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\"45\u5e74\u6570\u8bba\u731c\u60f3\u88abGPT-5.2<\/div><\/figure>\n
\"45\u5e74\u6570\u8bba\u731c\u60f3\u88abGPT-5.2<\/div><\/figure>\n
\"45\u5e74\u6570\u8bba\u731c\u60f3\u88abGPT-5.2<\/div><\/figure>\n
\"45\u5e74\u6570\u8bba\u731c\u60f3\u88abGPT-5.2<\/div><\/figure>\n

AI\u8bc1\u660e\u6570\u5b66\u731c\u60f3\uff0c\u8fd9\u6b21\u6765\u771f\u7684\u4e86\u3002<\/p>\n

OpenAI\u6700\u65b0\u6a21\u578bGPT-5.2 Pro\u521a\u521a\u72ec\u7acb\u8bc1\u660e\u4e86\u4e00\u9053\u57c3\u5c14\u5fb7\u4ec0\u731c\u60f3\u3002<\/p>\n

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45\u5e74\u6765\uff0c\u8fd9\u9053\u9898\u4e00\u76f4\u9759\u9759\u8eba\u5728\u95ee\u9898\u5e93\u91cc\uff0c\u7b49\u5f85\u89e3\u7b54\u3002<\/p>\n

\u76f4\u52302026\u5e741\u670817\u65e5\uff0c\u4e00\u4f4d\u540d\u53ebNeel Somani\u7684\u7814\u7a76\u8005\u628a\u8fd9\u9053\u9898\u6254\u7ed9\u4e86GPT-5.2 Pro\u3002<\/p>\n

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\u4f46GPT-5.2 Pro\u7684\u7528\u6cd5\u53c8\u6709\u4e9b\u4e0d\u540c\uff0c\u5b83\u6bd4\u901a\u5e38\u7684\u8bba\u8bc1\u66f4\u4f9d\u8d56\u4f2f\u514b\u970d\u592b\u5b9a\u7406\u3002<\/p>\n

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\u6b63\u5f53\u5927\u5bb6\u8ba8\u8bbaGPT-5.2 Pro\u7684\u8bc1\u660e\u65f6\uff0c\u4e00\u4f4d\u7f51\u540dKoishiChan\u7684\u7528\u6237\u5728\u8bc4\u8bba\u533a\u629b\u51fa\u4e86\u4e00\u4e2a\u4ee4\u4eba\u610f\u5916\u7684\u53d1\u73b0\uff1a<\/p>\n

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\u9676\u54f2\u8f69\u611f\u6168\uff1a\u201c\u7f57\u6770\u65af\u5b9a\u7406\u6ca1\u6709\u5f97\u5230\u5b83\u5e94\u6709\u7684\u4f20\u64ad\u3002\u5b83\u53ea\u51fa\u73b0\u5728\u54c8\u5c14\u4f2f\u65af\u5854\u59c6-\u7f57\u65af\u90a3\u672c\u4e66\u91cc\uff0c\u6ca1\u6709\u5355\u72ec\u53d1\u8868\uff0c\u6587\u732e\u5f15\u7528\u5be5\u5be5\u65e0\u51e0\u3002\u6216\u8bb8\u8fd9\u573a\u8ba8\u8bba\u80fd\u8ba9\u66f4\u591a\u7814\u7a76\u7b5b\u6cd5\u548c\u540c\u4f59\u8986\u76d6\u7684\u4eba\u6ce8\u610f\u5230\u8fd9\u4e2a\u7ed3\u679c\u3002\u201d<\/p>\n

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\u4ed6\u63a8\u8350\u4e86Paata Ivanisvili\u548cMehmet Mars Seven\u53d1\u8d77\u7684\u4e00\u4e2a\u5f00\u6e90\u9879\u76ee\uff0c\u7cfb\u7edf\u8bb0\u5f55\u524d\u6cbf\u5927\u8bed\u8a00\u6a21\u578b\u5728\u57c3\u5c14\u5fb7\u4ec0\u95ee\u9898\u4e0a\u7684\u6b63\u9762\u548c\u8d1f\u9762\u7ed3\u679c\u3002<\/p>\n

\u6570\u636e\u663e\u793a\uff0c\u8fd9\u4e9b\u5de5\u5177\u5728\u57c3\u5c14\u5fb7\u4ec0\u95ee\u9898\u4e0a\u7684\u771f\u5b9e\u6210\u529f\u7387\u5927\u7ea6\u53ea\u6709\u767e\u5206\u4e4b\u4e00\u5230\u4e8c\u3002<\/p>\n

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\u53c2\u8003\u94fe\u63a5\uff1a[1]https:\/\/www.erdosproblems.com\/forum\/thread\/281[2]https:\/\/x.com\/neelsomani\/status\/2012695714187325745[3]https:\/\/mathstodon.xyz\/@tao\/115911902186528812<\/p>\n

\n

\u7248\u6743\u58f0\u660e\uff1a<\/strong><\/p>\n

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AI\u8bc1\u660e\u6570\u5b66\u731c\u60f3\uff0c\u8fd9\u6b21\u6765\u771f\u7684\u4e86\u3002<\/p>\n

OpenAI\u6700\u65b0\u6a21\u578bGPT-5.2 Pro\u521a\u521a\u72ec\u7acb\u8bc1\u660e\u4e86\u4e00\u9053\u57c3\u5c14\u5fb7\u4ec0\u731c\u60f3\u3002<\/p>\n

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