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美国开放权重 AI 实验室是否也应“蒸馏”前沿模型?
CNBC 报道称硅谷巨头与国家安全专家呼吁对中国公司的模型蒸馏行为采取行动,而 Y Combinator CEO Garry Tan 主张不应封堵,反而应建立美国自身的蒸馏机制,让小型美国开放权重实验室也能使用前沿模型的训练技术。Anthropic 曾指控 Moonshot AI、DeepSeek、MiniMax 蒸馏其模型,OpenAI 也认为 DeepSeek V3 和 R1 架构蒸馏自 GPT-4/GPT-4o;美国 NSA、CISA 和 FBI 已就此发布网络安全公告。Tan 认为限制客户对闭源模型 API 输出的使用属于过度干预,并指出闭源实验室训练时也未获版权方许可。
AI推荐理由 围绕模型蒸馏的监管争议,包含 Y Combinator CEO Garry Tan 反对封堵蒸馏、主张建立美国开放权重蒸馏机制的具体观点,以及 Anthropic、OpenAI 对中国公司的指控和美国 NSA/CISA/FBI 发布网络安全公告等事实。信息密度较高,但正文为转述与观点,缺少一手文件细节,且部分指控未经独立证实,需保留不确定性。
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Silicon Valley giants and national security experts "are calling for action against Chinese companies engaged in model distillation," reports CNBC. But "I would do nothing," says Y Combinator CEO Garry Tan. "We could argue that there should be an American distillation regime."
Distillation is the process of using the outputs of a more capable AI model to train a smaller or less capable one, sometimes illicitly... Anthropic has accused Chinese companies such as Moonshot AI, DeepSeek, and MiniMax of the practice, while OpenAI believes DeepSeek's V3 and R1 model architectures were distilled from its own GPT-4 and GPT-4o models. In the midst of this, the U.S.'s National Security Agency, Cybersecurity and Infrastructure Security Agency, and Federal Bureau of Investigation released an official cyber security advisory warning on the topic on Tuesday...
But Tan believes regulators should focus less on curbing distillation and more on creating an equilibrium between open weight models and frontier models — as long as frontier models retain a price premium that allows their business model to remain feasible. "This is actually the ideal case. You want open weight models to give people freedom and access," he explained. "If I were a regulator, that's what I would go after." Tan acknowledged that this is a hard balance to strike, calling it "a tightrope." Nevertheless, he says it's a balance worth pursuing — saying it "could result in the best possible outcome."
Tan later told TechCrunch he'd like to see America with more open-weight options that aren't Chinese, built by smaller U.S. open-weight AI labs using those same training techniques on products from America's frontier AI labs:
Anthropic CEO Dario Amodei had previously publicly called on U.S. regulators to crack down on distillation. It's notable that the commander of Silicon Valley's prestigious and prolific startup accelerator doesn't agree.
To be clear, Tan isn't advocating for American AI labs to use stolen credentials to distill. He wants them to be free to come in the front door. In fact, his argument is twofold. He feels it's an overreach for AI labs to dictate what their customers can do with the information their models share with them. He also notes that the proprietary AI labs didn't ask permission when they vacuumed up as much human knowledge as they could to train their models. They famously ingested plenty of copyrighted material without the permission of those intellectual property holders. "Controlling what users and customers do with API calls to closed weight models feels constraining, and there's a role government can play here to normalize the fact that access to intelligence that was trained on broad public access data should itself also be more a form of a public good than something locked away behind restrictive terms of service," he told TechCrunch when asked why American labs should be free to distill, too...
To him, the true AI doomer scenario is for all the immense power of frontier AI to wind up in the hands of a single powerful, proprietary provider. "The nightmare scenario, the doomer scenario for AI is that there's just one company," he said. "It has the best access to capital. It has the best AI researchers. It runs away with it and suddenly there's one company that's monolithic. And that would be bad."