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Y\u8f66\u578b\u914d\u5907\u4e86\u6beb\u7c73\u6ce2\u96f7\u8fbe\uff0c\u4f46\u4e0d\u4e45\u4e4b\u524d\u4e5f\u6539\u88c5\u4e86\u7eaf\u89c6\u89c9\u65b9\u6848\u7684\u6444\u50cf\u5934\u6765\u8fdb\u884c\u8f85\u52a9\u9a7e\u9a76\u3002<\/p>\n<p>\u9a6c\u65af\u514b\u66fe\u5632\u7b11\uff0c\u4efb\u4f55\u4f9d\u9760\u6fc0\u5149\u96f7\u8fbe\u7684\u4f01\u4e1a\u6ce8\u5b9a\u6ca1\u6709\u672a\u6765\u3002<\/p>\n<p>\u4eba\u5bb6\u4e00\u76f4\u5f3a\u8c03\uff1a\u201c\u6444\u50cf\u5934\u548c\u795e\u7ecf\u7f51\u7edc\u662f\u5b9e\u73b0\u81ea\u52a8\u9a7e\u9a76\u7684\u5173\u952e\u3002\u6574\u4e2a\u9053\u8def\u7cfb\u7edf\u65e8\u5728\u4e0e\u5149\u5b66\u6210\u50cf\u5668\uff08\u773c\u775b\uff09\u548c\u795e\u7ecf\u7f51\u7edc\uff08\u5927\u8111\uff09\u914d\u5408\u4f7f\u7528\u3002\u56e0\u6b64\u6444\u50cf\u5934\u548c\u795e\u7ecf\u7f51\u7edc\u624d\u662f\u6839\u672c\u89e3\u51b3\u65b9\u6848\u3002\u201d<\/p>\n<p>\u4f5c\u4e3aAI\u6d3e\u7684\u9876\u6881\u67f1\uff0c\u7279\u65af\u62c9\u8ba4\u4e3a\u5355\u7eaf\u4f9d\u9760\u6444\u50cf\u5934\u5c31\u53ef\u4ee5\u5b8c\u6210\u81ea\u52a8\u9a7e\u9a76\u6240\u9700\u8981\u7684\u5468\u56f4\u73af\u5883\u611f\u77e5\u903b\u8f91\uff0c\u5178\u578b\u7684\u7b97\u6cd5\u51b3\u5b9a\u4e00\u5207\u7684\u8ba4\u77e5\u903b\u8f91\u3002<\/p>\n<p>\u4ed6\u4eec\u8ba4\u4e3a\uff0c\u667a\u80fd\u6c7d\u8f66\u7684\u611f\u5e94\u7cfb\u7edf\u5e94\u5c3d\u91cf\u6a21\u4eff\u4eba\uff0c\u667a\u80fd\u9a7e\u9a76\u6c7d\u8f66\u53ef\u4ee5\u901a\u8fc7\u8ba1\u7b97\u89c6\u89c9\u6765\u63a5\u8fd1\u4eba\u7c7b\u97602\u53ea\u773c\uff082\u4e2a\u6444\u50cf\u5934\uff09\u5904\u7406\u5f00\u8f66\u7684\u6c34\u5e73\u3002<\/p>\n<p>\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u8fd9\u4e9b\u4eba\u7684\u51fa\u8eab\u591a\u4e0e\u673a\u5668\u5b66\u4e60\u5c24\u5176\u662f\u6df1\u5ea6\u5b66\u4e60\u6709\u5173\uff0c\u4ed6\u4eec\u5bf9\u8ba1\u7b97\u89c6\u89c9\u7684\u4fe1\u5fc3\u6765\u81ea\u5bf9\u6df1\u5ea6\u5b66\u4e60\u7684\u4fe1\u5fc3\u3002<\/p>\n<p>\u6362\u53e5\u8bdd\u8bf4\uff0c\u504f\u5411\u7b97\u6cd5\u5de5\u7a0b\u5e08\u51fa\u8eab\u7684\u4ed6\u4eec\u8ba4\u4e3a\u6df1\u5ea6\u5b66\u4e60\u662f\u5168\u81ea\u52a8\u9a7e\u9a76\u6280\u672f\u7684\u672a\u6765\u3002<\/p>\n<p>\u53e6\u4e00\u8fb9\uff0c\u6fc0\u5149\u96f7\u8fbe\u6d3e\u5219\u4ee5\u6fc0\u5149\u96f7\u8fbe\u4e3a\u4e3b\u5bfc\uff0c\u914d\u5408\u6beb\u7c73\u6ce2\u96f7\u8fbe\u3001\u8d85\u58f0\u6ce2\u4f20\u611f\u5668\u3001\u6444\u50cf\u5934\u591a\u4f20\u611f\u5668\u878d\u5408\u5b8c\u6210\u5468\u56f4\u73af\u5883\u611f\u77e5\uff0c\u5c0f\u9e4fP5\u3001\u851a\u6765ET7\u4f7f\u7528\u7684\u662f\u6fc0\u5149\u96f7\u8fbe\u65b9\u6848\u3002<\/p>\n<p>\u8fd9\u7fa4\u4eba\u5c31\u662f\u73b0\u5b9e\u6d3e\uff0c\u8003\u8651\u5982\u4f55\u63a8\u53e0\u786c\u4ef6\u964d\u4f4e\u4e8b\u6545\u98ce\u9669\u3002<\/p>\n<p>\u6fc0\u5149\u96f7\u8fbe\u5c31\u662f\u5f88\u5b89\u5168\u7684\u63a2\u6d4b\u4eea\uff01<\/p>\n<p>\u5b83\u53ef\u4ee5\u63d0\u4f9b\u5173\u4e8e\u666f\u6df1\u7684\u4fe1\u606f\uff0c\u5176\u539f\u7406\u662f\u901a\u8fc7\u53d1\u5c04\u956d\u5c04\u5149\u5e76\u63a5\u53d7\u53cd\u5c04\u6765\u5efa\u7acb\u5468\u8fb9\u7684\u4e09\u7ef4\u7acb\u4f53\u56fe\u50cf\u3002<\/p>\n<p>\u6fc0\u5149\u96f7\u8fbe\u5728\u63a2\u6d4b\u7cbe\u5ea6\u3001\u8303\u56f4\u4ee5\u53ca\u7a33\u5b9a\u6027\u4e0a\uff0c\u66f4\u5177\u6709\u4f18\u52bf\uff0c\u53ef\u4ee5\u8fbe\u5230\u5398\u7c73\u7ea7\u3002<\/p>\n<p>\u5c24\u5176\u662f\u6fc0\u5149\u96f7\u8fbe\u8d1f\u8d23\u4e3b\u8981\u7684\u5468\u8fb9\u63a2\u6d4b\u5efa\u6a21\uff0c\u6beb\u7c73\u6ce2\u96f7\u8fbe\u7528\u6765\u8f85\u4f50\u6fc0\u5149\u96f7\u8fbe\uff0c\u53ef\u4ee5\u5728\u6076\u52a3\u5929\u6c14\u4e0b\u505a\u51fa\u66f4\u597d\u7684\u56de\u9988\uff0c\u52a0\u4e0a\u6444\u50cf\u5934\u63d0\u4f9b2D\u7684\u5b9e\u65f6\u5f71\u50cf\uff0c3D\u5efa\u6a21\u642d\u914d2D\u5f71\u50cf\uff0c\u5c31\u53ef\u4ee5\u66f4\u597d\u7684\u7528\u7b97\u6cd5\u548c\u6570\u636e\u5b66\u4e60\u80fd\u529b\uff0c\u5bf9\u5468\u8fb9\u7684\u4fe1\u606f\u505a\u5230\u66f4\u7cbe\u786e\u7684\u63a2\u6d4b\uff0c\u66f4\u7cbe\u786e\u7684\u5468\u56f4\u4fe1\u606f\uff0c\u5c31\u66f4\u80fd\u6709\u5229\u7684\u63d0\u5347\u8f85\u52a9\u9a7e\u9a76\u7684\u80fd\u529b\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-5916\" src=\"https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__4a0647ffea6d409f5fb4515adbe5bd9d.jpg\" width=\"707\" height=\"501\" srcset=\"https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__4a0647ffea6d409f5fb4515adbe5bd9d.jpg 707w, https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__4a0647ffea6d409f5fb4515adbe5bd9d-300x213.jpg 300w\" sizes=\"auto, (max-width: 707px) 100vw, 707px\" \/><\/p>\n<p><strong>03\u4e0d\u60f3\u4f9d\u8d56\u9ad8\u6e05\u5730\u56fe<\/strong><\/p>\n<p>\u53bb\u5e74\uff0c\u7279\u65af\u62c9<span class=\"hrefStyle\"><a title=\"\u4eba\u5de5\u667a\u80fd\" href=\"https:\/\/www.ofweek.com\/ai\/\" target=\"_blank\" rel=\"noopener\">\u4eba\u5de5\u667a\u80fd<\/a><\/span>\u4e0e\u81ea\u52a8\u9a7e\u9a76\u89c6\u89c9\u603b\u76d1Andrej Karpathy\u66fe\u8868\u6001\u4e3a\u4f55\u4e0d\u8ba4\u53ef\u6fc0\u5149\u96f7\u8fbe\u3002<\/p>\n<p>\u4ed6\u8ba4\u4e3a\uff0c\u5c06\u6fc0\u5149\u96f7\u8fbe\u6dfb\u52a0\u5230\u81ea\u52a8\u9a7e\u9a76\u5806\u6808\u4f1a\u5e26\u6765\u5176\u81ea\u8eab\u7684\u590d\u6742\u6027\u3002<\/p>\n<p>Karpathy\u8bf4\uff0c\u201c\u4f60\u5fc5\u987b\u7528\u6fc0\u5149\u96f7\u8fbe\u9884\u5148\u7ed8\u5236\u73af\u5883\u5730\u56fe\uff0c\u7136\u540e\u4f60\u5fc5\u987b\u521b\u5efa\u4e00\u5f20\u9ad8\u6e05\u5730\u56fe\uff0c\u4f60\u5fc5\u987b\u63d2\u5165\u6240\u6709\u8f66\u9053\u53ca\u5176\u8fde\u63a5\u65b9\u5f0f\u4ee5\u53ca\u6240\u6709\u4ea4\u901a\u4fe1\u53f7\u706f\uff0c\u6536\u96c6\u3001\u6784\u5efa\u548c\u7ef4\u62a4\u8fd9\u4e9b\u9ad8\u6e05\u6fc0\u5149\u96f7\u8fbe\u5730\u56fe\u662f\u4e0d\u53ef\u6269\u5c55\u7684\uff0c\u8ba9\u8fd9\u4e2a\u57fa\u7840\u8bbe\u65bd\u4fdd\u6301\u6700\u65b0\u72b6\u6001\u5c06\u662f\u6781\u5176\u56f0\u96be\u7684\u3002\u201d<\/p>\n<p>Karpathy\u8868\u793a\u7279\u65af\u62c9\u5728\u5176\u81ea\u52a8\u9a7e\u9a76\u5806\u6808\u4e2d\u4e0d\u4f7f\u7528\u6fc0\u5149\u96f7\u8fbe\u548c\u9ad8\u6e05\u5730\u56fe\uff0c\u201c\u53d1\u751f\u7684\u4e00\u5207\uff0c\u90fd\u662f\u7b2c\u4e00\u6b21\u53d1\u751f\u5728\u8f66\u5185\uff0c\u57fa\u4e8e\u56f4\u7ed5\u6c7d\u8f66\u7684\u516b\u4e2a\u6444\u50cf\u5934\u7684\u89c6\u9891\u201d\u3002<\/p>\n<p>Karpathy\u5177\u4f53\u89e3\u91ca\u4e86\u7279\u65af\u62c9\u7684\u89c6\u89c9\u65b9\u6848\u8fd0\u4f5c\u539f\u7406\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-5917\" src=\"https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__f801f5716682e4accef034b4984050b5.jpg\" width=\"558\" height=\"295\" srcset=\"https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__f801f5716682e4accef034b4984050b5.jpg 558w, https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__f801f5716682e4accef034b4984050b5-300x159.jpg 300w\" sizes=\"auto, (max-width: 558px) 100vw, 558px\" \/><\/p>\n<p>\u7279\u65af\u62c9\u6c7d\u8f66\u4e0a\u5b89\u88c5\u4e868\u4e2a\u6444\u50cf\u5934\uff0c\u6444\u50cf\u5934\u6ca1\u6709\u6df1\u5ea6\u4fe1\u606f\uff0c\u4ed6\u4eec\u7684\u76ee\u6807\u4e4b\u4e00\u5c31\u662f\u5f62\u6210\u77e2\u91cf\u7a7a\u95f4\u89c6\u56fe\u3002<\/p>\n<p>\u90a3\u4e48\u8981\u600e\u4e48\u77e5\u9053\u65c1\u8fb9\u4e00\u8f86\u8f66\u7a76\u7adf\u5728\u54ea\u91cc\u53c8\u6709\u591a\u957f\u5462\uff1f<\/p>\n<p>\u9996\u5148\u7684\u4e00\u4e2a\u96be\u70b9\u662f\uff0c\u4e0d\u540c\u89c6\u89d2\u7684\u6444\u50cf\u5934\u90fd\u53ea\u80fd\u770b\u5230\u5468\u8fb9\u73af\u5883\u7684\u4e00\u90e8\u5206\uff0c\u6709\u4e0d\u540c\u7684\u6821\u51c6\uff08calibration\uff09\u3001\u4f4d\u7f6e\uff08location\uff09\u3001\u53d6\u666f\u65b9\u5411\uff08view direction\uff09\u7b49\uff0c\u6bd4\u5982\u4ee5\u4e0b\u8fd9\u5f20\u56fe\uff0c\u8c01\u80fd\u77e5\u9053\u8fd9\u4e2a\u70b9\u5bf9\u5e94\u4e8e\u76f8\u673a\u89c6\u56fe\u7684\u54ea\u4e2a\u70b9\uff1f\u800c\u6211\u4eec\u53ea\u6709\u77e5\u9053\u8fd9\u4e9b\u4fe1\u606f\uff0c\u624d\u80fd\u628a\u5468\u56f4\u7269\u4f53\u51c6\u786e\u653e\u5230\u5411\u91cf\u7a7a\u95f4\u89c6\u56fe\uff08vector space view\uff09\u4e2d\u3002<\/p>\n<p>\u56e0\u6b64\u5c31\u9700\u8981\u4e00\u79cd\u5c06\u591a\u4e2a\u6444\u50cf\u5934\u7684\u4fe1\u606f\u878d\u5408\u5728\u4e00\u8d77\u7684\u6280\u672f\uff0c\u7279\u65af\u62c9\u4f7f\u7528\u4e86\u57282017\u5e74\u63d0\u51fa\uff0c\u5982\u4eca\u5df2\u7ecf\u5e2d\u5377<span class=\"hrefStyle\"><a title=\"\u81ea\u7136\u8bed\u8a00\u5904\u7406\" href=\"https:\/\/www.ofweek.com\/ai\/CAT-201718-nlp.html\" target=\"_blank\" rel=\"noopener\">\u81ea\u7136\u8bed\u8a00\u5904\u7406<\/a><\/span>\u548c<span class=\"hrefStyle\"><a title=\"\u8ba1\u7b97\u673a\u89c6\u89c9\" href=\"https:\/\/www.ofweek.com\/ai\/CAT-201716-cpv.html\" target=\"_blank\" rel=\"noopener\">\u8ba1\u7b97\u673a\u89c6\u89c9<\/a><\/span>\u9886\u57df\u7684Transformer\u795e\u7ecf\u7f51\u7edc\uff08Transformer Neural Network\uff09\u3002<\/p>\n<p>\u7136\u540e\u5219\u662f\u52a0\u5165\u6709\u65f6\u95f4\u6982\u5ff5\u65f6\u95f4\u7684RNN\uff08Recurrent Neural Network\uff0c\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\uff09\u4ee5\u5224\u65ad\u79fb\u52a8\u7269\u4f53\u7684\u901f\u5ea6\u4ee5\u53ca\u5bf9\u88ab\u906e\u6321\u7269\u8fdb\u884c\u9884\u6d4b\u3002<\/p>\n<p>RNN\u4f53\u73b0\u4e86\u201c\u4eba\u7684\u8ba4\u77e5\u662f\u57fa\u4e8e\u8fc7\u5f80\u7684\u7ecf\u9a8c\u548c\u8bb0\u5fc6\u201d\u7684\u89c2\u70b9\uff0c\u901a\u8fc7\u8bb0\u5fc6\u6765\u5904\u7406\u4efb\u610f\u65f6\u5e8f\u7684\u8f93\u5165\u5e8f\u5217\uff0c\u4ece\u800c\u5bf9\u63a5\u4e0b\u6765\u8981\u53d1\u751f\u7684\u4e8b\u60c5\u8fdb\u884c\u9884\u6d4b\u3002\u6bd4\u5982\u8fd9\u91cc\u5bf9\u88ab\u906e\u6321\u7269\u9884\u6d4b\uff0c\u901a\u8fc7\u5bf9\u906e\u6321\u524d\u7684\u7279\u5f81\u548c\u8f68\u8ff9\u7684\u8bb0\u5fc6\uff0c\u4f7f\u5f97\u89c6\u91ce\u88ab\u77ed\u6682\u906e\u853d\u7684\u60c5\u51b5\u4e0b\uff0c\u4f9d\u7136\u53ef\u4ee5\u9884\u6d4b\u906e\u6321\u89c6\u91ce\u540e\u7684\u7269\u4f53\u8fd0\u52a8\u8f68\u8ff9\uff0c\u5e76\u8bb0\u5f55\u5df2\u884c\u9a76\u8fc7\u7684\u8def\u6bb5\u7684\u5404\u79cd\u8def\u6807\u3002<\/p>\n<p>\u800c\u5bf9\u4e8e\u6df1\u5ea6\u4fe1\u606f\uff0c\u5728\u7f3a\u5c11\u4e86\u96f7\u8fbe\u4fe1\u606f\u540e\uff0c\u5219\u9700\u8981\u901a\u8fc7\u5bf9\u5927\u91cf\u7684\u6709\u6df1\u5ea6\u6807\u6ce8\u7684\u76f8\u673a\u6570\u636e\u8fdb\u884c\u8bad\u7ec3\u5f97\u5230\u7684\u68c0\u6d4b\u7b97\u6cd5\u6765\u5f97\u5230\u3002<\/p>\n<p>\u8fd9\u4e9b\u5e74\uff0c\u7279\u65af\u62c9\u4e00\u76f4\u5728\u8fed\u4ee3\u795e\u7ecf\u7f51\u7edc\uff0c\u5229\u7528\u4e86\u591a\u5934\u8def\u5f84\uff0c\u5176\u4e2d\u5305\u62ec\u6444\u50cf\u673a\u6821\u51c6\u3001\u7f13\u5b58\u3001\u961f\u5217\u548c\u4f18\u5316\u4ee5\u7b80\u5316\u6240\u6709\u4efb\u52a1\u3002<\/p>\n<p>\u53e6\u5916\uff0c\u7279\u65af\u62c9\u795e\u7ecf\u7f51\u7edc\u7cfb\u7edf\u6280\u672f\u7684\u80cc\u540e\u6709\u5343\u4eba\u7684\u6570\u636e\u6807\u8bb0\u56e2\u961f\uff0c\u53ef\u4ee5\u5bf9\u5404\u7c7b\u6570\u636e\u4f8b\u5982\u9053\u8def\u3001\u73af\u5883\u4ee5\u53ca\u884c\u4eba\u6570\u636e\u8fdb\u884c\u6807\u8bb0\uff0c\u53e6\u5916\u5f53\u4e0b\u4e5f\u5df2\u7ecf\u62e5\u6709\u4e86\u81ea\u52a8\u6807\u8bb0\u6280\u672f\uff0c\u8fd9\u6837\u5c31\u53ef\u4ee5\u81ea\u52a8\u9009\u53d6\u6709\u7279\u70b9\u7684\u6837\u672c\u6765\u4e0d\u65ad\u66f4\u65b0\u4f18\u5316\u81ea\u52a8\u9a7e\u9a76\u80fd\u529b\u3002<\/p>\n<p><strong>04\u4ece\u4e13\u5229\u770b\u7279\u65af\u62c9\u795e\u7ecf\u7f51\u7edc<\/strong><\/p>\n<p>\u795e\u7ecf\u7f51\u7edc\uff0c\u7099\u624b\u53ef\u70ed\u3002<\/p>\n<p>\u518d\u6b21\u79d1\u666e\u4e0b\u8fd9\u4e2a\u6982\u5ff5\uff01<\/p>\n<p>\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\uff08Artificial Neural Networks\uff0c\u7b80\u5199\u4e3aANNs\uff09\uff0c\u4e5f\u7b80\u79f0\u4e3a\u795e\u7ecf\u7f51\u7edc\uff08NNs\uff09\u6216\u79f0\u4f5c\u8fde\u63a5\u6a21\u578b\uff08Connection Model\uff09\uff0c\u5b83\u662f\u4e00\u79cd\u6a21\u4eff\u52a8\u7269\u795e\u7ecf\u7f51\u7edc\u884c\u4e3a\u7279\u5f81\uff0c\u8fdb\u884c\u5206\u5e03\u5f0f\u5e76\u884c\u4fe1\u606f\u5904\u7406\u7684\u7b97\u6cd5\u6570\u5b66\u6a21\u578b\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-5918\" src=\"https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__59d3c6907cfbee5a32c2d4369b762957.jpg\" width=\"975\" height=\"606\" srcset=\"https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__59d3c6907cfbee5a32c2d4369b762957.jpg 975w, https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__59d3c6907cfbee5a32c2d4369b762957-300x186.jpg 300w, https:\/\/aiforumimage.oss-cn-shanghai.aliyuncs.com\/wp-content\/uploads\/2022\/09\/wx_article__59d3c6907cfbee5a32c2d4369b762957-768x477.jpg 768w\" sizes=\"auto, (max-width: 975px) 100vw, 975px\" \/><\/p>\n<p>\u8fd9\u79cd\u7f51\u7edc\u4f9d\u9760\u7cfb\u7edf\u7684\u590d\u6742\u7a0b\u5ea6\uff0c\u901a\u8fc7\u8c03\u6574\u5185\u90e8\u5927\u91cf\u8282\u70b9\u4e4b\u95f4\u76f8\u4e92\u8fde\u63a5\u7684\u5173\u7cfb\uff0c\u4ece\u800c\u8fbe\u5230\u5904\u7406\u4fe1\u606f\u7684\u76ee\u7684\u3002<\/p>\n<p>\u795e\u7ecf\u7f51\u7edc\u5229\u7528\u73b0\u6709\u7684\u6570\u636e\u627e\u51fa\u8f93\u5165\u4e0e\u8f93\u51fa\u4e4b\u95f4\u5f97\u6743\u503c\u5173\u7cfb\uff08\u8fd1\u4f3c\uff09\uff0c\u7136\u540e\u5229\u7528\u8fd9\u6837\u7684\u6743\u503c\u5173\u7cfb\u8fdb\u884c\u4eff\u771f\uff0c\u4f8b\u5982\u8f93\u5165\u4e00\u7ec4\u6570\u636e\u4eff\u771f\u51fa\u8f93\u51fa\u7ed3\u679c\uff0c\u5f53\u7136\u4f60\u7684\u8f93\u5165\u8981\u548c\u8bad\u7ec3\u65f6\u91c7\u7528\u7684\u6570\u636e\u96c6\u5728\u4e00\u4e2a\u8303\u7574\u4e4b\u5185\u3002<\/p>\n<p>\u4f8b\u5982\u9884\u62a5\u5929\u6c14\uff1a\u5bfb\u627e\u57fa\u672c\u9884\u6d4b\u56e0\u5b50\uff0c\u5982\u6e29\u5ea6\u6e7f\u5ea6\u6c14\u538b\u7b49\u6c14\u8c61\u60c5\u51b5\uff0c\u5229\u7528\u5386\u53f2\u7684\u6c14\u8c61\u6570\u636e\u5728\u795e\u7ecf\u7f51\u7edc\u8fdb\u884c\u5173\u7cfb\u8bad\u7ec3\uff0c\u7136\u540e\u8f93\u5165\u4eca\u5929\u7684\u6e29\u5ea6\u6e7f\u5ea6\u6c14\u538b\u7b49\u56e0\u5b50\uff0c\u6839\u636e\u5386\u53f2\u6570\u636e\u6d4b\u7b97\u7684\u6982\u7387\u60c5\u51b5\u5f97\u5230\u4eca\u65e5\u6c14\u8c61\u9884\u6d4b\u7ed3\u679c\u8fdb\u884c\u9884\u62a5\uff0c\u8fd9\u662f\u795e\u7ecf\u7f51\u7edc\u7684\u5178\u578b\u5e94\u7528\u3002<\/p>\n<p>\u5728\u5fb7\u9ad8\u884c\u5168\u7403\u4e13\u5229\u5e93\u4e2d\uff0c\u4ee5\u795e\u7ecf\u7f51\u7edc\u4e3a\u5173\u952e\u8bcd\uff0c\u68c0\u7d22\u76f8\u5173\u7279\u65af\u62c9\u4e13\u5229\uff0cTesla \u5168\u7403AI\u4e13\u5229249\u4ef6\u3002<\/p>\n<p><strong>\u56fd\u5185\u6700\u65b0\u516c\u5f00\u76846\u4e2a\u4e13\u5229\uff1a<\/strong><\/p>\n<p>\u5e8f\u53f7<\/p>\n<p>\u6807\u9898<\/p>\n<p>\u6458\u8981<\/p>\n<p>\u516c\u5f00\u53f7<\/p>\n<p>1<\/p>\n<p>\u5177\u6709\u6307\u5b9a\u504f\u5dee\u6d6e\u70b9\u64cd\u4f5c\u6570\u7684\u77e9\u9635\u4e58\u6cd5\u6307\u4ee4\u7684\u7cfb\u7edf\u548c\u65b9\u6cd5<\/p>\n<p>\u4e00\u79cd\u5fae\u5904\u7406\u5668\u7cfb\u7edf\u5305\u62ec\u77e9\u9635\u8ba1\u7b97\u5355\u5143\u548c\u63a7\u5236\u5355\u5143\u3002\u77e9\u9635\u8ba1\u7b97\u5355\u5143\u5305\u62ec\u591a\u4e2a\u5904\u7406\u5143\u4ef6\u3002\u63a7\u5236\u5355\u5143\u88ab\u914d\u7f6e\u4e3a\u5411\u77e9\u9635\u8ba1\u7b97\u5355\u5143\u63d0\u4f9b\u77e9\u9635\u5904\u7406\u5668\u6307\u4ee4\u3002\u77e9\u9635\u5904\u7406\u5668\u6307\u4ee4\u6307\u5b9a\u4f7f\u7528\u7b2c\u4e00\u6d6e\u70b9\u8868\u793a\u683c\u5f0f\u683c\u5f0f\u5316\u7684\u6d6e\u70b9\u64cd\u4f5c\u6570\u3002\u77e9\u9635\u8ba1\u7b97\u5355\u5143\u7d2f\u52a0\u4f7f\u7528\u6d6e\u70b9\u64cd\u4f5c\u6570\u8ba1\u7b97\u7684\u4e2d\u95f4\u7ed3\u679c\u503c\u3002\u4e2d\u95f4\u7ed3\u679c\u503c\u91c7\u7528\u7b2c\u4e8c\u6d6e\u70b9\u8868\u793a\u683c\u5f0f\u3002<\/p>\n<p>CN113785271A<\/p>\n<p>2<\/p>\n<p>\u7528\u4e8e\u83b7\u53d6\u8bad\u7ec3\u6570\u636e\u7684\u7cfb\u7edf\u548c\u65b9\u6cd5<\/p>\n<p>\u63cf\u8ff0\u4e86\u7528\u4e8e\u83b7\u53d6\u8bad\u7ec3\u6570\u636e\u7684\u7cfb\u7edf\u548c\u65b9\u6cd5\u3002\u793a\u4f8b\u65b9\u6cd5\u5305\u62ec\u63a5\u6536\u4f20\u611f\u5668\u5e76\u4e14\u5c06\u795e\u7ecf\u7f51\u7edc\u5e94\u7528\u4e8e\u4f20\u611f\u5668\u6570\u636e\u3002\u89e6\u53d1\u5206\u7c7b\u5668\u88ab\u5e94\u7528\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u4e2d\u95f4\u7ed3\u679c\uff0c\u4ee5\u786e\u5b9a\u9488\u5bf9\u4f20\u611f\u5668\u6570\u636e\u7684\u5206\u7c7b\u5668\u5f97\u5206\u3002\u81f3\u5c11\u90e8\u5206\u5730\u57fa\u4e8e\u5206\u7c7b\u5668\u5f97\u5206\uff0c\u505a\u51fa\u4ee5\u4e0b\u786e\u5b9a\uff1a\u662f\u5426\u8981\u7ecf\u7531\u8ba1\u7b97\u673a\u7f51\u7edc\u4f20\u9001\u4f20\u611f\u5668\u6570\u636e\u7684\u81f3\u5c11\u4e00\u90e8\u5206\u3002\u5728\u80af\u5b9a\u7684\u786e\u5b9a\u65f6\uff0c\u4f20\u611f\u5668\u6570\u636e\u88ab\u4f20\u9001\u5e76\u4e14\u88ab\u7528\u6765\u751f\u6210\u8bad\u7ec3\u6570\u636e\u3002<\/p>\n<p>CN112771548A<\/p>\n<p>3<\/p>\n<p>\u7528\u4e8e\u81ea\u4e3b\u9a7e\u9a76\u7684\u6570\u636e\u7ba1\u7ebf\u548c\u6df1\u5ea6\u5b66\u4e60\u7cfb\u7edf<\/p>\n<p>\u63a5\u6536\u4f7f\u7528\u4ea4\u901a\u5de5\u5177\u4e0a\u7684\u4f20\u611f\u5668\u6355\u83b7\u7684\u56fe\u50cf\u5e76\u4e14\u5c06\u5176\u5206\u89e3\u4e3a\u591a\u4e2a\u5206\u91cf\u56fe\u50cf\u3002\u5c06\u591a\u4e2a\u5206\u91cf\u56fe\u50cf\u4e2d\u7684\u6bcf\u4e2a\u5206\u91cf\u56fe\u50cf\u4f5c\u4e3a\u4e0d\u540c\u8f93\u5165\u63d0\u4f9b\u7ed9\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u591a\u4e2a\u5c42\u4e2d\u7684\u4e0d\u540c\u5c42\uff0c\u4ee5\u786e\u5b9a\u7ed3\u679c\u3002\u4f7f\u7528\u4eba\u5de5\u795e\u7ecf\u7f51\u7edc\u7684\u7ed3\u679c\uff0c\u4ee5\u81f3\u5c11\u90e8\u5206\u5730\u81ea\u4e3b\u64cd\u4f5c\u4ea4\u901a\u5de5\u5177\u3002<\/p>\n<p>CN112639817A<\/p>\n<p>4<\/p>\n<p>\u7528\u4e8e\u57fa\u4e8e\u786c\u4ef6\u7684\u6c60\u5316\u7684\u7cfb\u7edf\u548c\u65b9\u6cd5<\/p>\n<p>\u672c\u6587\u63cf\u8ff0\u4e86\u7cfb\u7edf\u548c\u65b9\u6cd5\uff0c\u5176\u5229\u7528\u65b0\u9896\u7684\u57fa\u4e8e\u786c\u4ef6\u7684\u6c60\u5316\u67b6\u6784\u6765\u5904\u7406\u5377\u79ef\u5f15\u64ce\u7684\u8f93\u51fa\uff0c\u5377\u79ef\u5f15\u64ce\u7684\u8f93\u51fa\u8868\u793a\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\uff08CNN\uff09\u4e2d\u7684\u5377\u79ef\u5c42\u7684\u8f93\u51fa\u901a\u9053\u3002\u6c60\u5316\u7cfb\u7edf\u5c06\u8f93\u51fa\u8f6c\u6362\u4e3a\u4e00\u7ec4\u9635\u5217\uff0c\u5e76\u4e14\u6839\u636e\u6c60\u5316\u64cd\u4f5c\u5c06\u4e3a\u4e00\u7ec4\u9635\u5217\u5bf9\u51c6\u4ee5\u751f\u6210\u6c60\u5316\u7ed3\u679c\u3002\u5728\u67d0\u4e9b\u5b9e\u65bd\u4f8b\u4e2d\uff0c\u8fd9\u901a\u8fc7\u4f7f\u7528\u5bf9\u51c6\u5668\u6765\u5b9e\u73b0\uff0c\u8be5\u5bf9\u51c6\u5668\u4f8b\u5982\u5728\u591a\u4e2a\u7b97\u672f\u5faa\u73af\u4e0a\uff0c\u5c06\u8f93\u51fa\u4e2d\u7684\u6570\u636e\u7684\u9635\u5217\u5bf9\u51c6\u5230\u884c\u4e2d\uff0c\u5e76\u4e14\u4f7f\u884c\u76f8\u5bf9\u4e8e\u5f7c\u6b64\u79fb\u4f4d\u3002\u6c60\u5316\u5668\u5c06\u6c60\u5316\u64cd\u4f5c\u5e94\u7528\u4e8e\u6765\u81ea\u6bcf\u884c\u7684\u6570\u636e\u7684\u5b50\u96c6\u7684\u7ec4\u5408\uff0c\u4ee5\u751f\u6210\u6c60\u5316\u7ed3\u679c\u3002<\/p>\n<p>CN111758107A<\/p>\n<p>5<\/p>\n<p>\u7528\u4e8e\u5904\u7406\u8f7d\u5177\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668\u4e2d\u7684\u9519\u8bef\u7684\u7cfb\u7edf\u548c\u65b9\u6cd5<\/p>\n<p>\u4e00\u79cd\u7528\u4e8e\u5904\u7406\u795e\u7ecf\u7f51\u7edc\u4e2d\u7684\u9519\u8bef\u7684\u7cfb\u7edf\u5305\u62ec\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668\uff0c\u5176\u7528\u4e8e\u6267\u884c\u4e0e\u8f7d\u5177\u7684\u4f7f\u7528\u76f8\u5173\u8054\u7684\u795e\u7ecf\u7f51\u7edc\u3002\u8be5\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668\u5305\u62ec\uff1a\u9519\u8bef\u68c0\u6d4b\u5668\uff0c\u88ab\u914d\u7f6e\u4e3a\u68c0\u6d4b\u4e0e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computational unit\uff08\u77e2\u91cf\u8ba1\u7b97\u5355\u5143\uff09<\/p>\n<p>A microprocessor system comprises a computational array and a vector computational unit\uff0e The computational array includes a plurality of computation units\uff0e The vector computational unit is in communication with the computational array and includes a plurality of processing elements\uff0e The processing elements are configured to receive output data elements from the computational array and process in parallel the received output data elements\uff0e<\/p>\n<p>US11409692B2<\/p>\n<p>2<\/p>\n<p>Accelerated mathematical engine\uff08\u52a0\u901f\u6570\u5b66\u5f15\u64ce\uff09<\/p>\n<p>Various embodiments of the disclosure relate to an accelerated mathematical engine\uff0e In certain embodiments\uff0c \u00a0the accelerated mathematical engine is applied to image processing such that convolution of an image is accelerated by using a two\uff0ddimensional matrix processor comprising sub\uff0dcircuits that include an ALU\uff0c \u00a0output register and shadow register\uff0e This architecture supports a clocked\uff0c \u00a0two\uff0ddimensional architecture in which image data and weights are multiplied in a synchronized manner to allow a large number of mathematical operations to be performed in parallel\uff0e<\/p>\n<p>US11403069B2<\/p>\n<p>3<\/p>\n<p>PREDICTING THREE\uff0dDIMENSIONAL FEATURES FOR AUTONOMOUS DRIVING\uff08\u9884\u6d4b\u81ea\u52a8\u9a7e\u9a76\u7684\u4e09\u7ef4\u7279\u5f81\uff09<\/p>\n<p>A processor coupled to memory is configured to receive image data based on an image captured by a camera of a vehicle\uff0e The image data is used as a basis of an input to a trained machine learning model trained to predict a three\uff0ddimensional trajectory of a machine learning feature\uff0e The three\uff0ddimensional trajectory of the machine learning feature is provided for automatically controlling the vehicle\uff0e<\/p>\n<p>US20220107651A1<\/p>\n<p>4<\/p>\n<p>DATA PIPELINE AND DEEP LEARNING SYSTEM FOR AUTONOMOUS DRIVING\uff08\u7528\u4e8e\u81ea\u4e3b\u9a7e\u9a76\u7684\u6570\u636e\u7ba1\u9053\u548c\u6df1\u5ea6\u5b66\u4e60\u7cfb\u7edf\uff09<\/p>\n<p>An image captured using a sensor on a vehicle is received and decomposed into a plurality of component images\uff0e Each component image of the plurality of component images is provided as a different input to a different layer of a plurality of layers of an artificial neural network to determine a result\uff0e The result of the artificial neural network is used to at least in part autonomously operate the vehicle\uff0e<\/p>\n<p>US20220107652A1<\/p>\n<p>5<\/p>\n<p>Estimating object properties using visual image data\uff08\u5229\u7528\u89c6\u89c9\u56fe\u50cf\u6570\u636e\u4f30\u8ba1\u7269\u4f53\u5c5e\u6027\uff09<\/p>\n<p>A system is comprised of one or more processors coupled to memory\uff0e The one or more processors are configured to receive image data based on an image captured using a camera of a vehicle and to utilize the image data as a basis of an input to a trained machine learning model to at least in part identify a distance of an object from the vehicle\uff0e The trained machine learning model has been trained using a training image and a correlated output of an emitting distance sensor\uff0e<\/p>\n<p>US11288524B2<\/p>\n<p>6<\/p>\n<p>SYSTEM AND METHOD FOR HANDLING ERRORS IN A VEHICLE NEURAL NETWORK PROCESSOR\uff08\u7528\u4e8e\u5904\u7406\u8f66\u8f86\u795e\u7ecf\u7f51\u7edc\u5904\u7406\u5668\u4e2d\u7684\u8bef\u5dee\u7684\u7cfb\u7edf\u548c\u65b9\u6cd5\uff09<\/p>\n<p>A system for handling errors in a neural network includes a neural network processor for executing a neural network associated with use of a vehicle\uff0e The neural network processor includes an error detector configured to detect a data error associated with execution of the neural network and a neural network controller configured to receive a report of the data error from the error detector\uff0e In response to receiving the report\uff0c \u00a0the neural network controller is further configured to signal that a pending result of the neural network is tainted without terminating execution of the neural network\uff0e<\/p>\n<p>US20220083412A1<\/p>\n<p>7<\/p>\n<p>MULTI\uff0dCHANNEL SENSOR SIMULATION FOR AUTONOMOUS CONTROL SYSTEMS\uff08\u81ea\u4e3b\u63a7\u5236\u7cfb\u7edf\u7684\u591a\u901a\u9053\u4f20\u611f\u5668\u4eff\u771f\uff09<\/p>\n<p>An autonomous control system combines sensor data from multiple sensors to simulate sensor data from high\uff0dcapacity sensors\uff0e The sensor data contains information related to physical environments surrounding vehicles for autonomous guidance\uff0e For example\uff0c \u00a0the sensor data may be in the form of images that visually capture scenes of the surrounding environment\uff0c \u00a0geo\uff0dlocation of the vehicles\uff0c \u00a0and the like\uff0e The autonomous control system simulates high\uff0dcapacity sensor data of the physical environment from replacement sensors that may each have lower capacity than high\uff0dcapacity sensors\uff0e The high\uff0dcapacity sensor data may be simulated via one or more neural network models\uff0e The autonomous control system performs various detection and control algorithms on the simulated sensor data to guide the vehicle autonomously\uff0e<\/p>\n<p>US20220043449A1<\/p>\n<p>8<\/p>\n<p>Scalable matrix node engine with configurable data formats\uff08\u5177\u6709\u53ef\u914d\u7f6e\u6570\u636e\u683c\u5f0f\u7684\u53ef\u6269\u5c55\u77e9\u9635\u8282\u70b9\u5f15\u64ce\uff09<\/p>\n<p>A microprocessor system comprises a matrix computational unit and a control unit\uff0e The matrix computational unit includes one or more processing elements\uff0e The control unit is configured to provide a matrix processor instruction to the matrix computational unit\uff0e The matrix processor instruction specifies a floating\uff0dpoint operand formatted with an exponent that has been biased with a specified 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