{"id":74,"date":"2026-04-18T15:15:55","date_gmt":"2026-04-18T06:15:55","guid":{"rendered":"https:\/\/ai-cloud.kr\/?p=74"},"modified":"2026-04-18T15:19:33","modified_gmt":"2026-04-18T06:19:33","slug":"2026%eb%85%84-ai-%ed%8a%b8%eb%a0%8c%eb%93%9c-%ea%b1%b0%eb%8c%80%ed%95%a8-%eb%8c%80%ec%8b%a0-%ec%9e%91%ea%b3%a0-%eb%b9%a0%eb%a5%b8-%ec%97%a3%ec%a7%80-ai%ea%b0%80-%ec%98%a8%eb%8b%a4ai-trends-in-20","status":"publish","type":"post","link":"https:\/\/ai-cloud.kr\/?p=74","title":{"rendered":"2026\ub144 AI \ud2b8\ub80c\ub4dc: \uac70\ub300\ud568 \ub300\uc2e0 \uc791\uace0 \ube60\ub978 &#8216;\uc5e3\uc9c0 AI&#8217;\uac00 \uc628\ub2e4(AI Trends in 2026: Instead of Bigger, Smaller and Faster Edge AI Is Coming)"},"content":{"rendered":"<h2>2026\ub144 AI \ud2b8\ub80c\ub4dc, \uac70\ub300\ud568\uc5d0\uc11c &#8216;\uc791\uc74c&#8217;\uc73c\ub85c\uc758 \uc804\ud658<\/h2>\n<p>\uc778\uacf5\uc9c0\ub2a5(AI) \uae30\uc220\uc740 \ub208\ubd80\uc2e0 \uc18d\ub3c4\ub85c \ubc1c\uc804\ud558\uba70 \uc6b0\ub9ac \uc0b6\uc758 \uac70\uc758 \ubaa8\ub4e0 \uc601\uc5ed\uc5d0 \uae4a\uc219\uc774 \ud30c\uace0\ub4e4\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788 \ucd5c\uadfc \uba87 \ub144\uac04\uc740 GPT-3, GPT-4\uc640 \uac19\uc740 &#8216;\uac70\ub300 \uc5b8\uc5b4 \ubaa8\ub378(Large Language Model, LLM)&#8217;\uc758 \ub4f1\uc7a5\uc774 AI \ubc1c\uc804\uc758 \uc0c1\uc9d5\ucc98\ub7fc \uc5ec\uaca8\uc84c\uc2b5\ub2c8\ub2e4. \uc774 \ubaa8\ub378\ub4e4\uc740 \ubc29\ub300\ud55c \ub370\uc774\ud130\ub97c \ud559\uc2b5\ud558\uc5ec \ub180\ub77c\uc6b4 \uc218\uc900\uc758 \uc790\uc5f0\uc5b4 \uc774\ud574 \ubc0f \uc0dd\uc131 \ub2a5\ub825\uc744 \ubcf4\uc5ec\uc8fc\uc5c8\uc8e0. \ub9c8\uce58 \uc778\uac04\ucc98\ub7fc \ub300\ud654\ud558\uace0, \uae00\uc744 \uc4f0\uace0, \uc2ec\uc9c0\uc5b4 \ucf54\ub4dc\ub97c \uc9dc\uae30\ub3c4 \ud569\ub2c8\ub2e4.<\/p>\n<p>\ud558\uc9c0\ub9cc 2026\ub144\uc744 \uae30\uc810\uc73c\ub85c AI \ud2b8\ub80c\ub4dc\ub294 \uc0c8\ub85c\uc6b4 \uad6d\uba74\uc744 \ub9de\uc774\ud560 \uac83\uc73c\ub85c \uc608\uc0c1\ub429\ub2c8\ub2e4. \ubc14\ub85c &#8216;\uac70\ub300\ud568&#8217;\uc744 \ub118\uc5b4 &#8216;\uc791\uace0, \ube60\ub974\uace0, \uac00\uae4c\uc6b4&#8217; AI, \uc989 <strong>&#8216;\uc5e3\uc9c0 AI(Edge AI)&#8217;<\/strong>\uac00 \ud575\uc2ec\uc73c\ub85c \ub5a0\uc624\ub974\uace0 \uc788\ub2e4\ub294 \uc810\uc785\ub2c8\ub2e4. \uac70\ub300 AI \ubaa8\ub378\uc774 \ud074\ub77c\uc6b0\ub4dc \uae30\ubc18\uc73c\ub85c \ub9c9\ub300\ud55c \ucef4\ud4e8\ud305 \ud30c\uc6cc\ub97c \ud544\uc694\ub85c \ud558\ub294 \ubc18\uba74, \uc5e3\uc9c0 AI\ub294 \uae30\uae30 \uc790\uccb4 \ub610\ub294 \uadf8 \uac00\uae4c\uc6b4 \uacf3\uc5d0\uc11c \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud569\ub2c8\ub2e4. \uc65c \uc774\ub7f0 \ubcc0\ud654\uac00 \uc77c\uc5b4\ub098\uace0 \uc788\uc73c\uba70, \uc5e3\uc9c0 AI\ub294 \uc6b0\ub9ac\uc5d0\uac8c \uc5b4\ub5a4 \uc758\ubbf8\ub97c \uac00\uc9c8\uae4c\uc694?<\/p>\n<h3>\uac70\ub300 AI \ubaa8\ub378\uc758 \uc2dc\ub300, \uadf8\ub9ac\uace0 \uadf8 \ud55c\uacc4<\/h3>\n<p>\uac70\ub300 AI \ubaa8\ub378\uc740 \ubd84\uba85 \ud601\uc2e0\uc801\uc778 \ubc1c\uc804\uc744 \uac00\uc838\uc654\uc2b5\ub2c8\ub2e4. \uc218\ucc9c\uc5b5, \uc218\uc870 \uac1c\uc758 \ub9e4\uac1c\ubcc0\uc218(parameter)\ub97c \uac00\uc9c4 \uc774 \ubaa8\ub378\ub4e4\uc740 \uc778\ud130\ub137\uc5d0 \uc874\uc7ac\ud558\ub294 \uac70\uc758 \ubaa8\ub4e0 \ud14d\uc2a4\ud2b8\uc640 \uc774\ubbf8\uc9c0\ub97c \ud559\uc2b5\ud558\uba70 \uc778\uac04\uc758 \uc9c0\ub2a5\uc5d0 \uadfc\uc811\ud558\ub294 \ub2a5\ub825\uc744 \ubcf4\uc5ec\uc8fc\uc5c8\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ubaa8\ub378 \ub355\ubd84\uc5d0 \uc6b0\ub9ac\ub294 \uc774\uc804\uc5d0\ub294 \uc0c1\uc0c1\ud558\uae30 \uc5b4\ub824\uc6e0\ub358 \uc218\uc900\uc758 AI \uc11c\ube44\uc2a4\ub97c \uacbd\ud5d8\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc8e0.<\/p>\n<p>\ud558\uc9c0\ub9cc \uac70\ub300 AI \ubaa8\ub378\uc740 \uba87 \uac00\uc9c0 \uba85\ud655\ud55c \ud55c\uacc4\ub97c \uac00\uc9c0\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<ul>\n<li>\n<p><strong>\ub9c9\ub300\ud55c \ucef4\ud4e8\ud305 \uc790\uc6d0 \ubc0f \ube44\uc6a9:<\/strong> \uc774 \ubaa8\ub378\ub4e4\uc744 \ud6c8\ub828\uc2dc\ud0a4\uace0 \uc6b4\uc601\ud558\uae30 \uc704\ud574\uc11c\ub294 \uc5c4\uccad\ub09c \uc591\uc758 \ucef4\ud4e8\ud305 \ud30c\uc6cc\uac00 \ud544\uc694\ud569\ub2c8\ub2e4. \uc774\ub294 \uace7 \ub192\uc740 \uc5d0\ub108\uc9c0 \uc18c\ube44\uc640 \ub9c9\ub300\ud55c \ube44\uc6a9\uc73c\ub85c \uc774\uc5b4\uc9d1\ub2c8\ub2e4. \uc18c\uc218\uc758 \uac70\ub300 IT \uae30\uc5c5\ub9cc\uc774 \uc774\ub7ec\ud55c \uaddc\ubaa8\uc758 \ud22c\uc790\uac00 \uac00\ub2a5\ud558\uba70, \uc774\ub294 AI \uae30\uc220 \ubc1c\uc804\uc758 \ub3c5\uc810\uc744 \uc2ec\ud654\uc2dc\ud0ac \uc218 \uc788\ub2e4\ub294 \uc6b0\ub824\ub97c \ub0b3\uae30\ub3c4 \ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ub370\uc774\ud130 \uc804\uc1a1 \ubc0f \uc9c0\uc5f0 \ubb38\uc81c:<\/strong> \ub370\uc774\ud130\ub97c \ud074\ub77c\uc6b0\ub4dc\ub85c \ubcf4\ub0b4\uace0 \ucc98\ub9ac \uacb0\uacfc\ub97c \ub2e4\uc2dc \ubc1b\uc544\uc624\ub294 \uacfc\uc815\uc5d0\uc11c \ud544\uc5f0\uc801\uc73c\ub85c \uc9c0\uc5f0\uc774 \ubc1c\uc0dd\ud569\ub2c8\ub2e4. \uc2e4\uc2dc\uac04 \ubc18\uc751\uc774 \uc911\uc694\ud55c \uc11c\ube44\uc2a4(\uc608: \uc790\uc728\uc8fc\ud589, \uc2e4\uc2dc\uac04 \ud1b5\uc5ed)\uc5d0\uc11c\ub294 \uc774\ub7ec\ud55c \uc9c0\uc5f0\uc774 \uce58\uba85\uc801\uc778 \ubb38\uc81c\uac00 \ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \ubc0f \ubcf4\uc548:<\/strong> \ubaa8\ub4e0 \ub370\uc774\ud130\uac00 \uc911\uc559 \uc11c\ubc84\ub85c \uc804\uc1a1\ub418\uc5b4 \ucc98\ub9ac\ub418\ub294 \ubc29\uc2dd\uc740 \uac1c\uc778 \uc815\ubcf4 \uc720\ucd9c \ubc0f \ubcf4\uc548\uc5d0 \ub300\ud55c \uc6b0\ub824\ub97c \uc99d\ud3ed\uc2dc\ud0b5\ub2c8\ub2e4. \ubbfc\uac10\ud55c \uc815\ubcf4\uac00 \uc678\ubd80\ub85c \ub098\uac00\ub294 \uac83\uc5d0 \ub300\ud55c \ubd88\uc548\uac10\uc740 AI \ud65c\uc6a9\uc744 \ub9dd\uc124\uc774\uac8c \ud558\ub294 \uc694\uc778\uc774 \ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ud658\uacbd \ubb38\uc81c:<\/strong> \uac70\ub300 AI \ubaa8\ub378\uc744 \uc6b4\uc601\ud558\uae30 \uc704\ud55c \ub370\uc774\ud130 \uc13c\ud130\ub294 \uc5c4\uccad\ub09c \uc591\uc758 \uc804\ub825\uc744 \uc18c\ube44\ud558\uba70, \uc774\ub294 \ud0c4\uc18c \ubc30\ucd9c \uc99d\uac00\uc640 \ud658\uacbd \ubb38\uc81c\uc640 \uc9c1\uacb0\ub429\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<p>\uc774\ub7ec\ud55c \ud55c\uacc4\ub4e4\uc740 AI \uae30\uc220\uc774 \ub354\uc6b1 \ubcf4\ud3b8\ud654\ub418\uace0 \ub2e4\uc591\ud55c \ud658\uacbd\uc5d0 \uc801\uc6a9\ub418\uae30 \uc704\ud574\uc11c\ub294 \uc0c8\ub85c\uc6b4 \uc811\uadfc \ubc29\uc2dd\uc774 \ud544\uc694\ud568\uc744 \uc2dc\uc0ac\ud569\ub2c8\ub2e4.<\/p>\n<h3>\uc5e3\uc9c0 AI: &#8216;\uc791\uace0, \ube60\ub974\uace0, \uac00\uae4c\uc6b4&#8217; AI\uc758 \ub4f1\uc7a5<\/h3>\n<p>\uc774\ub7ec\ud55c \uac70\ub300 AI\uc758 \ud55c\uacc4\ub97c \uadf9\ubcf5\ud558\uae30 \uc704\ud55c \ub300\uc548\uc73c\ub85c \uc5e3\uc9c0 AI\uac00 \uc8fc\ubaa9\ubc1b\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc5e3\uc9c0 AI\ub294 \ub370\uc774\ud130\ub97c \uc911\uc559 \ud074\ub77c\uc6b0\ub4dc \uc11c\ubc84\ub85c \ubcf4\ub0b4\uc9c0 \uc54a\uace0, <strong>\ub370\uc774\ud130\uac00 \uc0dd\uc131\ub418\ub294 \uc7a5\uce58(\uc2a4\ub9c8\ud2b8\ud3f0, \uc6e8\uc5b4\ub7ec\ube14 \uae30\uae30, IoT \uc13c\uc11c, \uc790\ub3d9\ucc28 \ub4f1) \uc790\uccb4 \ub610\ub294 \ub124\ud2b8\uc6cc\ud06c \uac00\uc7a5\uc790\ub9ac(edge)\uc5d0 \uc788\ub294 \uc18c\uaddc\ubaa8 \uc11c\ubc84\uc5d0\uc11c \uc9c1\uc811 AI \uc5f0\uc0b0\uc744 \uc218\ud589\ud558\ub294 \uae30\uc220<\/strong>\uc744 \ub9d0\ud569\ub2c8\ub2e4.<\/p>\n<p>\uc27d\uac8c \ub9d0\ud574, &#8216;\ub1cc&#8217; \uc5ed\ud560\uc744 \ud558\ub294 AI\ub97c \uc911\uc559 \uc11c\ubc84\uc5d0\ub9cc \ub450\ub294 \uac83\uc774 \uc544\ub2c8\ub77c, &#8216;\ud314\ub2e4\ub9ac&#8217; \uc5ed\ud560\uc744 \ud558\ub294 \uac01 \uae30\uae30\uc5d0\ub3c4 \uc791\uace0 \ud6a8\uc728\uc801\uc778 &#8216;\ub1cc&#8217;\ub97c \ud0d1\uc7ac\ud558\ub294 \uac83\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n<h4>\uc5e3\uc9c0 AI\uc758 \ud575\uc2ec\uc801\uc778 \ud2b9\uc9d5<\/h4>\n<ol>\n<li>\n<p><strong>\uc18d\ub3c4 (Speed):<\/strong> \ub370\uc774\ud130\uac00 \uba3c \uac70\ub9ac\ub97c \uc774\ub3d9\ud558\uc9c0 \uc54a\uace0 \ubc14\ub85c \ucc98\ub9ac\ub418\ubbc0\ub85c \uc751\ub2f5 \uc18d\ub3c4\uac00 \ud68d\uae30\uc801\uc73c\ub85c \ube68\ub77c\uc9d1\ub2c8\ub2e4. \uc774\ub294 \uc2e4\uc2dc\uac04\uc131\uc774 \uc911\uc694\ud55c \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0 \ud544\uc218\uc801\uc785\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 (Privacy):<\/strong> \ubbfc\uac10\ud55c \uac1c\uc778 \ub370\uc774\ud130\uac00 \uc678\ubd80\ub85c \uc804\uc1a1\ub418\uc9c0 \uc54a\uace0 \uae30\uae30 \ub0b4\uc5d0\uc11c \ucc98\ub9ac\ub418\ubbc0\ub85c \uac1c\uc778 \uc815\ubcf4 \uc720\ucd9c \uc704\ud5d8\uc744 \ud06c\uac8c \uc904\uc77c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ud6a8\uc728\uc131 (Efficiency):<\/strong> \ud074\ub77c\uc6b0\ub4dc \ud1b5\uc2e0\uc5d0 \ud544\uc694\ud55c \ub300\uc5ed\ud3ed\uc744 \uc808\uc57d\ud558\uace0, \ub370\uc774\ud130 \uc804\uc1a1 \ubc0f \uc800\uc7a5 \ube44\uc6a9\uc744 \uc904\uc77c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub610\ud55c, \ud56d\uc0c1 \uc778\ud130\ub137 \uc5f0\uacb0\uc774 \ud544\uc694\ud55c \uac83\uc774 \uc544\ub2c8\ubbc0\ub85c \uc624\ud504\ub77c\uc778 \ud658\uacbd\uc5d0\uc11c\ub3c4 AI \uae30\ub2a5\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc2e0\ub8b0\uc131 (Reliability):<\/strong> \ub124\ud2b8\uc6cc\ud06c \uc5f0\uacb0\uc774 \ubd88\uc548\uc815\ud558\uac70\ub098 \ub04a\uc5b4\uc9c0\ub354\ub77c\ub3c4 \uae30\uae30 \uc790\uccb4\uc801\uc73c\ub85c AI \uae30\ub2a5\uc744 \uc218\ud589\ud560 \uc218 \uc788\uc5b4 \uc11c\ube44\uc2a4\uc758 \uc548\uc815\uc131\uc774 \ub192\uc544\uc9d1\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ub9de\ucda4\ud654 (Customization):<\/strong> \ud2b9\uc815 \uae30\uae30\ub098 \ud658\uacbd\uc5d0 \ucd5c\uc801\ud654\ub41c \uc791\uc740 AI \ubaa8\ub378\uc744 \uac1c\ubc1c\ud558\uc5ec \ud6a8\uc728\uc131\uc744 \uadf9\ub300\ud654\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ol>\n<h3>\uc5e3\uc9c0 AI\uac00 \uc8fc\ubaa9\ubc1b\ub294 \uc774\uc720<\/h3>\n<p>2026\ub144\uc744 \uae30\uc810\uc73c\ub85c \uc5e3\uc9c0 AI\uac00 \ub354\uc6b1 \ubd80\uc0c1\ud558\ub294 \ub370\uc5d0\ub294 \uc5ec\ub7ec \uac00\uc9c0 \uae30\uc220\uc801, \uc2dc\uc7a5\uc801 \uc694\uc778\uc774 \ubcf5\ud569\uc801\uc73c\ub85c \uc791\uc6a9\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h4>1. \ud558\ub4dc\uc6e8\uc5b4 \ubc1c\uc804: \ub354 \uc791\uace0 \uac15\ub825\ud574\uc9c4 AI \uce69<\/h4>\n<p>\uacfc\uac70\uc5d0\ub294 AI \uc5f0\uc0b0\uc744 \uc218\ud589\ud558\uae30 \uc704\ud574 \uace0\uc131\ub2a5 CPU\ub098 GPU\uac00 \ud544\uc218\uc801\uc774\uc5c8\uc2b5\ub2c8\ub2e4. \ud558\uc9c0\ub9cc \ucd5c\uadfc\uc5d0\ub294 <strong>AI \uc5f0\uc0b0\uc5d0 \ud2b9\ud654\ub41c \uc2e0\uacbd\ub9dd \ucc98\ub9ac \uc7a5\uce58(NPU, Neural Processing Unit)<\/strong>\uac00 \uc2a4\ub9c8\ud2b8\ud3f0, \ud0dc\ube14\ub9bf, \uc790\ub3d9\ucc28 \ub4f1 \ub2e4\uc591\ud55c \uae30\uae30\uc5d0 \ud0d1\uc7ac\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c NPU\ub294 \uae30\uc874 \uce69\ubcf4\ub2e4 \ud6e8\uc52c \uc801\uc740 \uc804\ub825\uc73c\ub85c \ub192\uc740 AI \ucc98\ub9ac \uc131\ub2a5\uc744 \uc81c\uacf5\ud558\uba70, \uc5e3\uc9c0 AI \uad6c\ud604\uc744 \uc704\ud55c \ud558\ub4dc\uc6e8\uc5b4\uc801 \uae30\ubc18\uc744 \ub9c8\ub828\ud588\uc2b5\ub2c8\ub2e4.<\/p>\n<p>\uc608\ub97c \ub4e4\uc5b4, \ucd5c\uc2e0 \uc2a4\ub9c8\ud2b8\ud3f0\uc5d0\ub294 \uc774\ubbf8 \uc0ac\ub78c\uc758 \uc5bc\uad74\uc744 \uc778\uc2dd\ud558\uac70\ub098 \uc0ac\uc9c4\uc744 \ubcf4\uc815\ud558\ub294 \ub4f1 \ub2e4\uc591\ud55c AI \uae30\ub2a5\uc744 \uae30\uae30 \uc790\uccb4\uc5d0\uc11c \ucc98\ub9ac\ud558\ub294 NPU\uac00 \ud0d1\uc7ac\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4. \uc790\ub3d9\ucc28\uc5d0\ub3c4 \ub9c8\ucc2c\uac00\uc9c0\ub85c \uc8fc\ud589 \ubcf4\uc870 \uc2dc\uc2a4\ud15c(ADAS)\uc774\ub098 \uc778\ud3ec\ud14c\uc778\uba3c\ud2b8 \uc2dc\uc2a4\ud15c\uc5d0 \uc5e3\uc9c0 AI \uce69\uc774 \uc801\uc6a9\ub418\uc5b4 \uc2e4\uc2dc\uac04\uc73c\ub85c \uc8fc\ubcc0 \ud658\uacbd\uc744 \uc778\uc2dd\ud558\uace0 \ubc18\uc751\ud569\ub2c8\ub2e4.<\/p>\n<h4>2. \uc18c\ud504\ud2b8\uc6e8\uc5b4 \ucd5c\uc801\ud654 \uae30\uc220\uc758 \ubc1c\uc804<\/h4>\n<p>AI \ubaa8\ub378\uc758 \ud06c\uae30\ub97c \uc904\uc774\uace0 \ud6a8\uc728\uc131\uc744 \ub192\uc774\ub294 <strong>&#8216;\ubaa8\ub378 \uacbd\ub7c9\ud654(Model Compression)&#8217; \uae30\uc220<\/strong> \uc5ed\uc2dc \uc5e3\uc9c0 AI \ud655\uc0b0\uc758 \uc911\uc694\ud55c \ub3d9\ub825\uc785\ub2c8\ub2e4.<\/p>\n<ul>\n<li>\n<p><strong>\uac00\uc9c0\uce58\uae30(Pruning):<\/strong> \ubaa8\ub378\uc5d0\uc11c \ubd88\ud544\uc694\ud558\uac70\ub098 \uc911\uc694\ub3c4\uac00 \ub0ae\uc740 \uc5f0\uacb0(\uac00\uc911\uce58)\uc744 \uc81c\uac70\ud558\uc5ec \ubaa8\ub378\uc758 \ud06c\uae30\ub97c \uc904\uc785\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc591\uc790\ud654(Quantization):<\/strong> \ubaa8\ub378\uc758 \uac00\uc911\uce58\ub97c \ud45c\ud604\ud558\ub294 \ub370 \uc0ac\uc6a9\ub418\ub294 \ube44\ud2b8 \uc218\ub97c \uc904\uc5ec(\uc608: 32\ube44\ud2b8 \ubd80\ub3d9\uc18c\uc218\uc810\uc5d0\uc11c 8\ube44\ud2b8 \uc815\uc218\ub85c) \ubaa8\ub378 \ud06c\uae30\ub97c \uc904\uc774\uace0 \uc5f0\uc0b0 \uc18d\ub3c4\ub97c \ub192\uc785\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc9c0\uc2dd \uc99d\ub958(Knowledge Distillation):<\/strong> \ud06c\uace0 \ubcf5\uc7a1\ud55c &#8216;\uad50\uc0ac \ubaa8\ub378&#8217;\uc758 \uc9c0\uc2dd\uc744 \uc791\uace0 \ud6a8\uc728\uc801\uc778 &#8216;\ud559\uc0dd \ubaa8\ub378&#8217;\uc5d0\uac8c \uc804\ub2ec\ud558\uc5ec, \uc131\ub2a5 \uc800\ud558\ub97c \ucd5c\uc18c\ud654\ud558\uba74\uc11c \ubaa8\ub378 \ud06c\uae30\ub97c \uc904\uc785\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<p>\uc774\ub7ec\ud55c \uae30\uc220 \ub355\ubd84\uc5d0 \uc774\uc804\uc5d0\ub294 \ub370\uc2a4\ud06c\ud1b1\uc774\ub098 \uc11c\ubc84\uc5d0\uc11c\ub9cc \uac00\ub2a5\ud588\ub358 \ubcf5\uc7a1\ud55c AI \ubaa8\ub378\uc744 \uc2a4\ub9c8\ud2b8\ud3f0\uc774\ub098 \uc18c\ud615 IoT \uc7a5\uce58\uc5d0\uc11c\ub3c4 \uc2e4\ud589\ud560 \uc218 \uc788\uac8c \ub418\uc5c8\uc2b5\ub2c8\ub2e4.<\/p>\n<h4>3. \ub370\uc774\ud130 \ud3ed\uc99d\uacfc \uc5f0\uacb0\uc131\uc758 \ud55c\uacc4<\/h4>\n<p>\uc0ac\ubb3c\uc778\ud130\ub137(IoT) \uae30\uae30\uc758 \ud655\uc0b0\uc73c\ub85c \uc778\ud574 \uc804 \uc138\uacc4\uc801\uc73c\ub85c \uc0dd\uc131\ub418\ub294 \ub370\uc774\ud130\uc758 \uc591\uc740 \uae30\ud558\uae09\uc218\uc801\uc73c\ub85c \uc99d\uac00\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ubc29\ub300\ud55c \ub370\uc774\ud130\ub97c \ubaa8\ub450 \uc911\uc559 \ud074\ub77c\uc6b0\ub4dc\ub85c \uc804\uc1a1\ud558\uc5ec \ucc98\ub9ac\ud558\ub294 \uac83\uc740 \ubb3c\ub9ac\uc801\uc73c\ub85c\ub098 \uacbd\uc81c\uc801\uc73c\ub85c \ud55c\uacc4\uac00 \uc788\uc2b5\ub2c8\ub2e4. \uc5e3\uc9c0 AI\ub294 \uac01 \uae30\uae30\uc5d0\uc11c \ud544\uc694\ud55c \ub370\uc774\ud130\ub97c \uc2a4\uc2a4\ub85c \ucc98\ub9ac\ud568\uc73c\ub85c\uc368 \ub370\uc774\ud130 \ucc98\ub9ac\uc758 \ubcd1\ubaa9 \ud604\uc0c1\uc744 \ud574\uc18c\ud558\uace0 \ud6a8\uc728\uc131\uc744 \ub192\uc785\ub2c8\ub2e4.<\/p>\n<p>\ub610\ud55c, \ubaa8\ub4e0 \uc9c0\uc5ed\uc5d0\uc11c \uc548\uc815\uc801\uc778 \uace0\uc18d \uc778\ud130\ub137 \uc5f0\uacb0\uc744 \ubcf4\uc7a5\ud558\uae30 \uc5b4\ub835\ub2e4\ub294 \uc810\ub3c4 \uc5e3\uc9c0 AI\uc758 \uc911\uc694\uc131\uc744 \ubd80\uac01\uc2dc\ud0b5\ub2c8\ub2e4. \uc5e3\uc9c0 AI\ub294 \uc778\ud130\ub137 \uc5f0\uacb0\uc774 \ubd88\uc548\uc815\ud558\uac70\ub098 \uc5c6\ub294 \ud658\uacbd\uc5d0\uc11c\ub3c4 AI \uae30\ub2a5\uc744 \uc720\uc9c0\ud560 \uc218 \uc788\uac8c \ud558\uc5ec \uc11c\ube44\uc2a4\uc758 \uc811\uadfc\uc131\uacfc \uc2e0\ub8b0\uc131\uc744 \ub192\uc785\ub2c8\ub2e4.<\/p>\n<h4>4. \uac15\ud654\ub418\ub294 \uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uaddc\uc81c<\/h4>\n<p>\uc804 \uc138\uacc4\uc801\uc73c\ub85c \uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638\uc5d0 \ub300\ud55c \uc778\uc2dd\uc774 \ub192\uc544\uc9c0\uace0 \uad00\ub828 \uaddc\uc81c\uac00 \uac15\ud654\ub418\uba74\uc11c, \ub370\uc774\ud130\uc758 \uc218\uc9d1, \uc800\uc7a5, \ucc98\ub9ac\uc5d0 \ub300\ud55c \uc81c\uc57d\uc774 \ub298\uc5b4\ub098\uace0 \uc788\uc2b5\ub2c8\ub2e4. \uc5e3\uc9c0 AI\ub294 \ubbfc\uac10\ud55c \uac1c\uc778 \ub370\uc774\ud130\ub97c \uae30\uae30 \uc678\ubd80\ub85c \uc804\uc1a1\ud558\uc9c0 \uc54a\uace0 \ucc98\ub9ac\ud558\ubbc0\ub85c, \uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uaddc\uc81c\ub97c \uc900\uc218\ud558\uba74\uc11c\ub3c4 AI \uc11c\ube44\uc2a4\ub97c \uc81c\uacf5\ud560 \uc218 \uc788\ub294 \ud6a8\uacfc\uc801\uc778 \ub300\uc548\uc774 \ub429\ub2c8\ub2e4.<\/p>\n<h3>\uc5e3\uc9c0 AI\uc758 \ub2e4\uc591\ud55c \ud65c\uc6a9 \uc0ac\ub840<\/h3>\n<p>\uc5e3\uc9c0 AI\ub294 \uc774\ubbf8 \uc6b0\ub9ac \uc0dd\ud65c \uacf3\uacf3\uc5d0\uc11c \ud65c\uc6a9\ub418\uace0 \uc788\uc73c\uba70, \uc55e\uc73c\ub85c \uadf8 \ubc94\uc704\ub294 \ub354\uc6b1 \ud655\ub300\ub420 \uac83\uc785\ub2c8\ub2e4.<\/p>\n<h4>1. \uc2a4\ub9c8\ud2b8\ud3f0 \ubc0f \ubaa8\ubc14\uc77c \uae30\uae30<\/h4>\n<ul>\n<li>\n<p><strong>\uc74c\uc131 \ube44\uc11c:<\/strong> \uc2a4\ub9c8\ud2b8\ud3f0\uc5d0\uc11c \uc9c1\uc811 \uc74c\uc131 \uba85\ub839\uc744 \uc778\uc2dd\ud558\uace0 \ucc98\ub9ac\ud558\uc5ec \uc751\ub2f5 \uc18d\ub3c4\ub97c \ub192\uc785\ub2c8\ub2e4. (\uc608: &#8220;Hey Google&#8221;, &#8220;Siri&#8221;)<\/p>\n<\/li>\n<li>\n<p><strong>\uce74\uba54\ub77c \uae30\ub2a5:<\/strong> \uc2e4\uc2dc\uac04 \uc7a5\uba74 \uc778\uc2dd, \uc790\ub3d9 \ucd08\uc810, \uc778\ubb3c \ubaa8\ub4dc, \uc774\ubbf8\uc9c0 \ubcf4\uc815 \ub4f1\uc744 \uae30\uae30 \uc790\uccb4\uc5d0\uc11c \ucc98\ub9ac\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc5bc\uad74 \uc778\uc2dd \uc7a0\uae08 \ud574\uc81c:<\/strong> \uce74\uba54\ub77c\ub85c \uc5bc\uad74\uc744 \uc778\uc2dd\ud558\uc5ec \uae30\uae30 \uc7a0\uae08\uc744 \ud574\uc81c\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc2e4\uc2dc\uac04 \ubc88\uc5ed:<\/strong> \uc778\ud130\ub137 \uc5f0\uacb0 \uc5c6\uc774\ub3c4 \ud14d\uc2a4\ud2b8\ub098 \uc74c\uc131\uc744 \uc2e4\uc2dc\uac04\uc73c\ub85c \ubc88\uc5ed\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uac74\uac15 \uad00\ub9ac:<\/strong> \uc6e8\uc5b4\ub7ec\ube14 \uae30\uae30\uc5d0\uc11c \uc2ec\ubc15\uc218, \ud65c\ub3d9\ub7c9 \ub4f1\uc744 \ubd84\uc11d\ud558\uc5ec \uac74\uac15 \uc0c1\ud0dc\ub97c \ubaa8\ub2c8\ud130\ub9c1\ud558\uace0 \uc774\uc0c1 \uc9d5\ud6c4\ub97c \uac10\uc9c0\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<h4>2. \uc790\ub3d9\ucc28 \uc0b0\uc5c5<\/h4>\n<ul>\n<li>\n<p><strong>\ucca8\ub2e8 \uc6b4\uc804\uc790 \ubcf4\uc870 \uc2dc\uc2a4\ud15c (ADAS):<\/strong> \ucc28\ub7c9 \uc8fc\ubcc0\uc758 \ubcf4\ud589\uc790, \ub2e4\ub978 \ucc28\ub7c9, \ucc28\uc120 \ub4f1\uc744 \uc2e4\uc2dc\uac04\uc73c\ub85c \uc778\uc2dd\ud558\uace0 \uacbd\uace0\ud558\uac70\ub098 \uc81c\uc5b4\ud569\ub2c8\ub2e4. (\uc608: \uc790\ub3d9 \uae34\uae09 \uc81c\ub3d9, \ucc28\uc120 \uc720\uc9c0 \ubcf4\uc870)<\/p>\n<\/li>\n<li>\n<p><strong>\uc790\uc728 \uc8fc\ud589:<\/strong> \uce74\uba54\ub77c, \ub808\uc774\ub354, \ub77c\uc774\ub2e4 \ub4f1 \ub2e4\uc591\ud55c \uc13c\uc11c \ub370\uc774\ud130\ub97c \uc2e4\uc2dc\uac04\uc73c\ub85c \ubd84\uc11d\ud558\uc5ec \ucc28\ub7c9\uc744 \uc2a4\uc2a4\ub85c \uc81c\uc5b4\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc6b4\uc804\uc790 \ubaa8\ub2c8\ud130\ub9c1:<\/strong> \uc6b4\uc804\uc790\uc758 \uc878\uc74c\uc774\ub098 \ubd80\uc8fc\uc758\ub97c \uac10\uc9c0\ud558\uc5ec \uacbd\uace0\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc778\ud3ec\ud14c\uc778\uba3c\ud2b8 \uc2dc\uc2a4\ud15c:<\/strong> \uc74c\uc131 \uba85\ub839\uc73c\ub85c \ucc28\ub7c9 \uae30\ub2a5\uc744 \uc81c\uc5b4\ud558\uac70\ub098 \uc5d4\ud130\ud14c\uc778\uba3c\ud2b8 \uc2dc\uc2a4\ud15c\uc744 \uc774\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<h4>3. \uc2a4\ub9c8\ud2b8 \ud648 \ubc0f IoT<\/h4>\n<ul>\n<li>\n<p><strong>\uc2a4\ub9c8\ud2b8 \uc2a4\ud53c\ucee4:<\/strong> \uc0ac\uc6a9\uc790\uc758 \uc74c\uc131 \uba85\ub839\uc744 \uc778\uc2dd\ud558\uace0 \ucc98\ub9ac\ud558\uc5ec \uc870\uba85, \uc628\ub3c4 \uc870\uc808, \uc74c\uc545 \uc7ac\uc0dd \ub4f1\uc744 \uc81c\uc5b4\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ubcf4\uc548 \uce74\uba54\ub77c:<\/strong> \uce68\uc785\uc790\ub97c \uac10\uc9c0\ud558\uace0 \ubd84\uc11d\ud558\uc5ec \uc0ac\uc6a9\uc790\uc5d0\uac8c \uc54c\ub9bc\uc744 \ubcf4\ub0c5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc2a4\ub9c8\ud2b8 \uac00\uc804:<\/strong> \uc0ac\uc6a9\uc790\uc758 \ud328\ud134\uc744 \ud559\uc2b5\ud558\uc5ec \uc790\ub3d9\uc73c\ub85c \uc791\ub3d9\ud558\uac70\ub098, \uc74c\uc131 \uba85\ub839\uc73c\ub85c \uc81c\uc5b4\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc0b0\uc5c5\uc6a9 IoT:<\/strong> \uacf5\uc7a5 \ub0b4 \uc124\ube44\uc758 \uc774\uc0c1 \uc9d5\ud6c4\ub97c \uc2e4\uc2dc\uac04\uc73c\ub85c \uac10\uc9c0\ud558\uc5ec \uc608\uc9c0 \ubcf4\uc804\uc744 \uc218\ud589\ud558\uace0, \uc0dd\uc0b0 \ud6a8\uc728\uc131\uc744 \ub192\uc785\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<h4>4. \uc758\ub8cc \ubd84\uc57c<\/h4>\n<ul>\n<li>\n<p><strong>\uc6e8\uc5b4\ub7ec\ube14 \uc758\ub8cc \uae30\uae30:<\/strong> \ud658\uc790\uc758 \uc0dd\uccb4 \uc2e0\ud638\ub97c \uc2e4\uc2dc\uac04\uc73c\ub85c \ubaa8\ub2c8\ud130\ub9c1\ud558\uace0 \uc774\uc0c1 \uc9d5\ud6c4\ub97c \uac10\uc9c0\ud558\uc5ec \uc758\ub8cc\uc9c4\uc5d0\uac8c \uc54c\ub9bd\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc758\ub8cc \uc601\uc0c1 \ubd84\uc11d:<\/strong> \uc18c\ud615 \uae30\uae30\uc5d0\uc11c\ub3c4 \uc758\ub8cc \uc601\uc0c1(X-ray, CT \ub4f1)\uc744 \ubd84\uc11d\ud558\uc5ec \uc9c8\ubcd1\uc744 \uc870\uae30\uc5d0 \uc9c4\ub2e8\ud558\ub294 \ub370 \ub3c4\uc6c0\uc744 \uc904 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc6d0\uaca9 \uc9c4\ub8cc:<\/strong> \ud658\uc790\uc758 \ub370\uc774\ud130\ub97c \ud604\uc7a5\uc5d0\uc11c \uc989\uc2dc \ubd84\uc11d\ud558\uc5ec \uc758\ub8cc\uc9c4\uc5d0\uac8c \uc804\ub2ec\ud568\uc73c\ub85c\uc368 \ud6a8\uc728\uc801\uc778 \uc9c4\ub8cc\ub97c \uc9c0\uc6d0\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<h4>5. \ub9ac\ud14c\uc77c \ubc0f \ubb3c\ub958<\/h4>\n<ul>\n<li>\n<p><strong>\uc2a4\ub9c8\ud2b8 \uacb0\uc81c:<\/strong> \ub9e4\uc7a5 \ub0b4 \uce74\uba54\ub77c\ub098 \uc13c\uc11c\ub97c \ud1b5\ud574 \uace0\uac1d\uc758 \ud589\ub3d9\uc744 \ubd84\uc11d\ud558\uace0, \ube44\uc811\ucd09 \uacb0\uc81c\ub97c \uc9c0\uc6d0\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc7ac\uace0 \uad00\ub9ac:<\/strong> \ub9e4\uc7a5 \ub0b4 \uc0c1\ud488\uc758 \uc7ac\uace0\ub97c \uc790\ub3d9\uc73c\ub85c \ud30c\uc545\ud558\uace0 \uad00\ub9ac\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ubb3c\ub958 \ucd5c\uc801\ud654:<\/strong> \ucc3d\uace0 \ub0b4 \ub85c\ubd07\uc774\ub098 \ub4dc\ub860\uc774 \uc2e4\uc2dc\uac04\uc73c\ub85c \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\uc5ec \ubb3c\ub958 \ub3d9\uc120\uc744 \ucd5c\uc801\ud654\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<h3>\uc5e3\uc9c0 AI\uc758 \uacfc\uc81c\uc640 \ubbf8\ub798 \uc804\ub9dd<\/h3>\n<p>\uc5e3\uc9c0 AI\ub294 \ubd84\uba85 \ub9ce\uc740 \uc7a5\uc810\uc744 \uac00\uc9c0\uace0 \uc788\uc9c0\ub9cc, \uc544\uc9c1 \ud574\uacb0\ud574\uc57c \ud560 \uacfc\uc81c\ub4e4\ub3c4 \uc874\uc7ac\ud569\ub2c8\ub2e4.<\/p>\n<ul>\n<li>\n<p><strong>\ubaa8\ub378\uc758 \uc131\ub2a5 \ud55c\uacc4:<\/strong> \uac70\ub300 AI \ubaa8\ub378\uc5d0 \ube44\ud574 \uc5e3\uc9c0 AI \ubaa8\ub378\uc740 \uc77c\ubc18\uc801\uc73c\ub85c \uc131\ub2a5\uc774 \uc81c\ud55c\uc801\uc77c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ubcf5\uc7a1\ud558\uace0 \uc815\uad50\ud55c \uc791\uc5c5\uc5d0\ub294 \uc5ec\uc804\ud788 \ud074\ub77c\uc6b0\ub4dc AI\uac00 \ud544\uc694\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ud558\ub4dc\uc6e8\uc5b4 \uc81c\uc57d:<\/strong> \uc18c\ud615 \uae30\uae30\uc5d0 \ud0d1\uc7ac\ub418\ub294 AI \uce69\uc740 \uc804\ub825 \uc18c\ubaa8 \ubc0f \ubc1c\uc5f4\uc5d0 \ub300\ud55c \uc81c\uc57d\uc774 \uc788\uc2b5\ub2c8\ub2e4. \uace0\uc131\ub2a5 AI \uc5f0\uc0b0\uc744 \uc9c0\uc18d\uc801\uc73c\ub85c \uc218\ud589\ud558\uae30\uc5d0\ub294 \ud55c\uacc4\uac00 \uc788\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ubaa8\ub378 \uad00\ub9ac \ubc0f \uc5c5\ub370\uc774\ud2b8:<\/strong> \uc218\ub9ce\uc740 \uc5e3\uc9c0 \uae30\uae30\uc5d0 \ubc30\ud3ec\ub41c AI \ubaa8\ub378\uc744 \uc77c\uad00\ub418\uac8c \uad00\ub9ac\ud558\uace0 \uc5c5\ub370\uc774\ud2b8\ud558\ub294 \uac83\uc740 \ubcf5\uc7a1\ud55c \ubb38\uc81c\uc785\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ubcf4\uc548 \ucde8\uc57d\uc810:<\/strong> \uae30\uae30 \uc790\uccb4\uc5d0 AI \ubaa8\ub378\uc774 \ud0d1\uc7ac\ub418\uba74\uc11c, \uae30\uae30 \uc790\uccb4\uc758 \ubb3c\ub9ac\uc801 \ubcf4\uc548 \ucde8\uc57d\uc810\uc774\ub098 \ubaa8\ub378 \ud0c8\ucde8\uc5d0 \ub300\ud55c \uc6b0\ub824\ub3c4 \uc874\uc7ac\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<p>\uadf8\ub7fc\uc5d0\ub3c4 \ubd88\uad6c\ud558\uace0 \uc5e3\uc9c0 AI\uc758 \ubbf8\ub798\ub294 \ub9e4\uc6b0 \ubc1d\uc2b5\ub2c8\ub2e4. AI \uae30\uc220\uc774 \ub354\uc6b1 \ubc1c\uc804\ud558\uace0 \ud558\ub4dc\uc6e8\uc5b4 \uc131\ub2a5\uc774 \ud5a5\uc0c1\ub428\uc5d0 \ub530\ub77c \uc5e3\uc9c0 AI\uc758 \uc131\ub2a5\uc740 \uc9c0\uc18d\uc801\uc73c\ub85c \uac1c\uc120\ub420 \uac83\uc785\ub2c8\ub2e4. \ub610\ud55c, \ud074\ub77c\uc6b0\ub4dc AI\uc640 \uc5e3\uc9c0 AI\uac00 \uc0c1\ud638 \ubcf4\uc644\uc801\uc73c\ub85c \uc791\ub3d9\ud558\ub294 <strong>&#8216;\ud558\uc774\ube0c\ub9ac\ub4dc AI&#8217;<\/strong> \ud615\ud0dc\uac00 \ub354\uc6b1 \ubcf4\ud3b8\ud654\ub420 \uac83\uc73c\ub85c \uc608\uc0c1\ub429\ub2c8\ub2e4.<\/p>\n<p>\uc608\ub97c \ub4e4\uc5b4, \uac04\ub2e8\ud55c \uc791\uc5c5\uc774\ub098 \uc2e4\uc2dc\uac04 \ubc18\uc751\uc774 \ud544\uc694\ud55c \uc791\uc5c5\uc740 \uc5e3\uc9c0\uc5d0\uc11c \ucc98\ub9ac\ud558\uace0, \ubcf5\uc7a1\ud558\uac70\ub098 \ubc29\ub300\ud55c \ub370\uc774\ud130 \ubd84\uc11d\uc774 \ud544\uc694\ud55c \uc791\uc5c5\uc740 \ud074\ub77c\uc6b0\ub4dc\uc5d0\uc11c \ucc98\ub9ac\ud558\ub294 \ubc29\uc2dd\uc785\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ud558\uc774\ube0c\ub9ac\ub4dc \uc811\uadfc \ubc29\uc2dd\uc740 \uc5e3\uc9c0 AI\uc758 \ud6a8\uc728\uc131\uacfc \ud074\ub77c\uc6b0\ub4dc AI\uc758 \uac15\ub825\ud55c \uc131\ub2a5\uc744 \ubaa8\ub450 \ud65c\uc6a9\ud560 \uc218 \uc788\uac8c \ud574\uc90d\ub2c8\ub2e4.<\/p>\n<p>2026\ub144\uc740 AI \uae30\uc220\uc774 &#8216;\uac70\ub300\ud568&#8217;\uc744 \ub118\uc5b4 &#8216;\ud6a8\uc728\uc131&#8217;\uacfc &#8216;\uac1c\uc778\ud654&#8217;\ub85c \ucd08\uc810\uc744 \uc62e\uaca8\uac00\ub294 \uc911\uc694\ud55c \uc804\ud658\uc810\uc774 \ub420 \uac83\uc785\ub2c8\ub2e4. \uc5e3\uc9c0 AI\ub294 \uc6b0\ub9ac\uc758 \uc77c\uc0c1\uc744 \ub354\uc6b1 \uc2a4\ub9c8\ud2b8\ud558\uace0 \ud3b8\ub9ac\ud558\uac8c \ub9cc\ub4e4 \ubfd0\ub9cc \uc544\ub2c8\ub77c, \ub370\uc774\ud130 \ud504\ub77c\uc774\ubc84\uc2dc\ub97c \ubcf4\ud638\ud558\uace0 \uc9c0\uc18d \uac00\ub2a5\ud55c \uae30\uc220 \ubc1c\uc804\uc744 \uc774\ub044\ub294 \ud575\uc2ec \ub3d9\ub825\uc774 \ub420 \uac83\uc785\ub2c8\ub2e4. \uc774\uc81c \uc6b0\ub9ac\ub294 \ub354 \uc774\uc0c1 \uba40\ub9ac \ub5a8\uc5b4\uc9c4 \uc11c\ubc84\uc758 AI\uc5d0 \uc758\uc874\ud558\ub294 \uac83\uc774 \uc544\ub2c8\ub77c, \uc6b0\ub9ac \uc190\uc548\uc758 \uae30\uae30, \uc6b0\ub9ac \uc8fc\ubcc0\uc758 \ubaa8\ub4e0 \uc0ac\ubb3c\uc5d0\uc11c \ub611\ub611\ud558\uac8c \uc791\ub3d9\ud558\ub294 AI\ub97c \ub9cc\ub098\uac8c \ub420 \uac83\uc785\ub2c8\ub2e4.<\/p>\n<h3>\uacb0\ub860: AI\uc758 \ubbf8\ub798, &#8216;\uac00\uae4c\uc6c0&#8217;\uc5d0\uc11c \ucc3e\ub2e4<\/h3>\n<p>2026\ub144 AI \ud2b8\ub80c\ub4dc\uc758 \ud575\uc2ec\uc740 \ub2e8\uc21c\ud788 \ubaa8\ub378\uc758 \ud06c\uae30\ub97c \ud0a4\uc6b0\ub294 \uac83\uc774 \uc544\ub2c8\ub77c, <strong>&#8216;\ub354 \uc791\uace0, \ub354 \ube60\ub974\uace0, \ub354 \uac00\uae4c\uc6b4&#8217; \uc5e3\uc9c0 AI<\/strong>\ub85c\uc758 \uc804\ud658\uc785\ub2c8\ub2e4. \uac70\ub300 AI \ubaa8\ub378\uc774 \uac00\uc838\uc628 \ud601\uc2e0\uc740 \ubd84\uba85\ud558\uc9c0\ub9cc, \uadf8 \ud55c\uacc4\ub294 \uba85\ud655\ud588\uc2b5\ub2c8\ub2e4. \uc5e3\uc9c0 AI\ub294 \uc774\ub7ec\ud55c \ud55c\uacc4\ub97c \uadf9\ubcf5\ud558\uace0 AI \uae30\uc220\uc744 \ub354\uc6b1 \ubcf4\ud3b8\uc801\uc774\uace0 \uc2e4\uc6a9\uc801\uc778 \ud615\ud0dc\ub85c \uc6b0\ub9ac \uc0b6\uc5d0 \ud1b5\ud569\uc2dc\ud0ac \uac83\uc785\ub2c8\ub2e4.<\/p>\n<ul>\n<li>\n<p><strong>\uc791\uc740 AI, \ud070 \ubcc0\ud654:<\/strong> \uc2a4\ub9c8\ud2b8\ud3f0\ubd80\ud130 \uc790\ub3d9\ucc28, \uc2a4\ub9c8\ud2b8 \ud648 \uae30\uae30\uae4c\uc9c0, \uc5e3\uc9c0 AI\ub294 \uc774\ubbf8 \uc6b0\ub9ac \uacc1\uc5d0\uc11c \uc791\ub3d9\ud558\uba70 \ud3b8\ub9ac\ud568\uc744 \ub354\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc18d\ub3c4\uc640 \ud504\ub77c\uc774\ubc84\uc2dc:<\/strong> \uc2e4\uc2dc\uac04 \ubc18\uc751\uacfc \uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638\ub77c\ub294 \ub450 \ub9c8\ub9ac \ud1a0\ub07c\ub97c \uc7a1\uc73c\uba70, AI \ud65c\uc6a9\uc758 \uc0c8\ub85c\uc6b4 \uac00\ub2a5\uc131\uc744 \uc5f4\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ubbf8\ub798\ub97c \uc704\ud55c \uc120\ud0dd:<\/strong> \uc5e3\uc9c0 AI\ub294 \ub370\uc774\ud130 \ud3ed\uc99d, \uc5f0\uacb0\uc131 \ubb38\uc81c, \ud658\uacbd \ubb38\uc81c \ub4f1 \ud604\ub300 \uc0ac\ud68c\uc758 \ub2e4\uc591\ud55c \ub09c\uc81c\ub97c \ud574\uacb0\ud558\ub294 \ub370 \uae30\uc5ec\ud560 \uac83\uc785\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ul>\n<p>\uc55e\uc73c\ub85c \uc5e3\uc9c0 AI \uae30\uc220\uc740 \ub354\uc6b1 \ubc1c\uc804\ud558\uc5ec \uc6b0\ub9ac\uc758 \uc0b6\uc744 \ub354\uc6b1 \ud48d\uc694\ub86d\uace0 \uc548\uc804\ud558\uac8c \ub9cc\ub4e4 \uac83\uc785\ub2c8\ub2e4. AI\uc758 \ubbf8\ub798\ub294 \uac70\ub300\ud55c \ud074\ub77c\uc6b0\ub4dc \ub108\uba38, \ubc14\ub85c \uc6b0\ub9ac \uacc1\uc5d0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<div class=\"content-links-section\">\n<p><strong>INTERNAL_LINKS:<\/strong> (\uc720\uc0ac\ud55c \uac8c\uc2dc\uae00 \uc785\ub825)<\/p>\n<p><strong>EXTERNAL_LINKS:<\/strong> <a href=\"https:\/\/www.korea.kr\/news\/policyNewsView.do?newsId=148935191\" target=\"_blank\" rel=\"noopener noreferrer\">AI \ubd84\uc57c\ubcc4 \ucd5c\uc2e0 \uae30\uc220 \ub3d9\ud5a5<\/a><\/p>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">AI Trends in 2026: Instead of Bigger, Smaller and Faster Edge AI Is Coming<\/h1>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">2026 AI Trends: The Shift from \u201cBigger\u201d to \u201cSmaller\u201d<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Artificial intelligence (AI) technology is advancing at a remarkable pace and penetrating nearly every area of daily life. In recent years, the rise of <strong>Large Language Models (LLMs)<\/strong> such as GPT-3 and GPT-4 has become a symbol of AI progress. These models, trained on enormous datasets, have demonstrated astonishing capabilities in natural language understanding and generation. They can converse like humans, write essays, and even generate code.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">However, beginning in 2026, AI trends are expected to enter a new phase. The focus is moving beyond \u201cbigness\u201d toward AI that is <strong>smaller, faster, and closer<\/strong>\u2014in other words, <strong>Edge AI<\/strong>. While large AI models rely on cloud infrastructure and massive computing power, Edge AI processes data on the device itself or near where the data is created. Why is this shift happening, and what does Edge AI mean for us?<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The Era of Large AI Models \u2014 and Their Limits<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Large AI models have unquestionably brought major innovation. With hundreds of billions or even trillions of parameters, these models have learned from vast portions of the internet\u2019s text and images, displaying capabilities that seem close to human intelligence. Thanks to them, people can now experience AI services at a level that would once have been difficult to imagine.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But large AI models also have several clear limitations.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Massive Computing Resources and Cost<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Training and operating these models requires enormous computing power. This leads directly to high energy consumption and huge costs. Only a small number of major technology companies can afford this scale of investment, raising concerns about deeper concentration of AI advancement in the hands of a few.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Data Transfer and Latency Issues<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">When data must be sent to the cloud and the processed result returned, delay is unavoidable. For services where real-time responsiveness is critical\u2014such as autonomous driving or live translation\u2014this latency can become a serious problem.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Privacy and Security Concerns<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Because all data is transmitted to a central server for processing, concerns about privacy leakage and security grow significantly. The fear of sensitive information leaving the user\u2019s device can discourage adoption of AI services.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Environmental Impact<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The data centers needed to operate large AI models consume enormous amounts of electricity, directly contributing to carbon emissions and broader environmental concerns.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">These limitations suggest that a new approach is necessary if AI is to become more widespread and be applied effectively across more environments.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Edge AI: The Rise of AI That Is \u201cSmaller, Faster, and Closer\u201d<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">As an alternative that can overcome the limitations of large-scale AI, <strong>Edge AI<\/strong> is drawing increasing attention. Edge AI refers to technology that performs AI computation directly on the device where data is generated\u2014such as smartphones, wearable devices, IoT sensors, and vehicles\u2014or on small servers at the network edge, instead of sending all data to a central cloud server.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Simply put, instead of placing the \u201cbrain\u201d of AI only in a central server, Edge AI equips each device\u2014the \u201carms and legs\u201d\u2014with its own small and efficient brain.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Core Characteristics of Edge AI<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Speed<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Because data does not need to travel far before being processed, response times become dramatically faster. This is essential for applications that require real-time performance.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Privacy<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Sensitive personal data can be processed on-device without being sent outside, significantly reducing the risk of privacy leakage.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Efficiency<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Edge AI saves bandwidth otherwise needed for cloud communication and reduces the cost of data transmission and storage. It also enables AI functions to work even offline, since constant internet connectivity is not required.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Reliability<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Even if the network is unstable or disconnected, the device can still perform AI tasks on its own, improving service stability.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Customization<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Small AI models optimized for specific devices or environments can be developed to maximize efficiency.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why Edge AI Is Gaining Attention<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Several technological and market factors are working together to accelerate the rise of Edge AI around 2026.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">1. Hardware Advances: Smaller but More Powerful AI Chips<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">In the past, high-performance CPUs or GPUs were essential for AI workloads. Today, however, <strong>Neural Processing Units (NPUs)<\/strong> specialized for AI computation are being integrated into smartphones, tablets, vehicles, and many other devices. These NPUs provide strong AI performance while consuming far less power than conventional chips, laying the hardware foundation for Edge AI.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, the latest smartphones already include NPUs that handle tasks such as facial recognition and photo enhancement directly on-device. In vehicles, Edge AI chips are being applied to ADAS (Advanced Driver Assistance Systems) and infotainment systems so that surroundings can be recognized and responded to in real time.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2. Advances in Software Optimization<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Model compression<\/strong> technology, which reduces model size and improves efficiency, is also a major driver of Edge AI adoption.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Pruning:<\/strong> Removes unnecessary or less important connections (weights) in the model, reducing size.<\/li>\n\n\n\n<li><strong>Quantization:<\/strong> Reduces the number of bits used to represent model weights\u2014for example, from 32-bit floating point to 8-bit integers\u2014thereby reducing model size and increasing speed.<\/li>\n\n\n\n<li><strong>Knowledge Distillation:<\/strong> Transfers knowledge from a large, complex \u201cteacher model\u201d to a smaller, more efficient \u201cstudent model,\u201d preserving as much performance as possible while reducing size.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">These technologies have made it possible to run AI models on smartphones and compact IoT devices that previously would have required desktops or servers.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3. Data Explosion and the Limits of Connectivity<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">With the spread of IoT devices, the amount of data generated globally is increasing exponentially. Sending all of this data to a central cloud for processing is becoming physically and economically impractical. Edge AI solves this bottleneck by letting devices process relevant data themselves.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In addition, not every location can guarantee stable, high-speed internet access. Edge AI makes it possible to retain AI functionality even in environments where connectivity is unstable or unavailable, improving both accessibility and reliability.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4. Stronger Privacy Regulations<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">As awareness of privacy grows worldwide and regulations become stricter, there are increasing limits on how data can be collected, stored, and processed. Because Edge AI processes sensitive personal data without sending it outside the device, it offers an effective way to deliver AI services while complying with privacy regulations.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Diverse Use Cases for Edge AI<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Edge AI is already being used in many parts of daily life, and its scope will continue to expand.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">1. Smartphones and Mobile Devices<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Voice assistants:<\/strong> Recognize and process voice commands directly on the device, improving response time.<\/li>\n\n\n\n<li><strong>Camera functions:<\/strong> Handle scene recognition, autofocus, portrait mode, and image enhancement on-device.<\/li>\n\n\n\n<li><strong>Face unlock:<\/strong> Recognize the user\u2019s face to unlock the device.<\/li>\n\n\n\n<li><strong>Real-time translation:<\/strong> Translate text or speech instantly even without internet access.<\/li>\n\n\n\n<li><strong>Health monitoring:<\/strong> Wearable devices analyze heart rate and activity levels to monitor health and detect anomalies.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">2. Automotive Industry<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>ADAS (Advanced Driver Assistance Systems):<\/strong> Detect pedestrians, vehicles, and lane markings in real time, then warn or intervene accordingly.<\/li>\n\n\n\n<li><strong>Autonomous driving:<\/strong> Analyze data from cameras, radar, and LiDAR in real time to control the vehicle.<\/li>\n\n\n\n<li><strong>Driver monitoring:<\/strong> Detect drowsiness or inattentiveness and issue warnings.<\/li>\n\n\n\n<li><strong>Infotainment systems:<\/strong> Use voice commands to control vehicle functions and entertainment features.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">3. Smart Homes and IoT<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Smart speakers:<\/strong> Recognize and process voice commands to control lighting, temperature, and music playback.<\/li>\n\n\n\n<li><strong>Security cameras:<\/strong> Detect and analyze intrusions and notify the user.<\/li>\n\n\n\n<li><strong>Smart appliances:<\/strong> Learn user patterns and operate automatically, or respond to voice commands.<\/li>\n\n\n\n<li><strong>Industrial IoT:<\/strong> Detect abnormal signs in factory equipment in real time for predictive maintenance and greater production efficiency.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">4. Healthcare<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Wearable medical devices:<\/strong> Monitor patients\u2019 vital signs in real time and alert medical staff when anomalies are detected.<\/li>\n\n\n\n<li><strong>Medical image analysis:<\/strong> Even on small devices, analyze X-rays, CT scans, and other medical images to help with early diagnosis.<\/li>\n\n\n\n<li><strong>Remote care:<\/strong> Analyze patient data immediately on-site and deliver results to healthcare professionals for more efficient treatment.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">5. Retail and Logistics<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Smart checkout:<\/strong> Use cameras and sensors in stores to analyze customer behavior and support contactless payment.<\/li>\n\n\n\n<li><strong>Inventory management:<\/strong> Automatically detect and manage inventory in stores.<\/li>\n\n\n\n<li><strong>Logistics optimization:<\/strong> Warehouse robots and drones process data in real time to optimize logistics routes.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Challenges and Future Outlook for Edge AI<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Edge AI clearly offers many advantages, but several challenges remain.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Performance Limitations<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Compared with large cloud-based AI models, Edge AI models may still have limited performance. Complex and highly sophisticated tasks may continue to require cloud AI.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Hardware Constraints<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">AI chips in compact devices face limitations related to power consumption and heat. Sustained high-performance AI computation can still be difficult.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Model Management and Updates<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Managing and updating AI models consistently across large numbers of edge devices is a complex problem.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Security Vulnerabilities<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Because the AI model resides on the device itself, there are concerns about physical security weaknesses and model theft.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Even so, the future of Edge AI looks extremely promising. As AI technology continues to improve and hardware becomes more capable, Edge AI performance will keep advancing. At the same time, <strong>hybrid AI<\/strong>\u2014where cloud AI and edge AI complement one another\u2014is expected to become more common.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, simple or real-time tasks can be handled at the edge, while more complex or large-scale analysis can be processed in the cloud. This hybrid approach makes it possible to combine the efficiency of Edge AI with the power of cloud AI.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The year 2026 is likely to become a major turning point, marking a shift in AI from a focus on sheer scale toward <strong>efficiency<\/strong> and <strong>personalization<\/strong>. Edge AI will not only make daily life smarter and more convenient, but also protect data privacy and support more sustainable technological development. Instead of depending solely on distant server-based AI, people will increasingly encounter AI that operates intelligently in the devices in their hands and in the objects around them.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion: The Future of AI Lies in Closeness<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The core of the 2026 AI trend is not simply making models larger, but shifting toward <strong>Edge AI that is smaller, faster, and closer<\/strong>. The innovation brought by large AI models is undeniable, but so are their limitations. Edge AI will overcome many of those limits and integrate AI into daily life in a more universal and practical form.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Small AI, Big Change<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">From smartphones to vehicles to smart home devices, Edge AI is already working around us and adding convenience to daily life.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Speed and Privacy<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">By combining real-time responsiveness with stronger privacy protection, Edge AI is opening new possibilities for how AI can be used.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">A Choice for the Future<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Edge AI can help address major challenges of modern society, including exploding data volumes, connectivity limitations, and environmental concerns.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Going forward, Edge AI will continue to develop and make life richer and safer. The future of AI lies not somewhere beyond a distant cloud, but right beside us.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>2026\ub144 AI \ud2b8\ub80c\ub4dc\ub294 \uac70\ub300\ud568\uc5d0\uc11c \ubc97\uc5b4\ub098 \uc791\uace0 \ube60\ub978 &#8216;\uc5e3\uc9c0 AI&#8217;\ub85c \uc804\ud658\ub420 \uc804\ub9dd\uc785\ub2c8\ub2e4. \uc5e3\uc9c0 AI\ub294 \ub370\uc774\ud130 \ucc98\ub9ac \uc18d\ub3c4 \ud5a5\uc0c1, \uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \uac15\ud654, \ube44\uc6a9 \uc808\uac10 \ub4f1 \ub2e4\uc591\ud55c \uc774\uc810\uc744 \uc81c\uacf5\ud558\uba70 \uc6b0\ub9ac\uc758 \uc0b6\uc744 \ub354\uc6b1 \ud3b8\ub9ac\ud558\uac8c \ub9cc\ub4e4 \uac83\uc785\ub2c8\ub2e4. \uc5e3\uc9c0 AI\uc758 \ud575\uc2ec\uc801\uc778 \ubcc0\ud654\uc640 \ubbf8\ub798\ub97c \uc790\uc138\ud788 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[4],"tags":[231,183,69,41,78,73,230,232,34,233,185,71,70,112,184,186,43,45,22,187],"class_list":["post-74","post","type-post","status-publish","format-standard","hentry","category-ai","tag-2026-ai-trends","tag-2026-ai-","tag-ai-technology","tag-ai-","tag-artificial-intelligence","tag-edge-ai","tag-lag","tag-large-language-model","tag-llm","tag-model-compression","tag-npu","tag-privacy-protection","tag-smartphone-ai","tag-112","tag-184","tag-186","tag--ai","tag-22"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=\/wp\/v2\/posts\/74","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=74"}],"version-history":[{"count":3,"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=\/wp\/v2\/posts\/74\/revisions"}],"predecessor-version":[{"id":79,"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=\/wp\/v2\/posts\/74\/revisions\/79"}],"wp:attachment":[{"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=74"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=74"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ai-cloud.kr\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=74"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}