{"id":477797,"date":"2023-08-09T09:20:26","date_gmt":"2023-08-09T09:20:26","guid":{"rendered":""},"modified":"2023-09-05T11:15:26","modified_gmt":"2023-09-05T11:15:26","slug":"large-language-models","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/kr\/wiki\/large-language-models\/","title":{"rendered":"\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378"},"content":{"rendered":"<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \uc0dd\uc131\ud558\ub3c4\ub85d \uc124\uacc4\ub41c \uc77c\uc885\uc758 \uc778\uacf5 \uc9c0\ub2a5(AI) \uae30\uc220\uc785\ub2c8\ub2e4. \uadf8\ub4e4\uc740 \ub525 \ub7ec\ub2dd \uc54c\uace0\ub9ac\uc998\uacfc \uc5c4\uccad\ub09c \uc591\uc758 \ub370\uc774\ud130\ub97c \ud65c\uc6a9\ud558\uc5ec \ub180\ub77c\uc6b4 \uc5b8\uc5b4 \ucc98\ub9ac \ub2a5\ub825\uc744 \ub2ec\uc131\ud569\ub2c8\ub2e4. \uc774\ub7ec\ud55c \ubaa8\ub378\uc740 \uc790\uc5f0\uc5b4 \ucc98\ub9ac, \uae30\uacc4 \ubc88\uc5ed, \uac10\uc815 \ubd84\uc11d, \ucc57\ubd07 \ub4f1 \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0 \ud601\uba85\uc744 \uc77c\uc73c\ucf30\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc758 \uae30\uc6d0\uc5d0 \uad00\ud55c \uc5ed\uc0ac<\/h2>\n<p>\uc5b8\uc5b4 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud55c\ub2e4\ub294 \uc544\uc774\ub514\uc5b4\ub294 AI \uc5f0\uad6c \ucd08\uae30\ub85c \uac70\uc2ac\ub7ec \uc62c\ub77c\uac11\ub2c8\ub2e4. \uadf8\ub7ec\ub098 2010\ub144\ub300 \ub525 \ub7ec\ub2dd\uc758 \ucd9c\ud604\uacfc \ubc29\ub300\ud55c \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uac00\uc6a9\uc131\uacfc \ud568\uaed8 \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc758 \ud68d\uae30\uc801\uc778 \ubc1c\uc804\uc774 \uc774\ub8e8\uc5b4\uc84c\uc2b5\ub2c8\ub2e4. \uc2e0\uacbd\ub9dd\uacfc \ub2e8\uc5b4 \uc784\ubca0\ub529\uc758 \uac1c\ub150\uc740 \ub354\uc6b1 \uac15\ub825\ud55c \uc5b8\uc5b4 \ubaa8\ub378\uc744 \uac1c\ubc1c\ud560 \uc218 \uc788\ub294 \uae38\uc744 \uc5f4\uc5c8\uc2b5\ub2c8\ub2e4.<\/p>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc5d0 \ub300\ud55c \uccab \ubc88\uc9f8 \uc5b8\uae09\uc740 Tomas Mikolov\uc640 Google\uc758 \ub3d9\ub8cc\ub4e4\uc774 Word2Vec \ubaa8\ub378\uc744 \uc18c\uac1c\ud558\ub294 2013\ub144 \ub17c\ubb38\uc5d0\uc11c \ucc3e\uc544\ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ubaa8\ub378\uc740 \uc2e0\uacbd\ub9dd\uc774 \uc5f0\uc18d \ubca1\ud130 \uacf5\uac04\uc5d0\uc11c \ub2e8\uc5b4\ub97c \ud6a8\uc728\uc801\uc73c\ub85c \ud45c\ud604\ud558\uace0 \ub2e8\uc5b4 \uac04\uc758 \uc758\ubbf8 \uad00\uacc4\ub97c \ud3ec\ucc29\ud560 \uc218 \uc788\uc74c\uc744 \ubcf4\uc5ec\uc8fc\uc5c8\uc2b5\ub2c8\ub2e4. \uc774\ub294 \ubcf4\ub2e4 \uc815\uad50\ud55c \uc5b8\uc5b4 \ubaa8\ub378 \uac1c\ubc1c\uc758 \uae38\uc744 \uc5f4\uc5c8\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \uc815\ubcf4<\/h2>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \uc218\uc5b5\uc5d0\uc11c \uc218\uc2ed\uc5b5 \uac1c\uc758 \ub9e4\uac1c\ubcc0\uc218\ub97c \ud3ec\ud568\ud558\ub294 \uc5c4\uccad\ub09c \ud06c\uae30\uac00 \ud2b9\uc9d5\uc785\ub2c8\ub2e4. \uc774\ub4e4\uc740 \uc804\ud1b5\uc801\uc778 \uc21c\ud658 \uc2e0\uacbd\ub9dd(RNN)\ubcf4\ub2e4 \ub354 \ubcd1\ub82c\uc801\uc774\uace0 \ud6a8\uc728\uc801\uc778 \ubc29\uc2dd\uc73c\ub85c \uc5b8\uc5b4\ub97c \ucc98\ub9ac\ud558\uace0 \uc0dd\uc131\ud560 \uc218 \uc788\ub294 \ubcc0\ud658\uae30 \uc544\ud0a4\ud14d\ucc98\ub97c \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc758 \uc8fc\uc694 \ubaa9\ud45c\ub294 \uc774\uc804 \ub2e8\uc5b4\uc758 \ub9e5\ub77d\uc744 \uace0\ub824\ud558\uc5ec \uc2dc\ud000\uc2a4\uc5d0\uc11c \ub2e4\uc74c \ub2e8\uc5b4\uc758 \uac00\ub2a5\uc131\uc744 \uc608\uce21\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uc5b8\uc5b4 \ubaa8\ub378\ub9c1\uc73c\ub85c \uc54c\ub824\uc9c4 \uc774 \ud504\ub85c\uc138\uc2a4\ub294 \ub2e4\uc591\ud55c \uc790\uc5f0\uc5b4 \uc774\ud574 \ubc0f \uc0dd\uc131 \uc791\uc5c5\uc758 \uae30\ucd08\ub97c \ud615\uc131\ud569\ub2c8\ub2e4.<\/p>\n<h2>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc758 \ub0b4\ubd80 \uad6c\uc870<\/h2>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \uc5ec\ub7ec \uacc4\uce35\uc758 self-attention \uba54\ucee4\ub2c8\uc998\uc73c\ub85c \uad6c\uc131\ub41c \ubcc0\ud658\uae30 \uc544\ud0a4\ud14d\ucc98\ub97c \uc0ac\uc6a9\ud558\uc5ec \uad6c\ucd95\ub429\ub2c8\ub2e4. self-attention \uba54\ucee4\ub2c8\uc998\uc744 \ud1b5\ud574 \ubaa8\ub378\uc740 \uc804\uccb4 \uc785\ub825 \uc2dc\ud000\uc2a4\uc758 \ub9e5\ub77d\uc5d0\uc11c \uac01 \ub2e8\uc5b4\uc758 \uc911\uc694\uc131\uc744 \ud3c9\uac00\ud558\uc5ec \uc7a5\uac70\ub9ac \uc885\uc18d\uc131\uc744 \ud6a8\uacfc\uc801\uc73c\ub85c \ud3ec\ucc29\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<p>\ubcc0\ud658\uae30 \uc544\ud0a4\ud14d\ucc98\uc758 \ud575\uc2ec \uad6c\uc131 \uc694\uc18c\ub294 \ucffc\ub9ac\uc640\uc758 \uad00\ub828\uc131(\ub2e4\ub978 \ub2e8\uc5b4\uc758 \ud3ec\ud568)\uc744 \uae30\ubc18\uc73c\ub85c \uac12(\uc77c\ubc18\uc801\uc73c\ub85c \ub2e8\uc5b4\uc758 \ud3ec\ud568)\uc758 \uac00\uc911 \ud569\uacc4\ub97c \uacc4\uc0b0\ud558\ub294 &quot;\uc8fc\uc758&quot; \uba54\ucee4\ub2c8\uc998\uc785\ub2c8\ub2e4. \uc774 \uc8fc\uc758 \uba54\ucee4\ub2c8\uc998\uc740 \ubaa8\ub378\uc744 \ud1b5\ud55c \ubcd1\ub82c \ucc98\ub9ac\uc640 \ud6a8\uc728\uc801\uc778 \uc815\ubcf4 \ud750\ub984\uc744 \ucd09\uc9c4\ud569\ub2c8\ub2e4.<\/p>\n<h2>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc758 \uc8fc\uc694 \ud2b9\uc9d5 \ubd84\uc11d<\/h2>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc758 \uc8fc\uc694 \uae30\ub2a5\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n<ol>\n<li>\n<p><strong>\ub300\uaddc\ubaa8 \ud06c\uae30:<\/strong> \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc5d0\ub294 \ubc29\ub300\ud55c \uc218\uc758 \ub9e4\uac1c\ubcc0\uc218\uac00 \uc788\uc5b4 \ubcf5\uc7a1\ud55c \uc5b8\uc5b4 \ud328\ud134\uacfc \ub258\uc559\uc2a4\ub97c \ud3ec\ucc29\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc0c1\ud669\uc5d0 \ub530\ub978 \uc774\ud574:<\/strong> \uc774\ub7ec\ud55c \ubaa8\ub378\uc740 \ub2e8\uc5b4\uac00 \ub098\ud0c0\ub098\ub294 \ubb38\ub9e5\uc744 \uae30\ubc18\uc73c\ub85c \ub2e8\uc5b4\uc758 \uc758\ubbf8\ub97c \uc774\ud574\ud560 \uc218 \uc788\uc73c\ubbc0\ub85c \ubcf4\ub2e4 \uc815\ud655\ud55c \uc5b8\uc5b4 \ucc98\ub9ac\uac00 \uac00\ub2a5\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\uc804\uc774 \ud559\uc2b5:<\/strong> \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \ucd5c\uc18c\ud55c\uc758 \ucd94\uac00 \uad50\uc721 \ub370\uc774\ud130\ub85c \ud2b9\uc815 \uc791\uc5c5\uc5d0 \ub9de\uac8c \ubbf8\uc138 \uc870\uc815\ud560 \uc218 \uc788\uc73c\ubbc0\ub85c \ub2e4\uc591\ud55c \uc751\uc6a9 \ud504\ub85c\uadf8\ub7a8\uc5d0 \ub2e4\uc6a9\ub3c4\ub85c \uc801\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ud14d\uc2a4\ud2b8 \uc0dd\uc131\uc758 \ucc3d\uc758\uc131:<\/strong> \uc77c\uad00\ub418\uace0 \uc0c1\ud669\uc5d0 \ub9de\ub294 \ud14d\uc2a4\ud2b8\ub97c \uc0dd\uc131\ud560 \uc218 \uc788\uc5b4 \ucc57\ubd07, \ucf58\ud150\uce20 \uc0dd\uc131 \ub4f1\uc5d0 \uc720\uc6a9\ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<li>\n<p><strong>\ub2e4\uad6d\uc5b4 \uae30\ub2a5:<\/strong> \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \uc5ec\ub7ec \uc5b8\uc5b4\ub85c \ub41c \ud14d\uc2a4\ud2b8\ub97c \ucc98\ub9ac\ud558\uace0 \uc0dd\uc131\ud558\uc5ec \uae00\ub85c\ubc8c \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \uc6a9\uc774\ud558\uac8c \ud569\ub2c8\ub2e4.<\/p>\n<\/li>\n<\/ol>\n<h2>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc758 \uc720\ud615<\/h2>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \ub2e4\uc591\ud55c \ud06c\uae30\uc640 \uad6c\uc131\uc73c\ub85c \uc81c\uacf5\ub429\ub2c8\ub2e4. \uc778\uae30 \uc788\ub294 \uc720\ud615\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n<table>\n<thead>\n<tr>\n<th>\ubaa8\ub378<\/th>\n<th>\ub9e4\uac1c\ubcc0\uc218<\/th>\n<th>\uc124\uba85<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>GPT-3<\/td>\n<td>1,750\uc5b5<\/td>\n<td>OpenAI\uc5d0\uc11c \uc54c\ub824\uc9c4 \uac00\uc7a5 \ud070 \ubaa8\ub378 \uc911 \ud558\ub098\uc785\ub2c8\ub2e4.<\/td>\n<\/tr>\n<tr>\n<td>BERT(\ubcc0\uc555\uae30\uc758 \uc591\ubc29\ud5a5 \uc778\ucf54\ub354 \ud45c\ud604)<\/td>\n<td>3\uc5b5 4\ucc9c\ub9cc<\/td>\n<td>Google\uc5d0\uc11c \ub3c4\uc785\ud55c \uc81c\ud488\uc73c\ub85c \uc591\ubc29\ud5a5 \uc791\uc5c5\uc5d0 \ud0c1\uc6d4\ud569\ub2c8\ub2e4.<\/td>\n<\/tr>\n<tr>\n<td>\ub85c\ubca0\ub974\ud0c0<\/td>\n<td>3\uc5b5 5\ucc9c 5\ubc31\ub9cc<\/td>\n<td>\uc0ac\uc804 \ud6c8\ub828\uc5d0 \ub354\uc6b1 \ucd5c\uc801\ud654\ub41c BERT\uc758 \ubcc0\ud615\uc785\ub2c8\ub2e4.<\/td>\n<\/tr>\n<tr>\n<td>XLNet<\/td>\n<td>3\uc5b5 4\ucc9c\ub9cc<\/td>\n<td>\uc21c\uc5f4 \uae30\ubc18 \uad50\uc721\uc744 \ud65c\uc6a9\ud558\uc5ec \uc131\ub2a5\uc744 \ud5a5\uc0c1\uc2dc\ud0b5\ub2c8\ub2e4.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378, \ubb38\uc81c \ubc0f \uc194\ub8e8\uc158\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95<\/h2>\n<h3>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95<\/h3>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \ub2e4\uc74c\uc744 \ud3ec\ud568\ud55c \ub2e4\uc591\ud55c \ub3c4\uba54\uc778\uc5d0 \uc801\uc6a9\ub429\ub2c8\ub2e4.<\/p>\n<ul>\n<li><strong>\uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP):<\/strong> \uac10\uc815 \ubd84\uc11d, \uba85\uba85\ub41c \uc5d4\ud130\ud2f0 \uc778\uc2dd, \ud14d\uc2a4\ud2b8 \ubd84\ub958\uc640 \uac19\uc740 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc5d0\uc11c \uc778\uac04 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \ucc98\ub9ac\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\uae30\uacc4 \ubc88\uc5ed:<\/strong> \ubcf4\ub2e4 \uc815\ud655\ud558\uace0 \uc0c1\ud669\uc5d0 \ub9de\ub294 \uc5b8\uc5b4 \uac04 \ubc88\uc5ed\uc744 \uac00\ub2a5\ud558\uac8c \ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\uc9c8\uc758 \uc751\ub2f5 \uc2dc\uc2a4\ud15c:<\/strong> \uc0ac\uc6a9\uc790 \ucffc\ub9ac\uc5d0 \uad00\ub828 \ub2f5\ubcc0\uc744 \uc81c\uacf5\ud558\uc5ec \ucc57\ubd07\uacfc \uac00\uc0c1 \ub3c4\uc6b0\ubbf8\ub97c \uac15\ud654\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\ud14d\uc2a4\ud2b8 \uc0dd\uc131:<\/strong> \ucf58\ud150\uce20 \uc81c\uc791, \uc2a4\ud1a0\ub9ac\ud154\ub9c1, \ucc3d\uc758\uc801 \uae00\uc4f0\uae30\ub97c \uc704\ud574 \uc778\uac04\uacfc \uc720\uc0ac\ud55c \ud14d\uc2a4\ud2b8\ub97c \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h3>\ubb38\uc81c \ubc0f \ud574\uacb0 \ubc29\ubc95<\/h3>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \uba87 \uac00\uc9c0 \uacfc\uc81c\uc5d0 \uc9c1\uba74\ud574 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<ul>\n<li><strong>\ub9ac\uc18c\uc2a4 \uc9d1\uc57d\uc801:<\/strong> \ud6c8\ub828 \ubc0f \ucd94\ub860\uc5d0\ub294 \uac15\ub825\ud55c \ud558\ub4dc\uc6e8\uc5b4\uc640 \uc0c1\ub2f9\ud55c \ucef4\ud4e8\ud305 \ub9ac\uc18c\uc2a4\uac00 \ud544\uc694\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\ud3b8\uacac\uacfc \uacf5\uc815\uc131:<\/strong> \ubaa8\ub378\uc740 \ud559\uc2b5 \ub370\uc774\ud130\uc5d0 \uc874\uc7ac\ud558\ub294 \ud3b8\ud5a5\uc744 \uc0c1\uc18d\ud558\uc5ec \ud3b8\ud5a5\ub41c \ucd9c\ub825\uc744 \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \ubb38\uc81c:<\/strong> \uc77c\uad00\ub41c \ud14d\uc2a4\ud2b8\ub97c \uc0dd\uc131\ud558\uba74 \uc758\ub3c4\uce58 \uc54a\uac8c \ubbfc\uac10\ud55c \uc815\ubcf4\uac00 \uc720\ucd9c\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ul>\n<p>\uc774\ub7ec\ud55c \ubb38\uc81c\ub97c \ud574\uacb0\ud558\uae30 \uc704\ud574 \uc5f0\uad6c\uc6d0\uacfc \uac1c\ubc1c\uc790\ub294 \ub2e4\uc74c\uacfc \uac19\uc774 \uc801\uadf9\uc801\uc73c\ub85c \ub178\ub825\ud558\uace0 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<ul>\n<li><strong>\ud6a8\uc728\uc801\uc778 \uc544\ud0a4\ud14d\ucc98:<\/strong> \uacc4\uc0b0 \uc694\uad6c \uc0ac\ud56d\uc744 \uc904\uc774\uae30 \uc704\ud574 \ubcf4\ub2e4 \ud6a8\uc728\uc801\uc778 \ubaa8\ub378\uc744 \uc124\uacc4\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\ud3b8\uacac \uc644\ud654:<\/strong> \uc5b8\uc5b4 \ubaa8\ub378\uc758 \ud3b8\ud5a5\uc744 \uc904\uc774\uace0 \uac10\uc9c0\ud558\ub294 \uae30\uc220\uc744 \uad6c\ud604\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\uc724\ub9ac\uc801 \uc9c0\uce68:<\/strong> \ucc45\uc784 \uc788\ub294 AI \uad00\ud589\uc744 \uc7a5\ub824\ud558\uace0 \uc724\ub9ac\uc801 \uc601\ud5a5\uc744 \uace0\ub824\ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h2>\uc8fc\uc694 \ud2b9\uc9d5 \ubc0f \uc720\uc0ac \uc6a9\uc5b4\uc640\uc758 \ube44\uad50<\/h2>\n<p>\ub2e4\uc74c\uc740 \uc720\uc0ac\ud55c \uc5b8\uc5b4 \uae30\uc220\uc744 \uc0ac\uc6a9\ud558\ub294 \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc744 \ube44\uad50\ud55c \uac83\uc785\ub2c8\ub2e4.<\/p>\n<table>\n<thead>\n<tr>\n<th>\uc6a9\uc5b4<\/th>\n<th>\uc124\uba85<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378<\/td>\n<td>\uc218\uc2ed\uc5b5 \uac1c\uc758 \ub9e4\uac1c\ubcc0\uc218\ub97c \uac16\ucd98 \ub300\uaddc\ubaa8 AI \ubaa8\ub378\ub85c NLP \uc791\uc5c5\uc5d0 \ud0c1\uc6d4\ud569\ub2c8\ub2e4.<\/td>\n<\/tr>\n<tr>\n<td>\ub2e8\uc5b4 \uc784\ubca0\ub529<\/td>\n<td>\uc758\ubbf8\ub860\uc801 \uad00\uacc4\ub97c \ud3ec\ucc29\ud558\ub294 \ub2e8\uc5b4\uc758 \ubca1\ud130 \ud45c\ud604\uc785\ub2c8\ub2e4.<\/td>\n<\/tr>\n<tr>\n<td>\uc21c\ud658 \uc2e0\uacbd\ub9dd(RNN)<\/td>\n<td>\uc5b8\uc5b4 \ucc98\ub9ac\ub97c \uc704\ud55c \uc804\ud1b5\uc801\uc778 \uc21c\ucc28 \ubaa8\ub378.<\/td>\n<\/tr>\n<tr>\n<td>\uae30\uacc4 \ubc88\uc5ed<\/td>\n<td>\uc5b8\uc5b4 \uac04 \ubc88\uc5ed\uc744 \uac00\ub2a5\ud558\uac8c \ud558\ub294 \uae30\uc220.<\/td>\n<\/tr>\n<tr>\n<td>\uac10\uc131\ubd84\uc11d<\/td>\n<td>\ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc758 \uac10\uc815(\uae0d\uc815\uc801\/\ubd80\uc815\uc801)\uc744 \uacb0\uc815\ud569\ub2c8\ub2e4.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\ubbf8\ub798\uc758 \uad00\uc810\uacfc \uae30\uc220<\/h2>\n<p>\ub2e4\uc74c \uc0ac\ud56d\uc5d0 \ucd08\uc810\uc744 \ub9de\ucd98 \uc9c0\uc18d\uc801\uc778 \uc5f0\uad6c\ub97c \ud1b5\ud574 \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc758 \ubbf8\ub798\ub294 \ubc1d\uc2b5\ub2c8\ub2e4.<\/p>\n<ul>\n<li><strong>\ub2a5\ub960:<\/strong> \uacc4\uc0b0 \ube44\uc6a9\uc744 \uc904\uc774\uae30 \uc704\ud574 \ubcf4\ub2e4 \ud6a8\uc728\uc801\uc778 \uc544\ud0a4\ud14d\ucc98\ub97c \uac1c\ubc1c\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\ub2e4\uc911 \ubaa8\ub4dc \ud559\uc2b5:<\/strong> \uc5b8\uc5b4 \ubaa8\ub378\uc744 \ube44\uc804 \ubc0f \uc624\ub514\uc624\uc640 \ud1b5\ud569\ud558\uc5ec \uc774\ud574\ub3c4\ub97c \ub192\uc785\ub2c8\ub2e4.<\/li>\n<li><strong>\uc81c\ub85c\uc0f7 \ud559\uc2b5:<\/strong> \ud2b9\uc815 \uad50\uc721 \uc5c6\uc774\ub3c4 \ubaa8\ub378\uc774 \uc791\uc5c5\uc744 \uc218\ud589\ud560 \uc218 \uc788\ub3c4\ub85d \ud558\uc5ec \uc801\uc751\uc131\uc744 \ud5a5\uc0c1\uc2dc\ud0b5\ub2c8\ub2e4.<\/li>\n<li><strong>\uc9c0\uc18d\uc801\uc778 \ud559\uc2b5:<\/strong> \ubaa8\ub378\uc774 \uc0ac\uc804 \uc9c0\uc2dd\uc744 \uc720\uc9c0\ud558\uba74\uc11c \uc0c8\ub85c\uc6b4 \ub370\uc774\ud130\ub85c\ubd80\ud130 \ud559\uc2b5\ud560 \uc218 \uc788\ub3c4\ub85d \ud569\ub2c8\ub2e4.<\/li>\n<\/ul>\n<h2>\ud504\ub85d\uc2dc \uc11c\ubc84 \ubc0f \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uacfc\uc758 \uc5f0\uad00\uc131<\/h2>\n<p>\ud504\ub85d\uc2dc \uc11c\ubc84\ub294 \ud074\ub77c\uc774\uc5b8\ud2b8\uc640 \uc778\ud130\ub137 \uc0ac\uc774\uc758 \uc911\uac1c\uc790 \uc5ed\ud560\uc744 \ud569\ub2c8\ub2e4. \uc5ec\ub7ec \uac00\uc9c0 \ubc29\ubc95\uc73c\ub85c \ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378 \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \ud5a5\uc0c1\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<ol>\n<li><strong>\ub370\uc774\ud130 \uc218\uc9d1:<\/strong> \ud504\ub85d\uc2dc \uc11c\ubc84\ub294 \uc0ac\uc6a9\uc790 \ub370\uc774\ud130\ub97c \uc775\uba85\ud654\ud558\uc5ec \ubaa8\ub378 \uad50\uc721\uc744 \uc704\ud55c \uc724\ub9ac\uc801\uc778 \ub370\uc774\ud130 \uc218\uc9d1\uc744 \ucd09\uc9c4\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<li><strong>\uac1c\uc778 \uc815\ubcf4 \ubcf4\ud638 \ubc0f \ubcf4\uc548:<\/strong> \ud504\ub85d\uc2dc \uc11c\ubc84\ub294 \ucd94\uac00 \ubcf4\uc548 \uacc4\uce35\uc744 \ucd94\uac00\ud558\uc5ec \uc7a0\uc7ac\uc801\uc778 \uc704\ud611\uc73c\ub85c\ubd80\ud130 \uc0ac\uc6a9\uc790\uc640 \ubaa8\ub378\uc744 \ubcf4\ud638\ud569\ub2c8\ub2e4.<\/li>\n<li><strong>\ubd84\uc0b0 \ucd94\ub860:<\/strong> \ud504\ub85d\uc2dc \uc11c\ubc84\ub294 \ubaa8\ub378 \ucd94\ub860\uc744 \uc5ec\ub7ec \uc704\uce58\uc5d0 \ubd84\uc0b0\ud558\uc5ec \ub300\uae30 \uc2dc\uac04\uc744 \uc904\uc774\uace0 \uc751\ub2f5 \uc2dc\uac04\uc744 \ud5a5\uc0c1\uc2dc\ud0ac \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/li>\n<\/ol>\n<h2>\uad00\ub828\ub41c \ub9c1\ud06c\ub4e4<\/h2>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \ub0b4\uc6a9\uc744 \ubcf4\ub824\uba74 \ub2e4\uc74c \ub9ac\uc18c\uc2a4\ub97c \ud0d0\uc0c9\ud558\uc138\uc694.<\/p>\n<ul>\n<li><a href=\"https:\/\/openai.com\/models\/gpt-3\" target=\"_new\" rel=\"noopener nofollow\">OpenAI\uc758 GPT-3<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1810.04805\" target=\"_new\" rel=\"noopener nofollow\">BERT: \uc5b8\uc5b4 \uc774\ud574\ub97c \uc704\ud55c \uc2ec\uce35 \uc591\ubc29\ud5a5 \ubcc0\ud658\uae30 \uc0ac\uc804 \ud6c8\ub828<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/1906.08237\" target=\"_new\" rel=\"noopener nofollow\">XLNet: \uc5b8\uc5b4 \uc774\ud574\ub97c \uc704\ud55c \uc77c\ubc18\ud654\ub41c \uc790\ub3d9 \ud68c\uadc0 \uc0ac\uc804 \ud6c8\ub828<\/a><\/li>\n<li><a href=\"https:\/\/oneproxy.pro\/kr\/\" target=\"_new\" rel=\"noopener\">\ud504\ub85d\uc2dc \uc11c\ubc84 \uacf5\uae09\uc790 \u2013 OneProxy<\/a><\/li>\n<\/ul>\n<p>\ub300\uaddc\ubaa8 \uc5b8\uc5b4 \ubaa8\ub378\uc740 \uc758\uc2ec\ud560 \uc5ec\uc9c0 \uc5c6\uc774 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \ubc0f AI \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc758 \ud658\uacbd\uc744 \ubcc0\ud654\uc2dc\ucf30\uc2b5\ub2c8\ub2e4. \uc5f0\uad6c\uac00 \uc9c4\ud589\ub418\uace0 \uae30\uc220\uc774 \ubc1c\uc804\ud568\uc5d0 \ub530\ub77c \uc6b0\ub9ac\ub294 \ubbf8\ub798\uc5d0 \ub354\uc6b1 \ud765\ubbf8\ub85c\uc6b4 \uac1c\ubc1c\uacfc \uc751\uc6a9\uc744 \uae30\ub300\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud504\ub85d\uc2dc \uc11c\ubc84\ub294 \uc774\ub7ec\ud55c \uac15\ub825\ud55c \uc5b8\uc5b4 \ubaa8\ub378\uc758 \ucc45\uc784\uac10 \uc788\uace0 \ud6a8\uc728\uc801\uc778 \uc0ac\uc6a9\uc744 \uc9c0\uc6d0\ud558\ub294 \ub370 \ud544\uc218\uc801\uc778 \uc5ed\ud560\uc744 \uacc4\uc18d\ud574\uc11c \uc218\ud589\ud560 \uac83\uc785\ub2c8\ub2e4.<\/p>","protected":false},"featured_media":468753,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477797","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Large Language Models<\/mark>","faq_items":[{"question":"What are Large Language Models?","answer":"<p>Large language models are advanced AI technologies designed to understand and generate human language. They utilize deep learning algorithms and massive data sets to achieve impressive language processing capabilities, revolutionizing various fields like natural language processing, machine translation, chatbots, and more.<\/p>"},{"question":"How did Large Language Models originate?","answer":"<p>The concept of language models has a long history in AI research, but the breakthrough for large language models came in the 2010s with the emergence of deep learning and access to vast datasets. The first mention of large language models can be traced back to a 2013 paper by Tomas Mikolov and colleagues at Google, introducing the Word2Vec model.<\/p>"},{"question":"How do Large Language Models work?","answer":"<p>Large language models rely on transformer architectures, which consist of multiple layers of self-attention mechanisms. These mechanisms enable the models to process and generate language more efficiently and in parallel. The models' primary objective is to predict the likelihood of the next word in a sequence based on the context of preceding words, known as language modeling.<\/p>"},{"question":"What are the key features of Large Language Models?","answer":"<p>The key features of large language models include their massive size with hundreds of millions to billions of parameters, contextual understanding of words based on the surrounding context, transfer learning for versatile applications, creativity in text generation, and multilingual capabilities.<\/p>"},{"question":"What types of Large Language Models exist?","answer":"<p>Various types of large language models are available, each with different parameter sizes and strengths. Some popular ones include GPT-3, BERT, RoBERTa, and XLNet, each excelling in specific language processing tasks.<\/p>"},{"question":"How are Large Language Models used, and what problems do they face?","answer":"<p>Large language models find application in natural language processing, machine translation, chatbots, and content generation. However, they face challenges like resource-intensive training, potential bias in outputs, and privacy concerns. Solutions include efficient architectures, bias mitigation techniques, and ethical guidelines.<\/p>"},{"question":"How do Large Language Models compare with other language technologies?","answer":"<p>Large language models differ from word embeddings, recurrent neural networks (RNNs), machine translation, and sentiment analysis in terms of scale, applications, and processing capabilities.<\/p>"},{"question":"What are the future perspectives of Large Language Models?","answer":"<p>The future of large language models looks promising with research focusing on efficiency, multimodal learning, zero-shot learning, and continual learning, enabling even more powerful and adaptable language processing systems.<\/p>"},{"question":"How are Proxy Servers associated with Large Language Models?","answer":"<p>Proxy servers play a vital role in supporting large language models by anonymizing user data for ethical data collection, enhancing security, and enabling distributed model inference for improved response times.<\/p>"},{"question":"Where can I find more information about Large Language Models?","answer":"<p>For further information about large language models, explore the following resources:<\/p><ul><li>OpenAI's GPT-3 (<a href=\"https:\/\/openai.com\/models\/gpt-3\" target=\"_new\">https:\/\/openai.com\/models\/gpt-3<\/a>)<\/li><li>BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (<a href=\"https:\/\/arxiv.org\/abs\/1810.04805\" target=\"_new\">https:\/\/arxiv.org\/abs\/1810.04805<\/a>)<\/li><li>XLNet: Generalized Autoregressive Pretraining for Language Understanding (<a href=\"https:\/\/arxiv.org\/abs\/1906.08237\" target=\"_new\">https:\/\/arxiv.org\/abs\/1906.08237<\/a>)<\/li><li>Proxy Server Provider - OneProxy (<a href=\"https:\/\/oneproxy.pro\" target=\"_new\">https:\/\/oneproxy.pro<\/a>)<\/li><\/ul><p>At OneProxy, we embrace the world of language AI and provide top-notch proxy server solutions to support your AI-driven endeavors.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/wiki\/477797","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/wiki\/477797\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/media\/468753"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/kr\/wp-json\/wp\/v2\/media?parent=477797"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}