\u673a\u5668\u4e4b\u5fc3\u62a5\u9053<\/span><\/p>\n

\u7f16\u8f91\uff1a\u675c\u4f1f\u3001\u5c0f\u821f<\/strong><\/span><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
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\u8ba9 AI \u50cf\u4eba\u7c7b\u4e00\u6837\u5b66\u4e60\u548c\u63a8\u7406\uff0c\u8fd9\u662f\u4eba\u5de5\u667a\u80fd\u8fc8\u5411\u4eba\u7c7b\u667a\u80fd\u7684\u91cd\u8981\u4e00\u6b65\u3002\u56fe\u7075\u5956\u5f97\u4e3b Yann LeCun \u66fe\u63d0\u51fa\u81ea\u76d1\u7763 + \u4e16\u754c\u6a21\u578b\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u5982\u4eca\u7ec8\u4e8e\u6709\u4e86\u7b2c\u4e00\u4e2a\u5b9e\u5b9e\u5728\u5728\u7684\u89c6\u89c9\u6a21\u578b\u3002<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
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\u53bb\u5e74\u521d\uff0cMeta \u9996\u5e2d AI \u79d1\u5b66\u5bb6 Yann LeCun \u9488\u5bf9\u300c\u5982\u4f55\u624d\u80fd\u6253\u9020\u51fa\u63a5\u8fd1\u4eba\u7c7b\u6c34\u5e73\u7684 AI\u300d\u63d0\u51fa\u4e86\u5168\u65b0\u7684\u601d\u8def\u3002\u4ed6\u52fe\u52d2\u51fa\u4e86\u6784\u5efa\u4eba\u7c7b\u6c34\u5e73 AI \u7684\u53e6\u4e00\u79cd\u613f\u666f\uff0c\u6307\u51fa\u5b66\u4e60\u4e16\u754c\u6a21\u578b\uff08\u5373\u4e16\u754c\u5982\u4f55\u8fd0\u4f5c\u7684\u5185\u90e8\u6a21\u578b\uff09\u7684\u80fd\u529b\u6216\u8bb8\u662f\u5173\u952e\u3002\u8fd9\u79cd\u5b66\u5230\u4e16\u754c\u8fd0\u4f5c\u65b9\u5f0f\u5185\u90e8\u6a21\u578b\u7684\u673a\u5668\u53ef\u4ee5\u66f4\u5feb\u5730\u5b66\u4e60\u3001\u89c4\u5212\u5b8c\u6210\u590d\u6742\u7684\u4efb\u52a1\uff0c\u5e76\u8f7b\u677e\u9002\u5e94\u4e0d\u719f\u6089\u7684\u60c5\u51b5\u3002<\/span><\/p>\n<\/section>\n
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LeCun \u8ba4\u4e3a\uff0c\u6784\u9020\u81ea\u4e3b AI \u9700\u8981\u9884\u6d4b\u4e16\u754c\u6a21\u578b\uff0c\u800c\u4e16\u754c\u6a21\u578b\u5fc5\u987b\u80fd\u591f\u6267\u884c\u591a\u6a21\u6001\u9884\u6d4b\uff0c\u5bf9\u5e94\u7684\u89e3\u51b3\u65b9\u6848\u662f\u4e00\u79cd\u53eb\u505a\u5206\u5c42 JEPA\uff08\u8054\u5408\u5d4c\u5165\u9884\u6d4b\u67b6\u6784\uff09\u7684\u67b6\u6784\u3002\u8be5\u67b6\u6784\u53ef\u4ee5\u901a\u8fc7\u5806\u53e0\u7684\u65b9\u5f0f\u8fdb\u884c\u66f4\u62bd\u8c61\u3001\u66f4\u957f\u671f\u7684\u9884\u6d4b\u3002<\/span><\/p>\n<\/section>\n
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6 \u6708 9 \u65e5\uff0c\u5728 2023 \u5317\u4eac\u667a\u6e90\u5927\u4f1a\u5f00\u5e55\u5f0f\u7684 keynote \u6f14\u8bb2\u4e2d\uff0cLeCun \u53c8\u518d\u6b21\u8bb2\u89e3\u4e86\u4e16\u754c\u6a21\u578b\u7684\u6982\u5ff5\uff0c\u4ed6\u8ba4\u4e3a\u57fa\u4e8e\u81ea\u76d1\u7763\u7684\u8bed\u8a00\u6a21\u578b\u65e0\u6cd5\u83b7\u5f97\u5173\u4e8e\u771f\u5b9e\u4e16\u754c\u7684\u77e5\u8bc6\uff0c\u8fd9\u4e9b\u6a21\u578b\u5728\u672c\u8d28\u4e0a\u662f\u4e0d\u53ef\u63a7\u7684\u3002<\/span><\/p>\n<\/section>\n
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\u4eca\u65e5\uff0cMeta \u63a8\u51fa\u4e86\u9996\u4e2a\u57fa\u4e8e LeCun \u4e16\u754c\u6a21\u578b\u6982\u5ff5\u7684 AI \u6a21\u578b\u3002\u8be5\u6a21\u578b\u540d\u4e3a\u56fe\u50cf\u8054\u5408\u5d4c\u5165\u9884\u6d4b\u67b6\u6784\uff08Image Joint Embedding Predictive Architecture, I-JEPA\uff09\uff0c\u5b83\u901a\u8fc7\u521b\u5efa\u5916\u90e8\u4e16\u754c\u7684\u5185\u90e8\u6a21\u578b\u6765\u5b66\u4e60\uff0c \u6bd4\u8f83\u56fe\u50cf\u7684\u62bd\u8c61\u8868\u793a\uff08\u800c\u4e0d\u662f\u6bd4\u8f83\u50cf\u7d20\u672c\u8eab\uff09\u3002<\/span><\/p>\n<\/section>\n
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I-JEPA \u5728\u591a\u9879\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\u4e0a\u53d6\u5f97\u975e\u5e38\u4e0d\u9519\u7684\u6548\u679c\uff0c\u5e76\u4e14\u8ba1\u7b97\u6548\u7387\u8fdc\u9ad8\u4e8e\u5176\u4ed6\u5e7f\u6cdb\u4f7f\u7528\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u6a21\u578b\u3002\u6b64\u5916 I-JEPA \u5b66\u5f97\u7684\u8868\u793a\u4e5f\u53ef\u4ee5\u7528\u4e8e\u5f88\u591a\u4e0d\u540c\u7684\u5e94\u7528\uff0c\u65e0\u9700\u8fdb\u884c\u5927\u91cf\u5fae\u8c03\u3002<\/span><\/p>\n<\/section>\n
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\u4e3e\u4e2a\u4f8b\u5b50\uff0cMeta \u5728 72 \u5c0f\u65f6\u5185\u4f7f\u7528 16 \u5757 A100 GPU \u8bad\u7ec3\u4e86\u4e00\u4e2a 632M \u53c2\u6570\u7684\u89c6\u89c9 transformer \u6a21\u578b\uff0c\u8fd8\u5728 ImageNet \u4e0a\u5b9e\u73b0\u4e86 low-shot \u5206\u7c7b\u7684 SOTA \u6027\u80fd\uff0c\u5176\u4e2d\u6bcf\u4e2a\u7c7b\u53ea\u6709 12 \u4e2a\u6807\u7b7e\u6837\u672c\u3002\u5176\u4ed6\u65b9\u6cd5\u901a\u5e38\u9700\u8981 2 \u5230 10 \u500d\u7684 GPU \u5c0f\u65f6\u6570\uff0c\u5e76\u5728\u4f7f\u7528\u76f8\u540c\u6570\u636e\u91cf\u8bad\u7ec3\u65f6\u8bef\u5dee\u7387\u66f4\u9ad8\u3002<\/span><\/p>\n<\/section>\n
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\u76f8\u5173\u7684\u8bba\u6587\u300aSelf-Supervised Learning from Images with a Joint-Embedding Predictive Architecture\u300b\u5df2\u88ab CVPR 2023 \u63a5\u6536\u3002\u5f53\u7136\uff0c\u6240\u6709\u7684\u8bad\u7ec3\u4ee3\u7801\u548c\u6a21\u578b\u68c0\u67e5\u70b9\u90fd\u5c06\u5f00\u6e90\u3002<\/span><\/p>\n<\/section>\n
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\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/pdf\/2301.08243.pdf<\/span><\/section>\n<\/li>\n
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GitHub \u5730\u5740\uff1ahttps:\/\/t.co\/DgS9XiwnMz<\/span><\/section>\n<\/li>\n<\/ul>\n<\/section>\n
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\u901a\u8fc7\u81ea\u76d1\u7763\u5b66\u4e60\u83b7\u53d6\u5e38\u8bc6\u578b\u77e5\u8bc6<\/strong><\/span><\/section>\n
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I-JEPA \u57fa\u4e8e\u4e00\u4e2a\u4e8b\u5b9e\uff0c\u5373\u4eba\u7c7b\u4ec5\u901a\u8fc7\u88ab\u52a8\u89c2\u5bdf\u5c31\u53ef\u4ee5\u4e86\u89e3\u5173\u4e8e\u4e16\u754c\u7684\u5927\u91cf\u80cc\u666f\u77e5\u8bc6\uff0c\u8fd9\u4e9b\u5e38\u8bc6\u4fe1\u606f\u88ab\u8ba4\u4e3a\u662f\u5b9e\u73b0\u667a\u80fd\u884c\u4e3a\u7684\u5173\u952e\u3002<\/span><\/p>\n<\/section>\n
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\u901a\u5e38\uff0cAI \u7814\u7a76\u4eba\u5458\u4f1a\u8bbe\u8ba1\u5b66\u4e60\u7b97\u6cd5\u6765\u6355\u83b7\u73b0\u5b9e\u4e16\u754c\u7684\u5e38\u8bc6\uff0c\u5e76\u5c06\u5176\u7f16\u7801\u4e3a\u7b97\u6cd5\u53ef\u8bbf\u95ee\u7684\u6570\u5b57\u8868\u5f81\u3002\u4e3a\u4e86\u9ad8\u6548\uff0c\u8fd9\u4e9b\u8868\u5f81\u9700\u8981\u4ee5\u81ea\u76d1\u7763\u7684\u65b9\u5f0f\u6765\u5b66\u4e60\uff0c\u5373\u76f4\u63a5\u4ece\u56fe\u50cf\u6216\u58f0\u97f3\u7b49\u672a\u6807\u8bb0\u7684\u6570\u636e\u4e2d\u5b66\u4e60\uff0c\u800c\u4e0d\u662f\u4ece\u624b\u52a8\u6807\u8bb0\u7684\u6570\u636e\u96c6\u4e2d\u5b66\u4e60\u3002<\/span><\/p>\n<\/section>\n
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\u5728\u9ad8\u5c42\u7ea7\u4e0a\uff0cJEPA \u7684\u4e00\u4e2a\u8f93\u5165\u4e2d\u67d0\u4e2a\u90e8\u5206\u7684\u8868\u5f81\u662f\u6839\u636e\u5176\u4ed6\u90e8\u5206\u7684\u8868\u5f81\u6765\u9884\u6d4b\u7684\u3002\u540c\u65f6\uff0c\u901a\u8fc7\u5728\u9ad8\u62bd\u8c61\u5c42\u6b21\u4e0a\u9884\u6d4b\u8868\u5f81\u800c\u4e0d\u662f\u76f4\u63a5\u9884\u6d4b\u50cf\u7d20\u503c\uff0cJEPA \u80fd\u591f\u76f4\u63a5\u5b66\u4e60\u6709\u7528\u7684\u8868\u5f81\uff0c\u540c\u65f6\u907f\u514d\u4e86\u751f\u6210\u6a21\u578b\u7684\u5c40\u9650\u6027\u3002<\/span><\/p>\n<\/section>\n
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\u76f8\u6bd4\u4e4b\u4e0b\uff0c\u751f\u6210\u6a21\u578b\u4f1a\u901a\u8fc7\u5220\u9664\u6216\u626d\u66f2\u6a21\u578b\u8f93\u5165\u7684\u90e8\u5206\u5185\u5bb9\u6765\u5b66\u4e60\u3002\u7136\u800c\uff0c\u751f\u6210\u6a21\u578b\u7684\u4e00\u4e2a\u663e\u8457\u7f3a\u70b9\u662f\u6a21\u578b\u8bd5\u56fe\u586b\u8865\u6bcf\u4e00\u70b9\u7f3a\u5931\u7684\u4fe1\u606f\uff0c\u5373\u4f7f\u73b0\u5b9e\u4e16\u754c\u672c\u8d28\u4e0a\u662f\u4e0d\u53ef\u9884\u6d4b\u7684\u3002\u56e0\u6b64\uff0c\u751f\u6210\u6a21\u578b\u8fc7\u4e8e\u5173\u6ce8\u4e0d\u76f8\u5173\u7684\u7ec6\u8282\uff0c\u800c\u4e0d\u662f\u6355\u6349\u9ad8\u7ea7\u53ef\u9884\u6d4b\u7684\u6982\u5ff5\u3002<\/span><\/p>\n<\/section>\n
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\u81ea\u76d1\u7763\u5b66\u4e60\u7684\u901a\u7528\u67b6\u6784\uff0c\u5176\u4e2d\u7cfb\u7edf\u5b66\u4e60\u6355\u83b7\u5176\u8f93\u5165\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/span><\/section>\n
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\u8fc8\u5411\u80fd\u529b\u5e7f\u6cdb\u7684 JEPA \u7684\u7b2c\u4e00\u6b65<\/strong><\/span><\/section>\n
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I-JEPA \u7684\u6838\u5fc3\u601d\u8def\u662f\u4ee5\u66f4\u7c7b\u4f3c\u4e8e\u4eba\u7c7b\u7406\u89e3\u7684\u62bd\u8c61\u8868\u5f81\u6765\u9884\u6d4b\u7f3a\u5931\u4fe1\u606f\u3002\u4e0e\u5728\u50cf\u7d20 \/token \u7a7a\u95f4\u4e2d\u8fdb\u884c\u9884\u6d4b\u7684\u751f\u6210\u65b9\u6cd5\u76f8\u6bd4\uff0cI-JEPA \u4f7f\u7528\u62bd\u8c61\u7684\u9884\u6d4b\u76ee\u6807\uff0c\u6f5c\u5728\u5730\u6d88\u9664\u4e86\u4e0d\u5fc5\u8981\u7684\u50cf\u7d20\u7ea7\u7ec6\u8282\uff0c\u4ece\u800c\u4f7f\u6a21\u578b\u5b66\u4e60\u66f4\u591a\u8bed\u4e49\u7279\u5f81\u3002<\/span><\/p>\n<\/section>\n
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\u53e6\u4e00\u4e2a\u5f15\u5bfc I-JEPA \u4ea7\u751f\u8bed\u4e49\u8868\u5f81\u7684\u6838\u5fc3\u8bbe\u8ba1\u662f\u591a\u5757\u63a9\u7801\u7b56\u7565\u3002\u8be5\u7814\u7a76\u4f7f\u7528\u4fe1\u606f\u4e30\u5bcc\u7684\u4e0a\u4e0b\u6587\u6765\u9884\u6d4b\u5305\u542b\u8bed\u4e49\u4fe1\u606f\u7684\u5757\uff0c\u5e76\u8868\u660e\u8fd9\u662f\u975e\u5e38\u5fc5\u8981\u7684\u3002<\/span><\/p>\n<\/section>\n
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I-JEPA \u4f7f\u7528\u5355\u4e2a\u4e0a\u4e0b\u6587\u5757\u6765\u9884\u6d4b\u6e90\u81ea\u540c\u4e00\u56fe\u50cf\u7684\u5404\u79cd\u76ee\u6807\u5757\u7684\u8868\u5f81\u3002<\/span><\/section>\n
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I-JEPA \u4e2d\u7684\u9884\u6d4b\u5668\u53ef\u4ee5\u770b\u4f5c\u662f\u4e00\u4e2a\u539f\u59cb\u7684\uff08\u548c\u53d7\u9650\u7684\uff09\u4e16\u754c\u6a21\u578b\uff0c\u5b83\u80fd\u591f\u4ece\u90e8\u5206\u53ef\u89c2\u5bdf\u7684\u4e0a\u4e0b\u6587\u4e2d\u6a21\u62df\u9759\u6001\u56fe\u50cf\u4e2d\u7684\u7a7a\u95f4\u4e0d\u786e\u5b9a\u6027\u3002\u66f4\u91cd\u8981\u7684\u662f\uff0c\u8fd9\u4e2a\u4e16\u754c\u6a21\u578b\u662f\u8bed\u4e49\u7ea7\u7684\uff0c\u56e0\u4e3a\u5b83\u9884\u6d4b\u56fe\u50cf\u4e2d\u4e0d\u53ef\u89c1\u533a\u57df\u7684\u9ad8\u7ea7\u4fe1\u606f\uff0c\u800c\u4e0d\u662f\u50cf\u7d20\u7ea7\u7ec6\u8282\u3002<\/span><\/p>\n<\/section>\n
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\u9884\u6d4b\u5668\u5982\u4f55\u5b66\u4e60\u5efa\u6a21\u4e16\u754c\u7684\u8bed\u4e49\u3002\u5bf9\u4e8e\u6bcf\u5f20\u56fe\u50cf\uff0c\u84dd\u6846\u5916\u7684\u90e8\u5206\u88ab\u7f16\u7801\u5e76\u4f5c\u4e3a\u4e0a\u4e0b\u6587\u63d0\u4f9b\u7ed9\u9884\u6d4b\u5668\u3002\u7136\u540e\u9884\u6d4b\u5668\u8f93\u51fa\u5b83\u671f\u671b\u5728\u84dd\u6846\u5185\u533a\u57df\u7684\u8868\u793a\u3002\u4e3a\u4e86\u53ef\u89c6\u5316\u9884\u6d4b\uff0cMeta \u8bad\u7ec3\u4e86\u4e00\u4e2a\u751f\u6210\u6a21\u578b\uff0c \u5b83\u751f\u6210\u4e86\u7531\u9884\u6d4b\u8f93\u51fa\u8868\u793a\u7684\u5185\u5bb9\u8349\u56fe\uff0c\u5e76\u5728\u84dd\u6846\u5185\u663e\u793a\u6837\u672c\u8f93\u51fa\u3002\u5f88\u660e\u663e\uff0c\u9884\u6d4b\u5668\u8bc6\u522b\u51fa\u4e86\u5e94\u8be5\u586b\u5145\u54ea\u4e9b\u90e8\u5206\u7684\u8bed\u4e49\uff08\u5982\u72d7\u7684\u5934\u90e8\u3001\u9e1f\u7684\u817f\u3001\u72fc\u7684\u524d\u80a2\u3001\u5efa\u7b51\u7269\u7684\u53e6\u4e00\u4fa7\uff09\u3002<\/span><\/section>\n
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\u4e3a\u4e86\u7406\u89e3\u6a21\u578b\u6355\u83b7\u7684\u5185\u5bb9\uff0cMeta \u8bad\u7ec3\u4e86\u4e00\u4e2a\u968f\u673a\u89e3\u7801\u5668\uff0c\u5c06 I-JEPA \u9884\u6d4b\u7684\u8868\u793a\u6620\u5c04\u56de\u50cf\u7d20\u7a7a\u95f4\uff0c\u8fd9\u5c55\u793a\u51fa\u4e86\u63a2\u9488\u64cd\u4f5c\u540e\u5728\u84dd\u6846\u4e2d\u8fdb\u884c\u9884\u6d4b\u65f6\u7684\u6a21\u578b\u8f93\u51fa\u3002\u8fd9\u79cd\u5b9a\u6027\u8bc4\u4f30\u8868\u660e\uff0cI-JEPA \u6b63\u786e\u6355\u83b7\u4e86\u4f4d\u7f6e\u4e0d\u786e\u5b9a\u6027\uff0c\u5e76\u751f\u6210\u4e86\u5177\u6709\u6b63\u786e\u59ff\u6001\u7684\u9ad8\u7ea7\u5bf9\u8c61\u90e8\u5206\uff08\u5982\u72d7\u7684\u5934\u90e8\u3001\u72fc\u7684\u524d\u80a2\uff09\u3002<\/span><\/p>\n<\/section>\n
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\u7b80\u800c\u8a00\u4e4b\uff0cI-JEPA \u80fd\u591f\u5b66\u4e60\u5bf9\u8c61\u90e8\u5206\u7684\u9ad8\u7ea7\u8868\u793a\uff0c\u800c\u4e0d\u4f1a\u4e22\u5f03\u5b83\u4eec\u5728\u56fe\u50cf\u4e2d\u7684\u5c40\u90e8\u4f4d\u7f6e\u4fe1\u606f\u3002<\/span><\/p>\n<\/section>\n
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\u9ad8\u6548\u7387\u3001\u5f3a\u6027\u80fd<\/strong><\/span><\/section>\n
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I-JEPA \u9884\u8bad\u7ec3\u5728\u8ba1\u7b97\u4e0a\u4e5f\u5f88\u9ad8\u6548\uff0c\u5728\u4f7f\u7528\u66f4\u591a\u8ba1\u7b97\u5bc6\u96c6\u578b\u6570\u636e\u589e\u5f3a\u6765\u751f\u6210\u591a\u4e2a\u89c6\u56fe\u65f6\u4e0d\u4f1a\u4ea7\u751f\u4efb\u4f55\u5f00\u9500\u3002\u76ee\u6807\u7f16\u7801\u5668\u53ea\u9700\u8981\u5904\u7406\u56fe\u50cf\u7684\u4e00\u4e2a\u89c6\u56fe\uff0c\u4e0a\u4e0b\u6587\u7f16\u7801\u5668\u53ea\u9700\u8981\u5904\u7406\u4e0a\u4e0b\u6587\u5757\u3002<\/span><\/p>\n<\/section>\n
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\u5b9e\u9a8c\u53d1\u73b0\uff0cI-JEPA \u5728\u4e0d\u4f7f\u7528\u624b\u52a8\u89c6\u56fe\u589e\u5f3a\u7684\u60c5\u51b5\u4e0b\u5b66\u4e60\u4e86\u5f3a\u5927\u7684\u73b0\u6210\u8bed\u4e49\u8868\u793a\uff0c\u5177\u4f53\u53ef\u89c1\u4e0b\u56fe\u3002\u6b64\u5916 I-JEPA \u8fd8\u5728 ImageNet-1K \u7ebf\u6027\u63a2\u9488\u548c\u534a\u76d1\u7763\u8bc4\u4f30\u4e0a\u4f18\u4e8e\u50cf\u7d20\u548c token \u91cd\u5efa\u65b9\u6cd5\u3002<\/span><\/p>\n<\/section>\n
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ImageNet-1k \u6570\u636e\u96c6\u4e0a\u7684\u7ebf\u6027\u8bc4\u4f30\u3002<\/span><\/section>\n
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I-JEPA \u8fd8\u80fd\u4e0e\u4ee5\u5f80\u5728\u8bed\u4e49\u4efb\u52a1\u4e0a\u4f9d\u8d56\u624b\u52a8\u6570\u636e\u589e\u5f3a\u7684\u65b9\u6cd5\u7ade\u4e89\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0cI-JEPA \u5728\u5bf9\u8c61\u8ba1\u6570\u548c\u6df1\u5ea6\u9884\u6d4b\u7b49\u4f4e\u7ea7\u89c6\u89c9\u4efb\u52a1\u4e0a\u53d6\u5f97\u4e86\u66f4\u597d\u7684\u6027\u80fd\u3002\u901a\u8fc7\u4f7f\u7528\u8f83\u5c0f\u521a\u6027\u5f52\u7eb3\u504f\u7f6e\u7684\u66f4\u7b80\u5355\u6a21\u578b\uff0cI-JEPA \u9002\u7528\u4e8e\u66f4\u5e7f\u6cdb\u7684\u4efb\u52a1\u96c6\u5408\u3002<\/span><\/p>\n<\/section>\n
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l<\/span>ow shot \u5206\u7c7b\u51c6\u786e\u6027\uff1a\u4f7f\u7528 1% \u6807\u7b7e\u65f6 ImageNet-1k \u4e0a\u7684\u534a\u76d1\u7763\u8bc4\u4f30\u7ed3\u679c\uff08\u6bcf\u7c7b\u53ea\u6709 12 \u5f20\u6807\u7b7e\u56fe\u50cf\uff09\u3002<\/span><\/span><\/section>\n
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AI \u667a\u80fd\u5411\u4eba\u7c7b\u6c34\u5e73\u66f4\u8fd1\u4e86\u4e00\u6b65<\/strong><\/span><\/section>\n
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I-JEPA \u5c55\u793a\u4e86\u65e0\u9700\u901a\u8fc7\u624b\u52a8\u56fe\u50cf\u53d8\u6362\u6765\u7f16\u7801\u989d\u5916\u77e5\u8bc6\u65f6\uff0c\u5b66\u4e60\u6709\u7ade\u4e89\u529b\u7684\u73b0\u6210\u56fe\u50cf\u8868\u793a\u7684\u6f5c\u529b\u3002\u7ee7\u7eed\u63a8\u8fdb JEPA \u4ee5\u4ece\u66f4\u4e30\u5bcc\u6a21\u6001\u4e2d\u5b66\u4e60\u66f4\u901a\u7528\u4e16\u754c\u6a21\u578b\u5c06\u53d8\u5f97\u7279\u522b\u6709\u8da3\uff0c\u6bd4\u5982\u4eba\u4eec\u4ece\u4e00\u4e2a\u77ed\u4e0a\u4e0b\u6587\u4e2d\u5bf9\u89c6\u9891\u4e2d\u7684\u5c06\u6765\u4e8b\u4ef6\u505a\u51fa\u957f\u671f\u7a7a\u95f4\u548c\u65f6\u95f4\u9884\u6d4b\uff0c\u5e76\u5229\u7528\u97f3\u9891\u6216\u6587\u672c prompt \u5bf9\u8fd9\u4e9b\u9884\u6d4b\u8fdb\u884c\u8c03\u6574\u3002<\/span><\/p>\n<\/section>\n
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Meta \u5e0c\u671b\u5c06 JEPA \u65b9\u6cd5\u6269\u5c55\u5230\u5176\u4ed6\u9886\u57df\uff0c\u6bd4\u5982\u56fe\u50cf – \u6587\u672c\u914d\u5bf9\u6570\u636e\u548c\u89c6\u9891\u6570\u636e\u3002\u672a\u6765\uff0cJEPA \u6a21\u578b\u53ef\u4ee5\u5728\u89c6\u9891\u7406\u89e3\u7b49\u4efb\u52a1\u4e2d\u5f97\u5230\u5e94\u7528\u3002\u8fd9\u662f\u5e94\u7528\u548c\u6269\u5c55\u81ea\u76d1\u7763\u65b9\u6cd5\u6765\u5b66\u4e60\u66f4\u901a\u7528\u4e16\u754c\u6a21\u578b\u7684\u91cd\u8981\u4e00\u6b65\u3002<\/span><\/p>\n<\/section>\n
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\u539f\u6587\u94fe\u63a5\uff1ahttps:\/\/ai.facebook.com\/blog\/yann-lecun-ai-model-i-jepa\/<\/span><\/section>\n<\/section>\n
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\u7279\u522b\u8bf4\u660e\uff1a\u672c\u6587\u4ec5\u7528\u4e8e\u5b66\u672f\u4ea4\u6d41\uff0c\u5982\u6709\u4fb5\u6743\u8bf7\u540e\u53f0\u8054\u7cfb\u5c0f\u7f16\u5220\u9664\u3002<\/span><\/section>\n<\/section>\n
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\u8f6c\u8f7d\u7f16\u8f91\uff1a\u4f55\u5e05<\/span><\/p>\n
\u5ba1\u6838\uff1a<\/span>\u8096\u5fd7\u6e05 \u674e\u957f\u5ead<\/span>\u00a0<\/span>\u9648\u6b23\u6021\u00a0\u6768\u747e<\/span><\/p>\n
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