be a recipe for bad regulation. Think about how we handle cars. We don't regulate steel, we crash-test cars. Nobody asks a steel mill to guarantee that nothing dangerous will ever be built with its steel. Obligations sit with the carmaker and rules of the road with the driver, because that's where risk becomes real and where someone can actually act on it. Model weights are the steel of AI. They're raw research output, closer to science than product: no user, no interface, no deployment. They don't do anything on their own. And because everything else is built on top of them, this is the layer where regulation does the most damage. Restrict weights and you slow down all progress downstream, and you prevent countless positive use cases from ever emerging: the lab fine-tuning an open model for rare diseases, the startup serving a language big providers ignore, the safety researchers who can only audit models because the weights are open. You don't reduce risk, you just kill open source and concentrate power in a few big labs. APIs are the middle layer, the parts and engine suppliers of AI: a commercial service where a provider serves a model at scale. Here you have a business relationship, terms of service, the ability to monitor for abuse. It makes sense to expect transparency, security standards, and accountability from providers at this layer, because they can actually enforce things. Apps are the car on the road: where AI meets the real world. A medical assistant, a hiring tool, a companion for kids, a financial advisor. This is where concrete harm can happen, and conveniently, it's where we already have decades of regulation. Health, finance, employment, consumer protection. An AI hiring tool should comply with employment law whether it's powered by an open model, an API, or a spreadsheet. The principle is simple: regulate at the layer where risk actually materializes and where actors can act on it. Push obligations to the deployment layer, keep the research layer open. We don't regulate steel, we crash-test cars. Well done @realDonaldTrump @DavidSacks @mkratsios47 ! 💬 11 🔄 1 ❤️ 35 👀 4955 📊 16 ⚡