{"id":36707,"date":"2025-01-17T00:00:25","date_gmt":"2025-01-16T16:00:25","guid":{"rendered":"https:\/\/17aitech.com\/?p=36707"},"modified":"2025-01-17T00:00:25","modified_gmt":"2025-01-16T16:00:25","slug":"%e4%bc%a0%e8%af%b4%e4%b8%adilya-sutskever%e7%b2%be%e9%80%89%e8%ae%ba%e6%96%87%e6%b8%85%e5%8d%95%ef%bc%9aai%e9%a2%86%e5%9f%9f40%e5%a4%a7%e8%ae%ba%e6%96%87%e5%ae%8c%e6%95%b4%e7%89%88%e3%80%8c%e7%a0%b4","status":"publish","type":"post","link":"https:\/\/17aitech.com\/?p=36707","title":{"rendered":"\u4f20\u8bf4\u4e2dIlya Sutskever\u7cbe\u9009\u8bba\u6587\u6e05\u5355\uff1aAI\u9886\u57df40\u5927\u8bba\u6587\u5b8c\u6574\u7248\u300c\u7834\u89e3\u300d\u5b8c\u6210"},"content":{"rendered":"<p>\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:<a href=\"https:\/\/www.jiqizhixin.com\/articles\/2024-11-16\" target=\"_blank\">\u4f20\u8bf4\u4e2dIlya Sutskever\u7cbe\u9009\u8bba\u6587\u6e05\u5355\uff1aAI\u9886\u57df40\u5927\u8bba\u6587\u5b8c\u6574\u7248\u300c\u7834\u89e3\u300d\u5b8c\u6210<\/a><\/p>\n<p>\u4eca\u5e74 5 \u6708\uff0c\u4e00\u4efd\u7f51\u4f20 OpenAI \u8054\u5408\u521b\u59cb\u4eba\u517c\u9996\u5e2d\u79d1\u5b66\u5bb6 Ilya Sutskever \u6574\u7406\u7684\u4e00\u4efd\u673a\u5668\u5b66\u4e60\u7814\u7a76<a data-itemshowtype=\"0\" data-linktype=\"2\" href=\"http:\/\/mp.weixin.qq.com\/s?__biz=MzA3MzI4MjgzMw==&amp;mid=2650917394&amp;idx=3&amp;sn=4402a0e41b15306c7066b7f0b267eb71&amp;chksm=84e40e6cb393877a6eb63724bf373196299616016b8c2ca6f3e51867ed1e9cf748b7a8c45160&amp;scene=21#wechat_redirect\" target=\"_blank\">\u6587\u7ae0\u6e05\u5355<\/a>\u706b\u4e86\u3002\u7f51\u53cb\u79f0\u300cIlya \u8ba4\u4e3a\u638c\u63e1\u4e86\u8fd9\u4e9b\u5185\u5bb9\uff0c\u4f60\u5c31\u4e86\u89e3\u4e86\u5f53\u524d\uff08\u4eba\u5de5\u667a\u80fd\u9886\u57df\uff09 90% \u7684\u91cd\u8981\u5185\u5bb9\u3002\u300d<\/p>\n<p><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-fcab2b92d42ff828e5ac24c1c947f6c7.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-fcab2b92d42ff828e5ac24c1c947f6c7.png\"><\/a><\/p>\n<p>\u636e\u8bf4\u8fd9\u4efd\u8bba\u6587\u6e05\u5355\u662f 2020 \u5e74 OpenAI \u7684\u8054\u5408\u521b\u59cb\u4eba\u3001\u9996\u5e2d\u79d1\u5b66\u5bb6 Ilya Sutskever \u7ed9\u53e6\u4e00\u4f4d\u8ba1\u7b97\u673a\u9886\u57df\u5927\u795e\uff0cid Software \u8054\u5408\u521b\u59cb\u4eba\uff0c\u81f4\u529b\u4e8e\u8f6c\u884c AGI \u7684 John Carmack \u7f16\u5199\u7684\u3002<\/p>\n<p>\u867d\u7136\u6e05\u5355\u51c6\u786e\u6027\u96be\u4ee5\u8003\u8bc1\uff08John Carmack \u672c\u4eba\u56de\u5e94\u8bf4\u5df2\u7ecf\u628a\u5217\u8868\u641e\u4e22\u4e86\uff09\uff0c\u800c\u4e14 AI \u9886\u57df\u53d1\u5c55\u65e5\u65b0\u6708\u5f02\uff0c\u4f46\u5176\u5185\u5bb9\u5f88\u5feb\u6d41\u4f20\u5f00\u6765\uff0c\u751a\u81f3\u6709\u4eba\u8868\u793a\u5b83\u662f OpenAI \u5165\u804c\u57f9\u8bad\u5185\u5bb9\u7684\u4e00\u90e8\u5206\u3002<\/p>\n<p>\u5f53\u65f6\uff0c\u8fd9\u4efd\u6e05\u5355\u5305\u542b 27 \u9879\u673a\u5668\u5b66\u4e60\u8d44\u6599\uff0c\u5305\u62ec\u8bba\u6587\u3001\u535a\u5ba2\u6587\u7ae0\u3001\u8bfe\u7a0b\u548c\u4e24\u672c\u4e66\u7684\u7ae0\u8282\uff0c\u5747\u6765\u81ea 1993 \u5e74\u81f3 2020 \u5e74\u3002<\/p>\n<p><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-75f2eb1685d3c085f8723a20411ae143.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-75f2eb1685d3c085f8723a20411ae143.png\"><\/a><\/p>\n<p>\u4f46\u636e\u79f0\uff0c\u53d7 Meta \u7535\u5b50\u90ae\u4ef6\u5220\u9664\u7b56\u7565\u7684\u5f71\u54cd\uff0c\u8be5\u6e05\u5355\u5e76\u4e0d\u5b8c\u6574\uff0c\u539f\u6e05\u5355\u4e2d\u5e94\u8be5\u5305\u542b\u7ea6 40 \u9879\u9605\u8bfb\u8d44\u6599\u3002<\/p>\n<p><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-3bda73162df48ae2e7d993b3d5235d7a.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-3bda73162df48ae2e7d993b3d5235d7a.png\"><\/a><\/p>\n<p><em>\u8f6c\u53d1\u6765\u8f6c\u53d1\u53bb\uff0c\u4e00\u5c0f\u534a\u5185\u5bb9\u88ab\u6324\u6389\u4e86\uff0c\u8fd9\u4f60\u53d7\u7684\u4e86\u5417\uff1f<\/em><\/p>\n<p>\u7279\u522b\u662f\uff0c\u6839\u636e\u4e0e\u8d44\u6599\u6e05\u5355\u4e00\u8d77\u5171\u4eab\u7684\u4e00\u9879\u58f0\u660e\uff0c\u6574\u4e2a\u300c\u5143\u5b66\u4e60\u300d\u7c7b\u8bba\u6587\u5217\u8868\u90fd\u4e22\u5931\u4e86\u3002\u5143\u5b66\u4e60\u662f\u673a\u5668\u5b66\u4e60\u7684\u4e00\u4e2a\u5b50\u9886\u57df\uff0c\u662f\u5c06\u81ea\u52a8\u5b66\u4e60\u7b97\u6cd5\u5e94\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u5b9e\u9a8c\u7684\u5143\u6570\u636e\u4e0a\u3002<\/p>\n<p>\u5c31\u50cf\u7ea2\u697c\u68a6\u7f3a\u5931\u7684 40 \u56de\uff0c\u6e05\u5355\u8d44\u6599\u7f3a\u5931\u7684 13 \u7bc7\u8bba\u6587\u5f15\u53d1\u4e86\u4e0d\u5c11\u8ba8\u8bba\uff0c\u5bf9\u4e8e\u54ea\u4e9b\u8bba\u6587\u8db3\u591f\u91cd\u8981\u800c\u5e94\u8be5\u5305\u62ec\u5728\u5185\uff0c\u4eba\u4eec\u63d0\u51fa\u4e86\u8bb8\u591a\u4e0d\u540c\u7684\u60f3\u6cd5\u3002<\/p>\n<p>\u6700\u8fd1\uff0c\u4e00\u4f4d\u540d\u4e3a Taro Langner \u7684\u7f51\u53cb\u6839\u636e Ilya Sutskever \u591a\u5e74\u6765\u6f14\u8bb2\u5185\u5bb9\u3001OpenAI \u5171\u4eab\u7684\u8d44\u6e90\u7b49\uff0c\u8bd5\u56fe\u627e\u51fa\u6e05\u5355\u4e22\u5931\u7684\u8d44\u6599\u3002\u6700\u540e\u8865\u5145\u5b8c\u6210\u4e86\u300c\u8986\u76d6 AI \u9886\u57df 90% \u77e5\u8bc6\u300d\u7684 AI \u8bba\u6587\u540d\u5355\u3002<\/p>\n<p><a href=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-35962e4714210a9582b1cc8f88488740.png\" data-fancybox=\"images\" data-fancybox=\"gallery\"><img decoding=\"async\" src=\"https:\/\/17aitech.com\/wp-content\/uploads\/2024\/11\/frc-35962e4714210a9582b1cc8f88488740.png\"><\/a><\/p>\n<p>\u4e0e\u6b64\u540c\u65f6\uff0c\u4ed6\u8fd8\u6307\u51fa\u4e86\u4e00\u4e9b\u4f60\u5fc5\u987b\u6ce8\u610f\u7684\u989d\u5916\u5185\u5bb9\uff0c\u5305\u62ec Yann LeCun\u3001Ian Goodfellow \u7b49\u91cd\u8981 AI \u5b66\u8005\u7684\u5de5\u4f5c\uff0c\u4ee5\u53ca\u5173\u4e8e U-Net\u3001YOLO \u76ee\u6807\u68c0\u6d4b\u3001GAN\u3001WaveNet\u3001Word2Vec \u7b49\u6280\u672f\u7684\u8bba\u6587\u3002<\/p>\n<p>\u8ba9\u6211\u4eec\u770b\u770b\u5176\u4e2d\u7684\u5185\u5bb9\uff0c\u548c\u8bba\u6587\u63a8\u8350\u7684\u7406\u7531\u3002<\/p>\n<p><strong>\u7f3a\u5931\u7684\u300c\u5143\u5b66\u4e60\u300d\u677f\u5757<\/strong><\/p>\n<p>\u73b0\u5728\u7684 AI \u7cfb\u7edf\u53ef\u4ee5\u901a\u8fc7\u5927\u91cf\u65f6\u95f4\u548c\u7ecf\u9a8c\u4ece\u5934\u5b66\u4e60\u4e00\u9879\u590d\u6742\u6280\u80fd\u3002\u4f46\u662f\uff0c\u6211\u4eec\u5982\u679c\u60f3\u4f7f\u667a\u80fd\u4f53\u638c\u63e1\u591a\u79cd\u6280\u80fd\u3001\u9002\u5e94\u591a\u79cd\u73af\u5883\uff0c\u5219\u4e0d\u5e94\u8be5\u4ece\u5934\u5f00\u59cb\u5728\u6bcf\u4e00\u4e2a\u73af\u5883\u4e2d\u8bad\u7ec3\u6bcf\u4e00\u9879\u6280\u80fd\uff0c\u800c\u662f\u9700\u8981\u667a\u80fd\u4f53\u901a\u8fc7\u5bf9\u4ee5\u5f80\u7ecf\u9a8c\u7684\u518d\u5229\u7528\u6765\u5b66\u4e60\u5982\u4f55\u5b66\u4e60\u591a\u9879\u65b0\u4efb\u52a1\uff0c\u56e0\u6b64\u6211\u4eec\u4e0d\u5e94\u8be5\u72ec\u7acb\u5730\u8bad\u7ec3\u6bcf\u4e00\u4e2a\u65b0\u4efb\u52a1\u3002<\/p>\n<p>\u8fd9\u79cd\u5b66\u4e60\u5982\u4f55\u5b66\u4e60\u7684\u65b9\u6cd5\uff0c\u53c8\u53eb\u5143\u5b66\u4e60\uff08meta-learning\uff09\uff0c\u662f\u901a\u5f80\u53ef\u6301\u7eed\u5b66\u4e60\u591a\u9879\u65b0\u4efb\u52a1\u7684\u591a\u9762\u667a\u80fd\u4f53\u7684\u5fc5\u7ecf\u4e4b\u8def\u3002<\/p>\n<p>Ilya Sutskever \u62c5\u4efb OpenAI \u9996\u5e2d\u79d1\u5b66\u5bb6\u65f6\u66fe\u53d1\u5e03\u6559\u80b2\u8d44\u6e90\u300cSpinning Up in Deep RL\u300d\uff0c\u5e76\u516c\u5f00\u53d1\u8868\u8fc7\u51e0\u6b21\u5173\u4e8e\u300c\u5143\u5b66\u4e60\u300d\u7684\u6f14\u8bb2\uff1a<\/p>\n<ul>\n<li>Meta Learning and Self Play &#8211; Ilya Sutskever, OpenAI (YouTube), 2017<\/li>\n<li>OpenAI &#8211; Meta Learning &amp; Self Play &#8211; Ilya Sutskever (YouTube), 2018<\/li>\n<li>Ilya Sutskever: OpenAI Meta-Learning and Self-Play (YouTube), 2018<\/li>\n<\/ul>\n<p>Taro Langner \u636e\u6b64\u63a8\u6d4b\u539f\u59cb\u6e05\u5355\u5e94\u8be5\u5305\u542b\u4ee5\u4e0b\u51e0\u7bc7\u7814\u7a76\u8bba\u6587\uff1a<\/p>\n<ul>\n<li>\u300aMeta-Learning with Memory-Augmented Neural Networks\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/proceedings.mlr.press\/v48\/santoro16.pdf<\/li>\n<li>\u300aPrototypical Networks for Few-shot Learning\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/1703.05175<\/li>\n<li>\u300aModel-Agnostic Meta-Learning for Fast Adaptation of Deep Networks\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/proceedings.mlr.press\/v70\/finn17a\/finn17a.pdf<\/li>\n<\/ul>\n<p>\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0cIlya Sutskever \u5728\u4e0a\u8ff0\u300c\u5143\u5b66\u4e60\u300d\u6f14\u8bb2\u4e2d\uff0c\u8fd8\u63d0\u5230\u4e86\u4ee5\u4e0b\u51e0\u7bc7\u8bba\u6587\uff1a<\/p>\n<ul>\n<li>\u300aHuman-level concept learning through probabilistic program induction\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/amygdala.psychdept.arizona.edu\/labspace\/JclubLabMeetings\/Lijuan-Science-2015-Lake-1332-8.pdf<\/li>\n<li>\u300aNeural Architecture Search with Reinforcement Learning\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/pdf\/1611.01578<\/li>\n<li>\u300aA Simple Neural Attentive Meta-Learner\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/pdf\/1707.03141<\/li>\n<\/ul>\n<p>\u53ef\u4ee5\u53d1\u73b0\uff0c\u5f3a\u5316\u5b66\u4e60 (RL) \u5728\u6f14\u8bb2\u4e2d\u4e5f\u5360\u6709\u91cd\u8981\u5730\u4f4d\uff0c\u56e0\u4e3a\u5f3a\u5316\u5b66\u4e60\u4e0e\u5143\u5b66\u4e60\u6709\u7740\u5bc6\u5207\u7684\u8054\u7cfb\u3002\u4e00\u4e2a\u5173\u952e\u6982\u5ff5\u662f\u7ade\u4e89\u6027\u81ea\u6211\u535a\u5f08\uff0c\u5176\u4e2d\u667a\u80fd\u4f53\u5728\u6a21\u62df\u73af\u5883\u4e2d\u8fdb\u884c\u4ea4\u4e92\u4ee5\u8fbe\u5230\u7279\u5b9a\u7684\u76ee\u6807\u3002<\/p>\n<p>Ilya Sutskever \u63d0\u51fa\u4e86\u4e00\u79cd\u8fdb\u5316\u751f\u7269\u5b66\u89c2\u70b9\uff0c\u5c06\u7ade\u4e89\u6027\u81ea\u6211\u535a\u5f08\u4e0e\u793e\u4ea4\u4e92\u52a8\u5bf9\u5927\u8111\u5927\u5c0f\u7684\u5f71\u54cd\u8054\u7cfb\u8d77\u6765\u3002\u6839\u636e\u4ed6\u7684\u5224\u65ad\uff0c\u5728\u6a21\u62df\u7684\u300c\u667a\u80fd\u4f53\u793e\u4f1a\u300d\u4e2d\u5feb\u901f\u83b7\u5f97\u80fd\u529b\u6700\u7ec8\u53ef\u80fd\u4f1a\u4e3a\u67d0\u79cd\u5f62\u5f0f\u7684\u901a\u7528\u4eba\u5de5\u667a\u80fd\u63d0\u4f9b\u4e00\u6761\u53ef\u884c\u7684\u9053\u8def\u3002<\/p>\n<p>\u8003\u8651\u5230\u4ed6\u8d4b\u4e88\u8fd9\u4e9b\u6982\u5ff5\u7684\u91cd\u8981\u6027\uff0c\u4e00\u4e9b\u88ab\u5f15\u7528\u7684\u6709\u5173\u81ea\u6211\u535a\u5f08\u7684\u8bba\u6587\u4e5f\u53ef\u80fd\u88ab\u7eb3\u5165\u9605\u8bfb\u6e05\u5355\uff1a<\/p>\n<ul>\n<li>\u300aHindsight Experience Replay\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/1707.01495<\/li>\n<li>\u300aContinuous control with deep reinforcement learning\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/1509.02971<\/li>\n<li>\u300aSim-to-Real Transfer of Robotic Control with Dynamics Randomization\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/1710.06537<\/li>\n<li>\u300aMeta Learning Shared Hierarchies\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/1710.09767<\/li>\n<li>\u300aTemporal Difference Learning and TD-Gammon \uff0c1995\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/www.csd.uwo.ca\/~xling\/cs346a\/extra\/tdgammon.pdf<\/li>\n<li>\u300aKarl Sims &#8211; Evolved Virtual Creatures, Evolution Simulation, 1994\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/dl.acm.org\/doi\/10.1145\/192161.192167<\/li>\n<li>\u300aEmergent Complexity via Multi-Agent Competition\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/1710.03748<\/li>\n<li>\u300aDeep reinforcement learning from human preferences\u300b<br \/>\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/1706.03741<\/li>\n<\/ul>\n<p><strong>\u5176\u4ed6\u53ef\u80fd\u6027<\/strong><\/p>\n<p>\u5f53\u7136\uff0c\u539f\u59cb\u7684 40 \u7bc7\u8bba\u6587\u540d\u5355\u4e0a\u53ef\u80fd\u8fd8\u6709\u8bb8\u591a\u5176\u4ed6\u4f5c\u54c1\u548c\u4f5c\u8005\uff0c\u4f46\u4ece\u73b0\u5728\u5f00\u59cb\uff0c\u8bc1\u636e\u8d8a\u6765\u8d8a\u8584\u5f31\u4e86\u3002<\/p>\n<p>\u603b\u4f53\u800c\u8a00\uff0c\u76ee\u524d\u8865\u5145\u5b8c\u6574\u7684\u8bba\u6587\u540d\u5355\u5728\u6db5\u76d6\u4e0d\u540c\u6a21\u578b\u7c7b\u522b\u3001\u5e94\u7528\u548c\u7406\u8bba\u7684\u540c\u65f6\uff0c\u8fd8\u6db5\u76d6\u4e86\u8be5\u9886\u57df\u7684\u8bb8\u591a\u8457\u540d\u4f5c\u8005\uff0c\u7aef\u6c34\u7aef\u5f97\u5df2\u7ecf\u633a\u7a33\u4e86\u3002\u4f46\u663e\u7136\uff0c\u8fd8\u6709\u5f88\u591a\u91cd\u8981\u5185\u5bb9\u503c\u5f97\u6ce8\u610f\u3002<\/p>\n<p>\u6211\u4eec\u4f3c\u4e4e\u53ef\u4ee5\u7ee7\u7eed\u5217\u5165\uff1a<\/p>\n<ul>\n<li>Yann LeCun \u7b49\u4eba\u7684\u5de5\u4f5c\uff0c\u4ed6\u5728 CNN \u7684\u5b9e\u9645\u5e94\u7528\u65b9\u9762\u505a\u51fa\u4e86\u5f00\u521b\u6027\u7684\u5de5\u4f5c \u2014\u2014\u300aGradient-based learning applied to document recognition\u300b<\/li>\n<li>Ian Goodfellow \u7b49\u4eba\u7684\u5de5\u4f5c\uff0c\u4ed6\u5728\u751f\u6210\u5bf9\u6297\u7f51\u7edc\uff08GAN\uff09\u65b9\u9762\u7684\u5de5\u4f5c\u957f\u671f\u4e3b\u5bfc\u4e86\u56fe\u50cf\u751f\u6210\u9886\u57df \u2014\u2014\u300aGenerative Adversarial Networks\u300b<\/li>\n<li>Demis Hassabis \u7b49\u4eba\u7684\u5de5\u4f5c\uff0c\u4ed6\u5728 AlphaFold \u65b9\u9762\u7684\u5f3a\u5316\u5b66\u4e60\u7814\u7a76\u83b7\u5f97\u4e86\u8bfa\u8d1d\u5c14\u5956 \u2014\u2014\u300aHuman-level control through deep reinforcement learning\u300b\u3001\u300aAlphaFold at CASP13\u300b<\/li>\n<\/ul>\n<p>\u5728\u66f4\u591a\u4fe1\u606f\u516c\u5e03\u4e4b\u524d\uff0c\u8fd9\u7bc7\u6587\u7ae0\u5728\u5f88\u5927\u7a0b\u5ea6\u4e0a\u4ecd\u662f\u63a8\u6d4b\u6027\u7684\u3002\u6bd5\u7adf\uff0c\u539f\u7248\u7684\u300cIlya \u9605\u8bfb\u6e05\u5355\u300d\u672c\u8eab\u4e5f\u4ece\u672a\u5f97\u5230\u5b98\u65b9\u8bc1\u5b9e\u662f\u771f\u7684\u3002\u5c3d\u7ba1\u5982\u6b64\uff0c\u4f60\u53ef\u4ee5\u770b\u51fa\u76ee\u524d\u8865\u5145\u597d\u7684\u5217\u8868\u662f\u7edd\u5bf9\u5177\u6709\u542b\u91d1\u91cf\u7684\u3002\u603b\u4e4b\u8ba9\u6211\u4eec\u5148\u586b\u8865\u597d\u7a7a\u767d\uff0c\u7528\u4f5c\u8005\u7684\u8bdd\u6765\u8bf4\uff0c\u8fd9\u5927\u81f4\u76f8\u5f53\u4e8e\u5f53\u65f6\u7f3a\u5931\u4e86\u300c\u91cd\u8981\u5185\u5bb9\u7684 30%\u300d\u3002<\/p>\n<p><em>\u53c2\u8003\u5185\u5bb9\uff1a<\/em><\/p>\n<p><em>https:\/\/tensorlabbet.com\/2024\/11\/11\/lost-reading-items\/<\/em><\/p>\n<p><em>https:\/\/www.reddit.com\/r\/MachineLearning\/comments\/1grti0x\/d_the_lost_reading_items_of_ilya_sutskevers_ai\/<\/em><\/p>\n<p>\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:<a href=\"https:\/\/www.jiqizhixin.com\/articles\/2024-11-16\" target=\"_blank\">\u4f20\u8bf4\u4e2dIlya Sutskever\u7cbe\u9009\u8bba\u6587\u6e05\u5355\uff1aAI\u9886\u57df40\u5927\u8bba\u6587\u5b8c\u6574\u7248\u300c\u7834\u89e3\u300d\u5b8c\u6210<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:\u4f20\u8bf4\u4e2dIlya Sut [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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