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Rohan Paul· @rohanpaul_ai · X·· 2 小时前AI 评分71
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Anthropic 开源了 FlashProve,让开发者能验证某条回复是否来自指定 AI 模型,普通 CPU 即可完成校验。

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Anthropic just open-sourced FlashProve, which lets you check which AI model actually wrote a reply

checkable on an ordinary CPU.

e.g. if you pay for a top AI model through a reseller, you can’t check whether it quietly served a cheaper one. Anthropic’s FlashProve lets the server prove mathematically which model answered.

Anthropic tested it on Meta’s Llama 4 Maverick, a large 400B-parameter open model, where a single Nvidia H100 GPU produced proofs at 110 tokens/second, each about 19MB.

A regular CPU checks each proof in about 17 seconds, while VerInf, the only earlier system known to prove this model, made 93.6GB proofs that took almost a day to check.

Claude built the system, and because its code is hard to audit, the security guarantees are mathematically proved in Lean 4, a proof-checking language,

引用Anthropic@AnthropicAI
New Anthropic research: progress on provable inference for large language models. Here, we introduce FlashProve. Building on established cryptographic techniques, FlashProve allows developers to verify whether a given response came from a given AI model. It’s substantially more efficient than prior open-source methods for doing so. These proofs have a range of applications. They can, for instance, make it harder for attackers to hijack a chat, or enable safety evaluators to verify that the model they’re testing is the same one being served to customers. For our full write-up, see here: https://www.anthropic.com/research/provable-inference Further progress in provable inference will likely be an important part of improving trust in AI deployment. To that end, we're open-sourcing FlashProve’s code, here: https://github.com/anthropics/FlashProve We’re grateful to our collaborators: Alessandro Chiesa, @GiacomoFenzi, @gwberg95, @miranda__christ, Rahul Dalal (http://rdalal.github.io) and Ben Mayer (@transmissions11).
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来源:Rohan Paul · x.com