Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the betterdocs domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /data/user/htdocs/wp-includes/functions.php on line 6114

Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the jnews-view-counter domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /data/user/htdocs/wp-includes/functions.php on line 6114

Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the wp-statistics domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /data/user/htdocs/wp-includes/functions.php on line 6114

Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the wpdiscuz domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /data/user/htdocs/wp-includes/functions.php on line 6114

Notice: 函数 _load_textdomain_just_in_time 的调用方法不正确。 jnews 域的翻译加载触发过早。这通常表示插件或主题中的某些代码运行过早。翻译应在 init 操作或之后加载。 请查阅调试 WordPress来获取更多信息。 （这个消息是在 6.7.0 版本添加的。） in /data/user/htdocs/wp-includes/functions.php on line 6114

Notice: 函数 _load_textdomain_just_in_time 的调用方法不正确。 jnews-like 域的翻译加载触发过早。这通常表示插件或主题中的某些代码运行过早。翻译应在 init 操作或之后加载。 请查阅调试 WordPress来获取更多信息。 （这个消息是在 6.7.0 版本添加的。） in /data/user/htdocs/wp-includes/functions.php on line 6114

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{"id":35166,"date":"2024-10-17T23:26:19","date_gmt":"2024-10-17T15:26:19","guid":{"rendered":"https:\/\/linguaresources.com\/?p=35166"},"modified":"2024-10-17T23:26:19","modified_gmt":"2024-10-17T15:26:19","slug":"%e7%bf%bb%e8%af%91%e5%ad%a6%e4%b9%a0-100%e4%b8%aa%e5%b8%b8%e8%a7%81ai%e5%90%8d%e8%af%8d%ef%bc%88%e9%99%84%e5%b8%a6%e8%a7%a3%e9%87%8a%ef%bc%8c%e4%b8%8b%e7%af%87%ef%bc%89","status":"publish","type":"post","link":"https:\/\/linguaresources.com\/?p=35166","title":{"rendered":"\u7ffb\u8bd1\u5b66\u4e60 | 100\u4e2a\u5e38\u89c1AI\u540d\u8bcd\uff08\u9644\u5e26\u89e3\u91ca\uff0c\u4e0b\u7bc7\uff09"},"content":{"rendered":"

\u7ffb\u8bd1\u5b66\u4e60 | 100\u4e2a\u5e38\u89c1AI\u540d\u8bcd\uff08\u9644\u5e26\u89e3\u91ca\uff0c\u4e0b\u7bc7\uff09<\/strong><\/h1>\n

<\/a>\u7ffb\u8bd1\u6280\u672f\u6559\u80b2\u4e0e\u7814\u7a76<\/span>\u00a02024\u5e7410\u670817\u65e5 00:03<\/em>\u00a0\u9655\u897f<\/span><\/em><\/span><\/p>\n

\u4ee5\u4e0b\u6587\u7ae0\u6765\u6e90\u4e8e\u7f51\u4e8b\u968f\u8a00<\/span>\u00a0\uff0c\u4f5c\u8005\u7f51\u4e8b\u968f\u8a00<\/span><\/p>\n

\"\"<\/span>\u7f51\u4e8b\u968f\u8a00<\/strong>.<\/span><\/a><\/p>\n

\u5728\u7e41\u5fd9\u7684\u7f51\u7edc\u4e16\u754c\u4e2d\uff0c\u6211\u4eec\u6bcf\u5929\u90fd\u88ab\u65e0\u6570\u4fe1\u606f\u5305\u56f4\u3002\u4ece\u793e\u4f1a\u70ed\u70b9\u5230\u5a31\u4e50\u516b\u5366\uff0c\u4ece\u79d1\u6280\u53d1\u5c55\u5230\u751f\u6d3b\u7410\u4e8b\uff0c\u8fd9\u4e9b\u201c\u7f51\u4e8b\u201d\u6784\u6210\u4e86\u6211\u4eec\u65e5\u5e38\u751f\u6d3b\u7684\u91cd\u8981\u7ec4\u6210\u90e8\u5206\u3002<\/p>\n

 <\/p>\n

\"\"<\/p>\n

51. \u7a00\u758f\u7f16\u7801\uff08Sparse Coding\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u7a00\u758f\u7f16\u7801\u662f\u4e00\u79cd\u65e0\u76d1\u7763\u5b66\u4e60\u65b9\u6cd5\uff0c\u65e8\u5728\u627e\u5230\u8f93\u5165\u6570\u636e\u7684\u7a00\u758f\u8868\u793a\u3002\u7a00\u758f\u8868\u793a\u4e2d\u7684\u5927\u591a\u6570\u5143\u7d20\u4e3a\u96f6\u6216\u63a5\u8fd1\u96f6\uff0c\u53ea\u6709\u5c11\u6570\u5143\u7d20\u5177\u6709\u663e\u8457\u503c\u3002\u8fd9\u79cd\u8868\u793a\u65b9\u6cd5\u53ef\u4ee5\u63d0\u9ad8\u6570\u636e\u7684\u53ef\u89e3\u91ca\u6027\u548c\u538b\u7f29\u6548\u7387\u3002
<\/span><\/p>\n

52. \u56fe\u795e\u7ecf\u7f51\u7edc\uff08Graph Neural Networks, GNNs\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1aGNNs\u662f\u4e00\u79cd\u7528\u4e8e\u5904\u7406\u56fe\u5f62\u6570\u636e\u7684\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\u3002\u5b83\u4eec\u901a\u8fc7\u9012\u5f52\u5730\u805a\u5408\u90bb\u5c45\u8282\u70b9\u7684\u4fe1\u606f\u6765\u66f4\u65b0\u8282\u70b9\u7684\u8868\u793a\uff0c\u4ece\u800c\u6355\u83b7\u56fe\u5f62\u4e2d\u7684\u7ed3\u6784\u548c\u5173\u7cfb\u3002
<\/span><\/p>\n

53. \u8fdb\u5316\u7b97\u6cd5\uff08Evolutionary Algorithms\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u8fdb\u5316\u7b97\u6cd5\u662f\u4e00\u7c7b\u6a21\u62df\u81ea\u7136\u9009\u62e9\u548c\u9057\u4f20\u5b66\u539f\u7406\u7684\u4f18\u5316\u7b97\u6cd5\u3002\u5b83\u4eec\u901a\u8fc7\u8fed\u4ee3\u5730\u9009\u62e9\u3001\u4ea4\u53c9\u548c\u53d8\u5f02\u5019\u9009\u89e3\u6765\u5bfb\u627e\u95ee\u9898\u7684\u6700\u4f18\u89e3\u3002
<\/span><\/p>\n

54. \u6a21\u7cca\u903b\u8f91\uff08<\/strong><\/span>Fuzzy Logic<\/strong><\/span>\uff09<\/strong><\/span><\/span><\/p>\n

\u89e3\u91ca\uff1a\u6a21\u7cca\u903b\u8f91\u662f\u4e00\u79cd\u5904\u7406\u4e0d\u7cbe\u786e\u548c\u6a21\u7cca\u4fe1\u606f\u7684\u903b\u8f91\u7cfb\u7edf\u3002\u5b83\u5141\u8bb8\u4f7f\u7528<\/span>\u96b6\u5c5e\u5ea6\u51fd\u6570<\/span>\u6765\u63cf\u8ff0\u4e8b\u7269\u5c5e\u4e8e\u67d0\u4e2a\u7c7b\u522b\u7684\u7a0b\u5ea6\uff0c\u5e76\u63d0\u4f9b\u4e86\u4e0e\u4f20\u7edf\u4e8c\u503c\u903b\u8f91\u4e0d\u540c\u7684\u63a8\u7406\u65b9\u6cd5\u3002<\/span><\/span>
<\/span><\/p>\n

55. \u7fa4\u4f53\u667a\u80fd\uff08Swarm Intelligence\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u7fa4\u4f53\u667a\u80fd\u662f\u6307\u901a\u8fc7\u6a21\u62df\u81ea\u7136\u754c\u4e2d\u7fa4\u4f53\u884c\u4e3a\uff08\u5982\u6606\u866b\u3001\u9e1f\u7c7b\u7b49\uff09\u6765\u89e3\u51b3\u590d\u6742\u95ee\u9898\u7684\u6280\u672f\u3002\u5b83\u5229\u7528\u5927\u91cf\u7b80\u5355\u4e2a\u4f53\u4e4b\u95f4\u7684\u76f8\u4e92\u4f5c\u7528\u548c\u534f\u4f5c\u6765\u5b9e\u73b0\u5168\u5c40\u4f18\u5316\u548c\u51b3\u7b56\u3002
<\/span><\/p>\n

56. \u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff08Deep Learning Frameworks\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u662f\u4e13\u95e8\u7528\u4e8e\u6784\u5efa\u548c\u8bad\u7ec3\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7684\u8f6f\u4ef6\u5e93\u3002\u5e38\u89c1\u7684\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\u5305\u62ecTensorFlow\u3001PyTorch\u3001Keras\u3001Caffe\u7b49\u3002\u8fd9\u4e9b\u6846\u67b6\u63d0\u4f9b\u4e86\u9ad8\u7ea7\u7684API\u548c\u5de5\u5177\uff0c\u4f7f\u7814\u7a76\u4eba\u5458\u548c\u5f00\u53d1\u8005\u80fd\u591f\u66f4\u9ad8\u6548\u5730\u6784\u5efa\u548c\u90e8\u7f72\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u3002
<\/span><\/p>\n

57. \u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u63a2\u7d22\u4e0e\u5229\u7528\uff08Exploration vs. Exploitation\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5728\u5f3a\u5316\u5b66\u4e60\u4e2d\uff0c\u667a\u80fd\u4f53\u9700\u8981\u5728\u63a2\u7d22\u65b0\u73af\u5883\u548c\u5229\u7528\u5df2\u77e5\u4fe1\u606f\u4e4b\u95f4\u505a\u51fa\u6743\u8861\u3002\u63a2\u7d22\u610f\u5473\u7740\u5c1d\u8bd5\u65b0\u7684\u52a8\u4f5c\u4ee5\u83b7\u53d6\u66f4\u591a\u5173\u4e8e\u73af\u5883\u7684\u4fe1\u606f\uff0c\u800c\u5229\u7528\u5219\u662f\u6307\u6839\u636e\u5f53\u524d\u7684\u77e5\u8bc6\u9009\u62e9\u6700\u4f18\u52a8\u4f5c\u3002\u8fd9\u79cd\u6743\u8861\u662f\u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u4e00\u4e2a\u91cd\u8981\u6311\u6218\u3002
<\/span><\/p>\n

58. \u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u7684\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\uff08Named Entity Recognition, NER\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u662f\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u7684\u4e00\u4e2a\u4efb\u52a1\uff0c\u65e8\u5728\u4ece\u6587\u672c\u4e2d\u8bc6\u522b\u51fa\u5177\u6709\u7279\u5b9a\u610f\u4e49\u7684\u5b9e\u4f53\uff0c\u5982\u4eba\u540d\u3001\u5730\u540d\u3001\u7ec4\u7ec7\u540d\u7b49\u3002\u8fd9\u4e9b\u5b9e\u4f53\u5bf9\u4e8e\u7406\u89e3\u6587\u672c\u7684\u542b\u4e49\u548c\u4e0a\u4e0b\u6587\u81f3\u5173\u91cd\u8981\u3002
<\/span><\/p>\n

59. \u8bed\u4e49\u89d2\u8272\u6807\u6ce8\uff08Semantic Role Labeling, SRL\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u8bed\u4e49\u89d2\u8272\u6807\u6ce8\u662f\u4e00\u79cd\u5206\u6790\u53e5\u5b50\u4e2d\u8c13\u8bcd-\u8bba\u5143\u7ed3\u6784\u7684\u6280\u672f\u3002\u5b83\u8bc6\u522b\u53e5\u5b50\u4e2d\u7684\u8c13\u8bcd\uff08\u5982\u52a8\u8bcd\u3001\u5f62\u5bb9\u8bcd\u7b49\uff09\u4ee5\u53ca\u4e0e\u4e4b\u76f8\u5173\u7684\u8bba\u5143\uff08\u5982\u65bd\u4e8b\u3001\u53d7\u4e8b\u7b49\uff09\uff0c\u5e76\u6807\u6ce8\u5b83\u4eec\u4e4b\u95f4\u7684\u8bed\u4e49\u5173\u7cfb\u3002\u8fd9\u5bf9\u4e8e\u7406\u89e3\u53e5\u5b50\u7684\u6df1\u5c42\u542b\u4e49\u548c\u6784\u5efa\u81ea\u7136\u8bed\u8a00\u5904\u7406\u7cfb\u7edf\u81f3\u5173\u91cd\u8981\u3002
<\/span><\/p>\n

60. \u8bed\u97f3\u5408\u6210\uff08Speech Synthesis\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u8bed\u97f3\u5408\u6210\u662f\u5c06\u6587\u672c\u8f6c\u6362\u4e3a\u81ea\u7136\u3001\u6d41\u7545\u7684\u8bed\u97f3\u7684\u6280\u672f\u3002\u5b83\u6d89\u53ca\u6587\u672c\u5206\u6790\u3001\u58f0\u5b66\u5efa\u6a21\u548c\u8bed\u97f3\u751f\u6210\u7b49\u591a\u4e2a\u6b65\u9aa4\uff0c\u5e38\u7528\u4e8e\u8bed\u97f3\u52a9\u624b\u3001\u865a\u62df\u89d2\u8272\u7b49\u5e94\u7528\u4e2d\u3002
<\/span><\/p>\n

61. \u751f\u6210\u6a21\u578b\uff08Generative Models\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u751f\u6210\u6a21\u578b\u662f\u4e00\u7c7b\u80fd\u591f\u751f\u6210\u65b0\u6570\u636e\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002\u5b83\u4eec\u901a\u8fc7\u5b66\u4e60\u6570\u636e\u7684\u6982\u7387\u5206\u5e03\u6765\u751f\u6210\u4e0e\u539f\u59cb\u6570\u636e\u76f8\u4f3c\u7684\u65b0\u6837\u672c\u3002\u5e38\u89c1\u7684\u751f\u6210\u6a21\u578b\u5305\u62ecGANs\u3001\u81ea\u7f16\u7801\u5668\uff08Autoencoders\uff09\u3001\u53d8\u5206\u81ea\u7f16\u7801\u5668\uff08Variational Autoencoders\uff09\u7b49\u3002
<\/span><\/p>\n

62. \u5224\u522b\u6a21\u578b\uff08Discriminative Models\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5224\u522b\u6a21\u578b\u662f\u4e00\u7c7b\u76f4\u63a5\u5b66\u4e60\u8f93\u5165\u5230\u8f93\u51fa\u6620\u5c04\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002\u5b83\u4eec\u7684\u76ee\u6807\u662f\u5b66\u4e60\u4e00\u4e2a\u51b3\u7b56\u8fb9\u754c\u6216\u51fd\u6570\uff0c\u7528\u4e8e\u533a\u5206\u4e0d\u540c\u7c7b\u522b\u7684\u6570\u636e\u3002\u5e38\u89c1\u7684\u5224\u522b\u6a21\u578b\u5305\u62ec\u652f\u6301\u5411\u91cf\u673a\uff08SVMs\uff09\u3001\u903b\u8f91\u56de\u5f52\uff08Logistic Regression\uff09\u3001\u795e\u7ecf\u7f51\u7edc\u7b49\u3002
<\/span><\/p>\n

63. \u795e\u7ecf\u7f51\u7edc\u7684\u53ef\u89c6\u5316\uff08Neural Network Visualization\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u795e\u7ecf\u7f51\u7edc\u7684\u53ef\u89c6\u5316\u6280\u672f\u5141\u8bb8\u7814\u7a76\u4eba\u5458\u548c\u5f00\u53d1\u8005\u66f4\u76f4\u89c2\u5730\u7406\u89e3\u795e\u7ecf\u7f51\u7edc\u7684\u5185\u90e8\u7ed3\u6784\u548c\u51b3\u7b56\u8fc7\u7a0b\u3002\u8fd9\u4e9b\u6280\u672f\u53ef\u4ee5\u663e\u793a\u795e\u7ecf\u5143\u7684\u6fc0\u6d3b\u60c5\u51b5\u3001\u6743\u91cd\u5206\u5e03\u3001\u7279\u5f81\u6620\u5c04\u7b49\uff0c\u4ece\u800c\u5e2e\u52a9\u4eba\u4eec\u66f4\u597d\u5730\u7406\u89e3\u6a21\u578b\u7684\u5de5\u4f5c\u539f\u7406\u548c\u6027\u80fd\u3002
<\/span><\/p>\n

64. \u5f3a\u5316\u5b66\u4e60\u4e2d\u7684<\/strong><\/span>\u591a\u667a\u80fd\u4f53\u7cfb\u7edf<\/strong><\/span>\uff08Multi-Agent Systems\uff09<\/strong><\/span><\/span><\/p>\n

\u89e3\u91ca\uff1a\u591a\u667a\u80fd\u4f53\u7cfb\u7edf\u6d89\u53ca\u591a\u4e2a\u667a\u80fd\u4f53\uff08\u6216\u4ee3\u7406\uff09\u5728\u5171\u4eab\u73af\u5883\u4e2d\u8fdb\u884c\u4ea4\u4e92\u548c\u534f\u4f5c\u3002\u5728\u5f3a\u5316\u5b66\u4e60\u4e2d\uff0c\u591a\u667a\u80fd\u4f53\u7cfb\u7edf\u53ef\u4ee5\u6a21\u62df\u73b0\u5b9e\u4e16\u754c\u4e2d\u590d\u6742\u7684\u4ea4\u4e92\u573a\u666f\uff0c\u5e76\u7814\u7a76\u667a\u80fd\u4f53\u4e4b\u95f4\u7684\u5408\u4f5c\u3001\u7ade\u4e89\u548c\u534f\u8c03\u7b49\u884c\u4e3a\u3002
<\/span><\/p>\n

65. \u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u5c42\u6b21\u5316\u5b66\u4e60\uff08Hierarchical Learning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5c42\u6b21\u5316\u5b66\u4e60\u662f\u4e00\u79cd\u5c06\u590d\u6742\u4efb\u52a1\u5206\u89e3\u4e3a\u591a\u4e2a\u5b50\u4efb\u52a1\u6216\u5c42\u6b21\u7684\u65b9\u6cd5\u3002\u5728\u5f3a\u5316\u5b66\u4e60\u4e2d\uff0c\u5c42\u6b21\u5316\u5b66\u4e60\u53ef\u4ee5\u5e2e\u52a9\u667a\u80fd\u4f53\u66f4\u597d\u5730\u5904\u7406\u957f\u671f\u4f9d\u8d56\u548c\u590d\u6742\u7b56\u7565\uff0c\u4ece\u800c\u63d0\u9ad8\u5b66\u4e60\u6548\u7387\u548c\u6027\u80fd\u3002
<\/span><\/p>\n

66. \u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\uff08Deep Reinforcement Learning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u662f\u5c06\u6df1\u5ea6\u5b66\u4e60\u548c\u5f3a\u5316\u5b66\u4e60\u76f8\u7ed3\u5408\u7684\u6280\u672f\u3002\u5b83\u4f7f\u7528\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u6765\u903c\u8fd1\u503c\u51fd\u6570\u6216\u7b56\u7565\u51fd\u6570\uff0c\u5e76\u901a\u8fc7\u5f3a\u5316\u5b66\u4e60\u7b97\u6cd5\u6765\u4f18\u5316\u8fd9\u4e9b\u51fd\u6570\u3002\u6df1\u5ea6\u5f3a\u5316\u5b66\u4e60\u5728\u5904\u7406\u9ad8\u7ef4\u8f93\u5165\u548c\u590d\u6742\u51b3\u7b56\u95ee\u9898\u65f6\u8868\u73b0\u51fa\u8272\u3002
<\/span><\/p>\n

67. \u4eba\u5de5\u667a\u80fd\u4f26\u7406\uff08AI Ethics\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u4eba\u5de5\u667a\u80fd\u4f26\u7406\u662f\u7814\u7a76AI\u7cfb\u7edf\u5728\u8bbe\u8ba1\u3001\u5f00\u53d1\u3001\u90e8\u7f72\u548c\u4f7f\u7528\u8fc7\u7a0b\u4e2d\u6d89\u53ca\u7684\u9053\u5fb7\u548c\u4f26\u7406\u95ee\u9898\u7684\u9886\u57df\u3002\u5b83\u5173\u6ce8\u4e8e\u786e\u4fddAI\u7cfb\u7edf\u7684\u516c\u5e73\u6027\u3001\u900f\u660e\u6027\u3001\u53ef\u89e3\u91ca\u6027\u548c\u8d23\u4efb\u6027\uff0c\u4ee5\u53ca\u51cf\u8f7b\u6f5c\u5728\u7684\u8d1f\u9762\u5f71\u54cd\u3002
<\/span><\/p>\n

68. \u4eba\u5de5\u667a\u80fd\u5b89\u5168\uff08AI Security\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u4eba\u5de5\u667a\u80fd\u5b89\u5168\u662f\u7814\u7a76\u5982\u4f55\u4fdd\u62a4AI\u7cfb\u7edf\u514d\u53d7\u653b\u51fb\u548c\u6ee5\u7528\u7684\u9886\u57df\u3002\u5b83\u6d89\u53ca\u8bc6\u522b\u6f5c\u5728\u7684\u5a01\u80c1\u548c\u6f0f\u6d1e\uff0c\u5e76\u5f00\u53d1\u76f8\u5e94\u7684\u9632\u5fa1\u7b56\u7565\u548c\u5de5\u5177\uff0c\u4ee5\u786e\u4fddAI\u7cfb\u7edf\u7684\u53ef\u9760\u6027\u548c\u5b89\u5168\u6027\u3002
<\/span><\/p>\n

69. \u8fb9\u7f18\u8ba1\u7b97\uff08<\/strong><\/span>Edge Computing<\/strong><\/span>\uff09<\/strong><\/span><\/span><\/p>\n

\u89e3\u91ca\uff1a\u8fb9\u7f18\u8ba1\u7b97\u662f\u4e00\u79cd\u5c06\u8ba1\u7b97\u548c\u6570\u636e\u5b58\u50a8\u4efb\u52a1\u4ece\u4e2d\u5fc3\u5316\u7684\u6570\u636e\u4e2d\u5fc3\u8f6c\u79fb\u5230\u7f51\u7edc\u8fb9\u7f18\uff08\u5982\u8bbe\u5907\u3001\u4f20\u611f\u5668\u7b49\uff09\u7684\u6280\u672f\u3002\u5b83\u5141\u8bb8\u66f4\u5feb\u901f\u5730\u5904\u7406\u548c\u5206\u6790\u6570\u636e\uff0c\u51cf\u5c11\u5ef6\u8fdf\u548c\u5e26\u5bbd\u9700\u6c42\uff0c\u5e76\u63d0\u9ad8\u7cfb\u7edf\u7684\u54cd\u5e94\u6027\u548c\u6548\u7387\u3002
<\/span><\/p>\n

70. \u8054\u90a6\u5b66\u4e60\u4e2d\u7684\u9690\u79c1\u4fdd\u62a4\uff08Privacy-Preserving Federated Learning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u9690\u79c1\u4fdd\u62a4\u8054\u90a6\u5b66\u4e60\u662f\u4e00\u79cd\u5728\u4fdd\u62a4\u7528\u6237\u9690\u79c1\u7684\u540c\u65f6\u8fdb\u884c\u5206\u5e03\u5f0f\u5b66\u4e60\u7684\u6280\u672f\u3002\u5b83\u901a\u8fc7\u4f7f\u7528\u52a0\u5bc6\u3001\u5dee\u5206\u9690\u79c1\u7b49\u6280\u672f\u6765\u4fdd\u62a4\u7528\u6237\u6570\u636e\u4e0d\u88ab\u6cc4\u9732\u6216\u6ee5\u7528\uff0c\u540c\u65f6\u5141\u8bb8\u591a\u4e2a\u53c2\u4e0e\u8005\u534f\u4f5c\u8bad\u7ec3\u6a21\u578b\u3002
<\/span><\/p>\n

71. \u8fc1\u79fb\u5b66\u4e60\uff08Transfer Learning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u8fc1\u79fb\u5b66\u4e60\u662f\u4e00\u79cd\u673a\u5668\u5b66\u4e60\u6280\u672f\uff0c\u65e8\u5728\u5c06\u4ece\u6e90\u4efb\u52a1\uff08\u6216\u9886\u57df\uff09\u5b66\u5230\u7684\u77e5\u8bc6\u8fc1\u79fb\u5230\u76ee\u6807\u4efb\u52a1\uff08\u6216\u9886\u57df\uff09\u4e2d\u3002\u5b83\u53ef\u4ee5\u5e2e\u52a9\u6a21\u578b\u5728\u76ee\u6807\u4efb\u52a1\u4e0a\u66f4\u5feb\u5730\u5b66\u4e60\uff0c\u7279\u522b\u662f\u5728\u76ee\u6807\u4efb\u52a1\u6570\u636e\u6709\u9650\u6216\u6807\u6ce8\u56f0\u96be\u7684\u60c5\u51b5\u4e0b\u3002
<\/span><\/p>\n

72. \u81ea\u76d1\u7763\u5b66\u4e60\uff08Self-Supervised Learning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u81ea\u76d1\u7763\u5b66\u4e60\u662f\u4e00\u79cd\u7279\u6b8a\u7684\u65e0\u76d1\u7763\u5b66\u4e60\u65b9\u6cd5\uff0c\u5b83\u5229\u7528\u6570\u636e\u672c\u8eab\u7684\u7279\u6027\u6765\u751f\u6210\u76d1\u7763\u4fe1\u53f7\u3002\u4f8b\u5982\uff0c\u5728\u56fe\u50cf\u6570\u636e\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u9884\u6d4b\u56fe\u50cf\u7684\u4e0d\u540c\u53d8\u6362\uff08\u5982\u65cb\u8f6c\u3001\u7ffb\u8f6c\uff09\u6765\u8bad\u7ec3\u6a21\u578b\uff0c\u4ece\u800c\u5b66\u4e60\u5230\u6709\u7528\u7684\u7279\u5f81\u8868\u793a\u3002
<\/span><\/p>\n

73. \u8054\u90a6\u5b66\u4e60\uff08Federated Learning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u8054\u90a6\u5b66\u4e60\u662f\u4e00\u79cd\u5206\u5e03\u5f0f\u673a\u5668\u5b66\u4e60\u6280\u672f\uff0c\u5b83\u5141\u8bb8\u591a\u4e2a\u8bbe\u5907\u6216\u670d\u52a1\u5668\u5728\u672c\u5730\u8bad\u7ec3\u6a21\u578b\uff0c\u5e76\u901a\u8fc7\u805a\u5408\u672c\u5730\u6a21\u578b\u7684\u66f4\u65b0\u6765\u5171\u540c\u4f18\u5316\u5168\u5c40\u6a21\u578b\u3002\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5728\u4fdd\u62a4\u7528\u6237\u9690\u79c1\u7684\u540c\u65f6\u5b9e\u73b0\u5206\u5e03\u5f0f\u8ba1\u7b97\u7684\u4f18\u52bf\u3002
<\/span><\/p>\n

74. \u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u9006\u5f3a\u5316\u5b66\u4e60\uff08Inverse Reinforcement Learning, IRL\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u9006\u5f3a\u5316\u5b66\u4e60\u662f\u4e00\u79cd\u4ece\u89c2\u5bdf\u5230\u7684\u884c\u4e3a\u6570\u636e\u4e2d\u63a8\u65ad\u5956\u52b1\u51fd\u6570\u7684\u6280\u672f\u3002\u4e0e\u4f20\u7edf\u7684\u5f3a\u5316\u5b66\u4e60\u4e0d\u540c\uff0c\u9006\u5f3a\u5316\u5b66\u4e60\u4e0d\u9700\u8981\u663e\u5f0f\u5b9a\u4e49\u5956\u52b1\u51fd\u6570\uff0c\u800c\u662f\u901a\u8fc7\u89c2\u5bdf\u667a\u80fd\u4f53\u7684\u884c\u4e3a\u6765\u63a8\u65ad\u51fa\u53ef\u80fd\u7684\u5956\u52b1\u51fd\u6570\u3002
<\/span><\/p>\n

75. \u795e\u7ecf\u7f51\u7edc\u526a\u679d\uff08Neural Network Pruning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u795e\u7ecf\u7f51\u7edc\u526a\u679d\u662f\u4e00\u79cd\u51cf\u5c11\u795e\u7ecf\u7f51\u7edc\u5927\u5c0f\u548c\u590d\u6742\u6027\u7684\u6280\u672f\u3002\u5b83\u901a\u8fc7\u53bb\u9664\u7f51\u7edc\u4e2d\u4e0d\u91cd\u8981\u7684\u8fde\u63a5\u6216\u795e\u7ecf\u5143\u6765\u51cf\u5c11\u8ba1\u7b97\u91cf\u548c\u5b58\u50a8\u9700\u6c42\uff0c\u540c\u65f6\u4fdd\u6301\u6216\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u3002
<\/span><\/p>\n

76. \u6a21\u578b\u538b\u7f29\uff08Model Compression\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u6a21\u578b\u538b\u7f29\u662f\u4e00\u79cd\u51cf\u5c11\u673a\u5668\u5b66\u4e60\u6a21\u578b\u5927\u5c0f\u548c\u590d\u6742\u6027\u7684\u6280\u672f\uff0c\u4ee5\u4fbf\u5728\u8d44\u6e90\u53d7\u9650\u7684\u8bbe\u5907\u4e0a\u90e8\u7f72\u6a21\u578b\u3002\u5b83\u53ef\u4ee5\u901a\u8fc7\u91cf\u5316\u3001\u526a\u679d\u3001\u84b8\u998f\u7b49\u6280\u672f\u6765\u5b9e\u73b0\u3002
<\/span><\/p>\n

77. \u6df1\u5ea6\u5b66\u4e60\u4e2d\u7684\u6fc0\u6d3b\u51fd\u6570\uff08Activation Functions\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u6fc0\u6d3b\u51fd\u6570\u662f\u795e\u7ecf\u7f51\u7edc\u4e2d\u7528\u4e8e\u5f15\u5165\u975e\u7ebf\u6027\u7279\u6027\u7684\u51fd\u6570\u3002\u5e38\u89c1\u7684\u6fc0\u6d3b\u51fd\u6570\u5305\u62ecSigmoid\u3001ReLU\uff08Rectified Linear Unit\uff09\u3001Tanh\u7b49\u3002\u8fd9\u4e9b\u51fd\u6570\u51b3\u5b9a\u4e86\u795e\u7ecf\u5143\u5bf9\u8f93\u5165\u4fe1\u53f7\u7684\u54cd\u5e94\u65b9\u5f0f\u3002
<\/span><\/p>\n

78. \u5bf9\u6297\u6837\u672c\uff08Adversarial Examples\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5bf9\u6297\u6837\u672c\u662f\u6545\u610f\u8bbe\u8ba1\u7528\u4e8e\u8bef\u5bfc\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u8f93\u5165\u6837\u672c\u3002\u5b83\u4eec\u901a\u8fc7\u6dfb\u52a0\u5fae\u5c0f\u7684\u6270\u52a8\u6765\u4f7f\u6a21\u578b\u4ea7\u751f\u9519\u8bef\u7684\u8f93\u51fa\uff0c\u63ed\u793a\u4e86\u673a\u5668\u5b66\u4e60\u6a21\u578b\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u7684\u8106\u5f31\u6027\u3002
<\/span><\/p>\n

79. \u751f\u6210\u5f0f\u5bf9\u6297\u7f51\u7edc\u4e2d\u7684\u6a21\u5f0f\u5d29\u6e83\uff08Mode Collapse\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u6a21\u5f0f\u5d29\u6e83\u662fGANs\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u53ef\u80fd\u51fa\u73b0\u7684\u4e00\u79cd\u95ee\u9898\uff0c\u5176\u4e2d\u751f\u6210\u5668\u53ea\u751f\u6210\u6709\u9650\u7684\u51e0\u79cd\u6837\u672c\uff0c\u800c\u5ffd\u7565\u4e86\u6570\u636e\u96c6\u4e2d\u7684\u5176\u4ed6\u6a21\u5f0f\u3002\u8fd9\u5bfc\u81f4\u751f\u6210\u7684\u6837\u672c\u7f3a\u4e4f\u591a\u6837\u6027\u3002
<\/span><\/p>\n

80. \u53ef\u89e3\u91ca\u6027AI\uff08Explainable AI, XAI\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u53ef\u89e3\u91ca\u6027AI\u65e8\u5728\u63d0\u9ad8\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u53ef\u89e3\u91ca\u6027\u548c\u900f\u660e\u5ea6\u3002\u5b83\u901a\u8fc7\u7814\u7a76\u6a21\u578b\u7684\u5de5\u4f5c\u673a\u5236\u3001\u53ef\u89c6\u5316\u6a21\u578b\u7684\u51b3\u7b56\u8fc7\u7a0b\u3001\u63d0\u4f9b\u6a21\u578b\u7684\u89e3\u91ca\u6027\u8f93\u51fa\u7b49\u65b9\u5f0f\uff0c\u5e2e\u52a9\u4eba\u4eec\u7406\u89e3\u6a21\u578b\u662f\u5982\u4f55\u505a\u51fa\u51b3\u7b56\u7684\u3002
<\/span><\/p>\n

81. \u5f31\u76d1\u7763\u5b66\u4e60\uff08Weakly Supervised Learning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5f31\u76d1\u7763\u5b66\u4e60\u662f\u4e00\u79cd\u4ecb\u4e8e\u65e0\u76d1\u7763\u548c\u5168\u76d1\u7763\u5b66\u4e60\u4e4b\u95f4\u7684\u5b66\u4e60\u65b9\u6cd5\u3002\u5b83\u4f7f\u7528\u6bd4\u5168\u76d1\u7763\u5b66\u4e60\u66f4\u5f31\u7684\u76d1\u7763\u4fe1\u53f7\uff08\u5982\u4e0d\u5b8c\u5168\u7684\u6807\u7b7e\u3001\u4e0d\u51c6\u786e\u7684\u6807\u7b7e\u7b49\uff09\u6765\u8bad\u7ec3\u6a21\u578b\u3002\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5728\u6807\u7b7e\u6570\u636e\u6709\u9650\u6216\u83b7\u53d6\u6210\u672c\u8f83\u9ad8\u7684\u60c5\u51b5\u4e0b\u4f7f\u7528\u3002
<\/span><\/p>\n

82. \u4e0a\u4e0b\u6587\u611f\u77e5\u8ba1\u7b97\uff08Context-Aware Computing\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u4e0a\u4e0b\u6587\u611f\u77e5\u8ba1\u7b97\u662f\u4e00\u79cd\u80fd\u591f\u611f\u77e5\u548c\u5229\u7528\u5468\u56f4\u73af\u5883\u4fe1\u606f\uff08\u5982\u4f4d\u7f6e\u3001\u65f6\u95f4\u3001\u7528\u6237\u72b6\u6001\u7b49\uff09\u7684\u8ba1\u7b97\u6280\u672f\u3002\u5b83\u53ef\u4ee5\u5e2e\u52a9\u7cfb\u7edf\u66f4\u597d\u5730\u7406\u89e3\u7528\u6237\u9700\u6c42\uff0c\u5e76\u63d0\u4f9b\u66f4\u667a\u80fd\u3001\u66f4\u4e2a\u6027\u5316\u7684\u670d\u52a1\u3002
<\/span><\/p>\n

83. \u60c5\u611f\u5206\u6790\uff08Sentiment Analysis\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u60c5\u611f\u5206\u6790\u662f\u4e00\u79cd\u81ea\u7136\u8bed\u8a00\u5904\u7406\u6280\u672f\uff0c\u7528\u4e8e\u81ea\u52a8\u8bc6\u522b\u548c\u5206\u7c7b\u6587\u672c\u4e2d\u7684\u60c5\u611f\u503e\u5411\uff08\u5982\u79ef\u6781\u3001\u6d88\u6781\u3001\u4e2d\u6027\u7b49\uff09\u3002\u5b83\u5728\u793e\u4ea4\u5a92\u4f53\u5206\u6790\u3001\u4ea7\u54c1\u8bc4\u8bba\u6316\u6398\u7b49\u9886\u57df\u6709\u5e7f\u6cdb\u5e94\u7528\u3002
<\/span><\/p>\n

84. \u95ee\u7b54\u7cfb\u7edf\uff08Question Answering Systems\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u95ee\u7b54\u7cfb\u7edf\u662f\u4e00\u79cd\u80fd\u591f\u81ea\u52a8\u56de\u7b54\u7528\u6237\u95ee\u9898\u7684\u7cfb\u7edf\u3002\u5b83\u4f7f\u7528\u81ea\u7136\u8bed\u8a00\u5904\u7406\u6280\u672f\u6765\u7406\u89e3\u7528\u6237\u7684\u95ee\u9898\uff0c\u5e76\u4ece\u77e5\u8bc6\u5e93\u3001\u6587\u6863\u6216\u5176\u4ed6\u4fe1\u606f\u6e90\u4e2d\u68c0\u7d22\u7b54\u6848\u3002\u95ee\u7b54\u7cfb\u7edf\u5728\u667a\u80fd\u52a9\u624b\u3001\u641c\u7d22\u5f15\u64ce\u7b49\u9886\u57df\u6709\u5e7f\u6cdb\u5e94\u7528\u3002
<\/span><\/p>\n

85. \u795e\u7ecf\u7f51\u7edc\u67b6\u6784\u641c\u7d22\uff08Neural Architecture Search, NAS\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\u641c\u7d22\u662f\u4e00\u79cd\u81ea\u52a8\u5316\u8bbe\u8ba1\u795e\u7ecf\u7f51\u7edc\u67b6\u6784\u7684\u6280\u672f\u3002\u5b83\u901a\u8fc7\u7b97\u6cd5\u6765\u641c\u7d22\u548c\u4f18\u5316\u7f51\u7edc\u7684\u7ed3\u6784\u548c\u53c2\u6570\uff0c\u4ee5\u627e\u5230\u6027\u80fd\u6700\u4f73\u7684\u6a21\u578b\u3002\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u8282\u7701\u624b\u52a8\u8bbe\u8ba1\u7f51\u7edc\u67b6\u6784\u7684\u65f6\u95f4\u548c\u7cbe\u529b\u3002
<\/span><\/p>\n

86. \u795e\u7ecf\u7b26\u53f7\u96c6\u6210\uff08Neuro-Symbolic Integration\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u795e\u7ecf\u7b26\u53f7\u96c6\u6210\u662f\u5c06\u795e\u7ecf\u7f51\u7edc\u548c\u7b26\u53f7\u63a8\u7406\u76f8\u7ed3\u5408\u7684\u6280\u672f\u3002\u5b83\u65e8\u5728\u7ed3\u5408\u4e24\u8005\u7684\u4f18\u52bf\uff0c\u4ee5\u540c\u65f6\u5904\u7406\u611f\u77e5\u548c\u63a8\u7406\u4efb\u52a1\u3002\u795e\u7ecf\u7b26\u53f7\u96c6\u6210\u5728\u590d\u6742\u51b3\u7b56\u3001\u63a8\u7406\u548c\u89e3\u91ca\u6027\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002
<\/span><\/p>\n

87. \u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u63a2\u7d22\u7b56\u7565\uff08Exploration Strategies\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5728\u5f3a\u5316\u5b66\u4e60\u4e2d\uff0c\u63a2\u7d22\u7b56\u7565\u5b9a\u4e49\u4e86\u667a\u80fd\u4f53\u5982\u4f55\u63a2\u7d22\u73af\u5883\u4ee5\u53d1\u73b0\u65b0\u7684\u7b56\u7565\u548c\u5956\u52b1\u3002\u5e38\u89c1\u7684\u63a2\u7d22\u7b56\u7565\u5305\u62ec\u03b5-\u8d2a\u5fc3\u7b56\u7565\u3001\u57fa\u4e8e\u4e0d\u786e\u5b9a\u6027\u7684\u63a2\u7d22\u3001\u57fa\u4e8e\u5185\u5728\u5956\u52b1\u7684\u63a2\u7d22\u7b49\u3002
<\/span><\/p>\n

88. \u5e8f\u5217\u751f\u6210\u6a21\u578b\uff08Sequence Generation Models\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5e8f\u5217\u751f\u6210\u6a21\u578b\u662f\u4e00\u7c7b\u80fd\u591f\u751f\u6210\u8fde\u7eed\u5e8f\u5217\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002\u5b83\u4eec\u901a\u5e38\u7528\u4e8e\u5904\u7406\u81ea\u7136\u8bed\u8a00\u6587\u672c\u3001\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u7b49\u3002\u5e38\u89c1\u7684\u5e8f\u5217\u751f\u6210\u6a21\u578b\u5305\u62ec\u5faa\u73af\u795e\u7ecf\u7f51\u7edc\uff08RNNs\uff09\u3001\u957f\u77ed\u65f6\u8bb0\u5fc6\u7f51\u7edc\uff08LSTMs\uff09\u3001Transformer\u7b49\u3002
<\/span><\/p>\n

89. \u795e\u7ecf\u98ce\u683c\u8fc1\u79fb\uff08Neural Style Transfer\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u795e\u7ecf\u98ce\u683c\u8fc1\u79fb\u662f\u4e00\u79cd\u4f7f\u7528\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u5c06\u4e00\u5e45\u56fe\u50cf\u7684\u98ce\u683c\u8fc1\u79fb\u5230\u53e6\u4e00\u5e45\u56fe\u50cf\u7684\u5185\u5bb9\u4e0a\u7684\u6280\u672f\u3002\u5b83\u901a\u5e38\u4f7f\u7528\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\uff08CNNs\uff09\u6765\u63d0\u53d6\u56fe\u50cf\u7684\u5185\u5bb9\u548c\u98ce\u683c\u7279\u5f81\uff0c\u5e76\u901a\u8fc7\u4f18\u5316\u7b97\u6cd5\u5c06\u4e24\u8005\u878d\u5408\u3002
<\/span><\/p>\n

90. \u5d4c\u5165\u8868\u793a\uff08Embedding Representations\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5d4c\u5165\u8868\u793a\u662f\u4e00\u79cd\u5c06\u79bb\u6563\u6570\u636e\uff08\u5982\u5355\u8bcd\u3001\u7528\u6237\u3001\u7269\u54c1\u7b49\uff09\u6620\u5c04\u5230\u8fde\u7eed\u5411\u91cf\u7a7a\u95f4\u4e2d\u7684\u6280\u672f\u3002\u5b83\u5141\u8bb8\u6211\u4eec\u5728\u8fde\u7eed\u7a7a\u95f4\u4e2d\u6bd4\u8f83\u548c\u64cd\u4f5c\u8fd9\u4e9b\u79bb\u6563\u6570\u636e\uff0c\u4ece\u800c\u63ed\u793a\u5b83\u4eec\u4e4b\u95f4\u7684\u6f5c\u5728\u5173\u7cfb\u548c\u76f8\u4f3c\u6027\u3002
<\/span><\/p>\n

91. \u6ce8\u610f\u529b\u673a\u5236\uff08Attention Mechanisms\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u6ce8\u610f\u529b\u673a\u5236\u662f\u4e00\u79cd\u5728\u795e\u7ecf\u7f51\u7edc\u4e2d\u6a21\u62df\u4eba\u7c7b\u6ce8\u610f\u529b\u5206\u914d\u7684\u6280\u672f\u3002\u5b83\u5141\u8bb8\u6a21\u578b\u5728\u5904\u7406\u8f93\u5165\u6570\u636e\u65f6\u4e13\u6ce8\u4e8e\u91cd\u8981\u7684\u90e8\u5206\uff0c\u4ece\u800c\u66f4\u6709\u6548\u5730\u63d0\u53d6\u4fe1\u606f\u3002\u6ce8\u610f\u529b\u673a\u5236\u5728\u81ea\u7136\u8bed\u8a00\u5904\u7406\u3001\u8ba1\u7b97\u673a\u89c6\u89c9\u7b49\u9886\u57df\u6709\u5e7f\u6cdb\u5e94\u7528\u3002
<\/span><\/p>\n

92. \u5bf9\u6297\u8bad\u7ec3\uff08Adversarial Training\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u5bf9\u6297\u8bad\u7ec3\u662f\u4e00\u79cd\u901a\u8fc7\u751f\u6210\u5bf9\u6297\u6837\u672c\u6765\u589e\u5f3a\u6a21\u578b\u9c81\u68d2\u6027\u7684\u6280\u672f\u3002\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\uff0c\u6a21\u578b\u4e0d\u4ec5\u88ab\u8bad\u7ec3\u6765\u8bc6\u522b\u539f\u59cb\u6837\u672c\uff0c\u8fd8\u88ab\u8bad\u7ec3\u6765\u8bc6\u522b\u7ecf\u8fc7\u5fae\u5c0f\u6270\u52a8\u7684\u5bf9\u6297\u6837\u672c\u3002\u8fd9\u79cd\u65b9\u6cd5\u53ef\u4ee5\u5e2e\u52a9\u6a21\u578b\u62b5\u5fa1\u5bf9\u6297\u653b\u51fb\u3002
<\/span><\/p>\n

93. \u81ea\u52a8\u5316\u673a\u5668\u5b66\u4e60\uff08Automated Machine Learning, AutoML\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u81ea\u52a8\u5316\u673a\u5668\u5b66\u4e60\u662f\u4e00\u79cd\u65e8\u5728\u81ea\u52a8\u5316\u673a\u5668\u5b66\u4e60\u6d41\u7a0b\u7684\u6280\u672f\u3002\u5b83\u4f7f\u7528\u7b97\u6cd5\u548c\u5de5\u5177\u6765\u81ea\u52a8\u9009\u62e9\u7b97\u6cd5\u3001\u8c03\u6574\u53c2\u6570\u3001\u8bc4\u4f30\u6a21\u578b\u7b49\uff0c\u4ee5\u51cf\u8f7b\u624b\u52a8\u914d\u7f6e\u548c\u8c03\u4f18\u7684\u8d1f\u62c5\u3002\u81ea\u52a8\u5316\u673a\u5668\u5b66\u4e60\u53ef\u4ee5\u52a0\u901f\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u5f00\u53d1\u548c\u90e8\u7f72\u3002
<\/span><\/p>\n

94. \u4ea4\u4e92\u5f0f\u673a\u5668\u5b66\u4e60\uff08Interactive Machine Learning, IML\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u4ea4\u4e92\u5f0f\u673a\u5668\u5b66\u4e60\u662f\u4e00\u79cd\u5141\u8bb8\u4eba\u7c7b\u4e0e\u673a\u5668\u5b66\u4e60\u6a21\u578b\u8fdb\u884c\u4ea4\u4e92\u548c\u534f\u4f5c\u7684\u6280\u672f\u3002\u5b83\u53ef\u4ee5\u901a\u8fc7\u63d0\u4f9b\u53cd\u9988\u3001\u7ea0\u6b63\u9519\u8bef\u3001\u6307\u5bfc\u6a21\u578b\u5b66\u4e60\u7b49\u65b9\u5f0f\u6765\u6539\u8fdb\u6a21\u578b\u7684\u6027\u80fd\u3002\u4ea4\u4e92\u5f0f\u673a\u5668\u5b66\u4e60\u53ef\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u51c6\u786e\u6027\u548c\u53ef\u9760\u6027\uff0c\u5e76\u4fc3\u8fdb\u4eba\u7c7b\u4e0eAI\u4e4b\u95f4\u7684\u5408\u4f5c\u3002
<\/span><\/p>\n

95. \u8bed\u4e49\u5206\u5272\uff08Semantic Segmentation\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u8bed\u4e49\u5206\u5272\u662f\u4e00\u79cd\u8ba1\u7b97\u673a\u89c6\u89c9\u4efb\u52a1\uff0c\u65e8\u5728\u5c06\u56fe\u50cf\u4e2d\u7684\u6bcf\u4e2a\u50cf\u7d20\u5206\u7c7b\u4e3a\u4e0d\u540c\u7684\u8bed\u4e49\u7c7b\u522b\uff08\u5982\u5929\u7a7a\u3001\u5efa\u7b51\u3001\u8f66\u8f86\u7b49\uff09\u3002\u5b83\u5141\u8bb8\u6211\u4eec\u66f4\u6df1\u5165\u5730\u7406\u89e3\u56fe\u50cf\u7684\u5185\u5bb9\uff0c\u5e76\u4e3a\u5404\u79cd\u5e94\u7528\uff08\u5982\u81ea\u52a8\u9a7e\u9a76\u3001\u533b\u5b66\u5f71\u50cf\u5206\u6790\uff09\u63d0\u4f9b\u57fa\u7840\u3002
<\/span><\/p>\n

96. \u534f\u540c\u8fc7\u6ee4\uff08Collaborative Filtering\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u534f\u540c\u8fc7\u6ee4\u662f\u4e00\u79cd\u63a8\u8350\u7cfb\u7edf\u6280\u672f\uff0c\u5b83\u901a\u8fc7\u5206\u6790\u7528\u6237\u7684\u5386\u53f2\u884c\u4e3a\u548c\u504f\u597d\u6765\u63a8\u8350\u76f8\u4f3c\u6216\u76f8\u5173\u7684\u9879\u76ee\u3002\u534f\u540c\u8fc7\u6ee4\u57fa\u4e8e\u7528\u6237-\u9879\u76ee\u4e4b\u95f4\u7684\u4ea4\u4e92\u6570\u636e\uff08\u5982\u8bc4\u5206\u3001\u8d2d\u4e70\u8bb0\u5f55\u7b49\uff09\u6765\u6784\u5efa\u6a21\u578b\uff0c\u5e76\u9884\u6d4b\u7528\u6237\u5bf9\u65b0\u9879\u76ee\u7684\u5174\u8da3\u7a0b\u5ea6\u3002
<\/span><\/p>\n

97. \u6df1\u5ea6\u4f2a\u9020\uff08Deepfakes\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u6df1\u5ea6\u4f2a\u9020\u662f\u6307\u4f7f\u7528\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u6765\u751f\u6210\u9ad8\u5ea6\u903c\u771f\u7684\u865a\u5047\u56fe\u50cf\u3001\u89c6\u9891\u6216\u97f3\u9891\u7684\u6280\u672f\u3002\u5b83\u53ef\u4ee5\u901a\u8fc7\u66ff\u6362\u56fe\u50cf\u6216\u89c6\u9891\u4e2d\u7684\u76ee\u6807\u4eba\u7269\u3001\u6539\u53d8\u8bed\u97f3\u7b49\u65b9\u5f0f\u6765\u521b\u5efa\u865a\u5047\u7684\u5a92\u4f53\u5185\u5bb9\u3002\u6df1\u5ea6\u4f2a\u9020\u6280\u672f\u7684\u6ee5\u7528\u53ef\u80fd\u5f15\u53d1\u4f26\u7406\u548c\u6cd5\u5f8b\u95ee\u9898\u3002
<\/span><\/p>\n

98. \u56e0\u679c\u63a8\u7406\uff08Causal Reasoning\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u56e0\u679c\u63a8\u7406\u662f\u4e00\u79cd\u7814\u7a76\u56e0\u679c\u5173\u7cfb\u548c\u56e0\u679c\u6548\u5e94\u7684\u6280\u672f\u3002\u5b83\u65e8\u5728\u8bc6\u522b\u548c\u7406\u89e3\u4e0d\u540c\u4e8b\u4ef6\u4e4b\u95f4\u7684\u56e0\u679c\u5173\u7cfb\uff0c\u5e76\u9884\u6d4b\u5e72\u9884\u63aa\u65bd\u5bf9\u7ed3\u679c\u7684\u5f71\u54cd\u3002\u56e0\u679c\u63a8\u7406\u5728\u51b3\u7b56\u652f\u6301\u7cfb\u7edf\u3001\u793e\u4f1a\u79d1\u5b66\u3001\u533b\u5b66\u7b49\u9886\u57df\u6709\u91cd\u8981\u5e94\u7528\u3002
<\/span><\/p>\n

99. \u5f3a\u5316\u5b66\u4e60\u4e2d\u7684\u7b56\u7565\u68af\u5ea6\u65b9\u6cd5\uff08Policy Gradient Methods\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u7b56\u7565\u68af\u5ea6\u65b9\u6cd5\u662f\u4e00\u79cd\u5f3a\u5316\u5b66\u4e60\u6280\u672f\uff0c\u5b83\u76f4\u63a5\u5bf9\u7b56\u7565\uff08\u5373\u667a\u80fd\u4f53\u9009\u62e9\u52a8\u4f5c\u7684\u51fd\u6570\uff09\u8fdb\u884c\u53c2\u6570\u5316\uff0c\u5e76\u901a\u8fc7\u68af\u5ea6\u4e0a\u5347\u7b97\u6cd5\u6765\u4f18\u5316\u7b56\u7565\u53c2\u6570\uff0c\u4ee5\u6700\u5927\u5316\u671f\u671b\u7684\u7d2f\u79ef\u5956\u52b1\u3002\u8fd9\u79cd\u65b9\u6cd5\u5141\u8bb8\u667a\u80fd\u4f53\u5728\u8fde\u7eed\u52a8\u4f5c\u7a7a\u95f4\u6216\u9ad8\u7ef4\u52a8\u4f5c\u7a7a\u95f4\u4e2d\u8fdb\u884c\u5b66\u4e60\u3002
<\/span><\/p>\n

100. \u795e\u7ecf\u6e32\u67d3\uff08Neural Rendering\uff09<\/strong><\/span><\/p>\n

\u89e3\u91ca\uff1a\u795e\u7ecf\u6e32\u67d3\u662f\u4e00\u79cd\u4f7f\u7528\u795e\u7ecf\u7f51\u7edc\u6765\u6a21\u62df\u548c\u751f\u6210\u56fe\u50cf\u6216\u89c6\u9891\u7684\u6280\u672f\u3002\u5b83\u7ed3\u5408\u4e86\u8ba1\u7b97\u673a\u56fe\u5f62\u5b66\u548c\u6df1\u5ea6\u5b66\u4e60\u7684\u539f\u7406\uff0c\u53ef\u4ee5\u751f\u6210\u903c\u771f\u7684\u865a\u62df\u573a\u666f\u3001\u89d2\u8272\u52a8\u753b\u548c\u7279\u6548\u3002\u795e\u7ecf\u6e32\u67d3\u5728\u7535\u5f71\u5236\u4f5c\u3001\u6e38\u620f\u5f00\u53d1\u548c\u865a\u62df\u73b0\u5b9e\u7b49\u9886\u57df\u6709\u5e7f\u6cdb\u5e94\u7528\u3002
<\/span><\/p>\n

\u901a\u8fc7\u8fd9\u4e24\u7bc7\u6587\u7ae0\uff08\u4e0a\u7bc7\u6587\u7ae0\u94fe\u63a5\uff1ahttps:\/\/mp.weixin.qq.com\/s\/oH1oy95oAq411eNL0dW5qw\uff09\uff0c\u5e0c\u671b\u4f60\u80fd\u591f\u5bf9\u4eba\u5de5\u667a\u80fd\u9886\u57df\u7684\u57fa\u672c\u672f\u8bed\u548c\u6982\u5ff5\u6709\u4e00\u4e2a\u6e05\u6670\u7684\u7406\u89e3\u3002
<\/span><\/p>\n

\u00a0<\/span><\/p>\n

\u638c\u63e1\u8fd9\u4e9b\u77e5\u8bc6\u4e0d\u4ec5\u80fd\u63d0\u5347\u4f60\u7684\u4e13\u4e1a\u7d20\u517b\uff0c\u4e5f\u80fd\u5e2e\u52a9\u4f60\u5728\u672a\u6765\u7684\u5b66\u4e60\u548c\u5de5\u4f5c\u4e2d\u66f4\u52a0\u81ea\u5982\u5730\u5e94\u5bf9AI\u76f8\u5173\u7684\u6311\u6218\u3002<\/span><\/p>\n

\u5982\u679c\u4f60\u5bf9\u67d0\u4e9b\u540d\u8bcd\u6709\u66f4\u6df1\u5165\u7684\u5174\u8da3\uff0c\u5efa\u8bae\u8fdb\u4e00\u6b65\u67e5\u9605\u76f8\u5173\u8d44\u6599\uff0c\u6301\u7eed\u5b66\u4e60\u548c\u63a2\u7d22\u3002\u611f\u8c22\u4f60\u7684\u9605\u8bfb\uff0c\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\u3002<\/span><\/p>\n

\n
\n
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