{"id":11235,"date":"2024-04-03T14:29:19","date_gmt":"2024-04-03T14:29:19","guid":{"rendered":"https:\/\/dailyai.com\/?p=11235"},"modified":"2024-04-03T14:29:19","modified_gmt":"2024-04-03T14:29:19","slug":"berkeley-researchers-build-ai-forecasting-system-that-bests-humans","status":"publish","type":"post","link":"https:\/\/dailyai.com\/fr\/2024\/04\/berkeley-researchers-build-ai-forecasting-system-that-bests-humans\/","title":{"rendered":"Des chercheurs de Berkeley mettent au point un syst\u00e8me de pr\u00e9vision par IA qui surpasse les humains"},"content":{"rendered":"

Des chercheurs de l'universit\u00e9 de Berkeley, en Californie, ont mis au point un syst\u00e8me de pr\u00e9vision IA capable de pr\u00e9dire des \u00e9v\u00e9nements futurs avec une pr\u00e9cision similaire \u00e0 celle de la sagesse des foules humaines.\u00a0<\/b><\/p>\n

Les LLM n'\u00e9tant pas con\u00e7us pour la pr\u00e9vision d'\u00e9v\u00e9nements, l'\u00e9quipe a construit un syst\u00e8me de pr\u00e9vision \u00e0 partir de GPT-4 en utilisant une nouvelle approche appel\u00e9e \"raisonnement augment\u00e9 par la recherche\".<\/p>\n

Ce processus en plusieurs \u00e9tapes a consist\u00e9 \u00e0 entra\u00eener le GPT-4 \u00e0 rechercher des informations pertinentes, \u00e0 \u00e9valuer leur pertinence et \u00e0 les int\u00e9grer dans son processus de raisonnement avant de faire une pr\u00e9diction.\u00a0<\/span><\/p>\n

Voici comment cela fonctionne :<\/span><\/p>\n

    \n
  1. R\u00e9cup\u00e9ration<\/b>: Le syst\u00e8me d'IA utilise GPT-4 pour g\u00e9n\u00e9rer des requ\u00eates de recherche bas\u00e9es sur la question de la pr\u00e9vision et les sous-questions, en r\u00e9cup\u00e9rant un large ensemble d'articles de presse potentiellement pertinents.<\/span><\/li>\n
  2. \u00c9valuation de la pertinence<\/b>: GPT-4 \u00e9value la pertinence de chaque article retrouv\u00e9, en \u00e9cartant les articles \u00e0 faible score afin de r\u00e9duire le nombre d'informations disponibles.<\/span><\/li>\n
  3. Synth\u00e8se<\/b>: Le GPT-4 r\u00e9sume chaque article \u00e0 ses points cl\u00e9s, en se concentrant sur les d\u00e9tails li\u00e9s \u00e0 la question de la pr\u00e9vision.<\/span><\/li>\n
  4. Raisonnement<\/b>: \u00c0 l'aide de \"messages-guides\", GPT-4 analyse les articles r\u00e9sum\u00e9s et produit une pr\u00e9vision d\u00e9taill\u00e9e accompagn\u00e9e d'une justification explicative. Ces invites guident le processus de r\u00e9flexion du mod\u00e8le, encourageant une approche syst\u00e9matique du raisonnement.<\/span><\/li>\n<\/ol>\n

    L'\u00e9quipe de Berkeley a ensuite pouss\u00e9 le syst\u00e8me un peu plus loin en proc\u00e9dant \u00e0 un r\u00e9glage fin auto-supervis\u00e9.\u00a0<\/span><\/p>\n

    Ils ont g\u00e9n\u00e9r\u00e9 un grand nombre de pr\u00e9visions d'IA sur des questions pass\u00e9es dont les r\u00e9ponses \u00e9taient connues et ont s\u00e9lectionn\u00e9 des exemples o\u00f9 l'IA avait surpass\u00e9 la \"sagesse de la foule\", d\u00e9finie comme l'ensemble des pr\u00e9dictions des pr\u00e9visionnistes humains.<\/span><\/p>\n

    En affinant GPT-4 sur ces exemples, les chercheurs ont appris au mod\u00e8le \u00e0 \u00e9muler les sch\u00e9mas de raisonnement qui ont permis d'obtenir les meilleures pr\u00e9visions.<\/span><\/p>\n

    R\u00e9sultats<\/h2>\n

    Test\u00e9e sur des questions de pr\u00e9vision \u00e0 partir de juin 2023, l'IA a obtenu un score de Brier de 0,179, contre un score de 0,149 pour le pr\u00e9visionniste humain.\u00a0<\/span><\/p>\n

    L'IA a \u00e9t\u00e9 particuli\u00e8rement performante sur les questions \u00e0 forte incertitude humaine au d\u00e9but du processus de pr\u00e9vision et lorsqu'elle avait acc\u00e8s \u00e0 un nombre suffisant d'articles pertinents sur un sujet particulier.\u00a0<\/span><\/p>\n

    \"Pr\u00e9visions
    (a) Le syst\u00e8me obtient de meilleurs r\u00e9sultats qu'un groupe de personnes lorsqu'il dispose de 0 \u00e0 10 articles pertinents.
    (b) Lorsque les personnes ne sont pas s\u00fbres de leurs pr\u00e9dictions (niveaux de confiance entre 0,3 et 0,7), le syst\u00e8me fait mieux, avec un score de Brier de 0,199 contre 0,246. Cependant, lorsque les personnes sont tr\u00e8s s\u00fbres d'elles (pr\u00e9dictions inf\u00e9rieures \u00e0 0,05), elles obtiennent de meilleurs r\u00e9sultats que notre syst\u00e8me.
    (c) La pr\u00e9cision du syst\u00e8me est plus \u00e9lev\u00e9e au d\u00e9but de la collecte d'informations. Source : ArXiv<\/a> (acc\u00e8s libre).<\/figcaption><\/figure>\n

    Les auteurs \u00e9crivent dans le <\/span>\u00e9tude<\/span><\/a>\u00c0 notre connaissance, il s'agit du premier syst\u00e8me automatis\u00e9 dont la capacit\u00e9 de pr\u00e9vision se rapproche du niveau de la foule humaine, qui est g\u00e9n\u00e9ralement plus forte que celle des pr\u00e9visionnistes humains.<\/span><\/p>\n

    Il y a eu une petite bizarrerie : le syst\u00e8me a sembl\u00e9 s'am\u00e9liorer avec plus d'articles et donc plus de certitude dans les pr\u00e9visions. Cela pourrait s'expliquer par le fait que le mod\u00e8le \"couvre\" ses pr\u00e9visions.<\/p>\n

    Les chercheurs d\u00e9crivent ce ph\u00e9nom\u00e8ne comme suit : \"Nous supposons que cela provient de la tendance de notre mod\u00e8le \u00e0 couvrir les pr\u00e9dictions en raison de sa formation \u00e0 la s\u00e9curit\u00e9\".<\/p>\n

    Implications<\/h2>\n

    Selon les chercheurs, les d\u00e9cideurs politiques, les entreprises et les responsables de la sant\u00e9 publique pourraient tous b\u00e9n\u00e9ficier de cette forme de pr\u00e9vision linguistique de l'IA.<\/span><\/p>\n

    \"\u00c0 l'avenir, les d\u00e9cideurs politiques pourraient consulter les IA sur les actions les plus susceptibles de produire les r\u00e9sultats souhait\u00e9s\", d\u00e9clare Dan Hendrycks du Center for AI Safety en Californie.<\/p>\n

    Il propose que des mod\u00e8les de pr\u00e9diction permettent de faire face aux risques \u00e0 venir pos\u00e9s par l'IA. \"Les robots de pr\u00e9vision nous aideraient \u00e0 anticiper et \u00e0 \u00e9viter ces risques\", explique M. Hendrycks. a d\u00e9clar\u00e9 au New Scientist<\/a>.<\/p>\n

    D'autres tentatives ont \u00e9t\u00e9 faites pour pr\u00e9dire les \u00e9v\u00e9nements complexes de la vie \u00e0 l'aide de l'IA, notamment un mod\u00e8le form\u00e9 par des chercheurs danois pour pr\u00e9dire les \u00e9v\u00e9nements de la vie. <\/span>pr\u00e9dire les risques de d\u00e9c\u00e8s pr\u00e9matur\u00e9<\/span><\/a>.\u00a0<\/span><\/p>\n

    L'exploitation de l'IA pour des applications pr\u00e9dictives qui affectent la vie des gens pose des questions \u00e9thiques, notamment celle de la transparence, de l'impartialit\u00e9 et du fondement \u00e9thique de ces syst\u00e8mes. <\/span><\/p>\n

    Cette nouvelle \u00e9tude de Berkeley montre comment l'IA peut faire des pr\u00e9visions efficaces, mais nous ne pouvons pas \u00e9valuer la pr\u00e9cision avec laquelle elle prend ses d\u00e9cisions.<\/span><\/p>\n

    L'utilisation de l'IA pour pr\u00e9dire des \u00e9v\u00e9nements soci\u00e9taux et individuels majeurs peut sembler un concept dystopique, mais c'est d\u00e9j\u00e0 une pratique r\u00e9pandue dans de nombreuses r\u00e9gions du monde.<\/span><\/p>\n

    Dans plusieurs pays d\u00e9mocratiques, dont les \u00c9tats-Unis, le Royaume-Uni, le Br\u00e9sil, l'Australie et les Pays-Bas, l'IA est utilis\u00e9e pour police<\/a>, la surveillance, et la prise de d\u00e9cision en mati\u00e8re d'aide sociale<\/a>.\u00a0<\/span><\/p>\n

    Une IA pourrait-elle pr\u00e9dire certains aspects de votre avenir en ce moment m\u00eame ? C'est tout \u00e0 fait possible.<\/p>","protected":false},"excerpt":{"rendered":"

    Des chercheurs de l'universit\u00e9 de Berkeley, en Californie, ont mis au point un syst\u00e8me de pr\u00e9vision IA permettant de pr\u00e9dire des \u00e9v\u00e9nements futurs avec une pr\u00e9cision similaire \u00e0 celle de la sagesse des foules humaines. Les LLM n'\u00e9tant pas con\u00e7us pour la pr\u00e9vision d'\u00e9v\u00e9nements, l'\u00e9quipe a construit un syst\u00e8me de pr\u00e9vision au-dessus de GPT-4 en utilisant une nouvelle approche appel\u00e9e raisonnement augment\u00e9 par la recherche d'informations. Ce processus en plusieurs \u00e9tapes a consist\u00e9 \u00e0 former le GPT-4 \u00e0 la recherche d'informations pertinentes, \u00e0 l'\u00e9valuation de leur pertinence et \u00e0 leur int\u00e9gration dans son processus de raisonnement avant de faire une pr\u00e9diction. Voici comment cela fonctionne : Recherche : Le syst\u00e8me d'IA utilise GPT-4 pour g\u00e9n\u00e9rer des requ\u00eates de recherche bas\u00e9es sur la question et les sous-questions de la pr\u00e9vision, en r\u00e9cup\u00e9rant un large ensemble d'informations potentiellement pertinentes.<\/p>","protected":false},"author":2,"featured_media":11237,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[105],"class_list":["post-11235","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-machine-learning"],"yoast_head":"\nBerkeley researchers build AI forecasting system that bests humans | 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\/04\/berkeley-researchers-build-ai-forecasting-system-that-bests-humans\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Berkeley researchers build AI forecasting system that bests humans | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers at the University of Berkeley, California, developed an AI forecasting system to predict future events with similar accuracy to human crowd wisdom.\u00a0 As LLMs are not purpose-built for event forecasting, the team built a forecasting system on top of GPT-4 using a novel approach called retrieval-augmented reasoning. This multi-step process involved training GPT-4 to search for pertinent information, assess its relevance, and integrate it into its reasoning process before making a prediction.\u00a0 Here\u2019s how it works: Retrieval: The AI system uses GPT-4 to generate search queries based on the forecasting question and sub-questions, retrieving a broad set of potentially\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/fr\/2024\/04\/berkeley-researchers-build-ai-forecasting-system-that-bests-humans\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-04-03T14:29:19+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2024\/04\/DALL\u00b7E-2024-04-03-15.16.51-Craft-a-landscape-image-that-focuses-more-on-the-concept-of-graphs-and-forecasting-rather-than-buildings-set-against-a-futuristic-night-sky.-Imagine-.webp\" \/>\n\t<meta property=\"og:image:width\" 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