{"id":13401,"date":"2024-07-14T14:53:31","date_gmt":"2024-07-14T14:53:31","guid":{"rendered":"https:\/\/dailyai.com\/?p=13401"},"modified":"2024-07-14T14:53:31","modified_gmt":"2024-07-14T14:53:31","slug":"ai-model-performance-is-it-reasoning-or-simply-reciting","status":"publish","type":"post","link":"https:\/\/dailyai.com\/fr\/2024\/07\/ai-model-performance-is-it-reasoning-or-simply-reciting\/","title":{"rendered":"Performance des mod\u00e8les d'IA : S'agit-il d'un raisonnement ou d'une simple r\u00e9citation ?"},"content":{"rendered":"

Lorsque ChatGPT vous donne la bonne r\u00e9ponse \u00e0 votre demande, raisonne-t-il \u00e0 travers la demande ou se souvient-il simplement de la r\u00e9ponse \u00e0 partir de ses donn\u00e9es d'entra\u00eenement ?<\/strong><\/p>\n

Les chercheurs du Computer Science and Artificial Intelligence Laboratory (CSAIL) du MIT ont con\u00e7u une s\u00e9rie de tests pour d\u00e9terminer si les mod\u00e8les d'IA \"pensent\" ou s'ils ont simplement une bonne m\u00e9moire.<\/p>\n

Lorsque vous demandez \u00e0 un mod\u00e8le d'intelligence artificielle de r\u00e9soudre un probl\u00e8me math\u00e9matique tel que \"Quel est le rapport entre 27 et 62 ? 89. Comment savoir s'il comprend l'arithm\u00e9tique sous-jacente ou s'il a simplement vu le probl\u00e8me dans ses donn\u00e9es d'apprentissage ?<\/p>\n

En leur document<\/a>Les chercheurs ont test\u00e9 GPT-4, GPT-3.5 Turbo, Claude 1.3 et PaLM2 pour voir s'ils pouvaient \"se g\u00e9n\u00e9raliser non seulement \u00e0 des instances in\u00e9dites de t\u00e2ches connues, mais aussi \u00e0 de nouvelles t\u00e2ches\".<\/p>\n

Ils ont con\u00e7u une s\u00e9rie de 11 t\u00e2ches l\u00e9g\u00e8rement diff\u00e9rentes des t\u00e2ches standard dans lesquelles les LLM obtiennent g\u00e9n\u00e9ralement de bons r\u00e9sultats.<\/p>\n

Les LLM devraient obtenir les m\u00eames r\u00e9sultats dans les \"t\u00e2ches contrefactuelles\" s'ils utilisent des proc\u00e9dures g\u00e9n\u00e9rales et transf\u00e9rables de r\u00e9solution des t\u00e2ches.<\/p>\n

Si un LLM \"comprend\" les math\u00e9matiques, il devrait fournir la r\u00e9ponse correcte \u00e0 un probl\u00e8me math\u00e9matique en base 10 et en base 9, rarement utilis\u00e9e, par exemple.<\/p>\n

Voici quelques exemples de t\u00e2ches et les performances de GPT-4.<\/p>\n

\"\"
Performances du GPT-4 dans les t\u00e2ches standard par d\u00e9faut (bleu) et dans les t\u00e2ches contrefactuelles l\u00e9g\u00e8rement modifi\u00e9es (orange). Des exemples de t\u00e2ches et de r\u00e9ponses correctes sont pr\u00e9sent\u00e9s ici. Source : arXiv<\/figcaption><\/figure>\n

Les performances du GPT-4 dans les tests standard (ligne bleue) sont bonnes, mais ses capacit\u00e9s en math\u00e9matiques, en raisonnement logique, en raisonnement spatial et autres (ligne orange) se d\u00e9gradent de mani\u00e8re significative lorsque la t\u00e2che est l\u00e9g\u00e8rement modifi\u00e9e.<\/p>\n

Les autres mod\u00e8les ont pr\u00e9sent\u00e9 une d\u00e9gradation similaire, le GPT-4 arrivant en t\u00eate.<\/p>\n

Malgr\u00e9 cette d\u00e9gradation, les performances dans les t\u00e2ches contrefactuelles sont rest\u00e9es sup\u00e9rieures au hasard. Les mod\u00e8les d'IA tentent de raisonner \u00e0 travers ces t\u00e2ches, mais ne sont pas tr\u00e8s performants.<\/p>\n

Les r\u00e9sultats montrent que les performances impressionnantes des mod\u00e8les d'IA dans des t\u00e2ches telles que les examens universitaires reposent sur un excellent rappel des donn\u00e9es d'apprentissage, et non sur le raisonnement. Cela montre en outre que les mod\u00e8les d'IA ne peuvent pas \u00eatre g\u00e9n\u00e9ralis\u00e9s \u00e0 des t\u00e2ches in\u00e9dites,<\/p>\n

Zhaofeng Wu, doctorant du MIT en g\u00e9nie \u00e9lectrique et en informatique, affili\u00e9 au CSAIL, et auteur principal de l'article, a d\u00e9clar\u00e9 : \"Nous avons d\u00e9couvert un aspect fascinant des grands mod\u00e8les de langage : ils excellent dans les sc\u00e9narios familiers, un peu comme un chemin bien trac\u00e9, mais \u00e9prouvent des difficult\u00e9s lorsque le terrain n'est pas familier. Cette d\u00e9couverte est cruciale car nous nous effor\u00e7ons d'am\u00e9liorer l'adaptabilit\u00e9 de ces mod\u00e8les et d'\u00e9largir leurs horizons d'application.\"<\/p>\n

Nous avons vu une d\u00e9monstration similaire de cette incapacit\u00e9 \u00e0 g\u00e9n\u00e9raliser lorsque nous avons explor\u00e9 \u00e0 quel point les mod\u00e8les d'IA sont mauvais \u00e0 la r\u00e9solution d'une \u00e9nigme simplifi\u00e9e de travers\u00e9e de rivi\u00e8re.<\/a><\/p>\n

Les chercheurs ont conclu que lorsque les d\u00e9veloppeurs analysent leurs mod\u00e8les, ils devraient \"consid\u00e9rer les capacit\u00e9s abstraites comme d\u00e9tach\u00e9es des performances observ\u00e9es\".<\/p>\n

L'approche \"formation-test\" peut faire progresser un mod\u00e8le dans les crit\u00e8res de r\u00e9f\u00e9rence, mais n'offre pas une v\u00e9ritable mesure de la mani\u00e8re dont le mod\u00e8le se comportera lorsqu'il sera confront\u00e9 \u00e0 une nouvelle t\u00e2che \u00e0 r\u00e9soudre.<\/p>\n

Selon les chercheurs, le probl\u00e8me vient en partie du fait que ces mod\u00e8les ne sont form\u00e9s que sur des textes de surface.<\/p>\n

Si les LLM sont expos\u00e9s \u00e0 davantage de donn\u00e9es contextualis\u00e9es et de repr\u00e9sentations s\u00e9mantiques du monde r\u00e9el, ils pourraient \u00eatre en mesure de g\u00e9n\u00e9raliser lorsqu'on leur pr\u00e9sente des variations de t\u00e2ches.<\/p>","protected":false},"excerpt":{"rendered":"

Lorsque ChatGPT vous donne la bonne r\u00e9ponse \u00e0 votre question, raisonne-t-il \u00e0 travers la demande ou se souvient-il simplement de la r\u00e9ponse \u00e0 partir de ses donn\u00e9es d'entra\u00eenement ? Les chercheurs du Computer Science and Artificial Intelligence Laboratory (CSAIL) du MIT ont con\u00e7u une s\u00e9rie de tests pour d\u00e9terminer si les mod\u00e8les d'IA \"pensent\" ou s'ils ont simplement une bonne m\u00e9moire. Lorsque vous demandez \u00e0 un mod\u00e8le d'IA de r\u00e9soudre un probl\u00e8me math\u00e9matique tel que \"Quel est le nombre 27+62 ?\", il vous donne rapidement la bonne r\u00e9ponse : 89. Comment savoir s'il comprend l'arithm\u00e9tique sous-jacente ou s'il a simplement vu le probl\u00e8me dans ses donn\u00e9es d'apprentissage ? Dans leur article, les chercheurs ont test\u00e9 le GPT-4,<\/p>","protected":false},"author":6,"featured_media":13404,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[118],"class_list":["post-13401","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-llms"],"yoast_head":"\nAI model performance: Is it reasoning or simply reciting? | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/fr\/2024\/07\/ai-model-performance-is-it-reasoning-or-simply-reciting\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI model performance: Is it reasoning or simply reciting? | DailyAI\" \/>\n<meta property=\"og:description\" content=\"When ChatGPT gives you the right answer to your prompt, does it reason through the request or simply remember the answer from its training data? MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers designed a series of tests to see if AI models \u201cthink\u201d or just have good memories. When you prompt an AI model to solve a math problem like \u201cWhat is 27+62?\u201d it comes back quickly with the correct answer: 89. How could we tell if it understands the underlying arithmetic or simply saw the problem in its training data? In their paper, the researchers tested GPT-4,\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/fr\/2024\/07\/ai-model-performance-is-it-reasoning-or-simply-reciting\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-07-14T14:53:31+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2024\/07\/AI-reasoning.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1792\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Eugene van der Watt\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:site\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"Eugene van der Watt\" \/>\n\t<meta name=\"twitter:label2\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"NewsArticle\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/ai-model-performance-is-it-reasoning-or-simply-reciting\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/ai-model-performance-is-it-reasoning-or-simply-reciting\\\/\"},\"author\":{\"name\":\"Eugene van der Watt\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/#\\\/schema\\\/person\\\/7ce525c6d0c79838b7cc7cde96993cfa\"},\"headline\":\"AI model performance: Is it reasoning or simply reciting?\",\"datePublished\":\"2024-07-14T14:53:31+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/ai-model-performance-is-it-reasoning-or-simply-reciting\\\/\"},\"wordCount\":532,\"publisher\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/ai-model-performance-is-it-reasoning-or-simply-reciting\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/dailyai.com\\\/wp-content\\\/uploads\\\/2024\\\/07\\\/AI-reasoning.webp\",\"keywords\":[\"LLMS\"],\"articleSection\":[\"Industry\"],\"inLanguage\":\"fr-FR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/ai-model-performance-is-it-reasoning-or-simply-reciting\\\/\",\"url\":\"https:\\\/\\\/dailyai.com\\\/2024\\\/07\\\/ai-model-performance-is-it-reasoning-or-simply-reciting\\\/\",\"name\":\"AI model performance: Is it reasoning or simply reciting? 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