{"id":1556,"date":"2018-02-08T11:47:42","date_gmt":"2018-02-08T10:47:42","guid":{"rendered":"http:\/\/www.datavaloris.com\/?p=1556"},"modified":"2019-11-14T16:14:57","modified_gmt":"2019-11-14T15:14:57","slug":"grandeur-decadence-de-lintelligence-artificielle-partie-1","status":"publish","type":"post","link":"https:\/\/www.datavaloris.com\/en\/grandeur-decadence-de-lintelligence-artificielle-partie-1\/","title":{"rendered":"Grandeur et d\u00e9cadence de l’Intelligence Artificielle – Partie 1\/3"},"content":{"rendered":"

La d\u00e9mocratisation de l’IA et plus particuli\u00e8rement des r\u00e9seaux de neurones a permis de d\u00e9terminer les domaines de pr\u00e9dilection de l’<\/b>I<\/b>ntelligence Artificielle mais surtout ses limites actuelles.<\/b> Ces m\u00eames limites engendrent incompr\u00e9hensions entre les \u00e9vang\u00e9listes de l’IA qui promettent monts et merveilles et les utilisateurs qui voient leurs esp\u00e9rances non assouvies aujourd’hui. Pour preuve cet article du Monde<\/a> (1) <\/sup>sur Watson, l’IA d’IBM, qui illustre cette incompr\u00e9hension.  <\/span><\/p>\n

Qui n’a pas entendu parler ces derniers mois de Machine Learning, Deep-Learning, rendu c\u00e9l\u00e8bre par AlphaGo de Google, de robotique et des cons\u00e9quences fantasm\u00e9es sur notre vie de tous les jours\u202f? <\/span><\/p>\n

Faut-il pour autant <\/b>rejeter tout cela en bloc\u202f?<\/b> <\/span><\/p>\n

\"\"
victoire encore impensable il y a encore 10 ans d’AlphaGo sur les plus grands champions mondiaux du jeu de GO<\/figcaption><\/figure>\n
Le<\/span><\/span> <\/span><\/span>R\u00e9seau<\/span><\/span> <\/span><\/span>de neurones, une branche de l\u2019IA<\/span><\/span> <\/span><\/h5>\n

Je ne parlerai ici que de r\u00e9seaux de neurones qui sont une des branches de l’IA qui fait le plus parler d’elle. Cette technologie existe depuis les ann\u00e9es 50 avec l’arriv\u00e9e du premier perceptron de Frank Rosenblatt. La course \u00e0 la puissance d\u00e9crite par la loi de Moore lui a permis de commencer \u00e0 se d\u00e9mocratiser depuis plus de 20 ans. Deep blue en a \u00e9t\u00e9 l’ambassadeur aupr\u00e8s du grand public. <\/span><\/p>\n

Compte tenu des enjeux grandissants de gestion de donn\u00e9es, le r\u00e9seau de neurones est d\u00e9sormais au c\u0153ur des pr\u00e9occupations de tous. Afin de r\u00e9pondre aux diff\u00e9rents enjeux du traitement des donn\u00e9es et du manque de puissance, il a \u00e9t\u00e9 d\u00e9velopp\u00e9 des topologies optimis\u00e9es mais limit\u00e9es \u00e0 quelques besoins tr\u00e8s sp\u00e9cifiques (ex : r\u00e9seaux neuronaux \u00e0 convolution qui reproduisent la topologie du cortex visuel pour le traitement d’image). <\/span><\/p>\n

Il existe aujourd’hui de nombreux mod\u00e8les topologiques de r\u00e9seaux de neurones dont voici un bestiaire<\/a>(2)<\/sup>. Ces topologies choisies sont malheureusement limitatives et emprisonnent leurs possibilit\u00e9s d’\u00e9volutions. <\/span><\/p>\n

Avant d\u2019entrer dans le d\u00e9tail de l’importance de la topologie il convient de revenir sur quelques mythes autour des r\u00e9seaux de neurones tels qu’ils existent aujourd’hui  <\/span><\/p>\n

Pour en savoir plus, ne manquez pas nos prochains articles\u202f:
\nGrandeur et d\u00e9cadence de l’Intelligence Artificielle – Partie 2\/3 :<\/strong>
\nQuestions\/r\u00e9ponses sur l\u2019IA, limites actuelles du r\u00e9seau de neurones. <\/strong><\/p>\n

\n
SOURCES<\/div>\n
    \n
  • Hubert Guillaud – blog lemonde.fr \u00abWatson : l\u2019Intelligence artificielle et ses limites\u00bb. 2017\/10\/07<\/li>\n
  • FJODOR VAN VEEN – The Asimov Institue \u00abThe Neural Network Zoo\u00bb. 2016\/09\/14<\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"

    La d\u00e9mocratisation de l’IA et plus particuli\u00e8rement des r\u00e9seaux de neurones a permis de d\u00e9terminer les domaines de pr\u00e9dilection de l’Intelligence Artificielle mais surtout ses limites actuelles. Ces m\u00eames limites engendrent incompr\u00e9hensions entre les \u00e9vang\u00e9listes de l’IA qui promettent monts et merveilles et les utilisateurs qui voient leurs esp\u00e9rances non assouvies aujourd’hui. Pour preuve cet article du […]<\/p>","protected":false},"author":2,"featured_media":1443,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[15],"tags":[16],"yoast_head":"\nGrandeur et d\u00e9cadence de l'Intelligence Artificielle - Partie 1\/3 - DATAVALORIS<\/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:\/\/www.datavaloris.com\/en\/grandeur-decadence-de-lintelligence-artificielle-partie-1\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Grandeur et d\u00e9cadence de l'Intelligence Artificielle - Partie 1\/3 - DATAVALORIS\" \/>\n<meta property=\"og:description\" content=\"La d\u00e9mocratisation de l’IA et plus particuli\u00e8rement des r\u00e9seaux de neurones a permis de d\u00e9terminer les domaines de pr\u00e9dilection de l’Intelligence Artificielle mais surtout ses limites actuelles. Ces m\u00eames limites engendrent incompr\u00e9hensions entre les \u00e9vang\u00e9listes de l’IA qui promettent monts et merveilles et les utilisateurs qui voient leurs esp\u00e9rances non assouvies aujourd’hui. 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