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{"id":2215675,"date":"2019-01-29T11:57:47","date_gmt":"2019-01-29T10:57:47","guid":{"rendered":"https:\/\/www.phonandroid.com\/?p=2215675"},"modified":"2019-01-29T11:57:47","modified_gmt":"2019-01-29T10:57:47","slug":"antutu-lance-ai-review-telechargez-lapk-pour-benchmarker-lia-de-votre-smartphone","status":"publish","type":"post","link":"https:\/\/www.phonandroid.com\/antutu-lance-ai-review-telechargez-lapk-pour-benchmarker-lia-de-votre-smartphone.html","title":{"rendered":"AnTuTu lance AI Review : t\u00e9l\u00e9chargez l’APK pour benchmarker l’IA de votre smartphone"},"content":{"rendered":"

AnTuTu lance enfin un nouvel outil pour comparer l'intelligence des IA. Baptis\u00e9 AI Review, cette nouvelle application de benchmark con\u00e7ue \u00e0 partir des SDK des SoC Qualcomm Snapdragon et HiSilicon Kirin s'appuie sur des exercices de classification d'images et de reconnaissance d'objet. Elle devrait enfin permettre de comparer avec une pr\u00e9cision scientifique des SoC dont les constructeurs exag\u00e8rent parfois les aptitudes en mati\u00e8re d'intelligence artificielle. Pour l'heure, n\u00e9anmoins, AI Review ne permet pas de tester de mani\u00e8re fiable les SoC Exynos et Apple Axx. Voici comment t\u00e9l\u00e9charger l'APK.\u00a0<\/strong><\/p>\n

\"AnTuTu\"<\/p>\n

Ces derni\u00e8res ann\u00e9es, un nombre croissant de fondeurs et constructeurs de smartphones mettent en avant les capacit\u00e9s en termes d'intelligence artificielle de leurs produits. Avec des chiffres impressionnants sur le papier – mais souvent sans base r\u00e9elle ou concr\u00e8te pour r\u00e9ellement savoir quel est l'apport de tel ou tel SoC dans ce domaine ou les comparer. Alors que Geekbench et AnTuTu publient r\u00e9guli\u00e8rement des benchmarks permettant de comparer la puissance brute des smartphones<\/a>, il n'existait jusqu'ici aucun moyen de mesurer les performances de l'intelligence artificielle de tel ou tel SoC. Car comme le souligne AnTuTu dans son post de blog<\/a>, l'intelligence artificielle est un domaine tr\u00e8s vaste. Avec des applications et impl\u00e9mentations diff\u00e9rentes d'un constructeur \u00e0 l'autre. Ainsi certains optent pour un Neural Processing Unit (NPU) d\u00e9di\u00e9 au machine learning. Quand d'autres confient cette t\u00e2che au DSP (normalement d\u00e9di\u00e9 au traitement du signal, en particulier pour am\u00e9liorer les photos).<\/p>\n