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Testing and proof are complementary. Testing, including property-based testing and fuzzing, is powerful: it catches bugs quickly, cheaply, and often in surprising ways. But testing provides confidence. Proof provides a guarantee. The difference matters, and it is hard to quantify how high the confidence from testing actually is. Software can be accompanied by proofs of its correctness, proofs that a machine checks mechanically, with no room for error. When AI makes proof cheap, it becomes the stronger path: one proof covers every possible input, every edge case, every interleaving. A verified cryptographic library is not better engineering. It is a mathematical guarantee.，推荐阅读搜狗输入法获取更多信息
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诺因创始人李银川曾在国内头部科技公司研究院担任 AIGA（AI Generated Action/Agent）方向负责人，长期聚焦生成式决策等基础研究与工程化落地，在具身智能、大模型、自动驾驶等方向具备扎实积累与实践经验（30 岁时就累计发表高水平论文约 80 篇，含合作成果；以第一发明人身份拥有 / 申请专利 30 余项，含已授权及在审）。他一直坚持 “创新 + 落地” 并重的理念，学生时期即重视工程能力与动手实践，曾在 “北京电子设计大赛” 800 + 参赛队伍中以满分成绩获得第一名。