{"id":127744,"date":"2018-03-11T16:04:10","date_gmt":"2018-03-11T16:04:10","guid":{"rendered":"https:\/\/\/alibaba-et-qualcomm-investissent-dans-lia\/"},"modified":"2018-03-11T16:04:10","modified_gmt":"2018-03-11T16:04:10","slug":"alibaba-et-qualcomm-investissent-dans-lia","status":"publish","type":"post","link":"https:\/\/www.ecinews.fr\/fr\/alibaba-et-qualcomm-investissent-dans-lia\/","title":{"rendered":"Alibaba et Qualcomm investissent dans l&rsquo;IA"},"content":{"rendered":"<p><span id=\"result_box\" lang=\"fr\"><span title=\"The three NPUs cover ultra-low power and high performance options with a 'goldilocks' standard processor as a standard offering in the middle.\">Les trois NPU couvrent les options de puissance ultra-basse et de haute performance avec un processeur standard &lsquo;goldilocks&rsquo; comme milieu de gamme. <\/span><span title=\"These are the KDP 300 ultra-low power version, the KDP 500 standard version, and the KDP 700 high-performance version, supporting various AI applications in smart home, smart surveillance, smartphones, and IoT devices.\n\n\">Il s&rsquo;agit de la version ultra-basse consommation KDP 300, de la version standard KDP 500 et de la version haute performance KDP 700, prenant en charge diverses applications AI dans la maison intelligente, la surveillance intelligente, les smartphones et les appareils IoT.<\/span><\/span><\/p>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"Unlike the other AI processors on the market that often consume several watts, Kneron NPU Series consumes under 0.5W, and the KDP 300 designed for facial recognition in smartphones is less than 5mW.\">Contrairement aux autres processeurs AI sur le march\u00e9 qui consomment souvent plusieurs watts, le Kneron NPU Series consomme moins de 0.5W, et le KDP 300 con\u00e7u pour la reconnaissance faciale dans les smartphones moins de 5mW. <\/span><span title=\"To achieve this figure the convolutional neural network (CNN) slice size is 150 by 150 with processing rate of 5 frames per second and a clock frequency of 20MHz.\n\n\">Pour atteindre cette performance, la taille de la tranche de r\u00e9seau neuronal convolutionnel (CNN) est de 150 par 150 avec un taux de traitement de 5 images par seconde et une fr\u00e9quence d&rsquo;horloge de 20 MHz.<\/span><\/span><\/p>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"The KDP 300 supports faster and a more accurate 3D live facial recognition through image analysis from 3D structured light and dual-lens cameras.\n\n\">Le KDP 300 prend en charge une reconnaissance faciale 3D en direct plus rapide et plus pr\u00e9cise gr\u00e2ce \u00e0 l&rsquo;analyse d&rsquo;images \u00e0 partir de la lumi\u00e8re structur\u00e9e 3D et des cam\u00e9ras \u00e0 double objectif.<\/span><\/span><\/p>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"The KDP 500 is beefed up to do real-time recognition, analysis, and deep learning for multiple faces, hand and body gestures, which makes it suitable for smart home and smart surveillance applications.\">Le KDP 500 est renforc\u00e9 pour la reconnaissance en temps r\u00e9el, l&rsquo;analyse et l&rsquo;apprentissage en profondeur pour les multiples visages, gestes de la main et du corps, ce qui le rend apte aux applications de surveillance intelligente et \u00e0 la maison intelligente. <\/span><span title=\"Its computing capacity is up to 152 GOPS at 500MHz while consuming 100mW.\n\n\">Sa capacit\u00e9 de calcul est de 152 GOPS \u00e0 500 MHz tout en ne consommant que 100 MW.<\/span><\/span><\/p>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"The KDP 700 supports more advanced and complex AI computing, as well as deep learning inference for high-end smartphones, robots, drones, and smart surveillance devices.\">Le KDP 700 prend en charge une informatique AI plus avanc\u00e9e et plus complexe, ainsi qu&rsquo;une inf\u00e9rence d&rsquo;apprentissage en profondeur pour les smartphones haut de gamme, robots, drones et dispositifs de surveillance intelligents. <\/span><span title=\"It is in development stage and expected to offer peak throughput up to 4.4 TOPS at 1GHz clock frequency while keeping the power consumption at between 300mW and 500mW.\n\n\">Il est en phase de d\u00e9veloppement et devrait offrir un d\u00e9bit de pointe allant jusqu&rsquo;\u00e0 4,4 TOPS \u00e0 une fr\u00e9quence d&rsquo;horloge de 1 GHz tout en maintenant la consommation d&rsquo;\u00e9nergie entre 300 mW et 500 mW.<\/span><\/span><\/p>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"What remains unclear is whether these will be offered as packaged components or licensable IP, or both.\">Ce qui reste peu clair, c&rsquo;est si ceux-ci seront offerts en tant que composants ou IP sous licence, ou les deux. <\/span><span title=\"And what datatypes are supported.\n\n\">Et quels types de donn\u00e9es sont support\u00e9s.<\/span><\/p>\n<p><span title=\"Next: Decomposition, compression and caching\n\n\">Suite: D\u00e9composition, compression et mise en cache<\/span><\/span><br \/>\n&nbsp;<\/p>\n<hr \/>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"Kneron said it has adopted a filter decomposition technology that allows the division of large-scale convolutional computing blocks into a number of smaller ones to compute in parallel.\">Kneron a d\u00e9clar\u00e9 qu&rsquo;il a adopt\u00e9 une technologie de d\u00e9composition par filtre qui permet la division de blocs de calculs convolutifs \u00e0 grande \u00e9chelle en un certain nombre de blocs plus petits permettant un calcul en parall\u00e8le. <\/span><span title=\"Together with the reconfigurable convolution accelerating technology, the computing results from the small blocks will be integrated to achieve better overall computing performance.\">Avec la technologie d&rsquo;acc\u00e9l\u00e9ration par convolution reconfigurable, les r\u00e9sultats de calcul des petits blocs seront int\u00e9gr\u00e9s pour obtenir une meilleure performance informatique globale. <\/span><span title=\"Model compression allows unoptimized models to be shrunk a few dozen times.\">La compression de mod\u00e8les permet de r\u00e9duire les mod\u00e8les non optimis\u00e9s quelques dizaines de fois. <\/span><span title=\"The multi-level caching technique reduces the use of CPU resources and further improves the overall operational efficiency.\n\n\">La technique de mise en cache \u00e0 plusieurs niveaux r\u00e9duit l&rsquo;utilisation des ressources du processeur et am\u00e9liore encore l&rsquo;efficacit\u00e9 op\u00e9rationnelle globale.<\/span><\/span><\/p>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"Kneron NPU IP Series allows ResNet, YOLO and other deep learning networks to run on edge devices including hardware IP, compiler, and model compression.\">Kneron NPU IP Series permet de faire tourner ResNet, YOLO et \u00e0 d&rsquo;autres r\u00e9seaux d&rsquo;apprentissage en profondeur de fonctionner sur des p\u00e9riph\u00e9riques edge, notamment l&rsquo;IP mat\u00e9riel, le compilateur et la compression de mod\u00e8le. <\/span><span title=\"It supports various types of  CNNs such as Resnet-18, Resnet-34, Vgg16, GoogleNet, and Lenet, as well as mainstream deep learning frameworks, including Caffe, Keras, and TensorFlow.\n\n\">Il prend en charge divers types de CNN, tels que Resnet-18, Resnet-34, Vgg16, GoogleNet et Lenet, ainsi que les principaux frameworks d&rsquo;apprentissage en profondeur, notamment Caffe, Keras et TensorFlow.<\/span><\/span><\/p>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"Albert Liu, Kneron\u00b4s founder and CEO said: &quot;Since the release of its first NPU IP in 2016, Kneron has been making continuous efforts to optimize its NPU design and specifications for various industrial applications. We are pleased to introduce the new NPU IP\">Albert Liu, fondateur et PDG de Kneron, a d\u00e9clar\u00e9: \u00abDepuis la publication de sa premi\u00e8re IP NPU en 2016, Kneron a d\u00e9ploy\u00e9 des efforts continus pour optimiser sa conception et ses sp\u00e9cifications NPU pour diverses applications industrielles. <\/span><span title=\"Series and to announce that the KDP 500 will be adopted by our customer and enter to the mask tape-out process in the upcoming second quarter.&quot;\n\n\">Nous sommes heureux de pr\u00e9senter le nouvel IP NPU S\u00e9ries et d&rsquo;annoncer que le KDP 500 sera adopt\u00e9 par notre client et entrer dans le process de fabrication au cours du prochain trimestre. \u00ab\u00a0<\/span><\/span><\/p>\n<p><span id=\"result_box\" lang=\"fr\"><span title=\"Kneron was founded in 2015 and completed a Series A financing round worth more than $10 million in November 2017. Alibaba Entrepreneurs Fund and CDIB Capital Group are the lead investors, and Himax Technologies, Qualcomm, Thundersoft, Sequoia Capital and Cy Zone are co-investors\">Kneron a \u00e9t\u00e9 fond\u00e9e en 2015 et a compl\u00e9t\u00e9 un tour de financement de s\u00e9rie A d&rsquo;une valeur de plus de 10 millions de dollars en novembre 2017. Alibaba Entrepreneurs Fund et CDIB Capital Group sont les principaux investisseurs et Himax Technologies, Qualcomm, Thundersoft, Sequoia Capital et Cy Zone sont co-investisseurs <\/span><span title=\".\">.<\/span><\/span><\/p>\n<p><a href=\"http:\/\/www.kneron.com\">www.kneron.com<\/a><\/p>\n<p><strong>La r\u00e9daction vous conseille auusi:<\/strong><\/p>\n<p><a href=\"http:\/\/www.electronique-eci.com\/news\/arm-lance-deux-processeurs-dapprentissage-automatique\"><strong>ARM lance deux processeurs d&rsquo;apprentissage automatique<\/strong><\/a><\/p>\n<p><a href=\"http:\/\/www.electronique-eci.com\/news\/la-synapse-artificielle-du-mit-premiere-etape-vers-un-cerveau-artificiel\"><strong>La synapse artificielle du MIT premi\u00e8re \u00e9tape vers un cerveau artificiel?<\/strong><\/a><\/p>\n<p><strong>News articles in English: <\/strong><\/p>\n<p><a href=\"http:\/\/www.eenewsanalog.com\/news\/st-preps-second-neural-network-ic\">ST preps second neural network IC<\/a><\/p>\n<p><a href=\"http:\/\/www.eenewsanalog.com\/news\/intel-launches-self-learning-processor\">Intel launches self-learning processor<\/a><\/p>\n<p><a href=\"http:\/\/www.eenewsanalog.com\/news\/arm-launches-two-machine-learning-processors\">ARM launches two machine learning processors<\/a><\/p>\n<p><a href=\"http:\/\/www.eenewsanalog.com\/news\/eta-raises-funds-spiking-neural-networks\">Eta raises funds for spiking neural networks<\/a><\/p>\n<p><a href=\"http:\/\/www.eenewsanalog.com\/news\/ceva-goes-non-dsp-neural-processor\">Ceva goes non-DSP with neural processor<\/a><\/p>\n<p><a href=\"http:\/\/www.eenewsanalog.com\/news\/brainchip-founder-focus-akida-chip\">BrainChip founder to focus on &lsquo;Akida&rsquo; chip<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Le KDP 300 prend en charge une reconnaissance faciale 3D en direct plus rapide et plus pr\u00e9cise gr\u00e2ce \u00e0 l&rsquo;analyse d&rsquo;images \u00e0 partir de la lumi\u00e8re structur\u00e9e 3D et des cam\u00e9ras \u00e0 double objectif. Kneron Inc. (San Diego, Californie), une soci\u00e9t\u00e9 d&rsquo;intelligence artificielle qui a re\u00e7u le soutien d&rsquo; Alibaba et Qualcomm entre autres, a annonc\u00e9 trois unit\u00e9s de traitement neuronal (NPU) pour les dispositifs edge.<\/p>\n","protected":false},"author":22,"featured_media":127745,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[],"tags":[906],"domains":[47],"ppma_author":[1149],"class_list":["post-127744","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","tag-mpus-mcus-fr","domains-electronique-eci"],"acf":[],"yoast_head":"<title>Alibaba et Qualcomm investissent dans l&#039;IA ...<\/title>\n<meta name=\"description\" content=\"Le KDP 300 prend en charge une reconnaissance faciale 3D en direct plus rapide et plus pr\u00e9cise gr\u00e2ce \u00e0 l&#039;analyse d&#039;images \u00e0 partir de la lumi\u00e8re...\" \/>\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.ecinews.fr\/fr\/wp-json\/wp\/v2\/posts\/127744\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Alibaba et Qualcomm investissent dans l&#039;IA\" \/>\n<meta property=\"og:description\" content=\"Le KDP 300 prend en charge une reconnaissance faciale 3D en direct plus rapide et plus pr\u00e9cise gr\u00e2ce \u00e0 l&#039;analyse d&#039;images \u00e0 partir de la lumi\u00e8re structur\u00e9e 3D et des cam\u00e9ras \u00e0 double objectif. Kneron Inc. (San Diego, Californie), une soci\u00e9t\u00e9 d&#039;intelligence artificielle qui a re\u00e7u le soutien d&#039; Alibaba et Qualcomm entre autres, a annonc\u00e9 trois unit\u00e9s de traitement neuronal (NPU) pour les dispositifs edge.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.ecinews.fr\/fr\/wp-json\/wp\/v2\/posts\/127744\/\" \/>\n<meta property=\"og:site_name\" content=\"EENewsEurope\" \/>\n<meta property=\"article:published_time\" content=\"2018-03-11T16:04:10+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.ecinews.fr\/wp-content\/uploads\/import\/default\/files\/sites\/default\/files\/images\/screen_shot_2018-03-07_at_16.57.19.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1014\" \/>\n\t<meta property=\"og:image:height\" content=\"682\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"eeNews Europe\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta 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