{"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\/ro\/blog\/news\/deepmind-predstavil-sistemu-mashinnogo-obucheniya-dlya-generaczii-koda-po-tekstovomu-opisaniyu-zadachi","title":{"rendered":"DeepMind a prezentat un sistem de \u00eenv\u0103\u021bare automat\u0103 pentru generarea de cod pe baza unei descrieri textuale a sarcinii.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Compania DeepMind, cunoscut\u0103 pentru dezvolt\u0103rile sale \u00een domeniul inteligen\u021bei artificiale \u0219i construirea de re\u021bele neuronale capabile s\u0103 joace jocuri pe computer \u0219i de mas\u0103 la nivel uman, a lansat proiectul AlphaCode, care dezvolt\u0103 un sistem de \u00eenv\u0103\u021bare automat\u0103 pentru generarea de cod, capabil s\u0103 participe la competi\u021bii de programare pe platforma Codeforces \u0219i s\u0103 demonstreze rezultate medii. Cea mai important\u0103 caracteristic\u0103 a dezvolt\u0103rii este capacitatea de a genera cod \u00een limbajele Python sau C++, primind ca input un text cu enun\u021bul problemei \u00een limba englez\u0103. <\/p>\n

Pentru testarea sistemului au fost selectate 10 noi competi\u021bii Codeforces cu peste 5000 de participan\u021bi, desf\u0103\u0219urate dup\u0103 finalizarea antrenamentului modelului de \u00eenv\u0103\u021bare automat\u0103. Rezultatele implement\u0103rii sarcinilor au permis sistemului AlphaCode s\u0103 ocupe aproximativ mijlocul clasamentului acestor competi\u021bii (54.3%). Ratingul total prev\u0103zut pentru AlphaCode a fost de 1238 de puncte, ceea ce asigur\u0103 intrarea \u00een Top 28% dintre to\u021bi participan\u021bii Codeforces care au participat cel pu\u021bin o dat\u0103 la competi\u021bii \u00een ultimele 6 luni. Se men\u021bioneaz\u0103 c\u0103 proiectul se afl\u0103 \u00eenc\u0103 \u00een stadiul ini\u021bial de dezvoltare \u0219i \u00een viitor se preconizeaz\u0103 \u00eembun\u0103t\u0103\u021birea calit\u0103\u021bii codului generat, precum \u0219i dezvoltarea AlphaCode \u00een direc\u021bia sistemelor care ajut\u0103 la scrierea codului sau a instrumentelor de dezvoltare a aplica\u021biilor care pot fi utilizate de c\u0103tre persoane f\u0103r\u0103 abilit\u0103\u021bi de programare. <\/p>\n

Proiectul utilizeaz\u0103 arhitectura de re\u021bea neuronal\u0103 \u201eTransformer\u201d \u00eempreun\u0103 cu metode de e\u0219antionare \u0219i filtrare, care permit generarea de diverse variante imprevizibile de cod, corespunz\u0103toare textului \u00een limbaj natural. Dup\u0103 filtrare, clustering \u0219i clasificare, din fluxul generat de variante este selectat cel mai optim cod opera\u021bional, care este apoi verificat pentru a ob\u021bine rezultatul corect (\u00een fiecare sarcin\u0103 a competi\u021biei sunt specificate exemple de date de intrare \u0219i rezultatul corespunz\u0103tor acestui exemplu, care trebuie ob\u021binut \u00een urma execu\u021biei programului).

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

Pentru antrenamentul robust al sistemului de \u00eenv\u0103\u021bare automat\u0103 a fost utilizat un cod disponibil \u00een repozitoarele publice de pe GitHub. Dup\u0103 preg\u0103tirea modelului ini\u021bial, a fost realizat\u0103 o faz\u0103 de optimizare, implementat\u0103 pe baza unei colec\u021bii de coduri cu exemple de probleme \u0219i solu\u021bii oferite participan\u021bilor la competi\u021biile Codeforces, CodeChef, HackerEarth, AtCoder \u0219i Aizu. \u00cen total, pentru antrenament s-au folosit 715 GB de cod de pe GitHub \u0219i mai mult de un milion de exemple de solu\u021bii pentru problemele tipice ale competi\u021biilor. \u00cenainte de a trece la generarea codului, textul problemei a trecut printr-o faz\u0103 de normalizare, \u00een care s-au exclus toate elementele inutile \u0219i au fost p\u0103strate doar p\u0103r\u021bile semnificative.

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

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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\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 a prezentat un sistem de \u00eenv\u0103\u021bare automat\u0103 pentru generarea de cod pe baza unei descrieri textuale a problemei | ProHoster","description":"Compania DeepMind, cunoscut\u0103 pentru dezvolt\u0103rile sale \u00een domeniul inteligen\u021bei artificiale \u0219i crearea re\u021belelor neuronale capabile s\u0103 joace jocuri pe computer \u0219i de societate la nivel uman, a 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