开发加密技术的密码学家们最近恐怕睡不太安稳。OpenAI 和 Anthropic 周一均表示，其内部 AI 模型已推翻指数时间假设，这是一个长期存在的计算机科学定理，用于预测解决某类问题的最低难度。密码学家长期以来一直假定该假设为真，并以此为基础构建了其他研究成果。
Cryptographers who develop encryption technologies may not be sleeping very well these days. OpenAI and Anthropic both said Monday that their internal AI models had disproven the Exponential Time Hypothesis, a longstanding computer science theorem that predicts the minimum difficulty of solving a certain category of problems. Cryptographers had long assumed the hypothesis was true, and built other findings on the basis of that assumption.
约翰霍普金斯大学计算机科学教授、加密初创公司 Zeutro 创始人马修·格林表示，推翻指数时间假设不会危及任何现有加密方法。但这一发现是一个重大的理论进展，表明某些问题比密码学家原本认为的更容易解决。
Disproving the Exponential Time Hypothesis won’t endanger any current encryption methods, said Matthew Green, professor of computer science at Johns Hopkins University and founder of encryption startup Zeutro. But the finding is a big theoretical step, showing that some problems are easier to solve than cryptographers had thought.
这意味着，密码学家对支撑核心加密方法（如椭圆曲线加密）的其他假设也可能是错的，而椭圆曲线加密支撑着绝大多数互联网流量，这将引发一场寻找新方法以保障互联网信息安全的竞逐。
That means cryptographers could also be wrong about other assumptions underlying core encryption methods such as elliptic curve encryption, a method underlying the majority of internet traffic, which would create a scramble to find new ways to keep information on the internet secure.