{"id":18770,"date":"2025-10-25T17:28:07","date_gmt":"2025-10-25T17:28:07","guid":{"rendered":"https:\/\/lexgoacademy.com\/?p=18770"},"modified":"2026-03-25T12:59:48","modified_gmt":"2026-03-25T12:59:48","slug":"ai-%e7%9a%84%e5%bf%ab%e6%80%9d%e8%88%87%e6%85%a2%e6%83%b3","status":"publish","type":"post","link":"https:\/\/lexgoacademy.com\/zh\/ai-%e7%9a%84%e5%bf%ab%e6%80%9d%e8%88%87%e6%85%a2%e6%83%b3\/","title":{"rendered":"AI \u7684\u5feb\u601d\u8207\u6162\u60f3"},"content":{"rendered":"
\n\t\t\t\t
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\u4eba\u5de5\u667a\u80fd\u7cfb\u7d71\u7684\u51fa\u73fe\u6e90\u65bc\u5e6b\u52a9\u4eba\u985e\u89e3\u6c7a\u554f\u984c\uff0c\u63d0\u4f9b\u5177\u6548\u80fd\u7684\u6c7a\u7b56\u53ca\u6e1b\u5c11\u932f\u8aa4\u3002\u6b63\u56e0\u70ba\u8981\u8207\u4eba\u985e\u76f8\u4e92\u5354\u4f5c\uff0c\u4eba\u5de5\u667a\u80fd\u7684\u601d\u8003\u5c11\u4e0d\u514d\u8981\u53c3\u8003\u4eba\u985e\u7684\u601d\u7dad\u6a21\u5f0f\u53bb\u8a2d\u8a08\u3002\u82e5\u4f60\u60f3\u5f9e\u9019\u89d2\u5ea6\u53bb\u8a8d\u8b58\u4eba\u5de5\u667a\u80fd\uff0c\u6211\u6703\u63a8\u85a6\u4f60\u95b1\u8b802002\u4e39\u5c3c\u723e\u00b7\u5eb7\u7d0d\u66fc (Daniel Kahneman) \u7684\u8457\u4f5c\u300a\u5feb\u601d\u6162\u60f3\u300b(Thinking, Fast and Slow) \u3002<\/p>

\u4e39\u5c3c\u723e\u00b7\u5eb7\u7d0d\u66fc\u662f\u8457\u540d\u7684\u5fc3\u7406\u5b78\u5bb6\u548c\u8afe\u8c9d\u723e\u7d93\u6fdf\u5b78\u734e\u5f97\u4e3b\u3002\u4ed6\u65bc1934\u5e74\u51fa\u751f\u65bc\u4ee5\u8272\u5217\uff0c\u5f8c\u4f86\u6210\u70ba\u7f8e\u570b\u666e\u6797\u65af\u9813\u5927\u5b78\u7684\u5fc3\u7406\u5b78\u6559\u6388\u3002\u5eb7\u7d0d\u66fc\u4ee5\u5176\u5c0d\u4eba\u985e\u601d\u7dad\u548c\u6c7a\u7b56\u904e\u7a0b\u7684\u7814\u7a76\u800c\u805e\u540d\uff0c\u7279\u5225\u662f\u5728\u884c\u70ba\u7d93\u6fdf\u5b78\u9818\u57df\u7684\u8ca2\u737b\u3002\u4ed6\u7684\u8457\u4f5c\u300a\u5feb\u601d\u6162\u60f3\u300b\u6df1\u5165\u63a2\u8a0e\u4e86\u4eba\u985e\u601d\u7dad\u7684\u5169\u7a2e\u7cfb\u7d71\uff0c\u7279\u5225\u662f\u5982\u4f55\u5728\u4e0d\u540c\u60c5\u5883\u4e0b\u505a\u51fa\u6c7a\u7b56\uff0c\u5e6b\u52a9\u4eba\u5011\u7406\u89e3\u601d\u7dad\u904e\u7a0b\u4e2d\u5b58\u5728\u7684\u504f\u898b\u548c\u932f\u8aa4\uff0c\u5c0d\u5fc3\u7406\u5b78\u548c\u7d93\u6fdf\u5b78\u90fd\u6709\u6df1\u9060\u7684\u5f71\u97ff\u3002\u4ed6\u7684\u7814\u7a76\u4e0d\u50c5\u5728\u5b78\u8853\u754c\u53d7\u5230\u9ad8\u5ea6\u8a55\u50f9\uff0c\u4e5f\u5c0d\u4f01\u696d\u7ba1\u7406\u548c\u516c\u5171\u653f\u7b56\u7522\u751f\u4e86\u5be6\u969b\u7684\u5f71\u97ff\u3002<\/p>

\u5feb\u601d\u6162\u60f3\u7684\u6982\u5ff5<\/strong><\/h4>

\u9019\u8457\u4f5c\u63d0\u51fa\u4e86\u4eba\u985e\u601d\u8003\u7684\u96d9\u7cfb\u7d71\u7406\u8ad6\uff0c\u5c07\u4eba\u7684\u601d\u7dad\u5206\u70ba \u300c\u7cfb\u7d71\u4e00\u300d(System 1) \u548c \u300c\u7cfb\u7d71\u4e8c\u300d(System 2)\u3002\u9019\u500b\u7406\u8ad6\u4e0d\u50c5\u6df1\u523b\u5730\u5f71\u97ff\u4e86\u5fc3\u7406\u5b78\u548c\u884c\u70ba\u7d93\u6fdf\u5b78\uff0c\u4e5f\u70ba\u6211\u5011\u7406\u89e3\u4eba\u5de5\u667a\u80fd (AI) \u7684\u601d\u8003\u6a21\u5f0f\u63d0\u4f9b\u4e86\u65b0\u7684\u8996\u89d2\u3002\u900f\u904e\u7406\u89e3 AI \u7684\u300c\u5feb\u300d\u8207\u300c\u6162\u300d\uff0c\u6211\u5011\u53ef\u4ee5\u66f4\u6709\u6548\u5730\u904b\u7528 AI \u5de5\u5177\uff0c\u4e26\u8207 AI \u5354\u4f5c\u89e3\u6c7a\u8907\u96dc\u7684\u554f\u984c\u3002<\/p>

.\u00a0 \u00a0\u7cfb\u7d711 (System 1)\uff1a\u5feb\u601d<\/strong><\/p>

\u9019\u7cfb\u7d71\u7684\u904b\u4f5c\u662f\u5feb\u901f\u4e14\u7121\u610f\u8b58\u7684\u3002\u5b83\u4f9d\u8cf4\u65bc\u76f4\u89ba\u3001\u7d93\u9a57\u6cd5\u5247\u548c\u60c5\u611f\uff0c\u80fd\u5920\u8fc5\u901f\u505a\u51fa\u5224\u65b7\u548c\u6c7a\u7b56\u3002\u4f8b\u5982\uff0c\u95b1\u8b80\u6d77\u5831\u4e0a\u7684\u6587\u5b57\u3001\u8fa8\u8b58\u8072\u97f3\u3001\u6216\u5728\u719f\u6089\u7684\u74b0\u5883\u4e2d\u884c\u8d70\uff0c\u90fd\u5c6c\u65bc\u7cfb\u7d71\u4e00\u7684\u904b\u4f5c\u3002\u5b83\u7684\u512a\u9ede\u662f\u5feb\u901f\u4e14\u7bc0\u7701\u80fd\u91cf\uff0c\u4f46\u7f3a\u9ede\u662f\u5bb9\u6613\u7522\u751f\u504f\u898b\u548c\u932f\u8aa4\u3002<\/p>

.\u00a0 \u00a0\u7cfb\u7d712 (System 2)\uff1a\u6162\u60f3<\/strong><\/p>

\u9019\u7cfb\u7d71\u7684\u904b\u4f5c\u662f\u7de9\u6162\u3001\u5be9\u614e\u548c\u908f\u8f2f\u5316\u3002\u5b83\u64c5\u9577\u8907\u96dc\u7684\u904b\u7b97\u3001\u908f\u8f2f\u63a8\u7406\u548c\u89e3\u96e3\u3002\u4f8b\u5982\uff0c\u89e3\u6578\u5b78\u984c\u3001\u4e0b\u68cb\u3001\u6216\u5728\u64c1\u64e0\u7684\u4eba\u7fa4\u4e2d\u5c0b\u627e\u67d0\u4eba\uff0c\u90fd\u9700\u8981\u7cfb\u7d71\u4e8c\u7684\u53c3\u8207\u3002\u5b83\u7684\u512a\u9ede\u662f\u6e96\u78ba\u4e14\u53ef\u9760\uff0c\u4f46\u7f3a\u9ede\u662f\u7de9\u6162\u517c\u4e14\u6d88\u8017\u8a8d\u77e5\u8cc7\u6e90.
\u4eba\u985e\u7684\u5927\u8166\u5728\u7cfb\u7d71\u4e00\u548c\u7cfb\u7d71\u4e8c\u4e4b\u9593\u9748\u6d3b\u5207\u63db\uff0c\u4ee5\u61c9\u5c0d\u4e0d\u540c\u7684\u60c5\u5883\u3002\u5728\u65e5\u5e38\u751f\u6d3b\u4e2d\uff0c\u6211\u5011\u5927\u90e8\u5206\u6642\u9593(\u8d85\u904e95%)\u90fd\u4f9d\u8cf4\u7cfb\u7d71\u4e00\u7684\u5feb\u901f\u5224\u65b7\u3002\u53ea\u6709\u5728\u9047\u5230\u8907\u96dc\u6216\u4e0d\u719f\u6089\u7684\u554f\u984c\u6642\uff0c\u624d\u6703\u555f\u52d5\u7cfb\u7d71\u4e8c\u9032\u884c\u6df1\u5165\u601d\u8003\u3002
AI\u7684\u5feb\u8207\u6162\u601d\u8003\u6a21\u5f0f<\/p>

.\u00a0 \u00a0AI \u7684\u300c\u5feb\u601d\u300d<\/strong>
\u5927\u578b\u8a9e\u8a00\u6a21\u578b Large Language Model (LLM)\uff0c\u5982 ChatGPT (OpenAI) \u548c LIama (Meta) \u7684\u67d0\u4e9b\u7248\u672c\uff0c\u5728\u67d0\u7a2e\u7a0b\u5ea6\u4e0a\u53ef\u4ee5\u88ab\u8996\u70ba AI \u7684\u300c\u7cfb\u7d71\u4e00\u300d\u3002\u5b83\u5011\u900f\u904e\u5206\u6790\u5927\u91cf\u8cc7\u6599\u4e2d\u7684\u6a21\u5f0f\u4f86\u751f\u6210\u6587\u672c\u3001\u56de\u7b54\u554f\u984c\u548c\u57f7\u884c\u6307\u4ee4\u3002LLM \u7684\u512a\u9ede\u662f\u5feb\u901f\u4e14\u80fd\u5920\u8655\u7406\u5404\u7a2e\u4efb\u52d9\uff0c\u4f46\u7f3a\u9ede\u662f\u7f3a\u4e4f\u771f\u6b63\u7684\u7406\u89e3\u548c\u63a8\u7406\u80fd\u529b\uff0c\u5bb9\u6613\u7522\u751f \u300c\u5e7b\u89ba\u300d(hallucinations)\uff0c\u5373\u751f\u6210\u4e0d\u6b63\u78ba\u6216\u7121\u610f\u7fa9\u7684\u5167\u5bb9\uff0c\u4fd7\u7a31\u300c\u8001\u4f5c\u300d\u3002<\/p>

.\u00a0 \u00a0AI \u7684\u300c\u6162\u60f3\u300d<\/strong>
\u4ee5DeepSeek R1 \u9019\u500bLarge Reasoning Model (LRM) \u70ba\u4f8b\u3002\u5b83\u56de\u61c9\u6307\u4ee4\u9700\u6642\uff0c\u5148\u53bb\u7406\u89e3\u554f\u984c\u672c\u8eab\uff0c\u9032\u884c\u5fb9\u5e95\u8a55\u4f30\uff0c\u7136\u5f8c\u518d\u5c0b\u627e\u89e3\u6c7a\u554f\u984c\u7684\u65b9\u5f0f\u3002LRM \u5c08\u6ce8\u65bc\u8907\u96dc\u7684\u6578\u64da\u5206\u6790\u548c\u63a8\u7406\uff0c\u9019\u8207\u7cfb\u7d71\u4e8c\u601d\u7dad\u7684\u6df1\u601d\u719f\u616e\u548c\u5206\u6790\u6027\u8cea\u76f8\u7b26\u3002\u9664\u6b64\u4e4b\u5916\uff0cAI Agent \u7684\u6982\u5ff5\u4ea6\u4ee5\u300c\u6162\u60f3\u300d\u7684\u6a21\u5f0f\u53bb\u601d\u8003\u66f4\u63a5\u8fd1\u7cfb\u7d71\u4e8c\uff0c\u80fd\u5920\u81ea\u4e3b\u5b8c\u6210\u5206\u6790\u3001\u8a18\u61b6\u3001\u8a08\u756b\u548c\u57f7\u884c\u7b49\u6b65\u9a5f\uff0c\u7121\u9700\u4efb\u4f55\u4eba\u70ba\u5e72\u9810\uff0c\u4e86\u89e3\u6e05\u695a\u554f\u984c\u5f8c\u5f9e\u800c\u5efa\u8b70\u4e00\u7cfb\u5217\u7684\u884c\u52d5\u53bb\u5b8c\u6210\u4efb\u52d9\u3002<\/p>

\u4eba\u985e\u8207AI\u7684\u672a\u4f86\u5354\u4f5c<\/strong><\/h4>

\u5feb\u601d\u6162\u60f3\u7684\u7406\u8ad6\u8207\u4eba\u5de5\u667a\u80fd\u7684\u767c\u5c55\u5b58\u5728\u8457\u6709\u8da3\u7684\u95dc\u806f\uff0c\u7279\u5225\u662f\u6a5f\u5668\u5b78\u7fd2 (machine learning) \u548c\u6df1\u5ea6\u5b78\u7fd2 (deep learning)\uff0c\u6b63\u5728\u6a21\u64ec\u6216\u8d85\u8d8a\u4eba\u985e\u7684\u67d0\u4e9b\u601d\u7dad\u904e\u7a0b\uff0c\u4f7f\u6211\u5011\u6709\u5fc5\u8981\u601d\u8003\u4eba\u985e\u601d\u7dad\u7684\u5c40\u9650\u6027\u548cAI \u7684\u6f5b\u5728\u512a\u52e2\u3002\u7576\u5927\u5bb6\u5c0d\u5feb\u601d\u6162\u60f3\u7684\u6982\u5ff5\u6709\u57fa\u672c\u8a8d\u77e5\u5f8c\uff0c\u6211\u60f3\u518d\u5206\u4eab\u4ee5\u4e0b\u5e7e\u500b\u4eba\u985e\u8207AI\u4e4b\u9593\u7684\u6709\u8da3\u95dc\u4fc2:
1. \u601d\u7dad\u7cfb\u7d71<\/strong>
\u2022 \u4eba\u985e\u7684\u7cfb\u7d711 (\u5feb\u901f\u3001\u76f4\u89ba\u7684\u601d\u7dad) \u8207AI\u7684\u5373\u6642\u53cd\u61c9\u80fd\u529b\u76f8\u4f3c\u3002AI\u80fd\u8fc5\u901f\u8655\u7406\u5927\u91cf\u4fe1\u606f\u4e26\u505a\u51fa\u6c7a\u7b56\uff0c\u985e\u4f3c\u65bc\u4eba\u985e\u7684\u76f4\u89ba\u53cd\u61c9\u3002
\u2022 \u7cfb\u7d712 (\u7de9\u6162\u3001\u7406\u6027\u7684\u601d\u7dad) \u5247\u9700\u8981\u6df1\u5165\u5206\u6790\u548c\u8a08\u7b97\uff0c\u9019\u90e8\u5206\u8207AI\u5728\u9032\u884c\u8907\u96dc\u63a8\u7406\u548c\u5206\u6790\u6642\u7684\u80fd\u529b\u76f8\u7b26\u3002
2. \u6c7a\u7b56\u504f\u898b<\/strong>
\u2022 \u300a\u5feb\u601d\u6162\u60f3\u300b\u63ed\u793a\u4e86\u4eba\u985e\u5728\u6c7a\u7b56\u4e2d\u5e38\u898b\u7684\u504f\u898b\uff0c\u9019\u4e9b\u504f\u898b\u5728AI\u7684\u8a2d\u8a08\u548c\u904b\u4f5c\u4e2d\u4e5f\u9700\u8981\u8003\u616e\u3002\u4f8b\u5982\uff0cAI\u6a21\u578b\u53ef\u80fd\u6703\u53d7\u5230\u8a13\u7df4\u6578\u64da\u7684\u504f\u898b\u5f71\u97ff\uff0c\u5c0e\u81f4\u4e0d\u7406\u60f3\u7684\u6c7a\u7b56\u3002
3. \u4eba\u6a5f\u5354\u4f5c<\/strong>
\u2022 \u7406\u89e3\u4eba\u985e\u601d\u7dad\u7684\u5c40\u9650\u6027\u53ef\u4ee5\u5e6b\u52a9\u8a2d\u8a08\u66f4\u6709\u6548\u7684AI\u7cfb\u7d71\uff0c\u4fc3\u9032\u4eba\u6a5f\u5354\u4f5c\u3002\u4f8b\u5982\uff0cAI\u53ef\u4ee5\u5728\u9700\u8981\u5feb\u901f\u53cd\u61c9\u7684\u60c5\u5883\u4e2d\u8f14\u52a9\u4eba\u985e\uff0c\u800c\u4eba\u985e\u5247\u53ef\u4ee5\u5728\u9700\u8981\u6df1\u601d\u719f\u616e\u7684\u60c5\u5883\u4e2d\u767c\u63ee\u4f5c\u7528\u3002
4. \u589e\u5f37\u6c7a\u7b56\u8cea\u91cf<\/strong>
\u2022 AI\u53ef\u4ee5\u5e6b\u52a9\u4eba\u985e\u8b58\u5225\u548c\u514b\u670d\u8a8d\u77e5\u504f\u898b\uff0c\u5f9e\u800c\u63d0\u9ad8\u6c7a\u7b56\u8cea\u91cf\u3002\u901a\u904e\u7d50\u5408AI\u7684\u5206\u6790\u80fd\u529b\u548c\u4eba\u985e\u7684\u5275\u9020\u529b\uff0c\u53ef\u4ee5\u9054\u5230\u66f4\u512a\u7684\u6c7a\u7b56\u7d50\u679c\u3002<\/p>

\u300a\u5feb\u601d\u6162\u60f3\u300b\u63d0\u4f9b\u7684\u96d9\u7cfb\u7d71\u7406\u8ad6\uff0c\u70ba\u6211\u5011\u7406\u89e3 AI \u7684\u601d\u8003\u6a21\u5f0f\u63d0\u4f9b\u4e86\u4e00\u500b\u5be6\u7528\u7684\u6846\u67b6\u3002\u900f\u904e\u7406\u89e3 AI \u7684\u300c\u5feb\u300d\u8207\u300c\u6162\u300d\uff0c\u6211\u5011\u53ef\u4ee5\u66f4\u6709\u6548\u5730\u904b\u7528 AI \u5de5\u5177\u4e26\u8207 AI \u5354\u4f5c\uff0c\u5171\u540c\u958b\u5275 AI \u6642\u4ee3\u7684\u65b0\u7bc7\u7ae0\u3002 \u672a\u4f86\uff0c\u96a8\u8457 AI \u6280\u8853\u7684\u4e0d\u65b7\u767c\u5c55\uff0c\u6211\u5011\u671f\u5f85\u770b\u5230\u66f4\u591a\u7d50\u5408\u300c\u5feb\u601d\u300d\u548c\u300c\u6162\u60f3\u300d\u7684\u6df7\u5408 AI \u7cfb\u7d71\u51fa\u73fe\uff0c\u70ba\u4eba\u985e\u5e36\u4f86\u66f4\u5927\u7684\u798f\u7949\u3002<\/p>

\u00a0<\/p>

\u64b0\u6587\ufe30\u90ed\u5fb7\u5049\uff08Andy Kwok\uff09 \u6578\u64da\u53ca\u4eba\u5de5\u667a\u80fd\u7d20\u990a\u5354\u6703 (DALA) \u8cc7\u6df1\u5275\u6703\u6703\u54e1\u517c OpenCertHub \u5275\u8fa6\u4eba\u53ca\u884c\u653f\u7e3d\u88c1<\/em><\/p>

*\u6b64\u6587<\/span>\u7ae0<\/span>\u540c\u6642\u8f49\u8f09\u65bc\u4fe1\u5831EJTech\u7db2\u7ad9<\/span><\/em><\/strong><\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

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