{"id":14615,"date":"2026-03-09T00:31:20","date_gmt":"2026-03-08T23:31:20","guid":{"rendered":"https:\/\/www.leaplytics.de\/?p=14615"},"modified":"2026-03-09T07:35:35","modified_gmt":"2026-03-09T06:35:35","slug":"andrej-karpathy-tikko-izlaida-autonomus-ai-agentus-kas-vada-petijumus-vienas-nakts-laika-luk-ko-tas-nozime-uznemumu-ai","status":"publish","type":"post","link":"https:\/\/www.leaplytics.de\/lv\/andrej-karpathy-tikko-izlaida-autonomus-ai-agentus-kas-vada-petijumus-vienas-nakts-laika-luk-ko-tas-nozime-uznemumu-ai\/","title":{"rendered":"Autom\u0101tisk\u0101 izp\u0113te - Andrejs Karpathy tikko izlaida autonomus m\u0101ksl\u012bg\u0101 intelekta a\u0123entus, kas veic p\u0113t\u012bjumus vienas nakts laik\u0101 - l\u016bk, ko tas noz\u012bm\u0113 uz\u0146\u0113mumu m\u0101ksl\u012bgajam intelektam"},"content":{"rendered":"<p><time datetime=\"2026-03-09\"><strong>2026. gada 9. marts<\/strong><\/time> - <em>Reakcija - AI Trends - 6 min las\u012bt<\/em><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:separator -->\n\n<hr class=\"wp-block-separator\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:heading {\"level\":2} -->\n\n<h2>Kas notika<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\n<p>Uz <time datetime=\"2026-03\">2026. gada marts<\/time>, Andrejs Karpati - biju\u0161ais Tesla AI direktors un OpenAI l\u012bdzdibin\u0101t\u0101js - public\u0113ja <a href=\"https:\/\/github.com\/karpathy\/autoresearch\" target=\"_blank\" rel=\"noopener noreferrer\">autoresearch par GitHub<\/a>, atv\u0113rt\u0101 koda ietvarstrukt\u016bra, kas \u013cauj m\u0101ksl\u012bg\u0101 intelekta a\u0123entiem autonomi veikt ma\u0161\u012bnm\u0101c\u012b\u0161an\u0101s eksperimentus vienas nakts laik\u0101, izmantojot vienu GPU. Galven\u0101 ideja: dodiet a\u0123entam apm\u0101c\u012bbas iestat\u012bjumu, ejiet gul\u0113t un pamostieties, lai redz\u0113tu 100 pabeigtus eksperimentus - katru no tiem modific\u0113jot kodu, apm\u0101cot piecas min\u016btes, p\u0101rbaudot, vai rezult\u0101ts uzlabojies, un atk\u0101rtojot. Cilp\u0101 nav iesaist\u012bts cilv\u0113ks. <strong>A\u0123ents nekad neapst\u0101jas, l\u012bdz j\u016bs to p\u0101rtraucat manu\u0101li.<\/strong> Da\u017eu dienu laik\u0101 p\u0113c izlai\u0161anas repo p\u0101rsniedza 8000 zvaig\u017e\u0146u.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:separator -->\n\n<hr class=\"wp-block-separator\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:heading {\"level\":2} -->\n\n<h2>Ko tas paties\u012bb\u0101 noz\u012bm\u0113 - ne tikai par to, kas tiek reklam\u0113ts<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\n<p>Preciz\u0113sim, kas ir un kas nav autom\u0101tisk\u0101 mekl\u0113\u0161ana. Tas nav visp\u0101r\u0113jas noz\u012bmes m\u0101ksl\u012bgais intelekts, kas aizst\u0101j datu zin\u0101tniekus. Tas ir stingri ierobe\u017eots cikls: viens a\u0123ents, viens fails, ko tas var modific\u0113t (<code>train.py<\/code>), viens fiks\u0113ts 5 min\u016b\u0161u nov\u0113rt\u0113\u0161anas logs, viena optimiz\u0113jam\u0101 metrika. Noz\u012bm\u012bga ir nevis darb\u012bbas joma, bet gan tas. <strong>arhitekt\u016bras l\u0113mums<\/strong> aiz t\u0101: piln\u012bgi autonoms a\u0123ents, kas veic eksperimentu, nolasa rezult\u0101tu, izlemj, ko izm\u0113\u0123in\u0101t t\u0101l\u0101k, un atk\u0101rto - ar skaidru nor\u0101d\u012bjumu kod\u0101, lai. <em>nekad neapst\u0101ties un nekad nepras\u012bt cilv\u0113kam at\u013cauju turpin\u0101t.<\/em><\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n\n<p>\u0160\u012b dizaina filozofija - autonoma, pa\u0161vad\u012bta, uz metriku balst\u012bta atk\u0101rto\u0161ana - ir veidne, uz kuru strauji virz\u0101s uz\u0146\u0113mumu m\u0101ksl\u012bgais intelekts. Ne tikai ML p\u0113tniec\u012bb\u0101, bet jebkur\u0101 jom\u0101, kur ir skaidrs m\u0113r\u0137is, izm\u0113r\u0101mi rezult\u0101ti un pietiekami liela mekl\u0113\u0161anas telpa, kur\u0101 cilv\u0113ka vad\u012bta iter\u0101cija ir v\u0101j\u0101 vieta. Tas raksturo iev\u0113rojamu da\u013cu no t\u0101, ko uz\u0146\u0113mumu BI un anal\u012btikas komandas dara katru dienu.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:separator -->\n\n<hr class=\"wp-block-separator\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:heading {\"level\":2} -->\n\n<h2>Tr\u012bs konkr\u0113tas sekas uz\u0146\u0113mumu komand\u0101m<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\n<p><strong>1. \"Agentic\" vairs nav p\u0113tniec\u012bbas j\u0113dziens - tas ir ra\u017eo\u0161anas modelis.<\/strong> Karpathy ieguld\u012bjums \u0161eit nav m\u0101ksl\u012bg\u0101 intelekta a\u0123entu ideja, bet gan pier\u0101d\u012bjums, ka ar t\u012bru, minim\u0101lu, viena faila implement\u0101ciju var veikt 100 noz\u012bm\u012bgus eksperimentus vienas nakts laik\u0101 uz komodit\u0101r\u0101s aparat\u016bras. Tikko iev\u0113rojami samazin\u0101j\u0101s barjera autonomo AI cilpu ievie\u0161anai uz\u0146\u0113mumu kontekst\u0101 - atskai\u0161u automatiz\u0101cijai, datu pl\u016bsmas optimiz\u0101cijai, dokumentu apstr\u0101dei. Komand\u0101m, kas ir gaid\u012bju\u0161as, kad tas \"nobried\u012bs\", vajadz\u0113tu p\u0101rkalibr\u0113t savus termi\u0146us.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n\n<p><strong>2. Cilv\u0113ka loma main\u0101s no dar\u012b\u0161anas uz p\u0101rskat\u012b\u0161anu.<\/strong> Starp eksperimentiem autom\u0101tisk\u0101s izp\u0113tes cilpa nepieprasa apstiprin\u0101jumu. T\u0101 \u0123ener\u0113, test\u0113, saglab\u0101 to, kas darbojas, noraida to, kas nedarbojas, un dodas t\u0101l\u0101k. Uz\u0146\u0113mumu izpratn\u0113 tas ir tie\u0161i saist\u012bts ar m\u0101ksl\u012bg\u0101 intelekta sist\u0113m\u0101m, kas sagatavo zi\u0146ojumus, veic scen\u0101riju anal\u012bzi vai autonomi apstr\u0101d\u0101 ien\u0101ko\u0161os piepras\u012bjumus - un izplata tikai tos rezult\u0101tus, par kuriem nepiecie\u0161ams cilv\u0113ka v\u0113rt\u0113jums. Tas neapdraud kvalific\u0113tus anal\u012bti\u0137us; tas ir vi\u0146u laika p\u0101rdal\u012bjums. Maz\u0101k \u0123ener\u0113\u0161anas, vair\u0101k nov\u0113rt\u0113\u0161anas.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n\n<p><strong>3. Datu kvalit\u0101te un skaidri pan\u0101kumu r\u0101d\u012bt\u0101ji k\u013c\u016bst oblig\u0101ti.<\/strong> Autom\u0101tisk\u0101 mekl\u0113\u0161ana darbojas, jo tai ir viennoz\u012bm\u012bga metrika: valid\u0101cijas bits uz baitu. Zem\u0101ks ir lab\u0101ks. Katrs eksperiments ir objekt\u012bvi sal\u012bdzin\u0101ms. Uz\u0146\u0113mumu vid\u0113 l\u012bdzv\u0113rt\u012bgs jaut\u0101jums ir \u0161\u0101ds: k\u0101ds ir j\u016bsu organiz\u0101cijas \"val_bpb\"? Ja j\u016bs nevarat defin\u0113t vienotu, izm\u0113r\u0101mu automatiz\u0113tas darba pl\u016bsmas veiksmes krit\u0113riju, autonomie a\u0123enti nevar optimiz\u0113ties t\u0101 sasnieg\u0161anai. Projekti, kas g\u016bs visliel\u0101ko labumu no a\u0123entu m\u0101ksl\u012bg\u0101 intelekta, ir tie, kas jau ir veiku\u0161i darbu, lai defin\u0113tu, ko noz\u012bm\u0113 \"lab\u0101k\" konkr\u0113tos, izm\u0113r\u0101mos terminos.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:separator -->\n\n<hr class=\"wp-block-separator\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:heading {\"level\":2} -->\n\n<h2>LeapLytics perspekt\u012bva<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\n<p>M\u0113s jau vair\u0101kus gadus veidojam m\u0101ksl\u012bg\u0101 intelekta sist\u0113mas uz\u0146\u0113mumu darba pl\u016bsm\u0101m - <a href=\"https:\/\/www.leaplytics.de\/lv\/maksligais-intelekts\/\">dokumentu apstr\u0101de, automatiz\u0113ta atskai\u0161u sagatavo\u0161ana, atbalsta automatiz\u0101cija.<\/a>. Karpathy demonstr\u0113 ML p\u0113tniec\u012bbas sl\u0101\u0146a modeli, kas ir t\u0101ds pats modelis, k\u0101du m\u0113s izmantojam biznesa procesu sl\u0101n\u012b: identific\u0113jiet atk\u0101rtojo\u0161os ciklu, defin\u0113jiet veiksmes krit\u0113riju, \u013caujiet a\u0123entam darboties un atkl\u0101jiet iz\u0146\u0113mumus, lai tos var\u0113tu p\u0101rbaud\u012bt cilv\u0113ks.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n\n<p>Autom\u0101tisk\u0101 izp\u0113te skaidri par\u0101da, ka <strong>\u0101truma starp\u012bba<\/strong>. 100 eksperimenti 8 stund\u0101s. Uz\u0146\u0113muma izteiksm\u0113: 100 dokumentu projekti p\u0101rskat\u012bti, 100 datu anom\u0101lijas atz\u012bm\u0113tas, 100 atbalsta bi\u013cetes kategoriz\u0113tas - kam\u0113r j\u016bsu komanda gu\u013c. Organiz\u0101cijas, kas to uzskata par zi\u0146k\u0101r\u012bbu, secin\u0101s, ka t\u0101s, kas to uzskata par infrastrukt\u016bru, b\u016bs iev\u0113rojami pavirz\u012bju\u0161\u0101s uz priek\u0161u l\u012bdz br\u012bdim, kad t\u0101s to p\u0101rdom\u0101s. Par \u0161o dinamiku m\u0113s jau esam rakst\u012bju\u0161i iepriek\u0161 saist\u012bb\u0101 ar <a href=\"https:\/\/www.leaplytics.de\/lv\/kapec-mes-izveidojam-savu-atbalsta-terzesanas-robotu-un-kas-cela-gaja-greizi\/\">m\u016bsu pa\u0161u p\u0101reja uz m\u0101ksl\u012bg\u0101 intelekta atbalstu.<\/a> - automatiz\u0101cijas priek\u0161roc\u012bbas nav redzamas, kam\u0113r t\u0101s nav redzamas.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:separator -->\n\n<hr class=\"wp-block-separator\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:heading {\"level\":2} -->\n\n<h2>Kas organiz\u0101cij\u0101m j\u0101dara tagad<\/h2>\n<!-- \/wp:heading -->\n\n<ul>\n  <li><strong>Identific\u0113jiet vienu atk\u0101rtotu, izm\u0113r\u0101mu darba procesu \u0161oned\u0113\u013c.<\/strong> Nevis neskaidrs \"mums j\u0101automatiz\u0113 zi\u0146o\u0161ana\". Konkr\u0113ts cikls: \u0161\u0101da veida dokuments, apstr\u0101d\u0101ts \u0161\u0101d\u0101 veid\u0101, nov\u0113rt\u0113ts p\u0113c \u0161\u012b krit\u0113rija. Autom\u0101tisk\u0101 mekl\u0113\u0161ana ir noder\u012bgs ment\u0101lais modelis - ja j\u016bs nevarat aprakst\u012bt savu darba pl\u016bsmu t\u0101, k\u0101 Karpathy apraksta savu apm\u0101c\u012bbas cilpu, t\u0101 v\u0113l nav gatava a\u0123entu automatiz\u0101cijai.<\/li>\n  <li><strong>Ieguldiet datu kvalit\u0101t\u0113 pirms a\u0123entu izvieto\u0161anas.<\/strong> Autonomie a\u0123enti pastiprina visu, ar ko tie str\u0101d\u0101. T\u012bri, konsekventi struktur\u0113ti ievades dati rada noder\u012bgu autonomu produkciju. Nek\u0101rt\u012bgi, nekonsekventi dati rada p\u0101rliecino\u0161i k\u013c\u016bdainu autonomo izvades rezult\u0101tu - 100x \u0101tr\u0101k nek\u0101 cilv\u0113ks, kas pie\u013cauj t\u0101du pa\u0161u k\u013c\u016bdu. Datu p\u0101rvald\u012bba tagad ir m\u0101ksl\u012bg\u0101 intelekta gatav\u012bbas jaut\u0101jums, nevis tikai m\u0101jsaimniec\u012bbas jaut\u0101jums.<\/li>\n  <li><strong>\"M\u0101ksl\u012bg\u0101 intelekta strat\u0113\u0123iju\" p\u0101rveidojiet k\u0101 \"kuras cilpas m\u0113s automatiz\u0113sim vispirms\".<\/strong> Liel\u0101k\u0101 da\u013ca uz\u0146\u0113mumu m\u0101ksl\u012bg\u0101 intelekta strat\u0113\u0123iju joproj\u0101m ir saist\u012btas ar r\u012bkiem un pieg\u0101d\u0101t\u0101jiem. Lietder\u012bg\u0101ka sist\u0113ma p\u0113c automatiz\u0113t\u0101s izp\u0113tes ir \u0161\u0101da: kuras no m\u016bsu darba pl\u016bsm\u0101m ir cilpa ar izm\u0113r\u0101mu rezult\u0101tu? Sarindojiet t\u0101s p\u0113c apjoma un ietekmes. S\u0101ciet ar visliel\u0101k\u0101 apjoma, visskaidr\u0101k izm\u0113r\u0101mo cilpu. T\u0101 ir j\u016bsu pirm\u0101 a\u0123enta izvieto\u0161ana.<\/li>\n<\/ul>\n\n<!-- wp:separator -->\n\n<hr class=\"wp-block-separator\"\/>\n<!-- \/wp:separator -->\n\n<!-- wp:heading {\"level\":2} -->\n\n<h2>Kas notiks t\u0101l\u0101k<\/h2>\n<!-- \/wp:heading -->\n\n<!-- wp:paragraph -->\n\n<p>Autom\u0101tisk\u0101 mekl\u0113\u0161ana ir apzin\u0101ti minim\u0101la - viens GPU, viens fails, viena metrika. T\u016bl\u012bt\u0113jais n\u0101kamais solis, kas jau ir redzams kopienas forkos, kas izriet no repo, ir vair\u0101ku a\u0123entu varianti: viens a\u0123ents \u0123ener\u0113 hipot\u0113zes, otrs veic eksperimentus, tre\u0161ais izv\u0113rt\u0113 un sintez\u0113 rezult\u0101tus. Uz\u0146\u0113muma izpratn\u0113 tas noz\u012bm\u0113 piln\u012bgu darba pl\u016bsmas automatiz\u0101ciju: uz\u0146em\u0161anu, apstr\u0101di, kvalit\u0101tes p\u0101rbaudi un rezult\u0101tu mar\u0161rut\u0113\u0161anu veic koordin\u0113ta a\u0123entu \u0137\u0113de ar cilv\u0113ka p\u0101rbaudi tikai noteiktos iz\u0146\u0113muma punktos.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n\n<p>Svar\u012bg\u0101kas p\u0101rmai\u0146as ir kult\u016bras jom\u0101. Karpathy formul\u0113jums, ka m\u0101ksl\u012bg\u0101 intelekta p\u0113tniec\u012bbu \"agr\u0101k veica ga\u013cas datori starp \u0113\u0161anu, gul\u0113\u0161anu un cit\u0101m izklaid\u0113m\", ir apzin\u0101ti provokat\u012bvs. Ta\u010du pamat\u0101 eso\u0161\u0101 j\u0113ga ir nopietna: konkurences priek\u0161roc\u012bbas ar m\u0101ksl\u012bgo intelektu saist\u012bt\u0101 darb\u0101 main\u0101s no cilv\u0113ka izpildes \u0101truma uz projekt\u0113to cilpu kvalit\u0101ti un metriku skaidr\u012bbu, uz kur\u0101m j\u016bs optimiz\u0113jat. Tas pats attiecas uz ML p\u0113tniec\u012bbu. T\u0101pat tas attiecas ar\u012b uz uz\u0146\u0113mumu anal\u012btiku, riska zi\u0146o\u0161anu un dokumentiem intens\u012bv\u0101m darba pl\u016bsm\u0101m. Jaut\u0101jums vairs nav par to, vai \u0161\u012bs cilpas veidot. Jaut\u0101jums ir par to, cik \u0101tri.<\/p>\n<!-- \/wp:paragraph --b>","protected":false},"excerpt":{"rendered":"<p>2026. gada 9. marts - Reakcija - AI Trends - 6 min\u016bte las\u012bt Kas notika 2026. gada mart\u0101 Andrejs Karpati (Andrej Karpathy) - biju\u0161ais Tesla AI direktors un OpenAI l\u012bdzdibin\u0101t\u0101js - GitHub vietn\u0113 public\u0113ja autoresearch - atv\u0113rt\u0101 koda ietvaru, kas \u013cauj m\u0101ksl\u012bg\u0101 intelekta a\u0123entiem autonomi veikt ma\u0161\u012bnm\u0101c\u012b\u0161an\u0101s eksperimentus vienas nakts laik\u0101, izmantojot vienu GPU. Galven\u0101 ideja: dot a\u0123entam ... <\/p>","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-14615","post","type-post","status-publish","format-standard","hentry","category-news","latest_post"],"_links":{"self":[{"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/posts\/14615","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/comments?post=14615"}],"version-history":[{"count":2,"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/posts\/14615\/revisions"}],"predecessor-version":[{"id":14617,"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/posts\/14615\/revisions\/14617"}],"wp:attachment":[{"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/media?parent=14615"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/categories?post=14615"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.leaplytics.de\/lv\/wp-json\/wp\/v2\/tags?post=14615"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}