{"id":103181,"date":"2022-02-03T09:36:41","date_gmt":"2022-02-03T07:36:42","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/deepmind-predstavil-sistemu-mashinnogo-obucheniya-dlya-generaczii-koda-po-tekstovomu-opisaniyu-zadachi"},"modified":"2022-02-03T09:36:41","modified_gmt":"2022-02-03T07:36:42","slug":"deepmind-predstavil-sistemu-mashinnogo-obucheniya-dlya-generaczii-koda-po-tekstovomu-opisaniyu-zadachi","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sl\/blog\/news\/deepmind-predstavil-sistemu-mashinnogo-obucheniya-dlya-generaczii-koda-po-tekstovomu-opisaniyu-zadachi","title":{"rendered":"DeepMind je predstavil sistem strojnega u\u010denja za generiranje kode na podlagi pisnega opisa naloge","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Podjetje DeepMind, znano po svojih razvojih na podro\u010dju umetne inteligence in gradnji nevronskih mre\u017e, ki so sposobne igrati ra\u010dunalni\u0161ke in namizne igre na ravni \u010dloveka, je predstavilo projekt AlphaCode, ki razvija sistem strojnega u\u010denja za generiranje kode, sposoben sodelovati na programskih tekmovanjih na platformi Codeforces in pokazati povpre\u010den rezultat. Klju\u010dna zna\u010dilnost razvoja je sposobnost generiranja kode v programskih jezikih Python ali C++, pri \u010demer sprejema besedilo z opredelitvijo naloge v angle\u0161\u010dini. <\/p>\n

Za testiranje sistema je bilo izbranih 10 novih tekmovanj Codeforces z ve\u010d kot 5000 udele\u017eenci, ki so potekala po koncu usposabljanja modela strojnega u\u010denja. Rezultati re\u0161evanja nalog so omogo\u010dili sistemu AlphaCode, da je dosegel pribli\u017eno sredino lestvice omenjenih tekmovanj (54,3 %). Napovedana skupna ocena AlphaCode je zna\u0161ala 1238 to\u010dk, kar zagotavlja uvrstitev v najvi\u0161jih 28 % vseh udele\u017eencev Codeforces, ki so vsaj enkrat sodelovali na tekmovanjih v zadnjih 6 mesecih. Opa\u017eeno je, da projekt trenutno \u0161e vedno v fazi razvoja in da se v prihodnosti na\u010drtuje izbolj\u0161anje kakovosti generirane kode ter razvoj AlphaCode v smeri sistemov, ki pomagajo pri pisanju kode ali orodij za razvoj aplikacij, ki jih lahko uporabljajo ljudje brez znanja programiranja. <\/p>\n

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\"DeepMind<\/center> <\/p>\n

Za grobu obu\u010davanje sistema ma\u0161inskog u\u010denja kori\u0161\u0107ena je kodna baza dostupna u javnim GitHub repozitorijumima. Nakon pripreme po\u010detnog modela, izvr\u0161avano je optimizovanje faze, zasnovano na kolekciji koda sa primerima zadataka i re\u0161enjima ponu\u0111enim u\u010desnicima takmi\u010denja Codeforces, CodeChef, HackerEarth, AtCoder i Aizu. Ukupno je za obu\u010davanje kori\u0161\u0107eno 715 GB koda sa GitHub-a i vi\u0161e od milion primera re\u0161enja standardnih zadataka takmi\u010denja. Pre prelaska na generisanje koda, tekst zadatka prolazi kroz fazu normalizacije, tokom koje se isklju\u010duju sve nepotrebne stvari i ostavljaju samo zna\u010dajni delovi.

\"DeepMind<\/center>
\n
Izvor: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f DeepMind, \u043f\u043e\u043b\u0443\u0447\u0438\u0432\u0448\u0430\u044f \u0438\u0437\u0432\u0435\u0441\u0442\u043d\u043e\u0441\u0442\u044c \u0441\u0432\u043e\u0438\u043c\u0438 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0430\u043c\u0438 \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 \u0438\u0441\u043a\u0443\u0441\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u0438\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0430 \u0438 \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439, \u0441\u043f\u043e\u0441\u043e\u0431\u043d\u044b\u0445 \u0438\u0433\u0440\u0430\u0442\u044c \u0432 \u043a\u043e\u043c\u043f\u044c\u044e\u0442\u0435\u0440\u043d\u044b\u0435 \u0438 \u043d\u0430\u0441\u0442\u043e\u043b\u044c\u043d\u044b\u0435 \u0438\u0433\u0440\u044b \u043d\u0430 \u0443\u0440\u043e\u0432\u043d\u0435 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[…]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":103182,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-103181","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47DeepMind je predstavio sistem ma\u0161inskog u\u010denja za generisanje koda na osnovu tekstualnog opisa zadatka | ProHoster","description":"Kompanija DeepMind, poznata po svojim razvojnim radovima u oblasti ve\u0161ta\u010dke inteligencije i izgradnji neuronskih mre\u017ea sposobnih da igraju kompjuterske i stolne igre na ljudskom nivou, predstavila je 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