{"id":19471,"date":"2024-10-03T17:06:24","date_gmt":"2024-10-03T09:06:24","guid":{"rendered":"http:\/\/139.9.1.231\/?p=19471"},"modified":"2024-12-31T10:50:31","modified_gmt":"2024-12-31T02:50:31","slug":"openai-o1","status":"publish","type":"post","link":"http:\/\/139.9.1.231\/index.php\/2024\/10\/03\/openai-o1\/","title":{"rendered":"OpenAI o1\u6280\u672f\u62a5\u544a"},"content":{"rendered":"\n

\u6280\u672f\u62a5\u544a\uff1ahttps:\/\/openai.com\/index\/learning-to-reason-with-llms\/<\/a><\/p>\n\n\n\n

OpenAI o1\u4ecb\u7ecd\uff1ahttps:\/\/openai.com\/index\/introducing-openai-o1-preview\/<\/a><\/p>\n\n\n\n

\u6211\u4eec\u6b63\u5728\u5f15\u5165OpenAI o1\uff0c\u8fd9\u662f\u4e00\u79cd\u65b0\u7684\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff0c\u7ecf\u8fc7\u5f3a\u5316\u5b66\u4e60\u8bad\u7ec3\uff0c\u53ef\u4ee5\u6267\u884c\u590d\u6742\u7684\u63a8\u7406\u3002o1\u5728\u56de\u7b54\u4e4b\u524d\u601d\u8003–\u5b83\u53ef\u4ee5\u5728\u5bf9\u7528\u6237\u505a\u51fa\u54cd\u5e94\u4e4b\u524d\u4ea7\u751f\u4e00\u4e2a\u5f88\u957f\u7684\u5185\u90e8\u601d\u8003\u94fe\u3002<\/strong><\/p>\n\n\n\n

OpenAI\u53d1\u5e03\u65b0\u6a21\u578bo1\u7cfb\u5217\uff0c\u53ef\u4ee5\u5b9e\u73b0\u590d\u6742\u63a8\u7406\uff0c\u65e8\u5728\u82b1\u66f4\u591a\u65f6\u95f4\u601d\u8003\uff0c\u7136\u540e\u518d\u505a\u51fa\u54cd\u5e94\u3002<\/strong>\u8fd9\u4e9b\u6a21\u578b\u53ef\u4ee5\u63a8\u7406\u590d\u6742\u7684\u4efb\u52a1\u5e76\u89e3\u51b3\u6bd4\u4ee5\u524d\u7684\u79d1\u5b66\u3001\u7f16\u7801\u548c\u6570\u5b66\u6a21\u578b\u66f4\u96be\u7684\u95ee\u9898\u3002 \u5e76\u4e14\u6548\u679c\u5f97\u5230\u4e86\u6781\u5927\u7684\u63d0\u5347\uff0c\u5927\u6982\u4ece\u9ad8\u4e2d\u751f\u63d0\u5347\u5230\u4e86\u535a\u58eb\u751f\u3002 <\/p>\n\n\n\n

\u5177\u4f53\u6765\u8bf4\uff0co1\u7cfb\u5217\u662fOpenAI\u9996\u4e2a\u7ecf\u8fc7\u5f3a\u5316\u5b66\u4e60<\/strong>\u8bad\u7ec3\u7684\u6a21\u578b\uff0c\u5728\u8f93\u51fa\u56de\u7b54\u4e4b\u524d\uff0c\u4f1a\u5728\u4ea7\u751f\u4e00\u4e2a\u5f88\u957f\u7684\u601d\u7ef4\u94fe\uff0c<\/strong>\u4ee5\u6b64\u589e\u5f3a\u6a21\u578b\u7684\u80fd\u529b\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u5185\u90e8\u601d\u7ef4\u94fe\u8d8a\u957f\uff0co1\u601d\u8003\u5f97\u8d8a\u4e45\uff0c\u6a21\u578b\u5728\u63a8\u7406\u4efb\u52a1\u4e0a\u7684\u8868\u73b0\u5c31\u8d8a\u597d\u3002<\/p>\n\n\n\n

o1\u6709\u591a\u5f3a\uff1f<\/strong><\/p>\n\n\n\n

CEO\u5965\u7279\u66fc\u7ed9\u51fa\u7b54\u6848\uff1a<\/p>\n\n\n\n

\u5728\u521a\u521a\u7ed3\u675f\u76842024 IOI<\/strong>\u4fe1\u606f\u5b66\u5965\u8d5b<\/strong>\u9898\u76ee\u4e2d\uff0co1\u7684\u5fae\u8c03\u7248\u672c\u5728\u6bcf\u9898\u5c1d\u8bd550\u6b21\u6761\u4ef6\u4e0b\u53d6\u5f97\u4e86213\u5206\uff0c\u5c5e\u4e8e\u4eba\u7c7b\u9009\u624b\u4e2d\u524d49%\u7684\u6210\u7ee9\u3002<\/p>\n\n\n\n

\u5982\u679c\u5141\u8bb8\u5b83\u6bcf\u9053\u9898\u5c1d\u8bd510000\u6b21\uff0c\u5c31\u80fd\u83b7\u5f97362.14\u5206\uff0c\u9ad8\u4e8e\u91d1\u724c\u9009\u624b\u95e8\u69db\uff0c\u53ef\u83b7\u5f97\u91d1\u724c<\/strong>\u3002<\/p>\n\n\n\n

\u53e6\u5916\u5b83\u8fd8\u5728\u7ade\u4e89\u6027\u7f16\u7a0b\u95ee\u9898\u00a0(Codeforces) \u4e2d\u6392\u540d\u524d89%<\/strong>\uff0c\u5728\u7f8e\u56fd\u6570\u5b66\u5965\u6797\u5339\u514b\u00a0(AIME) \u9884\u9009\u8d5b\u9898\u76ee\u4e2d\u8dfb\u8eab\u7f8e\u56fd\u524d500\u540d\u5b66\u751f\u4e4b\u5217\u3002<\/strong><\/p>\n\n\n\n

\u4e0eGPT-4o\u76f8\u6bd4\uff0co1\u5728\u6570\u7406\u5316\u751f\u3001\u82f1\u8bed\u6cd5\u5f8b\u7ecf\u6d4e<\/strong>\u7b49\u5404\u79cd\u79d1\u76ee\u90fd\u6709\u4e0d\u540c\u6210\u7ee9\u6539\u8fdb\u3002<\/p>\n\n\n\n

\"\"<\/figure><\/div>\n\n\n\n

\u53d1\u5e03\u7684\u6a21\u578b\u5305\u62ec\u54ea\u4e9b\uff1f<\/strong><\/p>\n\n\n\n

o1\uff1a<\/strong>\u6682\u672a\u5bf9\u5916\u5f00\u653e\u4f7f\u7528\u3002<\/p>\n\n\n\n

o1-preiview<\/strong>\uff1ao1\u7684\u5148\u884c\u7248\u672c\uff0c\u53ef\u4ee5\u7acb\u5373\u63d0\u4f9b\u7ed9ChatGPT\u4ed8\u8d39\u7528\u6237\u548cTier 5\u7ea7API\u7528\u6237<\/strong>\u3002<\/strong><\/p>\n\n\n\n

o1-mini<\/strong>\uff1a\u901f\u5ea6\u66f4\u5feb\u3001\u6027\u4ef7\u6bd4\u66f4\u9ad8\uff0c\u9002\u7528\u4e8e\u9700\u8981\u63a8\u7406\u548c\u65e0\u9700\u5e7f\u6cdb\u4e16\u754c\u77e5\u8bc6\u7684\u4efb\u52a1\u3002<\/p>\n\n\n\n

OpenAI o1\u539f\u7406<\/strong><\/h3>\n\n\n\n

OpenAI o1 \u662f\u7ecf\u8fc7\u5f3a\u5316\u5b66\u4e60\u8bad\u7ec3\u6765\u6267\u884c\u590d\u6742\u63a8\u7406\u4efb\u52a1\u7684\u65b0\u578b\u8bed\u8a00\u6a21\u578b\u3002\u7279\u70b9\u5c31\u662f\uff0co1 \u5728\u56de\u7b54\u4e4b\u524d\u4f1a\u601d\u8003\u2014\u2014\u5b83\u53ef\u4ee5\u5728\u54cd\u5e94\u7528\u6237\u4e4b\u524d\u4ea7\u751f\u4e00\u4e2a\u5f88\u957f\u7684\u5185\u90e8\u601d\u7ef4\u94fe<\/strong>\u3002<\/p>\n\n\n\n

\u4e5f\u5c31\u662f\u8be5\u6a21\u578b\u5728\u4f5c\u51fa\u53cd\u5e94\u4e4b\u524d\uff0c\u9700\u8981\u50cf\u4eba\u7c7b\u4e00\u6837\uff0c\u82b1\u66f4\u591a\u65f6\u95f4\u601d\u8003\u95ee\u9898\u3002\u901a\u8fc7\u8bad\u7ec3\uff0c\u5b83\u4eec\u5b66\u4f1a\u5b8c\u5584\u81ea\u5df1\u7684\u601d\u7ef4\u8fc7\u7a0b\uff0c\u5c1d\u8bd5\u4e0d\u540c\u7684\u7b56\u7565\uff0c\u5e76\u8ba4<\/strong>\u8bc6\u5230\u81ea\u5df1\u7684\u9519\u8bef\u3002<\/p>\n\n\n\n

\u5bf9\u4e8e\u590d\u6742\u7684\u63a8\u7406\u4efb\u52a1\u6765\u8bf4\uff0c\u8fd9\u662f\u4e00\u4e2a\u91cd\u5927\u8fdb\u6b65\uff0cOpenAI\u79f0\u4ee3\u8868\u4e86\u4eba\u5de5\u667a\u80fd\u7684\u6700\u9ad8\u6c34\u5e73\u3002<\/p>\n\n\n\n

\u9274\u4e8e\u6b64\uff0c\u4ed6\u4eec\u51b3\u5b9a\u5c06\u8ba1\u6570\u5668\u91cd\u7f6e\uff0c\u5e76\u5c06\u8be5\u7cfb\u5217\u6a21\u578b\u547d\u540d\u4e3aOpenAI o1\u3002<\/strong><\/p>\n\n\n\n

\u91cd\u70b9\u5728\u4e8e\uff0cOpenAI\u7684\u5927\u89c4\u6a21\u5f3a\u5316\u5b66\u4e60\u7b97\u6cd5\uff0c\u6559\u4f1a\u6a21\u578b\u5982\u4f55\u5728\u6570\u636e\u9ad8\u5ea6\u6709\u6548\u7684\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u5229\u7528\u5176\u601d\u60f3\u94fe\u8fdb\u884c\u9ad8\u6548\u601d\u8003\u3002<\/strong>\u6362\u8a00\u4e4b\uff0c\u7c7b\u4f3c\u4e8e\u5f3a\u5316\u5b66\u4e60\u7684 Scaling Law<\/strong>\u3002<\/p>\n\n\n\n

OpenAI\u53d1\u73b0\uff0c\u968f\u7740\u66f4\u591a\u7684\u5f3a\u5316\u5b66\u4e60\uff08\u8bad\u7ec3\u65f6\u8ba1\u7b97\uff09\u548c\u66f4\u591a\u7684\u601d\u8003\u65f6\u95f4\uff08\u6d4b\u8bd5\u65f6\u8ba1\u7b97\uff09\uff0co1\u7684\u6027\u80fd\u6301\u7eed\u63d0\u9ad8\u3002\u800c\u4e14\u6269\u5c55\u8fd9\u79cd\u65b9\u6cd5\u7684\u9650\u5236\u4e0e\u5927\u6a21\u578b\u9884\u8bad\u7ec3\u7684\u9650\u5236\u6709\u5f88\u5927\u4e0d\u540c\uff0cOpenAI\u4e5f\u8fd8\u5728\u7ee7\u7eed\u7814\u7a76\u3002<\/strong><\/p>\n\n\n\n

\"\"<\/figure><\/div>\n\n\n\n

\u6a21\u578b\u8bc4\u4f30<\/strong><\/h3>\n\n\n\n

\u4e3a\u4e86\u7a81\u51fa\u76f8\u5bf9\u4e8e GPT-4o \u7684\u63a8\u7406\u6027\u80fd\u6539\u8fdb\uff0cOpenAI \u5728\u4e00\u7cfb\u5217\u4e0d\u540c\u7684\u4eba\u7c7b\u8003\u8bd5\u548c\u673a\u5668\u5b66\u4e60\u57fa\u51c6\u6d4b\u8bd5\u4e2d\u6d4b\u8bd5\u4e86 o1 \u6a21\u578b\u3002\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e\uff0c\u5728\u7edd\u5927\u591a\u6570\u63a8\u7406\u4efb\u52a1\u4e2d\uff0co1 \u7684\u8868\u73b0\u660e\u663e\u4f18\u4e8e GPT-4o\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n

\u5728\u8bb8\u591a\u63a8\u7406\u5bc6\u96c6\u578b\u57fa\u51c6\u6d4b\u8bd5\u4e2d\uff0co1\u7684\u8868\u73b0\u53ef\u4e0e\u4eba\u7c7b\u4e13\u5bb6\u76f8\u5ab2\u7f8e\u3002\u6700\u8fd1\u7684\u524d\u6cbf\u6a21\u578b\u5728 MATH \u548cGSM8K \u4e0a\u8868\u73b0\u5f97\u975e\u5e38\u597d\uff0c\u4ee5\u81f3\u4e8e\u8fd9\u4e9b\u57fa\u51c6\u6d4b\u8bd5\u5728\u533a\u5206\u6a21\u578b\u65b9\u9762\u4e0d\u518d\u6709\u6548\u3002\u56e0\u6b64\uff0cOpenAI \u5728 AIME \u4e0a\u8bc4\u4f30\u4e86\u6570\u5b66\u6210\u7ee9\uff0c\u8fd9\u662f\u4e00\u9879\u65e8\u5728\u6d4b\u8bd5\u7f8e\u56fd\u6700\u806a\u660e\u9ad8\u4e2d\u6570\u5b66\u5b66\u751f\u7684\u8003\u8bd5\u3002<\/p>\n\n\n\n

OpenAI \u8fd8\u5728 GPQA Diamond \u57fa\u51c6\u4e0a\u8bc4\u4f30\u4e86 o1\uff0c\u8fd9\u662f\u4e00\u4e2a\u56f0\u96be\u7684\u667a\u529b\u57fa\u51c6\uff0c\u7528\u4e8e\u6d4b\u8bd5\u5316\u5b66\u3001\u7269\u7406\u548c\u751f\u7269\u5b66\u65b9\u9762\u7684\u4e13\u4e1a\u77e5\u8bc6\u3002\u4e3a\u4e86\u5c06\u6a21\u578b\u4e0e\u4eba\u7c7b\u8fdb\u884c\u6bd4\u8f83\uff0cOpenAI \u8058\u8bf7\u4e86\u62e5\u6709\u535a\u58eb\u5b66\u4f4d\u7684\u4e13\u5bb6\u6765\u56de\u7b54 GPQA Diamond \u57fa\u51c6\u95ee\u9898\u3002<\/p>\n\n\n\n

\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e\uff1ao1 \u8d85\u8d8a\u4e86\u4eba\u7c7b\u4e13\u5bb6\u7684\u8868\u73b0\uff0c\u6210\u4e3a\u7b2c\u4e00\u4e2a\u5728\u8be5\u57fa\u51c6\u6d4b\u8bd5\u4e2d\u505a\u5230\u8fd9\u4e00\u70b9\u7684\u6a21\u578b\u3002<\/strong><\/p>\n\n\n\n

\u542f\u7528\u89c6\u89c9\u611f\u77e5\u80fd\u529b\u540e\uff0co1 \u5728 MMMU \u57fa\u51c6\u4e0a\u5f97\u5206\u4e3a 78.2%\uff0c\u6210\u4e3a\u7b2c\u4e00\u4e2a\u4e0e\u4eba\u7c7b\u4e13\u5bb6\u76f8\u5f53\u7684\u6a21\u578b\u3002o1 \u8fd8\u5728 57 \u4e2a MMLU \u5b50\u7c7b\u522b\u4e2d\u7684 54 \u4e2a\u4e0a\u4f18\u4e8e GPT-4o\u3002<\/p>\n\n\n\n

\u601d\u7ef4\u94fe\uff08Chain of Thought\uff09<\/strong><\/strong><\/p>\n\n\n\n

\u4e0e\u4eba\u7c7b\u5728\u56de\u7b54\u96be\u9898\u4e4b\u524d\u4f1a\u957f\u65f6\u95f4\u601d\u8003\u7c7b\u4f3c\uff0co1 \u5728\u5c1d\u8bd5\u89e3\u51b3\u95ee\u9898\u65f6\u4f1a\u4f7f\u7528\u601d\u7ef4\u94fe\u3002\u901a\u8fc7\u5f3a\u5316\u5b66\u4e60\uff0co1 \u5b66\u4f1a\u78e8\u7ec3\u5176\u601d\u7ef4\u94fe\u5e76\u6539\u8fdb\u5176\u4f7f\u7528\u7684\u7b56\u7565\u3002o1 \u5b66\u4f1a\u4e86\u8bc6\u522b\u548c\u7ea0\u6b63\u9519\u8bef\uff0c\u5e76\u53ef\u4ee5\u5c06\u68d8\u624b\u7684\u6b65\u9aa4\u5206\u89e3\u4e3a\u66f4\u7b80\u5355\u7684\u6b65\u9aa4\u3002o1 \u8fd8\u5b66\u4f1a\u4e86\u5728\u5f53\u524d\u65b9\u6cd5\u4e0d\u8d77\u4f5c\u7528\u65f6\u5c1d\u8bd5\u4e0d\u540c\u7684\u65b9\u6cd5\u3002\u8fd9\u4e2a\u8fc7\u7a0b\u6781\u5927\u5730\u63d0\u9ad8\u4e86\u6a21\u578b\u7684\u63a8\u7406\u80fd\u529b\u3002<\/p>\n\n\n\n

\u7f16\u7a0b\u80fd\u529b\uff08Coding\uff09<\/strong><\/strong><\/p>\n\n\n\n

\u57fa\u4e8e o1 \u8fdb\u884c\u4e86\u521d\u59cb\u5316\u5e76\u8fdb\u4e00\u6b65\u8bad\u7ec3\u4e86\u5176\u7f16\u7a0b\u6280\u80fd\u540e\uff0cOpenAI \u8bad\u7ec3\u5f97\u5230\u4e86\u4e00\u4e2a\u975e\u5e38\u5f3a\u5927\u7684\u7f16\u7a0b\u6a21\u578b\uff08o1-ioi\uff09\u3002\u8be5\u6a21\u578b\u5728 2024 \u5e74\u56fd\u9645\u4fe1\u606f\u5b66\u5965\u6797\u5339\u514b\u7ade\u8d5b\uff08IOI\uff09\u8d5b\u9898\u4e0a\u5f97\u5230\u4e86 213 \u5206\uff0c\u8fbe\u5230\u4e86\u6392\u540d\u524d 49% \u7684\u6c34\u5e73\u3002\u5e76\u4e14\u8be5\u6a21\u578b\u53c2\u4e0e\u7ade\u8d5b\u7684\u6761\u4ef6\u4e0e 2024 IOI \u7684\u4eba\u7c7b\u53c2\u8d5b\u8005\u4e00\u6837\uff1a\u9700\u8981\u5728 10 \u4e2a\u5c0f\u65f6\u5185\u89e3\u7b54 6 \u4e2a\u9ad8\u96be\u5ea6\u7b97\u6cd5\u95ee\u9898\uff0c\u5e76\u4e14\u6bcf\u4e2a\u95ee\u9898\u4ec5\u80fd\u63d0\u4ea4 50 \u6b21\u7b54\u6848\u3002<\/p>\n\n\n\n

OpenAI\u53d1\u73b0\uff0c\u5982\u679c\u653e\u5bbd\u63d0\u4ea4\u9650\u5236\u6761\u4ef6\uff0c\u5219\u6a21\u578b\u6027\u80fd\u66f4\u662f\u80fd\u5927\u5e45\u63d0\u5347\u3002\u5982\u679c\u6bcf\u4e2a\u95ee\u9898\u5141\u8bb8\u63d0\u4ea4 1 \u4e07\u6b21\u7b54\u6848\uff0c\u5373\u4f7f\u4e0d\u4f7f\u7528\u4e0a\u8ff0\u6d4b\u8bd5\u65f6\u9009\u53d6\u7b56\u7565\uff0c\u8be5\u6a21\u578b\u4e5f\u80fd\u5f97\u5230 362.14 \u5206\u2014\u2014\u9ad8\u4e8e\u91d1\u724c\u95e8\u69db\u3002<\/strong><\/p>\n\n\n\n

\u6700\u540e\uff0cOpenAI \u6a21\u62dfCodeforces \u4e3b\u529e\u7684\u7ade\u4e89\u6027\u7f16\u7a0b\u7ade\u8d5b\uff0c\u4ee5\u5c55\u793a\u8be5\u6a21\u578b\u7684\u7f16\u7801\u6280\u80fd\u3002\u91c7\u7528\u7684\u8bc4\u4f30\u4e0e\u7ade\u8d5b\u89c4\u5219\u975e\u5e38\u63a5\u8fd1\uff0c\u5141\u8bb8\u63d0\u4ea4 10 \u4efd\u4ee3\u7801\u3002GPT-4o \u7684 Elo\u8bc4\u5206\u4e3a 808\uff0c\u5728\u4eba\u7c7b\u7ade\u4e89\u5bf9\u624b\u4e2d\u5904\u4e8e\u524d 11% \u7684\u6c34\u5e73\u3002\u8be5\u6a21\u578b\u8fdc\u8fdc\u8d85\u8fc7\u4e86 GPT-4o \u548c o1\u2014\u2014\u5b83\u7684 Elo \u8bc4\u5206\u4e3a 1807\uff0c\u8868\u73b0\u4f18\u4e8e 93% \u7684\u7ade\u4e89\u5bf9\u624b\u3002<\/strong><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u4eba\u7c7b\u504f\u597d\u8bc4\u4f30\uff08<\/strong>Human preference evaluation<\/strong>\uff09<\/strong><\/strong><\/p>\n\n\n\n

\u9664\u4e86\u8003\u8bd5\u548c\u5b66\u672f\u57fa\u51c6\u4e4b\u5916\uff0cOpenAI \u8fd8\u5728\u66f4\u591a\u9886\u57df\u7684\u5177\u6709\u6311\u6218\u6027\u7684\u5f00\u653e\u5f0f\u63d0\u793a\u4e0a\u8bc4\u4f30\u4e86\u4eba\u7c7b\u5bf9 o1-preview \u548c GPT-4o \u7684\u504f\u597d\u3002<\/p>\n\n\n\n

\u5728\u8fd9\u6b21\u8bc4\u4f30\u4e2d\uff0c\u4eba\u7c7b\u8bad\u7ec3\u8005\u5bf9 o1-preview \u548c GPT-4o \u7684\u63d0\u793a\u8fdb\u884c\u533f\u540d\u56de\u7b54\uff0c\u5e76\u6295\u7968\u9009\u51fa\u4ed6\u4eec\u66f4\u559c\u6b22\u7684\u56de\u7b54\u3002\u5728\u6570\u636e\u5206\u6790\u3001\u7f16\u7a0b\u548c\u6570\u5b66\u7b49\u63a8\u7406\u80fd\u529b\u8f83\u5f3a\u7684\u7c7b\u522b\u4e2d\uff0co1-preview \u7684\u53d7\u6b22\u8fce\u7a0b\u5ea6\u8fdc\u8fdc\u9ad8\u4e8e GPT-4o\u3002<\/strong>\u7136\u800c\uff0co1-preview \u5728\u67d0\u4e9b\u81ea\u7136\u8bed\u8a00\u4efb\u52a1\u4e0a\u5e76\u4e0d\u53d7\u6b22\u8fce\uff0c\u8fd9\u8868\u660e\u5b83\u5e76\u4e0d\u9002\u5408\u6240\u6709\u7528\u4f8b\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u5b89\u5168\u6027\uff08Safety\uff09<\/strong><\/strong><\/p>\n\n\n\n

\u601d\u7ef4\u94fe\uff08CoT\uff09\u63a8\u7406\u4e3a\u5b89\u5168\u548c\u5bf9\u9f50\u63d0\u4f9b\u4e86\u65b0\u7684\u601d\u8def\u3002OpenAI \u53d1\u73b0\uff0c\u5c06\u6a21\u578b\u884c\u4e3a\u7b56\u7565\u6574\u5408\u5230\u63a8\u7406\u6a21\u578b\u7684\u601d\u7ef4\u94fe\u4e2d\uff0c\u53ef\u4ee5\u9ad8\u6548\u3001\u7a33\u5065\u5730\u6559\u5bfc\u4eba\u7c7b\u4ef7\u503c\u89c2\u548c\u539f\u5219\u3002<\/strong>\u901a\u8fc7\u5411\u6a21\u578b\u6559\u5bfc\u81ea\u5df1\u7684\u5b89\u5168\u89c4\u5219\u4ee5\u53ca\u5982\u4f55\u5728\u4e0a\u4e0b\u6587\u4e2d\u63a8\u7406\u5b83\u4eec\uff0cOpenAI \u53d1\u73b0\u63a8\u7406\u80fd\u529b\u76f4\u63a5\u6709\u5229\u4e8e\u6a21\u578b\u7a33\u5065\u6027\u7684\u8bc1\u636e\uff1ao1-preview \u5728\u5173\u952e\u8d8a\u72f1\u8bc4\u4f30\u548c\u7528\u4e8e\u8bc4\u4f30\u6a21\u578b\u5b89\u5168\u62d2\u7edd\u8fb9\u754c\u7684\u6700\u4e25\u683c\u5185\u90e8\u57fa\u51c6\u4e0a\u53d6\u5f97\u4e86\u663e\u8457\u7684\u6539\u8fdb\u3002<\/p>\n\n\n\n

OpenAI\u8ba4\u4e3a\uff0c\u4f7f\u7528\u601d\u7ef4\u94fe\u53ef\u4ee5\u4e3a\u5b89\u5168\u548c\u5bf9\u9f50\u5e26\u6765\u91cd\u5927\u8fdb\u6b65\uff0c\u56e0\u4e3a<\/p>\n\n\n\n

1\uff09\u5b83\u80fd\u591f\u4ee5\u6e05\u6670\u7684\u65b9\u5f0f\u89c2\u5bdf\u6a21\u578b\u601d\u7ef4\uff1b<\/p>\n\n\n\n

2\uff09\u5173\u4e8e\u5b89\u5168\u89c4\u5219\u7684\u6a21\u578b\u63a8\u7406\u5bf9\u4e8e\u5206\u5e03\u5916\u573a\u666f\u66f4\u5177\u7a33\u5065\u6027\u3002<\/p>\n\n\n\n

\u4e3a\u4e86\u5bf9\u81ea\u5df1\u7684\u6539\u8fdb\u8fdb\u884c\u538b\u529b\u6d4b\u8bd5\uff0c OpenAI \u5728\u90e8\u7f72\u4e4b\u524d\u6839\u636e\u81ea\u5df1\u7684\u5b89\u5168\u51c6\u5907\u6846\u67b6\u8fdb\u884c\u4e86\u4e00\u7cfb\u5217\u5b89\u5168\u6d4b\u8bd5\u548c\u7ea2\u961f\u6d4b\u8bd5\u3002\u7ed3\u679c\u53d1\u73b0\uff0c\u601d\u7ef4\u94fe\u63a8\u7406\u6709\u52a9\u4e8e\u5728\u6574\u4e2a\u8bc4\u4f30\u8fc7\u7a0b\u4e2d\u63d0\u9ad8\u80fd\u529b\u3002\u5c24\u5176\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0cOpenAI \u89c2\u5bdf\u5230\u4e86\u6709\u8da3\u7684\u5956\u52b1\u9ed1\u5ba2\u653b\u51fb\u5b9e\u4f8b\u3002<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u9690\u5f0f\u601d\u7ef4\u94fe\uff08Hiding the Chains of Thought\uff09<\/strong><\/strong><\/p>\n\n\n\n

OpenAI\u8ba4\u4e3a\u9690\u5f0f\u601d\u7ef4\u94fe\u4e3a\u76d1\u63a7\u6a21\u578b\u63d0\u4f9b\u4e86\u72ec\u7279\u7684\u673a\u4f1a\u3002\u5047\u8bbe\u5b83\u662f\u5fe0\u5b9e\u4e14\u6e05\u6670\u7684\uff0c\u9690\u5f0f\u601d\u7ef4\u94fe\u4f7f\u5f97\u80fd\u591f\u8bfb\u61c2\u6a21\u578b\u7684\u601d\u60f3\u5e76\u4e86\u89e3\u5176\u601d\u7ef4\u8fc7\u7a0b\u3002\u4f8b\u5982\uff0c\u4eba\u4eec\u5c06\u6765\u53ef\u80fd\u5e0c\u671b\u76d1\u63a7\u601d\u7ef4\u94fe\u4ee5\u5bfb\u627e\u64cd\u63a7\u7528\u6237\u7684\u8ff9\u8c61\u3002<\/p>\n\n\n\n

\u4f46\u8981\u505a\u5230\u8fd9\u4e00\u70b9\uff0c\u6a21\u578b\u5fc5\u987b\u80fd\u591f\u81ea\u7531\u5730\u4ee5\u672a\u6539\u53d8\u7684\u5f62\u5f0f\u8868\u8fbe\u5176\u601d\u60f3\uff0c\u56e0\u6b64\u4e0d\u80fd\u5728\u601d\u7ef4\u94fe\u8bad\u7ec3\u8fdb\u884c\u4efb\u4f55\u653f\u7b56\u5408\u89c4\u6027\u6216\u7528\u6237\u504f\u597d\u6027\u8bad\u7ec3\u3002OpenAI\u4e5f\u4e0d\u60f3\u8ba9\u7528\u6237\u76f4\u63a5\u770b\u5230\u4e0d\u4e00\u81f4\u7684\u601d\u7ef4\u94fe\u3002<\/p>\n\n\n\n

\u56e0\u6b64\uff0c\u5728\u6743\u8861\u7528\u6237\u4f53\u9a8c\u3001\u7ade\u4e89\u4f18\u52bf\u548c\u8ffd\u6c42\u601d\u7ef4\u94fe\u76d1\u63a7\u7684\u9009\u9879\u7b49\u591a\u79cd\u56e0\u7d20\u540e\uff0cOpenAI\u51b3\u5b9a\u4e0d\u5411\u7528\u6237\u5c55\u793a\u539f\u59cb\u7684\u601d\u7ef4\u94fe\u3002<\/strong>OpenAI\u627f\u8ba4\u8fd9\u4e2a\u51b3\u5b9a\u6709\u4e0d\u597d\u7684\u5730\u65b9\uff0c\u56e0\u6b64\u52aa\u529b\u901a\u8fc7\u6559\u5bfc\u6a21\u578b\u5728\u7b54\u6848\u4e2d\u91cd\u73b0\u601d\u7ef4\u94fe\u4e2d\u7684\u4efb\u4f55\u6709\u7528\u60f3\u6cd5\u6765\u90e8\u5206\u5f25\u8865\u3002\u540c\u65f6\u5bf9\u4e8e o1 \u6a21\u578b\u7cfb\u5217\uff0cOpenAI\u5c55\u793a\u4e86\u6a21\u578b\u751f\u6210\u7684\u601d\u7ef4\u94fe\u6458\u8981\u3002<\/p>\n\n\n\n

OpenAI o1-mini<\/strong><\/p>\n\n\n\n

o1\u7cfb\u5217\u64c5\u957f\u51c6\u786e\u751f\u6210\u548c\u8c03\u8bd5\u590d\u6742\u4ee3\u7801\u3002\u4e3a\u4e86\u4e3a\u5f00\u53d1\u4eba\u5458\u63d0\u4f9b\u66f4\u6709\u6548\u7684\u89e3\u51b3\u65b9\u6848\uff0cOpenAI\u8fd8\u53d1\u5e03\u4e86OpenAI o1-mini\uff0c\u8fd9\u662f\u4e00\u79cd\u66f4\u5feb\u3001\u66f4\u4fbf\u5b9c\u7684\u63a8\u7406\u6a21\u578b\uff0c\u5728\u7f16\u7801\u65b9\u9762\u7279\u522b\u6709\u6548\u3002\u4f5c\u4e3a\u4e00\u4e2a\u8f83\u5c0f\u7684\u6a21\u578b\uff0co1-mini\u6bd4o1-preview\u4fbf\u5b9c80%\uff0c\u4f7f\u5176\u6210\u4e3a\u9700\u8981\u63a8\u7406\u4f46\u4e0d\u9700\u8981\u5e7f\u6cdb\u77e5\u8bc6\u7684\u5e94\u7528\u7a0b\u5e8f\u7684\u5f3a\u5927\u3001\u7ecf\u6d4e\u9ad8\u6548\u7684\u6a21\u578b\u3002<\/strong><\/p>\n\n\n\n

o1-mini\u64c5\u957fSTEM\uff0c\u5c24\u5176\u662f\u6570\u5b66\u548c\u7f16\u7801\u2014\u2014\u5728AIME\u548cCodeforce\u7b49\u8bc4\u4f30\u57fa\u51c6\u4e0a\u51e0\u4e4e\u4e0eOpenAI o1\u7684\u6027\u80fd\u76f8\u5f53\u3002\u9884\u8ba1o1-mini\u5c06\u662f\u4e00\u79cd\u66f4\u5feb\u3001\u66f4\u5177\u6210\u672c\u6548\u76ca\u7684\u6a21\u578b\uff0c\u9002\u7528\u4e8e\u9700\u8981\u5728\u6ca1\u6709\u5e7f\u6cdb\u77e5\u8bc6\u7684\u60c5\u51b5\u4e0b\u8fdb\u884c\u63a8\u7406\u7684\u5e94\u7528\u7a0b\u5e8f\u3002<\/p>\n\n\n\n

STEM<\/strong>\u63a8\u7406\u4f18\u5316\uff08Optimized for STEM Reasoning\uff09<\/strong><\/strong><\/p>\n\n\n\n

\u50cfo1\u8fd9\u6837\u7684\u5927\u578b\u8bed\u8a00\u6a21\u578b\u662f\u5728\u5e9e\u5927\u7684\u6587\u672c\u6570\u636e\u96c6\u4e0a\u9884\u5148\u8bad\u7ec3\u7684\u3002\u867d\u7136\u8fd9\u4e9b\u9ad8\u5bb9\u91cf\u6a21\u578b\u5177\u6709\u5e7f\u6cdb\u7684\u4e16\u754c\u77e5\u8bc6\uff0c\u4f46\u5bf9\u4e8e\u73b0\u5b9e\u4e16\u754c\u7684\u5e94\u7528\u6765\u8bf4\uff0c\u5b83\u4eec\u53ef\u80fd\u65e2\u6602\u8d35\u53c8\u7f13\u6162\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0co1-mini\u662f\u4e00\u4e2a\u8f83\u5c0f\u7684\u6a21\u578b\uff0c\u5728\u9884\u8bad\u7ec3\u671f\u95f4\u9488\u5bf9STEM\u63a8\u7406\u8fdb\u884c\u4e86\u4f18\u5316\u3002\u5728\u4f7f\u7528\u4e0eo1\u76f8\u540c\u7684\u9ad8\u8ba1\u7b97\u5f3a\u5316\u5b66\u4e60\uff08RL\uff09\u7ba1\u9053\u8fdb\u884c\u8bad\u7ec3\u540e\uff0co1-mini\u5728\u8bb8\u591a\u6709\u7528\u7684\u63a8\u7406\u4efb\u52a1\u4e0a\u53d6\u5f97\u4e86\u76f8\u5f53\u7684\u6027\u80fd\uff0c\u540c\u65f6\u5177\u6709\u66f4\u9ad8\u7684\u6027\u4ef7\u6bd4\u3002<\/p>\n\n\n\n

\u5f53\u5728\u9700\u8981\u667a\u80fd\u548c\u63a8\u7406\u7684\u57fa\u51c6\u4e0a\u8fdb\u884c\u8bc4\u4f30\u65f6\uff0co1-mini\u4e0eo1-preview\u548co1\u76f8\u6bd4\u8868\u73b0\u826f\u597d\u3002\u7136\u800c\uff0co1-mini\u5728\u9700\u8981\u975eSTEM\u4e8b\u5b9e\u77e5\u8bc6\u7684\u4efb\u52a1\u4e0a\u8868\u73b0\u8f83\u5dee\u3002<\/strong><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u6570\u5b66\u80fd\u529b\uff1a<\/strong>\u5728\u9ad8\u4e2dAIME\u6570\u5b66\u7ade\u8d5b\u4e2d\uff0co1-mini\uff0870.0%\uff09\u4e0eo1\uff0874.4%\uff09\u5177\u6709\u7ade\u4e89\u529b\uff0c\u540c\u65f6\u4ef7\u683c\u660e\u663e\u66f4\u4f4e\uff0c\u8868\u73b0\u4f18\u4e8eo1-preview\uff0844.6%\uff09\u3002o1-mini\u7684\u5206\u6570\uff08\u7ea611\/15\u4e2a\u95ee\u9898\uff09\u4f7f\u5176\u8dfb\u8eab\u7f8e\u56fd\u9ad8\u4e2d\u751f\u524d500\u540d\u5de6\u53f3\u3002<\/p>\n\n\n\n

\u7f16\u7801\u80fd\u529b\uff1a<\/strong>\u5728 Codeforces \u7ade\u8d5b\u7f51\u7ad9\u4e0a\uff0co1-mini \u7684 Elo \u5f97\u5206\u4e3a 1650\uff0c\u4e0e o1 (1673) \u4e0d\u76f8\u4e0a\u4e0b\uff0c\u5e76\u4e14\u9ad8\u4e8e o1-preview (1258)\u3002\u6b64\u5916\uff0co1-mini \u5728 HumanEval \u7f16\u7801\u57fa\u51c6\u548c\u9ad8\u4e2d\u7f51\u7edc\u5b89\u5168\u593a\u65d7\u6311\u6218 (CTF) \u4e2d\u4e5f\u8868\u73b0\u51fa\u8272\u3002<\/p>\n\n\n\n

STEM\uff1a<\/strong>\u5728\u4e00\u4e9b\u9700\u8981\u63a8\u7406\u7684\u5b66\u672f\u57fa\u51c6\u4e0a\uff0c\u4f8b\u5982 GPQA\uff08\u79d1\u5b66\uff09\u548c MATH-500\uff0co1-mini \u7684\u8868\u73b0\u4f18\u4e8e GPT-4o\u3002o1-mini \u5728MMLU \u7b49\u4efb\u52a1\u4e0a\u7684\u8868\u73b0\u5219\u4e0d\u5982 GPT-4o\uff0c\u5e76\u4e14\u7531\u4e8e\u7f3a\u4e4f\u5e7f\u6cdb\u7684\u4e16\u754c\u77e5\u8bc6\u800c\u5728 GPQA \u57fa\u51c6\u4e0a\u843d\u540e\u4e8e o1-preview\u3002<\/p>\n\n\n\n

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\u5b89\u5168\u6027<\/strong><\/strong><\/p>\n\n\n\n

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\u6280\u672f\u62a5\u544a\uff1ahttps:\/\/openai.com\/index\/learning-to-reason-with-l … \u7ee7\u7eed\u9605\u8bfbOpenAI o1\u6280\u672f\u62a5\u544a<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[21,4],"tags":[],"_links":{"self":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/19471"}],"collection":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/comments?post=19471"}],"version-history":[{"count":40,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/19471\/revisions"}],"predecessor-version":[{"id":21002,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/posts\/19471\/revisions\/21002"}],"wp:attachment":[{"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/media?parent=19471"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/categories?post=19471"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/139.9.1.231\/index.php\/wp-json\/wp\/v2\/tags?post=19471"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}