{"id":36549,"date":"2025-01-13T18:00:28","date_gmt":"2025-01-13T10:00:28","guid":{"rendered":"https:\/\/17aitech.com\/?p=36549"},"modified":"2025-01-13T18:00:28","modified_gmt":"2025-01-13T10:00:28","slug":"%e5%85%b7%e8%ba%ab%e6%99%ba%e8%83%bdgpt-2%e6%97%b6%e5%88%bb%e5%88%b0%e4%ba%86%ef%bc%81%e8%bf%99%e5%ae%b6%e5%9b%bd%e5%86%85%e5%85%ac%e5%8f%b8%e5%b7%b2%e5%81%9a%e5%87%ba%e5%85%a8%e7%90%83%e6%9c%80","status":"publish","type":"post","link":"https:\/\/17aitech.com\/?p=36549","title":{"rendered":"\u5177\u8eab\u667a\u80fdGPT-2\u65f6\u523b\u5230\u4e86\uff01\u8fd9\u5bb6\u56fd\u5185\u516c\u53f8\u5df2\u505a\u51fa\u5168\u7403\u6700\u5927\u89c4\u6a21\u7684\u7aef\u5230\u7aef\u7edf\u4e00\u5177\u8eab\u5927\u6a21\u578b\u2014\u2014\u4e13\u8bbf\u81ea\u53d8\u91cf\u673a\u5668\u4eba\u56e2\u961f"},"content":{"rendered":"

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\u8fd1\u65e5\uff0c\u5173\u4e8e Open AI \u88ab\u6295\u4f01\u4e1a Physical Intelligence (PI) \u7684\u4e00\u7cfb\u5217\u62a5\u9053\uff0c\u8ba9\u4eba\u4eec\u5173\u6ce8\u5230\u5177\u8eab\u667a\u80fd\u5927\u6a21\u578b\u5f15\u53d1\u7684\u673a\u5668\u4eba\u65f6\u4ee3\u53d8\u9769\u3002<\/p>\n

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\u8fd9\u79cd\u5904\u7406\u590d\u6742\u4efb\u52a1\u4ee5\u53ca\u300c\u6cdb\u5316\u300d\u7684\u80fd\u529b\uff0c\u6b63\u662f\u81ea\u53d8\u91cf\u673a\u5668\u4eba\u56e2\u961f\u5bf9\u673a\u5668\u4eba\u300cScaling Law\u300d\u7684\u63a2\u7d22\u6210\u679c\uff0c\u4ed6\u4eec\u5e0c\u671b\u7528\u5355\u4e00\u7684\u5927\u6a21\u578b\u6765\u9a71\u52a8\u7aef\u5230\u7aef\u7684\u673a\u5668\u4eba manipulation\u3002<\/p>\n

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\u81ea\u53d8\u91cf\u673a\u5668\u4eba\u8ba4\u4e3a\uff0c\u76ee\u524d Great Wall \u7cfb\u5217\u7684 WALL-A \u7c7b\u4f3c\u4e8e\u300cGPT-2\u300d\uff0c\u4f34\u968f\u7740\u6a21\u578b\u7684\u4e0d\u65ad\u8fed\u4ee3\uff0c\u673a\u5668\u4eba\u9886\u57df\u7684\u300cChatGPT\u300d\u65f6\u523b\u53ef\u80fd\u4f1a\u5728\u4e0d\u4e45\u540e\u6765\u5230\u3002<\/strong><\/p>\n

\u4ee4\u5927\u5bb6\u597d\u5947\u7684\u662f\uff0c\u8fd9\u5bb6\u5e74\u8f7b\u7684\u521d\u521b\u516c\u53f8\uff0c\u5c06\u4f1a\u5982\u4f55\u5b9e\u73b0\u8fd9\u4e00\u5b8f\u4f1f\u76ee\u6807\uff1f<\/p>\n

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WALL-A \u662f\u4e16\u754c\u4e0a\u6700\u5927\u89c4\u6a21\u7684\u7aef\u5230\u7aef\u7edf\u4e00\u5177\u8eab\u5927\u6a21\u578b\u3002\u5728\u591a\u4e2a\u7ef4\u5ea6\u4e0a\uff0c\u6211\u4eec\u7684\u6a21\u578b\u90fd\u8d85\u8fc7\u4e86\u76ee\u524d\u5df2\u77e5\u7684\u6240\u6709\u6a21\u578b\u7684\u80fd\u529b\u3002<\/p>\n

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2017 \u5e74\uff0c\u4e00\u4e2a\u975e\u5e38\u6709\u540d\u7684\u673a\u5668\u4eba\u6559\u6388\u5f53\u9762\u8ddf\u6211\u8bf4\uff1a\u300c\u4f60\u641e\u7684\u8fd9\u79cd\u7aef\u5230\u7aef\u7684\u8def\u7ebf\u6c38\u8fdc\u53ea\u80fd\u662f Toy Model\uff0c\u6c38\u8fdc\u4e0d\u53ef\u80fd\u8d70\u901a\u3002\u300d\u6211\u5230\u4eca\u5929\u8fd8\u8bb0\u5f97\u5f88\u6e05\u695a\u3002\u4e00\u76f4\u5230\u4eca\u5e74\u521d\uff0c\u7aef\u5230\u7aef\u5728\u56fd\u5185\u90fd\u4ecd\u7136\u662f\u975e\u4e3b\u6d41\u7684\u5224\u65ad\uff0c\u6211\u4eec\u53bb\u5e74\u4e0b\u534a\u5e74\u8bf4\u8981\u505a\u7aef\u5230\u7aef\uff0c\u5927\u5bb6\u8fd8\u662f\u4ee5\u4e0d\u4fe1\u4e3a\u4e3b\uff0c\u8bf4\u5b9e\u8bdd\u6211\u4eec\u5f97\u8c22\u8c22\u9a6c\u65af\u514b\uff0c\u7279\u65af\u62c9 FSDv12 \u7ed9\u4e86\u5927\u5bb6\u5f88\u5927\u7684\u51b2\u51fb\u3002\u5230\u4e86\u4eca\u5e74\u5e74\u4e2d\uff0c\u7aef\u5230\u7aef\u5c31\u5df2\u7ecf\u300c\u6cdb\u6ee5\u300d\u4e86\uff0c\u5927\u5bb6\u90fd\u4e89\u76f8\u6050\u540e\u6324\u5230\u8fd9\u6761\u8d5b\u9053\u4e0a\u3002<\/p>\n

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\u4e4b\u6240\u4ee5\u8bf4\u300cFoundation Model\u300d\u662f\u53cd\u76f4\u89c9\u7684\u9053\u8def\uff0c\u56e0\u4e3a\u4eba\u4eec\u57fa\u4e8e\u81ea\u8eab\u7684\u7ecf\u9a8c\uff0c\u672c\u80fd\u7684\u4f1a\u89c9\u5f97\u628a\u6570\u636e\u96c6\u4e2d\u5728\u4e00\u4e2a\u9886\u57df\u505a\u4e13\u5bb6\u6a21\u578b\u7684\u6548\u679c\u4f1a\u66f4\u597d\uff0c\u4f46\u4eca\u5929\u6211\u4eec\u770b\u5230\uff0c\u300c\u901a\u624d\u6a21\u578b\u300d\u624d\u662f\u771f\u6b63\u80fd\u591f\u6253\u7834\u5929\u82b1\u677f\uff0c\u5728\u76f8\u540c\u6295\u5165\u4e0b\u8fbe\u5230\u66f4\u9ad8\u80fd\u529b\u7684\u6b63\u786e\u8def\u5f84\u3002<\/p>\n

\u8fd9\u6761\u8def\u7ebf\u5176\u5b9e\u5728\u5176\u4ed6\u9886\u57df\u5df2\u7ecf\u6709\u6bd4\u8f83\u597d\u7684\u7ed3\u679c\u3002\u4f8b\u5982\uff0cChatGPT \u662f\u7aef\u5230\u7aef\u7684\u7edf\u4e00\u6a21\u578b\uff0c\u4e5f\u662f\u6240\u6709\u4efb\u52a1\u7edf\u4e00\u7684\u6a21\u578b\u3002\u53c8\u6bd4\u5982\u521a\u624d\u63d0\u5230\u7684\u7279\u65af\u62c9 FSD\uff0c\u867d\u7136\u53ea\u505a\u4e00\u4e2a\u9886\u57df\u4efb\u52a1\uff0c\u4f46\u662f\u4e5f\u662f\u7aef\u5230\u7aef\u5b8c\u5168\u7edf\u4e00\u548c\u6240\u6709\u4efb\u52a1\u7684\u5b8c\u5168\u7edf\u4e00\u3002<\/p>\n

\u738b\u660a\uff1a\u8fd8\u6709\u5173\u952e\u7684\u4e00\u70b9\uff0c\u673a\u5668\u4eba\u505a\u5b66\u4e60\u6700\u56f0\u96be\u7684\u70b9\uff0c\u662f\u6570\u636e\uff1b\u8981\u5f7b\u5e95\u89e3\u51b3\u6570\u636e\u95ee\u9898\uff0c\u53ea\u6709\u901a\u8fc7\u628a\u6240\u6709\u4efb\u52a1\u7684\u6570\u636e\u653e\u5230\u4e00\u4e2a\u7edf\u4e00\u6a21\u578b\u91cc\u9762\uff0c\u9760\u5b66\u4e60\u6240\u6709\u4efb\u52a1\u4e2d\u4e00\u81f4\u7684 Common Structure\uff0c\u6bd4\u5982\u7269\u7406\u89c4\u5f8b\u3001\u7269\u4f53\u7279\u5f81\uff0c\u8fd9\u4e5f\u9700\u8981 Foundation Model \u6765\u89e3\u51b3\u3002<\/p>\n

\u673a\u5668\u4eba\u7684\u300cGPT-2 \u65f6\u523b\u300d\u4e0e Scaling Law<\/strong><\/p>\n

\u6570\u636e\u8d28\u91cf >> \u6570\u636e\u591a\u6837\u6027 >> \u6570\u636e\u91cf<\/strong><\/p>\n

\u673a\u5668\u4e4b\u5fc3\uff1a\u4e1a\u754c\u8fd1\u6765\u5e38\u8bf4\u300c\u673a\u5668\u4eba\u9886\u57df\u7684 Scaling Law\u300d\uff0c\u600e\u4e48\u7406\u89e3\uff1f<\/p>\n

\u738b\u6f5c\uff1a\u5f88\u591a\u4eba\u8bf4\u5230 Scaling Law\uff0c\u60f3\u5230\u7684\u4e00\u4e2a\u8bcd\u53eb\u300c\u5927\u529b\u51fa\u5947\u8ff9\u300d\uff0c\u6211\u89c9\u5f97\u8fd9\u662f\u5bf9 Scaling Law \u5eb8\u4fd7\u548c\u8868\u9762\u5316\u7684\u7406\u89e3\u3002\u5173\u4e8e\u8fd9\u70b9\uff0c\u738b\u660a\u5e94\u8be5\u6709\u66f4\u6df1\u7684\u611f\u89e6\u3002<\/p>\n

\u738b\u660a\uff1a\u56e0\u4e3a\u6211\u7b97\u662f\u56fd\u5185\u5f53\u65f6\u6700\u65e9\u505a\u5927\u6a21\u578b\u65b9\u5411\u7684\u4e00\u6279\u4eba\uff0c\u5305\u62ec\u5728\u56fd\u5185\u6700\u65e9\u53d1\u5e03\u4e86\u767e\u4ebf\u6a21\u578b\uff0c\u4f46\u5f53\u65f6\u9760\u89c4\u6a21\u6216\u8005\u5927\u529b\u5e76\u6ca1\u6709\u660e\u663e\u5730\u300c\u51fa\u5947\u8ff9\u300d\u3002ChatGPT \u51fa\u6765\u4e4b\u540e\uff0c\u5728\u6700\u65e9\u671f\u7684\u65f6\u5019\u5927\u5bb6\u90fd\u53d1\u73b0\u5355\u7eaf\u505a\u5927\u6570\u636e\u89c4\u6a21\u6839\u672c\u590d\u73b0\u4e0d\u51fa\u6765\uff0c\u76f4\u5230\u6709\u4eba\u5f00\u59cb\u4ece ChatGPT \u4e0a\u76f4\u63a5\u62c9\u6570\u636e\u505a\u5fae\u8c03\uff0c\u624d\u6709\u4e86\u7b2c\u4e00\u6279\u505a\u51fa\u6765\u7684\u5927\u6a21\u578b\u3002<\/p>\n

\u4e3a\u4ec0\u4e48\u4f1a\u6709\u8fd9\u79cd\u60c5\u51b5\u51fa\u73b0\uff0c\u6211\u89c9\u5f97\u6838\u5fc3\u8fd8\u662f\u6570\u636e\u7684\u8d28\u91cf\u3002\u6211\u4eec\u81ea\u5df1\u8bad\u7ec3\u7684\u611f\u53d7\u662f\uff1a\u6570\u636e\u8d28\u91cf\u5bf9\u6a21\u578b\u5f71\u54cd\u6781\u5927\uff0c\u597d\u7684\u6570\u636e\u53ef\u80fd\u51e0\u5343\u6761\u751a\u81f3\u51e0\u767e\u6761\u5c31\u6709\u975e\u5e38\u660e\u663e\u7684\u6548\u679c\uff0c\u5dee\u7684\u6570\u636e\u54ea\u6015\u51e0\u5343\u4e07\u4e0a\u4ebf\u6761\uff0c\u53cd\u800c\u4f1a\u8ba9\u6a21\u578b\u8d8a\u8bad\u7ec3\u8d8a\u5dee\uff0c\u8fd9\u90fd\u662f\u6211\u4eec\u5728\u8bad\u7ec3\u8bed\u8a00\u5927\u6a21\u578b\u548c\u591a\u6a21\u6001\u5927\u6a21\u578b\u5b9e\u8df5\u8fc7\u7a0b\u4e2d\u5207\u5b9e\u770b\u5230\u8fc7\u7684\uff0c\u8fd9\u4e2a\u53ef\u80fd\u786e\u5b9e\u548c\u4e00\u822c\u4eba\u5fc3\u4e2d\u7684\u300c\u5927\u529b\u51fa\u5947\u8ff9\u300d\u4e0d\u4e00\u6837\u3002<\/p>\n

\u738b\u6f5c\uff1a\u786e\u5b9e\uff0c\u6570\u636e\u8d28\u91cf\u5728 Scaling Law \u91cc\u624d\u662f\u6700\u6838\u5fc3\u7684\u8981\u7d20\uff0c\u5176\u6b21\u662f\u6570\u636e\u7684\u591a\u6837\u6027\uff0c\u6392\u5728\u6700\u540e\u7684\u624d\u662f\u6570\u636e\u91cf\u3002<\/strong><\/p>\n

\u5f53\u7136\u4e5f\u4e0d\u662f\u8bf4\u6570\u636e\u91cf\u5b8c\u5168\u5c31\u4e0d\u91cd\u8981\u4e86\uff0c\u6709\u4e9b\u63a2\u8ba8 Scaling Law \u7684\u5de5\u4f5c\u5728\u6bcf\u4e00\u4e2a\u6a21\u578b\u4e0a\u53ea\u6709\u51e0\u5341\u6761\u5230\u51e0\u767e\u6761\u6570\u636e\u7684\u7ed3\u679c\uff0c\u6211\u4eec\u89c9\u5f97\u610f\u4e49\u4f3c\u4e4e\u6bd4\u8f83\u6709\u9650\u3002\u771f\u6b63\u7ed9\u51fa\u673a\u5668\u4eba Scaling Law \u51b3\u5b9a\u6027\u8bc1\u636e\u7684\u662f RT-X\uff0c\u56e0\u4e3a\u5b83\u786e\u5b9e\u662f\u5728\u4e00\u4e2a\u6a21\u578b\u4e0a\u653e\u4e86\u51e0\u5341\u4e07\u6761\u6570\u636e\u3002<\/p>\n

\u5927\u6a21\u578b + \u673a\u5668\u4eba\uff0c\u8def\u5f84\u8d70\u901a\u4e86<\/strong><\/p>\n

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ChatGPT \u4ece\u6839\u672c\u4e0a\u6539\u53d8\u4e86 AI \u6574\u4e2a\u9886\u57df\uff0c\u5bf9\u673a\u5668\u4eba\u6765\u8bf4\u6709\u4e24\u4e2a\u70b9\uff1a\u4e00\u662f\u5f88\u591a\u4ee5\u524d\u89c9\u5f97\u6781\u5176\u56f0\u96be\u7684\u95ee\u9898\u83b7\u5f97\u4e86\u7a81\u98de\u731b\u8fdb\u7684\u53d1\u5c55\uff0c\u4f8b\u5982 Planning\u3001Reasoning\u3001Language Interaction\uff1b\u4e8c\u662f\u4ece\u65b9\u6cd5\u8bba\u4e0a\u6307\u660e\u4e86\u89e3\u51b3\u673a\u5668\u4eba\u901a\u7528\u64cd\u4f5c\u8fd9\u4e00\u6700\u6838\u5fc3\u95ee\u9898\u7684\u8def\u7ebf\uff0c\u4e00\u4e0b\u5b50\u5c31\u770b\u5f97\u5f88\u6e05\u695a\u4e86\uff0c\u5bf9\u5927\u5bb6\u7684\u89e3\u91ca\u6210\u672c\u4e00\u4e0b\u5b50\u53d8\u5f97\u5f88\u4f4e\u3002<\/strong><\/p>\n

\u6211\u81ea\u5df1\u4ece 2016 \u5e74\u5f00\u59cb\u505a\u7aef\u5230\u7aef\u7684\u673a\u5668\u4eba\u6a21\u578b\uff0c19 \u5e74\u5230 21 \u5e74\u57fa\u672c\u4e0a\u770b\u6e05\u695a\u4e86\u7edf\u4e00\u5927\u6a21\u578b\u8fd9\u4e2a\u5927\u65b9\u5411\uff0c\u4f46\u90a3\u4e2a\u65f6\u5019\u4e0d\u7ba1\u662f\u8d44\u672c\u8fd8\u662f\u5b66\u672f\u754c\u7684\u4e3b\u6d41\uff0c\u8ba9\u5927\u5bb6\u7406\u89e3\u548c\u63a5\u53d7\u8fd9\u79cd\u65b9\u6cd5\u8bba\u90fd\u662f\u6709\u6781\u5927\u7684\u969c\u788d\u7684\u3002\u6709\u4e86 ChatGPT \u4e4b\u540e\uff0c\u300c\u65e2\u7136\u5bf9 NLP \u8fd9\u4e48\u590d\u6742\u7684\u4efb\u52a1\u8fd9\u5957\u8def\u7ebf\u80fd\u591f work\uff0c\u5bf9\u673a\u5668\u4eba\u8fd9\u4e2a\u590d\u6742\u5ea6\u7c7b\u4f3c\u7684\u4efb\u52a1\u5e94\u8be5\u4e5f\u80fd work\u300d\uff0c\u8fd9\u79cd\u903b\u8f91\u88ab\u5927\u5bb6\u6240\u7406\u89e3\u4e86\u3002<\/p>\n

\u6240\u4ee5\u6211\u7684\u51b3\u5fc3\u662f 22 \u5e74\u4e0b\u7684\uff0c\u4f46 23 \u5e74\u4e0a\u534a\u5e74\u6211\u8fd8\u5728\u8003\u8651\u662f\u5426\u5728\u7f8e\u56fd\u505a\u8fd9\u4e2a\u5927\u6a21\u578b\u4e0e\u673a\u5668\u4eba\u6df1\u5ea6\u8026\u5408\u7684\u521b\u4e1a\u66f4\u5bb9\u6613\u6210\uff0c\u5230\u5e74\u4e2d\u9010\u6e10\u660e\u786e\u4e86\u8fd9\u4ef6\u4e8b\u60c5\u5728\u4e2d\u56fd\u505a\u6709\u672c\u8d28\u7684\u4f18\u52bf\u3002\u6b63\u597d\u8fd9\u4e0e\u738b\u660a\u5728\u5177\u8eab\u667a\u80fd\u4e0a\u7684\u60f3\u6cd5\u76f8\u5951\u5408\uff0c\u6240\u4ee5\u6211\u4eec\u5c31\u4e00\u8d77\u7ec4\u5efa\u4e86\u8fd9\u4e2a\u56e2\u961f\u3002<\/p>\n

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\u673a\u5668\u4e4b\u5fc3\uff1a\u4f60\u4eec\u5982\u4f55\u786e\u5b9a\u73b0\u5728\u662f\u505a\u8fd9\u4ef6\u4e8b\u7684\u6b63\u786e\u65f6\u523b\uff1f<\/p>\n

\u738b\u6f5c\uff1a2015 \u5e74\u524d\u540e\uff0c\u6df1\u5ea6\u5b66\u4e60\u5f00\u59cb\u7cfb\u7edf\u5f15\u5165\u673a\u5668\u4eba\u9886\u57df\u7279\u522b\u662f manipulation \u9886\u57df\uff0c\u5f53\u65f6\u5927\u5bb6\u662f\u62b1\u6709\u5f88\u5927\u7684\u671f\u671b\u7684\uff0c\u5305\u62ec\u73b0\u5728 Physical Intelligence \u7684 Sergey Levine \u548c\u6211\u4eec\u8d70\u7684\u7aef\u5230\u7aef\u7684\u8def\u7ebf\uff0c\u4e5f\u5305\u62ec\u5176\u4ed6\u4eba\u8d70\u7684\u5206\u5c42\u5206\u6b65\u7684\u8def\u7ebf\uff0c\u5927\u5bb6\u90fd\u89c9\u5f97\u6253\u7834\u4e86\u4e4b\u524d\u7684\u5929\u82b1\u677f\u4e4b\u540e\uff0c\u5e94\u8be5\u80fd\u76f4\u63a5\u53d6\u5f97\u7c7b\u4f3c\u5f53\u65f6\u5728 CV \u6216\u8005\u56f4\u68cb\u4e0a\u53d6\u5f97\u7684\u90a3\u79cd\u5f88\u5927\u7684\u6210\u529f\u3002<\/p>\n

\u4f46\u5230\u4e86 2018 \u5e74\u5de6\u53f3\uff0c\u60c5\u51b5\u6bd4\u8f83\u6e05\u695a\u4e86\uff1a\u5355\u7eaf\u9760\u6df1\u5ea6\u7f51\u7edc + \u5f3a\u5316\u5b66\u4e60\u505a\u4e0d\u6210 manipulation\uff0c\u6838\u5fc3\u95ee\u9898\u8fd8\u662f\u5728\u6570\u636e\u6548\u7387\u3002<\/p>\n

\u673a\u5668\u4eba\u7684\u6570\u636e\u83b7\u53d6\u5b9e\u5728\u592a\u96be\u4e86\uff0c\u66f4\u5173\u952e\u7684\u662f\u6570\u636e\u9700\u6c42\u968f\u7740\u4efb\u52a1\u590d\u6742\u6027\u7684\u63d0\u5347\u662f\u6307\u6570\u7ea7\u589e\u957f\uff0c\u5c31\u51b3\u5b9a\u4e86\u50cf\u56f4\u68cb\u6216\u8005\u56fe\u50cf\u8bc6\u522b\u90a3\u6837\u89e3\u51b3\u673a\u5668\u4eba\u4efb\u52a1\u662f\u4e0d\u53ef\u884c\u7684\u3002\u6240\u4ee5\u5f53\u65f6\u6700\u4e3b\u6d41\u7684\u60f3\u6cd5\u662f\u5927\u89c4\u6a21\u505a simulation \u7136\u540e\u505a Sim2Real\uff0c\u6211\u81ea\u5df1\u4e5f\u5728\u8fd9\u4e2a\u65b9\u5411\u4e0a\u63a2\u7d22\u4e86\u5f88\u957f\u65f6\u95f4\u3002\u4f46\u5230\u4e86 2019 \u5e74\uff0c\u6211\u7684\u7ed3\u8bba\u662f\u4ece\u7406\u8bba\u4e0a\u6765\u8bf4\uff0c\u81f3\u5c11\u5bf9 manipulation \u8fd9\u4e2a\u9886\u57df\uff0cSim2Real \u7684\u5929\u82b1\u677f\u662f\u4f4e\u800c\u4e14\u96be\u4ee5\u7a81\u7834\u7684 \u2014\u2014 \u8fd9\u6761\u8def\u7ebf\u4e0d make sense\u3002<\/p>\n

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\u540e\u6765\uff0c\u4e24\u4e2a\u6807\u5fd7\u6027\u4e8b\u4ef6\u53d1\u751f\u4e86\uff1a\u8c37\u6b4c RT-1 \u548c ChatGPT\u3002<\/strong><\/p>\n

\u8c37\u6b4c RT-1 \u7684\u51fa\u73b0\uff0c\u53ef\u4ee5\u8bf4\u9769\u65b0\u4e86\u673a\u5668\u4eba\u9886\u57df\u7684\u7814\u7a76\u8303\u5f0f\u3002RT-1 \u7684\u9769\u547d\u6027\u6709\u51e0\u70b9\uff0c\u7b2c\u4e00\u662f\u7a81\u7834\u4e86\u4e4b\u524d\u5360\u636e\u4e3b\u6d41\u7684 RL\uff08\u5f3a\u5316\u5b66\u4e60\uff09+Sim2Real \u8303\u5f0f\u6240\u9762\u4e34\u7684\u660e\u663e\u7684\u5929\u82b1\u677f\uff0c\u4eba\u7c7b\u7b2c\u4e00\u6b21\u770b\u5230\u4e86\u901a\u7528\u673a\u5668\u4eba\u7684\u5e0c\u671b\uff1b\u7b2c\u4e8c\u662f\u6307\u51fa\u4e86\u673a\u5668\u4eba\u6a21\u578b\u540c\u6837\u53ef\u80fd\u5177\u6709 Scaling Law\uff0c\u8fd9\u4e00\u70b9\u5728\u4e4b\u540e\u7684 RT-X \u4e2d\u5f97\u5230\u4e86\u786e\u8bc1\u3002\u00a0<\/p>\n

\u4f46\u662f\u673a\u5668\u4eba\u4e0a\u5373\u4f7f\u51fa\u73b0\u4e86 Scaling Law\uff0c\u8fd9\u6761\u8def\u662f\u5426\u80fd\u8d70\u5230\u7ec8\u70b9\u4ecd\u7136\u662f\u4e2a\u5de8\u5927\u7684\u95ee\u53f7\uff0c\u672c\u8d28\u4e0a\u8fd8\u662f\u56e0\u4e3a\u673a\u5668\u4eba\u7279\u6709\u4e5f\u662f\u6700\u56f0\u96be\u7684\u6570\u636e\u95ee\u9898\u30022015 \u5e74\u505a\u673a\u5668\u4eba\u7684\u65f6\u5019\uff0c\u5927\u90e8\u5206\u5f88\u597d\u7684\u5de5\u4f5c\u90fd\u662f\u51e0\u767e\u51e0\u5343\u6761\u6570\u636e\uff0c\u5bf9\u6bd4\u4e4b\u4e0b\uff0c\u5f53\u65f6 CV \u548c NLP \u7684\u6570\u636e\u91cf\u5c31\u5728\u51e0\u767e\u4e07\u3001\u51e0\u5343\u4e07\u8fd9\u4e2a\u6570\u91cf\u7ea7\uff0c\u5904\u5728\u90a3\u4e2a\u65f6\u95f4\u70b9\u4e0a\uff0c\u5f88\u96be\u60f3\u8c61\u673a\u5668\u4eba\u9762\u4e34\u7684\u8fd9\u4e2a\u95ee\u9898\u80fd\u591f\u6709\u7c7b\u4f3c CV \u548c NLP \u9886\u57df\u7684\u7a81\u7834\u3002<\/p>\n

\u8fd9\u4e2a\u65f6\u5019\u4e00\u9524\u5b9a\u97f3\u7684\u662f ChatGPT\u3002\u5728 ChatGPT \u4e0a\u6211\u4eec\u7b2c\u4e00\u6b21\u660e\u786e\u5730\u770b\u5230\u4e86 In-Context Learning\uff0c\u6216\u8005\u53ef\u4ee5\u53eb Zero-Shot Learning \u7684\u53d1\u751f\uff0c\u5f53\u7136\u4e4b\u524d\u4e5f\u6709\u9010\u6e10\u51fa\u73b0 Fine-Tuning \u548c Few-Shot Learning\uff0c\u4f46 In-Context Learning \u662f\u6700\u7ec8\u51fa\u73b0\u7684\u6781\u81f4\uff0c\u5c31\u662f\u6211\u4eec\u6240\u8c13\u7684\u300c\u6d8c\u73b0\u300d\u3002<\/p>\n

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\u4eba\u4eec\u57fa\u4e8e\u81ea\u8eab\u7684\u7ecf\u9a8c\uff0c\u672c\u80fd\u7684\u4f1a\u89c9\u5f97\u628a\u6570\u636e\u96c6\u4e2d\u5728\u4e00\u4e2a\u9886\u57df\u505a\u4e13\u5bb6\u6a21\u578b\u7684\u6548\u679c\u4f1a\u66f4\u597d\uff0c\u4f46\u4eca\u5929\u6211\u4eec\u770b\u5230\u901a\u624d\u6a21\u578b\u624d\u662f\u771f\u6b63\u80fd\u591f\u6253\u7834\u5929\u82b1\u677f\uff0c\u5728\u76f8\u540c\u6295\u5165\u4e0b\u8fbe\u5230\u66f4\u9ad8\u80fd\u529b\u7684\u6b63\u786e\u8def\u5f84\u3002<\/p>\n

\u673a\u5668\u4e4b\u5fc3\uff1a\u5728\u5b66\u672f\u754c\u80fd\u505a\u8fd9\u4ef6\u4e8b\u5417\uff1f<\/p>\n

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