{"id":1642,"date":"2026-03-06T00:00:21","date_gmt":"2026-03-05T16:00:21","guid":{"rendered":"https:\/\/cleardatascience.com\/?p=1642"},"modified":"2026-02-06T10:17:28","modified_gmt":"2026-02-06T02:17:28","slug":"edge-ai-revolution-deploying-intelligent-agents-on-iot-devices-for-real-time-innovation","status":"publish","type":"post","link":"https:\/\/cleardatascience.com\/zh-hant\/edge-ai-revolution-deploying-intelligent-agents-on-iot-devices-for-real-time-innovation\/","title":{"rendered":"\u908a\u7de3\u4eba\u5de5\u667a\u6167\u9769\u547d\uff1a\u5728\u7269\u806f\u7db2\u8a2d\u5099\u4e0a\u90e8\u7f72\u667a\u80fd\u4ee3\u7406\u4ee5\u5be6\u73fe\u5373\u6642\u5275\u65b0"},"content":{"rendered":"

 <\/p>\n

\"\"<\/p>\n

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 <\/p>\n

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\u70ba\u4ec0\u9ebc\u908a\u7de3\u4ee3\u7406\u9769\u547d\u6b63\u5728\u767c\u751f<\/strong><\/h2>\n

\u4e09\u80a1\u532f\u805a\u7684\u529b\u91cf\u6b63\u5728\u4fc3\u6210\u9019\u4e00\u5207\uff1a<\/p>\n

    \n
  1. \u786c\u9ad4\u6548\u7387\u98db\u8e8d\uff1a<\/strong>\u4f9d\u5faa CES 2026 \u7684\u8da8\u52e2\uff0c\u65b0\u7684\u5fae\u63a7\u5236\u5668\uff08MCU\uff09\u548c\u7cfb\u7d71\u55ae\u6676\u7247\uff08SoC\uff09\uff0c\u5982\u745e\u85a9\u7684<\/strong> RA8<\/strong> \u6216\u65b0\u4e00\u4ee3 ARM Ethos-U NPU<\/strong>\uff0c\u5c07\u5c08\u7528 AI \u52a0\u901f\u529f\u80fd\u6574\u5408\u9032\u4f4e\u529f\u8017\u8a2d\u8a08\u4e2d\u3002\u5b83\u5011\u53ef\u4ee5\u5728\u6beb\u74e6\u7d1a\u529f\u8017\u4e0b\u904b\u884c\u5341\u5104\u53c3\u6578\u6a21\u578b\uff0c\u6700\u7d42\u70ba\u88dd\u7f6e\u7aef\u63a8\u7406\u63d0\u4f9b\u5fc5\u8981\u7684\u904b\u7b97\u80fd\u529b\u3002<\/li>\n
  2. \u8d85\u5c0f\u578b\u5c08\u7528\u6a21\u578b\u7684\u5d1b\u8d77\uff1a<\/strong>\u958b\u6e90\u751f\u614b\u7cfb\u7d71\u6b63\u5728\u7522\u51fa\u5b8c\u7f8e\u9069\u7528\u65bc\u908a\u7de3\u8a08\u7b97\u7684\u6a21\u578b\u3002\u4e0d\u8981\u53ea\u60f3\u5230\u64c1\u6709 700 \u5104\u53c3\u6578\u7684\u5de8\u578b\u6a21\u578b\uff0c\u800c\u61c9\u95dc\u6ce8\u90a3\u4e9b\u4f4e\u65bc 10 \u5104\u53c3\u6578\u7684\u6a21\u578b\uff0c\u4f8b\u5982\u8c37\u6b4c\u7684<\/strong> Nano 2<\/strong>\u3001Meta <\/strong>\u7684 Llama 3.1 8B<\/strong>\uff08\u9ad8\u5ea6\u91cf\u5316\uff09\u6216 Ologn AI<\/strong> \u91dd\u5c0d\u611f\u6e2c\u5668\u6578\u64da\u5fae\u8abf\u7684\u5c08\u7528\u6a21\u578b\u3002\u9019\u4e9b\u6a21\u578b\u5c0f\u5230\u53ef\u4ee5\u76f4\u63a5\u8f09\u5165\u88dd\u7f6e\u5167\u5b58\uff0c\u537b\u80fd\u57f7\u884c\u8907\u96dc\u7684\u5206\u985e\u3001\u9810\u6e2c\u548c\u6c7a\u7b56\u4efb\u52d9\u3002<\/li>\n
  3. \u9650\u5236\u74b0\u5883\u4e2d\u80fd\u52d5\u6846\u67b6\u7684\u6210\u719f\uff1a<\/strong>\u8f15\u91cf\u7d1a\u3001\u57fa\u65bc Rust \u6216 C++ \u7684\u63a8\u7406\u904b\u884c\u6642\uff08\u5982 TensorFlow Lite Micro <\/strong>\u548c Apache TVM<\/strong>\uff09\u6b63\u5728\u8207\u6975\u7c21\u4ee3\u7406\u7de8\u6392\u908f\u8f2f\u6574\u5408\u3002\u9019\u5141\u8a31\u958b\u767c\u8005\u5728\u69cb\u5efa\u78ba\u5b9a\u6027\u7684\u300c\u5982\u679c-\u5247\u300d\u898f\u5247\u7684\u540c\u6642\uff0c\u7d50\u5408\u6982\u7387\u578b AI \u63a8\u7406\uff0c\u5f9e\u800c\u70ba\u4e0d\u53ef\u9810\u6e2c\u7684\u73fe\u5be6\u74b0\u5883\u5275\u5efa\u7a69\u5065\u7684\u6df7\u5408\u578b\u4ee3\u7406\u3002<\/li>\n<\/ol>\n

    \u908a\u7de3\u539f\u751f\u667a\u80fd\u4ee3\u7406\u67b6\u69cb\u8a2d\u8a08<\/strong><\/h2>\n

    \u5c07\u4ee3\u7406\u90e8\u7f72\u5230\u8cc7\u6e90\u53d7\u9650\u7684\u8a2d\u5099\u9700\u8981\u4e00\u7a2e\u8207\u4ee5\u96f2\u70ba\u4e2d\u5fc3\u7684\u8a2d\u8a08\u6839\u672c\u4e0d\u540c\u7684\u67b6\u69cb\u3002<\/p>\n

    \u908a\u7de3\u4eba\u5de5\u667a\u6167\u4ee3\u7406\u7684\u6838\u5fc3\u7d44\u4ef6\uff1a<\/strong><\/p>\n

      \n
    • \u672c\u5730\u611f\u5b98\u611f\u77e5\uff1a<\/strong>\u76f4\u63a5\u8207\u8a2d\u5099\u7684\u611f\u6e2c\u5668\uff08\u651d\u50cf\u982d\u3001\u52a0\u901f\u5ea6\u8a08\u3001\u71b1\u654f\u96fb\u963b\uff09\u6574\u5408\uff0c\u4ee5\u9032\u884c\u5373\u6642\u6578\u64da\u63a1\u96c6\u3002<\/li>\n
    • \u88dd\u7f6e\u7aef\u63a8\u7406\u5f15\u64ce\uff1a<\/strong>\u4e00\u500b\u91cf\u5316\u7684 SLM \u6216\u5fae\u578b Transformer \u6a21\u578b\uff0c\u80fd\u8655\u7406\u611f\u6e2c\u5668\u6578\u64da\uff0c\u4e26\u5c07\u5176\u8207\u5b58\u5132\u65bc\u672c\u5730\u8a18\u61b6\u7684\u6b77\u53f2\u6578\u64da\u9032\u884c\u60c5\u5883\u5316\uff0c\u7136\u5f8c\u57f7\u884c\u9810\u5148\u5b9a\u7fa9\u7684\u6c7a\u7b56\u6a39\u6216\u751f\u6210\u8a08\u5283\u3002<\/li>\n
    • \u8f15\u91cf\u7d1a\u884c\u52d5\u5354\u8abf\u5668\uff1a<\/strong>\u5fae\u578b\u7a0b\u5f0f\u78bc\uff0c\u5c07\u4ee3\u7406\u7684\u6c7a\u7b56\u8f49\u5316\u70ba\u5373\u6642\u884c\u52d5\u2014\u9a45\u52d5\u99ac\u9054\u3001\u8abf\u7bc0\u95a5\u9580\u3001\u9583\u720d\u8b66\u793a LED\uff0c\u6216\u900f\u904e\u672c\u5730\u7db2\u72c0\u7db2\u8def\uff08\u5982 Bluetooth LE \u6216 Thread\uff09\u5411\u9130\u8fd1\u8a2d\u5099\u50b3\u9001\u7c21\u6f54\u7684\u8b66\u793a\u5c01\u5305\u3002<\/li>\n
    • \u9078\u64c7\u6027\u96f2\u7aef\u540c\u6b65\uff1a<\/strong>\u4ee3\u7406\u5927\u90e8\u5206\u6642\u9593\uff0899%\uff09\u81ea\u884c\u904b\u4f5c\u3002\u5b83\u50c5\u5728\u9700\u8981\u5831\u544a\u5f59\u7e3d\u7684\u6d1e\u5bdf\u3001\u8acb\u6c42\u6a21\u578b\u66f4\u65b0\uff0c\u6216\u5c07\u8d85\u51fa\u5176\u64cd\u4f5c\u53c3\u6578\u7684\u771f\u6b63\u7570\u5e38\u4e8b\u4ef6\u5347\u7d1a\u6642\uff0c\u624d\u8207\u96f2\u7aef\u9032\u884c\u901a\u8a0a\u3002<\/li>\n<\/ul>\n

      \u908a\u7de3\u4ee3\u7406\u958b\u767c\u7684\u958b\u6e90\u5806\u758a<\/strong><\/p>\n

      \u9019\u88e1\u7684\u5275\u65b0\u662f\u7531\u53ef\u7372\u5f97\u7684\u6a21\u7d44\u5316\u5de5\u5177\u63a8\u52d5\u7684\uff1a<\/p>\n

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      • \u6a21\u578b\u8a13\u7df4\u8207\u58d3\u7e2e\uff1a<\/strong>\u5f9e\u4e00\u500b\u5c0f\u578b\u57fa\u790e\u6a21\u578b\uff08\u4f8b\u5982 Phi-3-mini<\/strong>\uff09\u958b\u59cb\uff0c\u4f7f\u7528 PyTorch<\/strong> \u6216 JAX<\/strong> \u5728\u4f60\u7684\u7279\u5b9a\u611f\u6e2c\u5668\u6578\u64da\u4e0a\u9032\u884c\u5fae\u8abf\u3002\u7136\u5f8c\uff0c\u4f7f\u7528 GPTQ<\/strong> \u9032\u884c\u7a4d\u6975\u91cf\u5316\uff0c\u6216\u5c07\u5176\u8f49\u63db\u70ba\u908a\u7de3\u512a\u5316\u683c\u5f0f\uff0c\u5982 ONNX<\/strong> \u6216 TensorFlow Lite FlatBuffer<\/strong>\u3002<\/li>\n
      • \u57f7\u884c\u6642\u8207\u7de8\u6392\uff1a<\/strong>\u4f7f\u7528 TensorFlow Lite Micro<\/strong> \u6216 MLC-LLM Runtime<\/strong> \u90e8\u7f72\u6a21\u578b\uff0c\u9019\u4e9b\u90fd\u662f\u70ba\u5fae\u63a7\u5236\u5668\u8a2d\u8a08\u7684\u3002\u5c0d\u65bc\u4ee3\u7406\u908f\u8f2f\uff0c\u53ef\u4ee5\u7528 Rust \u6216 C \u7de8\u5beb\u4e00\u500b\u7c21\u7d04\u7684\u72c0\u614b\u6a5f\uff0c\u6216\u8005\u5728\u529f\u80fd\u8f03\u5f37\u7684\u786c\u9ad4\u4e0a\u4f7f\u7528\u985e\u4f3c MicroPython<\/strong> \u7684\u7cbe\u7c21\u6846\u67b6\u7248\u672c\u3002<\/li>\n
      • \u958b\u767c\u8207\u6a21\u64ec\uff1a<\/strong>\u4f7f\u7528 Edge Impulse<\/strong> \u6216 Qeexo<\/strong> \u7b49\u5e73\u53f0\uff0c\u5728\u90e8\u7f72\u5230\u5be6\u9ad4\u8a2d\u5099\u4e4b\u524d\uff0c\u5728\u865b\u64ec\u786c\u9ad4\u4e0a\u6a21\u64ec\u6574\u500b\u6d41\u7a0b\u2014\u2014\u6578\u64da\u6536\u96c6\u3001\u6a21\u578b\u8a13\u7df4\u548c\u90e8\u7f72\u2014\u2014\u53ef\u4ee5\u5927\u5e45\u52a0\u5feb\u539f\u578b\u8a2d\u8a08\u9031\u671f\u3002<\/li>\n<\/ul>\n

        \u5be6\u969b\u61c9\u7528\u6848\u4f8b\uff1a\u5f9e\u6548\u7387\u5230\u81ea\u4e3b<\/strong><\/p>\n

        \u9019\u5834\u9769\u547d\u89e3\u9396\u4e86\u4e4b\u524d\u53d7\u9650\u65bc\u5ef6\u9072\u3001\u983b\u5bec\u6216\u6210\u672c\u7684\u61c9\u7528\uff1a<\/p>\n

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        • \u91cd\u5de5\u696d\u9810\u6e2c\u6027\u7dad\u8b77\uff1a<\/strong>\u6e26\u8f2a\u6a5f\u4e0a\u7684\u632f\u52d5\u611f\u6e2c\u5668\u4e0d\u50c5\u50c5\u50b3\u9001\u539f\u59cb\u6578\u64da\u3002\u5176\u5167\u5efa\u4ee3\u7406\u6703\u5373\u6642\u5206\u6790\u983b\u7387\u6a21\u5f0f\uff0c\u8b58\u5225\u8ef8\u627f\u6545\u969c\u7684\u65e9\u671f\u7279\u5fb5\uff0c\u4e26\u7acb\u5373\u89f8\u767c\u5c40\u90e8\u505c\u6a5f\u7a0b\u5e8f\uff0c\u540c\u6642\u767c\u9001\u4e00\u689d\u9ad8\u512a\u5148\u7d1a\u7684\u7dad\u8b77\u8b66\u5831\u3002<\/li>\n
        • \u81ea\u4e3b\u8fb2\u696d\u7cfb\u7d71\uff1a<\/strong>\u4e00\u67b6\u7528\u65bc\u7530\u9593\u5075\u67e5\u7684\u7121\u4eba\u6a5f\u4e0d\u9700\u8981\u50b3\u8f38\u9ad8\u6e05\u8996\u983b\u3002\u5176\u908a\u7de3\u4ee3\u7406\u672c\u5730\u8655\u7406\u5f71\u50cf\uff0c\u4ee595%\u7684\u4fe1\u5fc3\u8b58\u5225\u5165\u4fb5\u96dc\u8349\u7684\u5340\u57df\uff0c\u4e26\u6307\u63ee\u7cbe\u6e96\u5674\u5634\u50c5\u5728\u9019\u4e9b\u5ea7\u6a19\u4e0a\u555f\u52d5\u2014\u2014\u6240\u6709\u9019\u4e9b\u90fd\u5728\u540c\u4e00\u6b21\u98db\u884c\u4e2d\u5b8c\u6210\uff0c\u4e14\u7121\u9700\u4efb\u4f55\u9023\u63a5<\/li>\n
        • \u667a\u80fd\u5efa\u7bc9\u7ba1\u7406\uff1a<\/strong>\u667a\u80fd\u5efa\u7bc9\u4e2d\u7684\u4f54\u7528\u611f\u6e2c\u5668\u4f7f\u7528\u5176\u4ee3\u7406\u5b78\u7fd2\u623f\u9593\u7684\u4f7f\u7528\u6a21\u5f0f\u3002\u5b83\u4e0d\u50c5\u50c5\u5831\u544a\u201c\u5075\u6e2c\u5230\u52d5\u4f5c\u201d\u3002\u5b83\u9084\u53ef\u4ee5\u9810\u6e2c\u623f\u9593\u4e0b\u4e00\u6b21\u88ab\u4f54\u7528\u7684\u6642\u9593\uff0c\u4e26\u900f\u904e\u4f4e\u529f\u8017\u7db2\u683c\u7db2\u8def\u8207\u672c\u5730\u6696\u901a\u7a7a\u8abf\u4ee3\u7406\u4e3b\u52d5\u5354\u5546\uff0c\u9810\u5148\u8abf\u7bc0\u623f\u9593\u74b0\u5883\uff0c\u4ee5\u512a\u5316\u8212\u9069\u5ea6\u548c\u80fd\u6e90\u6548\u7387\u3002<\/li>\n<\/ul>\n

          \u5be6\u65bd\u85cd\u5716<\/strong><\/h2>\n
            \n
          1. \u5b9a\u7fa9\u81ea\u4e3b\u5faa\u74b0\uff1a<\/strong>\u6e05\u695a\u95e1\u8ff0\u611f\u77e5-\u6c7a\u7b56-\u884c\u52d5\u7684\u5faa\u74b0\u3002\u9019\u500b\u88dd\u7f6e\u5fc5\u9808\u81ea\u884c\u505a\u51fa\u7684\u55ae\u4e00\u3001\u95dc\u9375\u6c7a\u7b56\u662f\u4ec0\u9ebc\uff1f\u5f9e\u4e00\u500b\u72f9\u7a84\u4f46\u9ad8\u50f9\u503c\u7684\u81ea\u4e3b\u76ee\u6a19\u958b\u59cb\u3002<\/li>\n
          2. \u00a0<\/strong>\u7121\u60c5\u5730\u5206\u6790\u9650\u5236\u689d\u4ef6\uff1a<\/strong>\u7e6a\u88fd\u786c\u6027\u9650\u5236\u5730\u5716\uff1a\u53ef\u7528\u7684 RAM\/ROM\u3001\u529f\u7387\u9810\u7b97\uff08\u96fb\u6c60\u6216\u6709\u7dda\uff09\u3001\u71b1\u8a2d\u8a08\u7bc4\u570d\uff0c\u4ee5\u53ca\u5ef6\u9072\u8981\u6c42\uff08\u5fae\u79d2\u7d1a vs \u6beb\u79d2\u7d1a\uff09\u3002<\/li>\n
          3. \u9078\u64c7\u6a21\u578b\u8207\u786c\u9ad4\u6642\u9700\u4e92\u76f8\u4f9d\u8cf4\uff1a<\/strong>\u5c07\u8655\u7406\u5668\u8207 AI \u6a21\u578b\u4f5c\u70ba\u4e00\u500b\u6574\u9ad4\u4f86\u9078\u64c7\u3002\u6a21\u578b\u5fc5\u9808\u7b26\u5408\u786c\u9ad4\u7684\u80fd\u529b\uff1b\u786c\u9ad4\u4e5f\u5fc5\u9808\u9054\u5230\u6a21\u578b\u5c0d\u5be6\u7528\u7cbe\u78ba\u5ea6\u7684\u6700\u4f4e\u9700\u6c42<\/li>\n
          4. \u63a1\u7528\u300c\u5c0f\u6a21\u578b\u8a13\u7df4\uff0c\u5168\u9762\u90e8\u7f72\u300d\u7684\u7406\u5ff5\uff1a<\/strong>\u5728\u96f2\u7aef\u958b\u767c\u4e26\u8a13\u7df4\u60a8\u7684\u5fae\u578b\u6a21\u578b\uff0c\u7136\u5f8c\u5c07\u5176\u4e00\u6a21\u4e00\u6a23\u5730\u90e8\u7f72\u5230\u6578\u5343\u500b\u908a\u7de3\u7bc0\u9ede\u4e0a\u3002\u4f7f\u7528\u806f\u5408\u5b78\u7fd2\u6280\u8853\uff0c\u5141\u8a31\u8a2d\u5099\u5728\u4e0d\u8f38\u51fa\u539f\u59cb\u6578\u64da\u7684\u60c5\u6cc1\u4e0b\u5354\u540c\u6539\u9032\u5171\u4eab\u6a21\u578b\u3002<\/li>\n<\/ol>\n

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