{"id":1650,"date":"2026-04-10T00:00:44","date_gmt":"2026-04-09T16:00:44","guid":{"rendered":"https:\/\/cleardatascience.com\/?p=1650"},"modified":"2026-02-06T10:23:15","modified_gmt":"2026-02-06T02:23:15","slug":"neuromorphic-computing-and-tinyml-next-gen-hardware-for-custom-edge-ai-agents","status":"publish","type":"post","link":"https:\/\/cleardatascience.com\/zh-hant\/neuromorphic-computing-and-tinyml-next-gen-hardware-for-custom-edge-ai-agents\/","title":{"rendered":"\u795e\u7d93\u5f62\u614b\u8a08\u7b97\u8207 TinyML\uff1a\u70ba\u81ea\u8a02\u908a\u7de3 AI \u4ee3\u7406\u6253\u9020\u7684\u6b21\u4e16\u4ee3\u786c\u9ad4"},"content":{"rendered":"

\"\"<\/p>\n

 <\/p>\n

 <\/p>\n

\u5c0d\u65bc\u5728\u908a\u7de3\u9818\u57df\u63a8\u52d5\u53ef\u80fd\u6027\u6975\u9650\u7684\u5275\u65b0\u8005\u4f86\u8aaa\uff0c\u4e00\u500b\u6839\u672c\u7684\u9650\u5236\u6b63\u8feb\u5728\u7709\u776b\uff1a\u99ae\u00b7\u8afe\u4f9d\u66fc\u67b6\u69cb\u3002\u50b3\u7d71\u8655\u7406\u5668\uff0c\u5373\u4f7f\u662f\u5c08\u9580\u7684\u4eba\u5de5\u667a\u6167\u52a0\u901f\u5668\uff0c\u4e5f\u5728\u5373\u6642\u3001\u611f\u6e2c\u9a45\u52d5\u7684\u61c9\u7528\u4e2d\u9054\u5230\u4e86\u6548\u7387\u7684\u7269\u7406\u6975\u9650\u3002\u5b83\u5011\u5728\u7368\u7acb\u7684\u8a18\u61b6\u9ad4\u8207\u904b\u7b97\u55ae\u5143\u4e4b\u9593\u50b3\u8f38\u6578\u64da\u6642\u6d6a\u8cbb\u4e86\u5927\u91cf\u80fd\u6e90\u2014\u2014\u5c0d\u65bc\u5fc5\u9808\u8655\u7406\u4e0d\u53ef\u9810\u6e2c\u611f\u6e2c\u6578\u64da\u6d41\u7684\u6301\u7e8c\u904b\u884c\u3001\u4f9d\u8cf4\u96fb\u6c60\u4f9b\u96fb\u7684\u8a2d\u5099\u800c\u8a00\uff0c\u9019\u662f\u4e00\u500b\u6bc0\u6ec5\u6027\u7684\u4f4e\u6548\u7387\u3002\u4e0b\u4e00\u6b65\u5b9a\u5236\u5316\u908a\u7de3\u4eba\u5de5\u667a\u6167\u7684\u98db\u8e8d\uff0c\u9700\u8981\u5f9e\u8a08\u7b97\u8f49\u5411\u6a21\u64ec<\/strong>\u7684\u7bc4\u5f0f\u8f49\u8b8a\uff0c\u5176\u9748\u611f\u76f4\u63a5\u4f86\u81ea\u6211\u5011\u6240\u77e5\u6548\u7387\u6700\u9ad8\u7684\u8655\u7406\u5668\uff1a\u751f\u7269\u5927\u8166\u3002<\/p>\n

\u9032\u5165\u985e\u8166\u8a08\u7b97\uff08Neuromorphic Computing<\/strong>\uff09\u8207 TinyML<\/strong> \u7684\u4ea4\u532f\u9ede\u3002\u985e\u8166\u6676\u7247\u662f\u6a21\u4eff\u5927\u8166\u795e\u7d93\u7d50\u69cb\u7684\u4e0b\u4e00\u4ee3\u786c\u9ad4\uff0c\u4f7f\u7528\u300c\u5c16\u5cf0\u795e\u7d93\u5143\u300d\u4ee5\u5927\u898f\u6a21\u5e73\u884c\u3001\u4e8b\u4ef6\u9a45\u52d5\u548c\u8d85\u4f4e\u529f\u8017\u7684\u65b9\u5f0f\u8655\u7406\u8cc7\u8a0a\u3002TinyML \u5247\u662f\u5c07\u6a5f\u5668\u5b78\u7fd2\u6a21\u578b\u90e8\u7f72\u5728\u5fae\u63a7\u5236\u5668\u548c\u8cc7\u6e90\u53d7\u9650\u8a2d\u5099\u4e0a\u7684\u5b78\u79d1\u3002\u5169\u8005\u7d50\u5408\uff0c\u5f62\u6210\u4e86\u4e00\u500b\u5b8c\u6574\u7684\u5806\u758a\uff0c\u70ba\u4e00\u985e\u5168\u65b0\u7684\u5b9a\u5236\u908a\u7de3\u667a\u80fd\u4ee3\u7406\u63d0\u4f9b\u57fa\u790e\uff0c\u9019\u4e9b\u4ee3\u7406\u80fd\u4ee5\u524d\u6240\u672a\u6709\u7684\u6548\u7387\u548c\u81ea\u4e3b\u6027\u611f\u77e5\u3001\u5b78\u7fd2\u4e26\u5728\u73fe\u5be6\u4e16\u754c\u4e2d\u884c\u52d5\u3002\u9019\u4e0d\u50c5\u50c5\u662f\u6f38\u9032\u5f0f\u7684\u6539\u9032\uff1b\u5b83\u662f\u65b0\u4e00\u6ce2\u667a\u80fd\u3001\u97ff\u61c9\u8fc5\u901f\u4e14\u53ef\u6301\u7e8c\u8a2d\u5099\u7684\u57fa\u790e\u3002<\/p>\n

\u5f9e\u6642\u9418\u9a45\u52d5\u5230\u4e8b\u4ef6\u9a45\u52d5\uff1a\u6838\u5fc3\u67b6\u69cb\u8f49\u8b8a<\/strong><\/h2>\n

\u8981\u4e86\u89e3\u6f5b\u529b\uff0c\u5fc5\u9808\u7406\u89e3\u9019\u4e9b\u7cfb\u7d71\u8655\u7406\u8cc7\u8a0a\u65b9\u5f0f\u7684\u6839\u672c\u5dee\u7570\u3002<\/p>\n

    \n
  • \u50b3\u7d71\u908a\u7de3 AI<\/strong>\uff08\u6642\u9418\u9a45\u52d5\uff09\uff1a<\/strong>CPU \u6216 GPU \u4ee5\u56fa\u5b9a\u7684\u6642\u9418\u9031\u671f\u904b\u4f5c\uff0c\u4e0d\u8ad6\u662f\u5426\u6709\u5be6\u8cea\u8b8a\u5316\uff0c\u90fd\u6703\u4e0d\u65b7\u8f2a\u8a62\u611f\u6e2c\u5668\u4e26\u6279\u6b21\u8655\u7406\u8cc7\u6599\u3002\u9019\u5c31\u50cf\u6574\u5929\u6bcf\u5206\u9418\u90fd\u53bb\u67e5\u770b\u90f5\u7bb1\u2014\u2014\u6548\u7387\u6975\u4f4e\u3002<\/li>\n
  • \u985e\u795e\u7d93\u5f62\u614b\u4eba\u5de5\u667a\u6167\uff08\u4e8b\u4ef6\u9a45\u52d5\uff09\uff1a<\/strong>\u985e\u795e\u7d93\u6676\u7247\u7684\u8a2d\u8a08\u9748\u611f\u4f86\u81ea\u5927\u8166\uff0c\u5b83\u5011\u6c92\u6709\u5168\u57df\u6642\u9418\u3002\u55ae\u500b\u4eba\u5de5\u300c\u795e\u7d93\u5143\u300d\u50c5\u5728\u6536\u5230\u5176\u4ed6\u795e\u7d93\u5143\u7684\u8a0a\u865f\u6642\u624d\u6703\u767c\u5c04\uff08\u6216\u300c\u5c16\u5cf0\u300d\uff09\u4e26\u6d88\u8017\u80fd\u91cf\uff0c\u985e\u4f3c\u65bc\u6211\u5011\u7684\u611f\u89ba\u795e\u7d93\u50c5\u6703\u5c0d\u8b8a\u5316\u4f5c\u51fa\u53cd\u61c9\u3002\u9019\u7a2e\u57fa\u65bc\u4e8b\u4ef6\u6216\u300c\u5c16\u5cf0\u300d\u7684\u795e\u7d93\u7db2\u7d61\uff08<\/strong>SNN<\/strong>\uff09<\/strong>\u67b6\u69cb\u672c\u8cea\u4e0a\u662f\u7a00\u758f\u4e14\u975e\u540c\u6b65\u7684\u3002<\/li>\n<\/ul>\n

    \u9019\u4e00\u8f49\u8b8a\u70ba\u81ea\u8a02\u908a\u7de3\u4ee3\u7406\u89e3\u9396\u4e86\u5169\u5927\u9769\u547d\u6027\u512a\u52e2\uff1a<\/p>\n

      \n
    1. \u8d85\u4f4e\u529f\u8017\uff1a<\/strong>\u50c5\u5728\u8655\u7406\u6709\u610f\u7fa9\u7684\u4e8b\u4ef6\u6642\u624d\u6d88\u8017\u96fb\u529b\u3002\u985e\u795e\u7d93\u6676\u7247\u5982\u82f1\u7279\u723e\u7684<\/strong> Loihi 2 <\/strong>\u6216 SynSense <\/strong>\u7684 Speck<\/strong> \u80fd\u4ee5\u6beb\u74e6\u751a\u81f3\u5fae\u74e6<\/strong>\u7d1a\u7684\u529f\u8017\u57f7\u884c\u8907\u96dc\u7684\u611f\u77e5\u4efb\u52d9\u2014\u2014\u6bd4\u50b3\u7d71 MCU \u4f4e\u6578\u500b\u6578\u91cf\u7d1a\uff0c\u5f9e\u800c\u5be6\u73fe\u6578\u5341\u5e74\u7684\u96fb\u6c60\u58fd\u547d\u6216\u80fd\u91cf\u6536\u96c6\u3002<\/li>\n
    2. \u539f\u751f\u5373\u6642\u8655\u7406\uff1a<\/strong>\u4e8b\u4ef6\u9a45\u52d5\u6a21\u578b\u6d88\u9664\u4e86\u5ef6\u9072\u3002\u4f8b\u5982\uff0c\u5728\u8996\u89ba\u611f\u6e2c\u5668\u4e2d\uff0c\u6bcf\u500b\u50cf\u7d20\u6703\u7368\u7acb\u4e14\u975e\u540c\u6b65\u5730\u50c5\u56de\u5831\u4eae\u5ea6\u8b8a\u5316\uff08\u5373\u300c\u4e8b\u4ef6\u6d41\u300d\uff09\u3002\u795e\u7d93\u5f62\u614b\u6676\u7247\u4e0a\u7684\u8108\u885d\u795e\u7d93\u7db2\u8def\uff08SNN\uff09\u53ef\u4ee5\u4ee5\u4e9e\u6beb\u79d2\u5ef6\u9072<\/strong>\u8655\u7406\u9019\u500b\u4e8b\u4ef6\u6d41\uff0c\u5be6\u73fe\u6846\u67b6\u5f0f\u7cfb\u7d71\u7121\u6cd5\u505a\u5230\u7684\u5373\u6642\u8ffd\u8e64\u8207\u6c7a\u7b56\u3002<\/li>\n<\/ol>\n

      \u958b\u6e90\u5275\u65b0\u5806\u758a\uff1aTinyML <\/strong>\u9047\u4e0a\u795e\u7d93\u5f62\u614b<\/strong><\/h2>\n

      \u9019\u4e00\u9818\u57df\u6b63\u53d7\u5230\u84ec\u52c3\u767c\u5c55\u7684\u958b\u6e90\u751f\u614b\u7cfb\u7d71\u63a8\u52d5\uff0c\u4f7f\u5176\u5c0d\u5148\u9a45\u8005\u800c\u8a00\u66f4\u6613\u63a5\u8fd1\u3002<\/p>\n

        \n
      • \u5275\u65b0\u8005\u7684\u786c\u9ad4\u5e73\u53f0\uff1a<\/strong>\n
          \n
        • Intel Loihi 2<\/strong>\uff1a<\/strong>\u4e00\u6b3e\u53ef\u900f\u904e Kapoho Point<\/strong> \u548c Nahuku<\/strong> \u7cfb\u7d71\u53d6\u5f97\u7684\u7814\u7a76\u6676\u7247\uff0c\u63d0\u4f9b 100 \u842c\u500b\u795e\u7d93\u5143\u4ee5\u7528\u65bc\u8907\u96dc SNN \u7684\u539f\u578b\u8a2d\u8a08\u3002<\/li>\n
        • SynSense Speck<\/strong>\uff1a<\/strong>\u4e00\u6b3e\u5b8c\u6574\u7684\u4f4e\u529f\u8017\u7cfb\u7d71\u55ae\u6676\u7247\uff0c\u5177\u6709\u52d5\u614b\u8996\u89ba\u611f\u6e2c\u5668\uff08DVS\uff09\u8f38\u5165\uff0c\u5c08\u70ba\u6301\u7e8c\u904b\u4f5c\u7684\u667a\u6167\u611f\u6e2c\u8a2d\u8a08\u3002<\/li>\n
        • BrainChip Akida<\/strong>\uff1a<\/strong>\u4e00\u6b3e\u5546\u7528\u7684\u795e\u7d93\u5f62\u614b\u77e5\u8b58\u7522\u6b0a\uff08IP\uff09\u8207 PCIe \u677f\uff0c\u5c08\u6ce8\u65bc\u70ba\u908a\u7de3\u61c9\u7528\u63d0\u4f9b\u9ad8\u6548\u7684\u7247\u4e0a\u5b78\u7fd2\u3002<\/li>\n<\/ul>\n<\/li>\n
        • \u8edf\u9ad4\u67b6\u69cb\u8207\u5de5\u5177\uff1a<\/strong>\n
            \n
          • Lava & NxTF<\/strong>\uff1a<\/strong>Intel \u63d0\u4f9b\u7684\u4e00\u500b\u958b\u6e90\u8edf\u9ad4\u6846\u67b6\uff0c\u7528\u65bc\u5728\u795e\u7d93\u5f62\u614b\u786c\u9ad4\u4e0a\u958b\u767c\u548c\u57f7\u884c\u61c9\u7528\u7a0b\u5f0f\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u500b\u57fa\u65bc Python \u7684\u751f\u614b\u7cfb\u7d71\uff0c\u7528\u65bc\u69cb\u5efa\u8108\u885d\u795e\u7d93\u7db2\u8def\uff08SNN\uff09\u3002<\/li>\n
          • SINABS<\/strong>\uff1a<\/strong>\u4e00\u500b\u57fa\u65bc PyTorch \u7684\u5eab\uff0c\u7528\u65bc\u69cb\u5efa\u548c\u8a13\u7df4\u8108\u885d\u795e\u7d93\u7db2\u8def\uff0c\u4f7f SNN \u7684\u958b\u767c\u5c0d\u6a5f\u5668\u5b78\u7fd2\u793e\u7fa4\u66f4\u70ba\u719f\u6089\u3002<\/li>\n
          • TinyML <\/strong>\u5de5\u5177\u93c8\uff1a<\/strong>\u50cf TensorFlow Lite for Microcontrollers<\/strong> \u9019\u6a23\u7684\u6a19\u6e96 TinyML \u6846\u67b6\uff0c\u958b\u59cb\u63a2\u7d22\u7528\u65bc\u795e\u7d93\u5f62\u614b\u786c\u9ad4\u7684\u5f8c\u7aef\uff0c\u5c07\u50b3\u7d71\u6a21\u578b\u8a13\u7df4\u8207\u65b0\u578b\u90e8\u7f72\u76ee\u6a19\u4e4b\u9593\u7684\u5dee\u8ddd\u6a4b\u63a5\u8d77\u4f86\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n

            \u6253\u9020\u81ea\u8a02\u795e\u7d93\u5f62\u614b TinyML <\/strong>\u4ee3\u7406\uff1a\u5be6\u7528\u6846\u67b6<\/strong><\/h2>\n

            \u70ba\u9019\u7a2e\u7bc4\u5f0f\u958b\u767c\u9700\u8981\u65b0\u7684\u5de5\u4f5c\u6d41\u7a0b\uff0c\u5c08\u6ce8\u65bc\u7a00\u758f\u3001\u4e8b\u4ef6\u9a45\u52d5\u7684\u6578\u64da\u4ee5\u53ca\u65b0\u7a4e\u7684\u6a21\u578b\u67b6\u69cb\u3002<\/p>\n

            \u7b2c\u4e00\u968e\u6bb5\uff1a\u554f\u984c\u9078\u64c7\u8207\u6578\u64da\u7372\u53d6<\/strong>
            \n\u7784\u6e96\u90a3\u4e9b\u5c0d\u8d85\u4f4e\u5ef6\u9072\u548c\u8d85\u4f4e\u529f\u8017\u6709\u7d55\u5c0d\u8981\u6c42\uff0c\u4e14\u6578\u64da\u672c\u8cea\u4e0a\u7a00\u758f\u4e14\u57fa\u65bc\u4e8b\u4ef6\u7684\u61c9\u7528\u3002<\/p>\n

              \n
            • \u5b8c\u7f8e\u4f7f\u7528\u6848\u4f8b\uff1a<\/strong>\u6a5f\u68b0\u632f\u52d5\u7684\u7cbe\u78ba\u7570\u5e38\u6aa2\u6e2c\u3001\u57fa\u65bc\u4e8b\u4ef6\u7684\u76f8\u6a5f\u7684\u5373\u6642\u624b\u52e2\u8b58\u5225\u3001\u5608\u96dc\u74b0\u5883\u4e2d\u7684\u6301\u7e8c\u95dc\u9375\u8a5e\u8b58\u5225\u3001\u6a5f\u5668\u4eba\u7684\u9810\u6e2c\u63a7\u5236\u3002<\/li>\n
            • \u611f\u6e2c\u5668\u878d\u5408\uff1a<\/strong>\u5c07\u4e8b\u4ef6\u578b\u611f\u6e2c\u5668\uff08\u4f8b\u5982 DVS \u76f8\u6a5f\u3001\u4e8b\u4ef6\u578b\u9ea5\u514b\u98a8\uff09\u76f4\u63a5\u8207\u795e\u7d93\u5f62\u614b\u6676\u7247\u914d\u5c0d\uff0c\u4ee5\u5efa\u7acb\u539f\u751f\u7684\u7aef\u5c0d\u7aef\u4e8b\u4ef6\u9a45\u52d5\u6d41\u7a0b\u3002<\/li>\n<\/ul>\n

              \u7b2c\u4e8c\u968e\u6bb5\uff1a\u6a21\u578b\u958b\u767c\u8207\u300c\u985e\u795e\u7d93\u5f62\u614b\u8f49\u63db\u300d<\/strong><\/p>\n

                \n
              1. \u8a13\u7df4\u6a19\u6e96\u6a21\u578b\uff08\u4eba\u5de5\u795e\u7d93\u7db2\u7d61\uff0cANN<\/strong>\uff09\uff1a<\/strong>\u9996\u5148\uff0c\u4f7f\u7528\u60a8\u7684\u4e8b\u4ef6\u578b\u8cc7\u6599\uff08\u8f49\u63db\u70ba\u5f71\u683c\u6216\u6642\u9593\u5e8f\u5217\uff09\u4f86\u958b\u767c\u9ad8\u6e96\u78ba\u7387\u7684\u50b3\u7d71\u4eba\u5de5\u795e\u7d93\u7db2\u7d61\uff08ANN\uff09\u3002<\/li>\n
              2. \u8f49\u63db\u70ba\u8108\u885d\u795e\u7d93\u7db2\u8def\uff08SNN<\/strong>\uff09\uff1a<\/strong>\u4f7f\u7528\u958b\u6e90\u8f49\u63db\u5de5\u5177\uff08\u5982 Nengo<\/strong> \u6216 SINABS<\/strong> \u51fd\u5f0f\u5eab\u4e2d\u7684\u5de5\u5177\uff09\u5c07\u8a13\u7df4\u597d\u7684\u4eba\u5de5\u795e\u7d93\u7db2\u8def\uff08ANN\uff09\u8f49\u63db\u70ba\u7bc0\u80fd\u7684\u8108\u885d\u795e\u7d93\u7db2\u8def\u3002\u6b64\u904e\u7a0b\u6d89\u53ca\u5c07 ANN \u7684\u6fc0\u6d3b\u503c\u6620\u5c04\u5230\u8108\u885d\u795e\u7d93\u5143\u7684\u767c\u706b\u7387\u3002<\/li>\n
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