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Cr\u00e9dits : TPUv2 de Google<\/figcaption><\/figure>\n

Depuis de nombreuses ann\u00e9es maintenant, Google met un point d'orgue \u00e0 int\u00e9grer de l'IA dans la grande majorit\u00e9 de ses applications et services. Lors de sa conf\u00e9rence Google I\/O 2021<\/a>, la firme de Mountain View a par exemple pr\u00e9sent\u00e9 un outil d'assistance dermatologique boost\u00e9 \u00e0 l'IA, qui permettra aux utilisateurs d'identifier leurs probl\u00e8mes de peau \u00e0 l'aide de quelques photos<\/a>.<\/p>\n

Cette fois-ci, les chercheurs de Google ont d\u00e9cid\u00e9 de mettre \u00e0 profit l'apprentissage automatique de leurs IA pour concevoir leurs prochaines puces \u00e9lectroniques, et plus pr\u00e9cis\u00e9ment leur prochain TPU<\/strong> (Tensor Processing Unit). Pour rappel, il s'agit d'un circuit int\u00e9gr\u00e9 sp\u00e9cialement con\u00e7u par Google pour justement am\u00e9liorer les syst\u00e8mes d'intelligence artificielle par r\u00e9seaux de neurones. En d'autres termes, Google utilise l'IA pour acc\u00e9l\u00e9rer le d\u00e9veloppement de l'IA.\u00a0<\/strong><\/p>\n

Comme l'explique Google, trouver le design id\u00e9al d'une puce pour allier performances et vitesse d'ex\u00e9cution prend g\u00e9n\u00e9ralement des mois \u00e0 des ing\u00e9nieurs. Cette t\u00e2che, appel\u00e9e “floorplanning<\/em>” consiste \u00e0 trouver la disposition optimale des sous-syst\u00e8mes d'une puce<\/strong>. Or, selon les chercheurs du g\u00e9ant californien, en seulement 6 heures de travail<\/strong> les algorithmes ont \u00e9t\u00e9 capables de d\u00e9velopper des puces plus efficaces que celles con\u00e7ues par les humains.<\/p>\n

\u00c0 lire \u00e9galement : Facebook veut cr\u00e9er une IA capable de finir le jeu vid\u00e9o le plus dur de l\u2019histoire<\/a><\/p>\n