company:baidu

  • Yandex : quand le « Google russe » se fait cyberespionner par les agences du « Five Eyes »
    https://cyberguerre.numerama.com/1521-yandex-quand-le-google-russe-se-fait-cyberespionner-par-l

    Le moteur de recherche et portail russe connu sous le nom de Yandex a été piraté par une ou plusieurs agences de renseignement appartenant à l’alliance Five Eyes. Confirmée par un porte-parole de l’entreprise, l’opération de cyberespionnage visait avant tout à dérober des informations techniques relatives aux processus d’authentification des utilisateurs. Google aux quatre coins du globe, Baidu en Chine et Yandex en Russie. Voilà comment se résume la répartition des moteurs de recherche sur notre (...)

    #Yandex #données #Five_Eyes #hacking

    //c2.lestechnophiles.com/cyberguerre.numerama.com//content/uploads/sites/2/2019/07/russia-3005269_1920.jpg

  • Anne Tercinet : « Entreprises et consommateurs victimes d’abus de position dominante demanderont réparation des préjudices subis »
    https://www.lemonde.fr/idees/article/2019/06/14/anne-tercinet-entreprises-et-consommateurs-victimes-d-abus-de-position-domin

    Si les autorités de la concurrence restent limitées à infliger des amendes, ce sont les actions en justice des consommateurs lésés par les abus de position dominante qui pourraient inquiéter les GAFAM, explique, dans une tribune au « Monde », la professeure de droit. La puissance de Google, Amazon, Facebook, Apple et Microsoft (GAFAM) est mondiale. Tout du moins, les situations de monopole dont ces entreprises jouissent dans l’économie numérique affectent l’ensemble du monde occidental - la Chine (...)

    #Alibaba #Apple #Google #Microsoft #Tencent #Xiaomi #Amazon #Alibaba.com #Facebook #Baidu #procès #domination #BATX (...)

    ##GAFAM

  • « Les opérateurs télécom étaient les maîtres du web, ils en sont devenus les prolétaires »
    https://usbeketrica.com/article/les-operateurs-telecom-sont-devenus-les-proletaires-du-web

    « On peut encore croire à un âge de raison des réseaux », nous dit le chercheur Olivier Auber, qui dans son nouveau livre, Anoptikon (FYP éditions, 2019), plaide pour un changement de perspective afin de faire d’Internet le grand espace de partage qu’il promettait d’être à ses débuts. Il est des livres qui vous confrontent assez rapidement à vos limites. Anoptikon (FYP éditions, 2019), d’Olivier Auber, est de ceux là. Englober dans un seul ouvrage la naissance du langage, le navire de Darwin (le HMS (...)

    #Alibaba #Google #Tencent #Xiaomi #Facebook #Alibaba.com #Baidu #BATX #GAFAM #surveillance #web (...)

    ##art

  • L’intelligence artificielle : un instrument de puissance ?
    https://www.arte.tv/fr/videos/083964-008-A/le-dessous-des-cartes

    Depuis la mise au point de la machine à décrypter les messages d’Alan Turing, l’intelligence artificielle a fait de gigantesques progrès. Elle se décline aujourd’hui en logiciels pour traders, en robots ménagers, en assistants numériques, et demain, sans doute, en voitures autonomes. Tour d’horizon des États et des géants du numérique qui ont pris la mesure des formidables enjeux de (...)

    #Alibaba #Apple #Google #Microsoft #Tencent #Xiaomi #Alibaba.com #Amazon #Baidu #Facebook #Xiaonei #algorithme #bracelet #CCTV #domotique #drone #élections #manipulation #biométrie #données #militarisation #BigData #marketing #surveillance #vidéo-surveillance #Five_Eyes (...)

    ##SocialCreditSystem

  • JP Morgan Launches Its Own Digital Currency, And China’s Baidu Reveals #blockchain OS
    https://hackernoon.com/jp-morgan-launches-its-own-digital-currency-and-chinas-baidu-reveals-blo

    The State of The Market — February 15, 2019 BTC: $3,640.40 (+0.69%) ETH: $123.21 (+0.91%) XRP: $0.303646 (+0.20%)After a slow decline in the last couple of days, the #crypto market posted small gains today. While #bitcoin is still struggling to move past $3,650, the total market cap added nearly $1.5 Billion in the last 24 hours. All of the top 10 cryptocurrencies are in green right now, posting single-digit gains. A clear trend could emerge over the weekend when volumes are low. Meanwhile, Ethereum managed to defend its support at $100 this week, and Ripple has bounced back above $0.30.In other news, Coinsquare, one of the largest #cryptocurrency exchanges in Canada, has announced the acquisition of the StellarX decentralized exchange as it continues to evolve its platform. The StellarX (...)

    #cryptocurrency-investment

  • La Chine distribue des bons et des mauvais points à ses citoyens
    https://www.franceinter.fr/monde/la-chine-distribue-des-bons-et-des-mauvais-points-a-ses-citoyens

    Depuis mars 2018, le gouvernement chinois a franchi une étape supplémentaire dans la mise en oeuvre de son programme de « crédit social », basé sur la collecte d’informations sur les réseaux sociaux et via les caméras de surveillance intelligentes. Les citoyens « mal notés » sont restreints dans leur accès aux transports. C’est un programme digne d’un épisode de la série Black Mirror qui est actuellement expérimenté par le Parti communiste chinois. Lancé en 2014, en vue de son déploiement effectif en 2020, (...)

    #Alibaba #Tencent #Xiaomi #Alibaba.com #Baidu #WeChat #CCTV #activisme #sécuritaire #voyageurs #web #surveillance #vidéo-surveillance #BATX (...)

    ##voyageurs
    ##SocialCreditSystem

  • Huawei : c’est de la politique, stupide !
    https://www.letemps.ch/opinions/huawei-cest-politique-stupide

    Dans la bataille des technologies de l’information et de l’intelligence artificielle, le rôle des Etats est déterminant. Il est temps pour l’Europe de se doter à son tour d’une politique industrielle dans ces secteurs qui domineront le XXIe siècle, écrit Frédéric Koller Pékin a raison. La vingtaine de chefs d’inculpation prononcés cette semaine par un tribunal de New York contre Huawei et sa directrice financière, Meng Wanzhou, ont des « visées politiques ». Pour défendre ses industries, et freiner (...)

    #Alibaba #Apple #Google #Huawei #Microsoft #Nokia_Siemens #Sony #Tencent #Alibaba.com #Amazon #Baidu #Facebook #algorithme #spyware #exportation #sécuritaire #concurrence #web #surveillance (...)

    ##GAFAM

  • Le moteur de recherche Bing est désormais bloqué en Chine
    https://www.numerama.com/politique/457917-le-moteur-de-recherche-bing-est-desormais-bloque-en-chine.html

    Microsoft confirme que son moteur de recherche, Bing, est inaccessible en Chine. Périodiquement, la Chine ajoute de nouveaux noms à sa longue liste de sites et de services bloqués dans le pays. Twitch, WhatsApp, les réseaux privés virtuels (VPN)… les exemples ne manquent pas. L’histoire récente a même son lot de situations cocasses, à l’image des mesures prises contre la lettre « N » ou de la mésaventure de celui qui a conçu l’outil de filtrage chinois, qui a subi les effets de sa création. Désormais, (...)

    #Microsoft #Bing #WhatsApp #Twitch #censure #web #surveillance #Baidu

    //c0.lestechnophiles.com/www.numerama.com/content/uploads/2018/08/drapeau-chine.jpg

  • En pleine crise des « gilets jaunes », Bruno Le Maire alerte sur les inégalités
    https://www.latribune.fr/economie/france/en-pleine-crise-des-gilets-jaunes-bruno-le-maire-alerte-sur-les-inegalites

    A la veille d’un événement organisé au ministère de l’Economie en compagnie de Melinda Gates, Bruno Le Maire a mis l’accent sur les effets néfastes des écarts de richesse. Reste à savoir comment le gouvernement va s’attaquer à ce sujet dans les prochains alors que la France va présider le G7 finances dédié aux inégalités.

    « L’Europe bascule, le capitalisme bascule, les technologies basculent, c’est un moment où le politique est plus que jamais nécessaire. » Dans le contexte du ralentissement de l’économie mondiale et de la montée des populismes, Bruno Le Maire a tiré la sonnette d’alarme ce lundi matin. « Nous pensons que la croissance française reste robuste mais le refus croissant des inégalités et des injustices liées au capitalisme est de plus en plus visible », a expliqué le ministre de l’Economie devant plusieurs journalistes.
    […]
    Face à ces signaux d’alerte, le locataire de Bercy indique « qu’il est nécessaire de défendre notre vision du capitalisme. Il y a une place pour une vision française et européenne du système capitaliste ». A l’approche du sommet G7 finances que la France doit présider au mois de juillet prochain à Biarritz, l’ancien ministre de l’agriculture a énuméré les quatre priorités du gouvernement :

    D’abord, « construire une fiscalité du XXIème siècle qui doit permettre de financer des biens publics et une justice. » Il a notamment insisté sur la nécessité d’une taxation des géants du numérique en mentionnant les noms des pays européens qui refusaient encore d’appliquer une telle fiscalité. « Il s’agit de la Suède, la Finlande, le Danemark et l’Irlande. » Il a également expliqué qu’il avait appelé récemment le secrétaire au Trésor américain, Steven Mnuchin, lui rappelant qu’il ne voulait pas simplement « cibler les entreprises américaines mais aussi les géants asiatiques (BATX, Baidu, Alibaba, Tencent et Xiaomi) ». Pour les questions de fiscalité, il a plaidé « pour un passage d’un vote à l’unanimité à un vote à la majorité qualifiée au sein de l’Union européenne », pour éviter de nombreux blocages.

    Deuzio : mettre en place « une imposition minimale » pour les entreprises qui ont implanté leur siège dans des paradis fiscaux. « Ce sont les plus grandes entreprises qui échappent à l’impôt. L’impôt minimal permet de réduire ces contournements ». A l’automne dernier, le ministre allemand des finances Olaf Scholz avait plaidé également pour la mise en oeuvre d’un tel dispositif. « Une telle initiative serait un prolongement du mécanisme de l’OCDE de lutte contre l’érosion de la base d’imposition et le transfert de bénéfices (BEPS) », soulignait l’agence Reuters.

    Troisièmement « limiter la concentration capitalistique ». Sur ce sujet, le ministre a fait référence à certaines entreprises qui réalisent des capitalisations boursières record "à plus de 600, 700 voire 1.000 milliards de dollars". Sans directement la nommer, le ministre faisait référence au géant Apple qui avait franchi la barre symbolique des 1.000 milliards de dollars l’été dernier. Enfin, la réduction des inégalités à l’intérieur des pays développés. M. Le Maire a appelé à construire des outils communs entre tous les pays pour faciliter les comparaisons.

    • La « taxe Gafa » de Bruno Le Maire, coup d’épée dans l’eau ou coup de poker ?
      https://www.latribune.fr/technos-medias/internet/taxe-gafa-de-bruno-le-maire-un-repli-strategique-et-des-questions-804641.h

      Le ministre de l’Economie Bruno Le Maire vient d’annoncer qu’un projet de loi pour taxer les géants du numérique à hauteur de 3% minimum de leur chiffre d’affaires en France, sera présenté d’ici à fin février. Un repli stratégique face au blocage des négociations en Europe, pour une loi essentiellement symbolique.
      […]
      D’après plusieurs sources, les Gafa eux-mêmes, notamment Google et Facebook, considéreraient la taxation de leurs revenus comme inévitable et seraient prêts à céder maintenant pour éviter plus tard une addition encore plus salée. D’autant plus que d’autres pays, notamment le Royaume-Uni pourtant très libéral, mais aussi l’Autriche ou l’Espagne, agissent également dans ce sens.

      « Par son impact limité sur les recettes de l’Etat et les effets de seuils, l’annonce d’une taxe sur les géants du numérique est surtout symbolique, résume Guillaume Glon, de Pwc Avocats. C’est un message politique à double portée. Le premier répond à la pression populaire des Gilets jaunes en s’attaquant aux entreprises qui dominent l’économie. Le deuxième vise à peser davantage sur les discussions au niveau européen ».

  • Algocratie : L’inégalité programmée - #DATAGUEULE 84
    https://www.youtube.com/watch?v=oJHfUv9RIY0

    Ils sont partout autour de nous et pourtant on s’arrête rarement pour les regarder vraiment : les algorithmes. Puissants outils de calcul, ces lignes de code sont aujourd’hui principalement utilisées pour tenter d’optimiser le monde qui nous entoure. Mais que produit cette optimisation ? Quels sont ses effets sur notre perception de la réalité quand il s’agit de trier des infos ? Et que produisent les algorithmes quand ils deviennent des leviers de décisions incontestables ? Prenons le temps de (...)

    #algorithme #domination #criminalité #prédictif #prédiction #santé #solutionnisme #discrimination #NSA #Skynet #Alibaba #Google #Microsoft #Tencent #Apple #Alibaba.com #Baidu #Facebook #BATX (...)

    ##criminalité ##santé ##GAFAM

  • Faut-il avoir peur des GAFA chinois ?
    https://www.franceculture.fr/emissions/du-grain-a-moudre/faut-il-avoir-peur-des-gafa-chinois

    Méconnus en France, les géants du web chinois, Baidu, Alibaba, Tencent, Xiaomu (les « BATX ») inquiètent. Comment appréhender l’arrivée de tels mastodontes numériques en Europe ? Leurs pratiques sont-elles plus problématiques que celles de Google, Apple, Facebook et Amazon (les « GAFA ») ? Derrière l’acronyme BATX : Baidu, Alibaba, Tencent et Xiaomi, ou les quatre entreprises les plus puissantes de l’économie numérique chinoise. Qui a dit que l’humour n’avait pas de frontières ? Dolce & Gabbana vient (...)

    #Alibaba #Tencent #Alibaba.com #Baidu #données #surveillance #BATX #web #BigData

  • Browser Mining — An Effective Revenue Generation Alternative to #advertising
    https://hackernoon.com/browser-mining-an-effective-revenue-generation-alternative-to-advertisin

    Browser Mining : An Effective Revenue Generation Alternative to AdvertisingAdvertising revenue is an important income source for the internet domain; even tech giants like Google, Yahoo, Baidu, etc., rely on it. Advertisement mediums such as premium-posting, pop-ups, banner spaces, sidebar ads, etc., generate commissions via click-through rates or sales. However, these advertisements come with a fair share of pitfalls. The revenue generated from ads is considered intrusive and adversely impacts the overall user experience, resulting in higher bounce and dropout rates. Websites that become too dependent on these ads end up losing visitors and potential customers. Below are some more critical setbacks of generating revenue through online advertisement.Impacts the Viewing ExperienceWhen (...)

    #cryptocurrency #business #technology #blockchain

  • [FranceCulture] Faut-il avoir peur des GAFA chinois ?
    https://www.laquadrature.net/2018/12/05/franceculture-faut-il-avoir-peur-des-gafa-chinois

    Méconnus en France, les géants du web chinois, Baidu, Alibaba, Tencent, Xiaomu (les « BATX ») inquiètent. Comment appréhender l’arrivée de tels mastodontes numériques en Europe ? Leurs pratiques sont-elles plus problématiques que celles de Google, Apple, Facebook…

    #Cite_La_Quadrature_du_Net #Revue_de_presse #Vie_privée_-_Données_personnelles #revue_de_presse

  • How Cheap Labor Drives China’s A.I. Ambitions - The New York Times
    https://www.nytimes.com/2018/11/25/business/china-artificial-intelligence-labeling.html


    Workers at the headquarters of Ruijin Technology Company in Jiaxian, in central China’s Henan Province. They identify objects in images to help artificial intelligence make sense of the world.
    CreditCreditYan Cong for The New York Times

    Some of the most critical work in advancing China’s technology goals takes place in a former cement factory in the middle of the country’s heartland, far from the aspiring Silicon Valleys of Beijing and Shenzhen. An idled concrete mixer still stands in the middle of the courtyard. Boxes of melamine dinnerware are stacked in a warehouse next door.

    Inside, Hou Xiameng runs a company that helps artificial intelligence make sense of the world. Two dozen young people go through photos and videos, labeling just about everything they see. That’s a car. That’s a traffic light. That’s bread, that’s milk, that’s chocolate. That’s what it looks like when a person walks.

    I used to think the machines are geniuses,” Ms. Hou, 24, said. “Now I know we’re the reason for their genius.

    • via Antonio A. Casili sur FB, qui l’accompagne de ces utiles compléments :

      Ce n’est pas vraiment une surprise : d’après cette enquête du New York Times, derrière le système de reconnaissance faciale Face++ du chinois Megvii Technology, des micro-tâcherons qui, avec leur travail du clic, entraînent des IA depuis une ancienne usine de ciment. Là où ça redevient intéressant (et où l’enquête du New York Times s’interrompt) c’est quand on va fouiller sur les sites de sous-traitance de la tech chinoise et internationale, avec un petit coup de pouce de collègues sinophones que ma discrétion m’interdit de nommer ici. On y découvre l’étendue du portefeuille clients de la Nangong Yunzhi Data Processing, la petite usine à clics à laquelle le New York Times fait la part belle.

      Tout d’abord, ses micro-travailleur•ses font pas mal de classification de produits pour entraîner les algorithmes de recommandation des plateformes d’e-commerce, comme Jingdong & Taobao. Ils s’adonnent aussi à l’annotation audio pour l’entreprise spécialisée en traduction automatique SpeechOcean (contrôlée de la Beijing Haitian Ruisheng Science Technology Ltd., qui a son tour marchande des corpus annotés pour traduction et analyse lexicale sur sa propre plateforme, King Line Data Center).

      Après quoi, on sort les gros calibres, avec de la reconnaissance d’images pour Baidu Total View, concurrent chinois de Google Street View (pour la petite histoire, Google Street View semble recruter beaucoup moins de micro-travailleurs parce que... ses images sont largement reconnues par ses utilisateur•rices mêmes, digital laborers « gratuit•es », à l’aide des reCAPTCHA visuels).

      L’un des clients les plus inquiétants est Tencent, pour lequel notre usine à clics fait de la retranscription speech-to-text. Le géant chinois de la messagerie possède, entre autres, la communauté QQ et l’application WeChat avec son important trafic de voix-sur-IP et sa fonctionnalité de retranscription « automatique » de messages vocaux. Comme quoi, quand vous parlez dans ce machin, il y a toujours des chances que quelqu’un vous écoute pour retranscrire en temps quasi-réel ou pour corriger des transcriptions défectueuses de l’appli même. Bonjour, la privacy.
      Et à propos de privacy, notre Nangong Yunzhi Data Processing compte parmi ses projets la labellisation et la prépration des pièces d’identités indonésiennes — les tristement célèbres e-KTP qui contiennent une quantité pharamineuse de données biométriques et concernent plus de 100 millions de citoyen•nes.

      Enfin, le must : du véhicule autonome ! Plus précisément, de l’entraînement du système de reconnaissance faciale embarqué des véhicules NIO—nécessaire pour éviter vols, fraudes à l’assurance, ou vérifier que le conducteur ne soit pas distrait. Et oui, le « conducteur ». Parce qu’évidemment une voiture « driverless » doit toujours être conduit par quelqu’un.

      A suivre...

  • Chinese search firm Baidu joins global AI ethics body
    https://www.theguardian.com/technology/2018/oct/17/baidu-chinese-search-firm-joins-global-ai-ethics-body-google-apple-face

    Company is first Chinese member of Partnership on AI, following, Google, Apple, Facebook and others The AI ethics body formed by five of the largest US corporations has expanded to include its first Chinese member, the search firm Baidu. The Partnership on Artificial Intelligence to Benefit People and Society – known as the Partnership on AI (PAI) – was formed in 2016 by Google, Facebook, Amazon, IBM and Microsoft to act as an umbrella organisation for the five companies to conduct (...)

    #Google #Microsoft #IBM #Amazon #Baidu #algorithme #éthique

    https://i.guim.co.uk/img/media/36a0e34fef9da3e451c09c32ac69df46c80554c4/77_765_2217_1330/master/2217.jpg

  • La Chine, locomotive de l’intelligence artificielle ?
    https://usbeketrica.com/article/la-chine-locomotive-de-l-intelligence-artificielle

    La Chine est aujourd’hui l’un des principaux concurrents des États-Unis dans le domaine de l’intelligence artificielle (IA). Alors que le budget global des start-up chinoises liées à l’IA est encore loin de celui des Etats-Unis, les débouchés du secteur en Chine sont déjà impressionnants (en particulier dans le secteur de la fintech) et pourraient même surpasser ceux de tous les autres pays du globe. Dans le monde de la technologie, l’équilibre des pouvoirs est en pleine mutation. La Chine, après des (...)

    #Alibaba #Ant #Google #Microsoft #Tencent #Alibaba.com #Baidu #Facebook #algorithme #robotique #bénéfices #BigData #profiling #marketing (...)

    ##prédictif

  • #blockchain Technology Application Summit 2018— Changing the World to Create the Future
    https://hackernoon.com/blockchain-technology-application-summit-2018-changing-the-world-to-crea

    The Silicon Valley of China recently held its main annual technology conference and this year the focus was Blockchain.Some of the key speakers including LoveBlock CEO Raffael KrauseThe event was huge, including sponsors such as Sina — the Chinese equivalent of Twitter and the financial website Meirijinrong which is partnered with the likes of Huawei and Baidu.As a result, projects from across China and beyond flew into Chengdu for a weekend full of discussion and networking on all things blockchain.There was an immense variety of projects on display from the revolutionary forward thinkers to the downright wacky and weird.BitPig — Blockchain Project based on… Pigs?Bit猪 (zhū) or known as BitPig in English was the standout candidate for strangest Blockchain offering. Claiming to revolutionize the (...)

    #crypto #blockchain-technology #singapore #blockchain-summit

  • Inside China’s Vast New Experiment in Social Ranking
    https://www.wired.com/story/age-of-social-credit/?mbid=social_twitter

    In 2015, when Lazarus Liu moved home to China after studying logistics in the United Kingdom for three years, he quickly noticed that something had changed : Everyone paid for everything with their phones. At McDonald’s, the convenience store, even at mom-and-pop restaurants, his friends in Shanghai used mobile payments. Cash, Liu could see, had been largely replaced by two smartphone apps : Alipay and WeChat Pay. One day, at a vegetable market, he watched a woman his mother’s age pull out (...)

    #Alibaba #Tencent #WeChat #Baidu #carte #smartphone #réseaux #StateControl #contrôle #SocialNetwork #prédictif #journalisme #surveillance #vidéo-surveillance #web #marketing (...)

    ##profiling

  • #china’s True Crypto Giants- #tencent, Baidu, #alibaba and JD
    https://hackernoon.com/chinas-true-crypto-giants-tencent-baidu-alibaba-and-jd-91bf7786413b?sour

    Regulation is not a sexy topic, unless we are discussing crypto regulations.In the last few weeks, many countries have voiced their unique ways to welcome ( or not so much) the crypto community. Korea has decided to regulate crypto exchanges as banks, while Thailand has permitted certain cryptocurrencies to be traded and exchanges to be opened. Even the SEC made remarks on BTC and ETH not being securities (horay!). China certainly has voiced their opinions too, this time through their permitting of e-commerce company JD to build a blockchain-backed token.This is particularly important, for 2 reasons. For one, we now know that China doesn’t just care about blockchain, it cares about tokens too. Past announcements only suggested the former, such as President Xi’s recent speech touting the (...)

    #cryptocurrency-investment #regulation

  • Baidu’s new system can learn to imitate every accent
    https://www.theverge.com/2017/10/24/16526370/baidu-deepvoice-3-ai-text-to-speech-voice

    One AI, 2,500 different characters At the start of this year, Chinese search giant Baidu introduced a new system called DeepVoice. It uses deep learning, a popular artificial intelligence technique, to build a system that can convert text-to-speech. The first version was able to produce short sentences that, at least on a cursory listen, were nearly indistinguishable from a real person. That system could learn one voice at a time, and required hours of data to master each one. DeepVoice (...)

    #smartphone #biométrie #voix #DeepVoice

  • Baidu’s new A.I. can mimic your voice after listening to it for just one minute
    https://www.digitaltrends.com/cool-tech/baidu-ai-emulate-your-voice

    Researchers at Chinese search giant Baidu say they have developed an artificial intelligence that can learn to precisely mimic a person’s voice based on less than 60 seconds’ worth of listening to it. They note this milestone uses Baidu’s text-to-speech synthesis system Deep Voice, which was trained on more than 800 hours of audio from 2,400 speakers. The team says Deep Voice requires only 100 five-second segments of vocal training data to sound its best, but a version trained on only 10 five-second samples was able to deceive a voice-recognition system more than 95 percent of the time. “We see many great use cases or applications for this technology,” says Baidu’s Leo Zou. “For example, voice cloning could help patients who lost their voices. This is also an important breakthrough in the direction of personalized human-machine interfaces.” Zou also thinks the technique could advance the creation of original digital content.

    De mieux en mieux. Et la reconnaissance vocale, elle peut se rhabiller !

  • Who really contributes to open source | InfoWorld
    https://www.infoworld.com/article/3253948/open-source-tools/who-really-contributes-to-open-source.html

    Microsoft has been nipping at the top open source contributor position for years, but a new analysis by Adobe developer Fil Maj puts Microsoft into a whole other universe of contributions. Or, at least, of contributors.

    Using the GitHub REST API to pull public profile information from all 2,060,011 GitHub users who were active in 2017 (“active” meaning ten or more commits to public projects), Maj was able to pull the total number of corporate contributors to GitHub, with results that might surprise you.

    Which leaves us with Microsoft having twice the number of contributors of its next nearest competitor, Google. For those of us that were around when Microsoft castigated open source as a “cancer” and “anti-American,” this is a remarkable change of heart (or, as I’ve argued, a change of business model). Microsoft has long appreciated the value of developers, but Azure has given Microsoft license to embrace open source as a way to attract them to its platform.

    Meanwhile, Amazon, so often snubbed as an open source ne’er-do-well, comes in at No. 6 in the rankings, with close to 900 contributors. Amazon has perhaps not worn open source on its sleeve in quite the same was as Google and Microsoft have, but it remains a strong contributor to the projects that feed its developer community.

    Other takeaways? Chinese companies like Baidu, Tencent, and Alibaba, which have long been perceived to be net consumers of open source, actually contribute quite a bit. Ditto Oracle, a company to which I’m generally happy to hand out criticism, ranks very high amongst its legacy peers, largely due to its contributions to MySQL and Linux, though not exclusively so.

    #Logiciel_libre #Open_source #Developpeurs #Microsoft

  • The Biggest Misconceptions about Artificial Intelligence
    http://knowledge.wharton.upenn.edu/article/whats-behind-the-hype-about-artificial-intelligence-separat

    Knowledge@Wharton: Interest in artificial intelligence has picked up dramatically in recent times. What is driving this hype? What are some of the biggest prevailing misconceptions about AI and how would you separate the hype from reality?

    Apoorv Saxena: There are multiple factors driving strong interest in AI recently. First is significant gains in dealing with long-standing problems in AI. These are mostly problems of image and speech understanding. For example, now computers are able to transcribe human speech better than humans. Understanding speech has been worked on for almost 20 to 30 years, and only recently have we seen significant gains in that area. The same thing is true of image understanding, and also of specific parts of human language understanding such as translation.

    Such progress has been made possible by applying an old technique called deep learning and running it on highly distributed and scalable computing infrastructure. This combined with availability of large amounts of data to train these algorithms and easy-to-use tools to build AI models, are the major factors driving interest in AI.

    It is natural for people to project the recent successes in specific domains into the future. Some are even projecting the present into domains where deep learning has not been very effective, and that creates a lot of misconception and also hype. AI is still pretty bad in how it learns new concepts and extending that learning to new contexts.

    For example, AI systems still require a tremendous amount of data to train. Humans do not need to look at 40,000 images of cats to identify a cat. A human child can look at two cats and figure out what a cat and a dog is — and to distinguish between them. So today’s AI systems are nowhere close to replicating how the human mind learns. That will be a challenge for the foreseeable future.

    Alors que tout est clean, la dernière phrase est impressionnante : « That will be a challenge for the foreseeable future ». Il ne s’agit pas de renoncer à la compréhension/création de concepts par les ordinateurs, mais de se donner le temps de le faire demain. Dans World without mind , Franklin Foer parle longuement de cette volonté des dirigeants de Google de construire un ordinateur qui serait un cerveau humain amélioré. Mais quid des émotions, des sentiments, de la relation physique au monde ?

    As I mentioned in narrow domains such as speech recognition AI is now more sophisticated than the best humans while in more general domains that require reasoning, context understanding and goal seeking, AI can’t even compete with a five-year old child. I think AI systems have still not figured out to do unsupervised learning well, or learned how to train on a very limited amount of data, or train without a lot of human intervention. That is going to be the main thing that continues to remain difficult . None of the recent research have shown a lot of progress here.

    Knowledge@Wharton: In addition to machine learning, you also referred a couple of times to deep learning. For many of our readers who are not experts in AI, could you explain how deep learning differs from machine learning? What are some of the biggest breakthroughs in deep learning?

    Saxena: Machine learning is much broader than deep learning. Machine learning is essentially a computer learning patterns from data and using the learned patterns to make predictions on new data. Deep learning is a specific machine learning technique.

    Deep learning is modeled on how human brains supposedly learn and use neural networks — a layered network of neurons to learn patterns from data and make predictions. So just as humans use different levels of conceptualization to understand a complex problem, each layer of neurons abstracts out a specific feature or concept in an hierarchical way to understand complex patterns. And the beauty of deep learning is that unlike other machine learning techniques whose prediction performance plateaus when you feed in more training data, deep learning performance continues to improve with more data. Also deep learning has been applied to solve very different sets of problems and shown good performance, which is typically not possible with other techniques. All these makes deep learning special, especially for problems where you could throw in more data and computing power easily.

    Knowledge@Wharton: The other area of AI that gets a lot of attention is natural language processing, often involving intelligent assistants, like Siri from Apple, Alexa from Amazon, or Cortana from Microsoft. How are chatbots evolving, and what is the future of the chatbot?

    Saxena: This is a huge area of investment for all of the big players, as you mentioned. This is generating a lot of interest, for two reasons. It is the most natural way for people to interact with machines, by just talking to them and the machines understanding. This has led to a fundamental shift in how computers and humans interact. Almost everybody believes this will be the next big thing.

    Still, early versions of this technology have been very disappointing. The reason is that natural language understanding or processing is extremely tough. You can’t use just one technique or deep learning model, for example, as you can for image understanding or speech understanding and solve everything. Natural language understanding inherently is different. Understanding natural language or conversation requires huge amounts of human knowledge and background knowledge. Because there’s so much context associated with language, unless you teach your agent all of the human knowledge, it falls short in understanding even basic stuff.

    De la compétition à l’heure du vectorialisme :

    Knowledge@Wharton: That sounds incredible. Now, a number of big companies are active in AI — especially Google, Microsoft, Amazon, Apple in the U.S., or in China you have Baidu, Alibaba and Tencent. What opportunities exist in AI for startups and smaller companies? How can they add value? How do you see them fitting into the broader AI ecosystem?

    Saxena: I see value for both big and small companies. A lot of the investments by the big players in this space are in building platforms where others can build AI applications. Almost every player in the AI space, including Google, has created platforms on which others can build applications. This is similar to what they did for Android or mobile platforms. Once the platform is built, others can build applications. So clearly that is where the focus is. Clearly there is a big opportunity for startups to build applications using some of the open source tools created by these big players.

    The second area where startups will continue to play is with what we call vertical domains. So a big part of the advances in AI will come through a combination of good algorithms with proprietary data. Even though the Googles of the world and other big players have some of the best engineering talent and also the algorithms, they don’t have data. So for example, a company that has proprietary health care data can build a health care AI startup and compete with the big players. The same thing is true of industries such as finance or retail.

    #Intelligence_artificielle #vectorialisme #deep_learning #Google

  • Why China Is Leading the Fintech Race - Knowledge Wharton
    http://knowledge.wharton.upenn.edu/article/why-china-leads-the-fintech-race

    But there are actually seven tech firms in the global top 10 now — the other two are Chinese: Alibaba and Tencent. In China, everyone knows “BAT” (Baidu, the Chinese Google, along with Alibaba and Tencent). There is much less BAT buzz outside China, for two reasons.

    First, the Chinese government’s “great firewall” around the internet not only restricts the flow of information in China, it also helps protect Chinese firms from international competition. Second, the Chinese tech companies have tended to be rapid adopters and adapters of innovations generated elsewhere rather than breakthrough inventors themselves.

    The first point continues to hold: “techno-nationalism” is a new term of concern in the West when it comes to China’s aspirations to chart its own course to global prominence in technology, by protecting the domestic market and always with a close eye on the IP of others.
    Knowledge@Wharton High School

    But the second reason for discounting Chinese tech — that they are incapable of creating true innovation — is rapidly receding as a viable criticism. Anyone who ignores Alibaba and Tencent does so at their own peril because of real innovations they are implementing in China, and what they hope to do globally tomorrow.

    When it comes to Alibaba, think less eBay meets Wal-Mart and Amazon, and more fintech. For Tencent, think less social media and e-sports and more fintech.

    Four hundred and sixty-nine million people made online payments in China in 2016. A larger number used phones to pay in offline retail stores. For comparison, the user base of Apple Pay, by far the dominant American player, was 12 million in the U.S. last year. I am now used to seeing people in China paying for everything from taxis and coffee to clothes and meals with either WeChat (Weixin) Pay or Alipay (Zhifubao) — another world from the China of the early 2000s when you had to pay hotel bills with a series of 100 RMB notes.

    No one knows who will win this global competition, but the recent history of digital payments underlines a key fact. The extraordinary innovativeness of the U.S. tech sector is justly acclaimed. However, it is no longer immune to the forces of globalization and global competition that have disrupted so many other industries in the past few decades.

    #GAFA #TAB #Chine #Fintech #Alibaba #Tencent #Baidu

  • The Geopolitical Economy of the Global Internet Infrastructure on JSTOR
    https://www.jstor.org/stable/10.5325/jinfopoli.7.2017.0228

    Article très intéressant qui repositionne les Etats dans la gestion de l’infrastructure globale de l’internet. En fait, une infrastructure globale pour le déploiement du capital (une autre approche de la géopolitique, issue de David Harvey).

    According to many observers, economic globalization and the liberalization of telecoms/internet policy have remade the world in the image of the United States. The dominant roles of Amazon, Apple, Facebook, and Google have also led to charges of US internet imperialism. This article, however, argues that while these internet giants dominate some of the most popular internet services, the ownership and control of core elements of the internet infrastructure—submarine cables, internet exchange points, autonomous system numbers, datacenters, and so on—are tilting increasingly toward the EU and BRICS (i.e., Brazil, Russia, India, China, and South Africa) countries and the rest of the world, complicating views of hegemonic US control of the internet and what Susan Strange calls the knowledge structure.

    This article takes a different tack. It argues that while US-based internet giants do dominate some of the middle and top layers of the internet—for example, operating systems (iOS, Windows, Android), search engines (Google), social networks (Facebook), online retailing (Amazon), over-the-top TV (Netflix), browsers (Google Chrome, Apple Safari, Microsoft Explorer), and domain names (ICANN)—they do not rule the hardware, or material infrastructure, upon which the internet and daily life, business, governments, society, and war increasingly depend. In fact, as the article shows, ownership and control of many core elements of the global internet infrastructure—for example, fiber optic submarine cables, content delivery networks (CDNs), autonomous system numbers (ASN), and internet exchange points (IXPs)—are tilting toward the rest of the world, especially Europe and the BRICS (i.e., Brazil, Russia, India, China, and South Africa). This reflects the fact that the United States’ standing in the world is slipping while an ever more multipolar world is arising.

    International internet backbone providers, internet content companies, and CDNs interconnect with local ISPs and at one or more of the nearly 2000 IXPs around the world. The largest IXPs are in New York, London, Amsterdam, Frankfurt, Seattle, Chicago, Moscow, Sao Paulo, Tokyo, and Hong Kong. They are core elements of the internet that switch traffic between all the various networks that comprise the internet system, and help to establish accessible, affordable, fast, and secure internet service.

    In developed markets, internet companies such as Google, Baidu, Facebook, Netflix, Youku, and Yandex use IXPs to interconnect with local ISPs such as Deutsche Telecoms in Germany, BT or Virgin Media in Britain, or Comcast in the United States to gain last-mile access to their customers—and vice versa, back up the chain. Indeed, 99 percent of internet traffic handled by peering arrangements among such parties occurs without any money changing hands or a formal contract.50 Where IXPs do not exist or are rare, as in Africa, or run poorly, as in India, the cost of bandwidth is far more expensive. This is a key factor that helps to explain why internet service is so expensive in areas of the world that can least afford it. It is also why the OECD and EU encourage developing countries to make IXPs a cornerstone of economic development and telecoms policy work.

    The network of networks that make up the internet constitute a sprawling, general purpose platform upon which financial markets, business, and trade, as well as diplomacy, spying, national security, and war depend. The world’s largest electronic payments system operator, the Society for Worldwide Interbank Financial Telecommunications’ (SWIFT) secure messaging network carries over 25 million messages a day involving payments that are believed to be worth over $7 trillion USD.59 Likewise, the world’s biggest foreign currency settlement system, the CLS Bank, executes upward of a million trades a day worth between $1.5 and $2.5 trillion over the global cable systems—although that is down by half from its high point in 2008.60 As Stephen Malphrus, former chief of staff to the US Federal Reserve Chairman Ben Bernanke, observed, when “communications networks go down, the financial services sector does not grind to a halt, rather it snaps to a halt.”61

    Governments and militaries also account for a significant portion of internet traffic. Indeed, 90 to 95 percent of US government traffic, including sensitive diplomatic and military orders, travels over privately owned cables to reach officials in the field.62 “A major portion of DoD data traveling on undersea cables is unmanned aerial vehicle video,” notes a study done for the Department of Homeland Security by MIT scholar Michael Sechrist.63 Indeed, the Department of Defense’s entire Global Information Grid shares space in these cables with the general public internet.64

    The 3.6 billion people as of early 2016 who use the internet to communicate, share music, ideas and knowledge, browse, upload videos, tweet, blog, organize social events and political protests, watch pornography, read sacred texts, and sell stuff are having the greatest influence on the current phase of internet infrastructure development. Video currently makes up an estimated two-thirds of all internet traffic, and is expected to grow to 80 percent in the next five years,69 with US firms leading the way. Netflix single-handedly accounts for a third of all internet traffic. YouTube is the second largest source of internet traffic on fixed and mobile networks alike the world over. Altogether, the big five internet giants account for roughly half of all “prime-time” internet traffic, a phrasing that deliberately reflects the fact that internet usage swells and peaks at the same time as the classic prime-time television period, that is, 7 p.m. to 11 p.m.

    Importance des investissements des compagnies de l’internet dans les projets de câbles.

    Several things stand out from this analysis. First, in less than a decade, Google has carved out a very large place for itself through its ownership role in four of the six projects (the SJC, Faster, Unity, and Pacific Cable Light initiatives), while Facebook has stakes in two of them (APG and PLCN) and Microsoft in the PLCN project. This is a relatively new trend and one that should be watched in the years ahead.

    A preliminary view based on the publicly available information is that the US internet companies are important but subordinate players in consortia dominated by state-owned national carriers and a few relatively new competitors. Keen to wrest control of core elements of the internet infrastructure that they perceive to have been excessively dominated by United States interests in the past, Asian governments and private investors have joined forces to change things in their favor. In terms of the geopolitical economy of the internet, there is both a shift toward the Asia-Pacific region and an increased role for national governments.

    Return of the State as Regulator of Concentrated Markets

    In addition to the expanded role of the state as market builder, regulator, and information infrastructure policy maker, many regulators have also rediscovered the reality of significant market concentration in the telecom-internet and media industries. Indeed, the US government has rejected several high-profile telecoms mergers in recent years, such as AT&T’s proposal to take over T-Mobile in 2011, T-Mobile’s bid for Sprint in 2014, and Comcast’s attempt to acquire Time Warner Cable last year. Even the approval of Comcast’s blockbuster takeover of NBC Universal in 2011, and Charter Communications acquisition of Time Warner Cable last year, respectively, came with important strings attached and ongoing conduct regulation designed to constrain the companies’ ability to abuse their dominant market power.87 The FCC’s landmark 2016 ruling to reclassify broadband internet access as a common carrier further indicated that US regulators have been alert to the realities of market concentration and telecoms-internet access providers’ capacity to abuse that power, and the need to maintain a vigilant eye to ensure that their practices do not swamp people’s rights to freely express themselves, maintain control over the collection, retention, use, and disclosure of their personal information, and to access a diverse range of services over the internet.88 The 28 members of the European Union, along with Norway, India, and Chile, have adopted similar “common carriage/network neutrality/open network”89 rules to offset the reality that concentration in core elements of these industries is “astonishingly high”90 on the basis of commonly used indicators (e.g., concentration ratios and the Herfindahl–Hirschman Index).

    These developments indicate a new phase in internet governance and control. In the first phase, circa the 1990s, technical experts and organizations such as the Internet Engineers Task Force played a large role, while the state sat relatively passively on the sidelines. In the second phase, circa the early to mid-2000s, commercial forces surged to the fore, while internet governance revolved around the ICANN and the multi-stakeholder model. Finally, the revelations of mass internet surveillance by many states and ongoing disputes over the multi-stakeholder, “internet freedom” agenda on the one side, versus the national sovereignty, multilateral model where the ITU and UN system would play a larger role in internet governance all indicate that significant moves are afoot where the relationship between states and markets is now in a heightened state of flux.

    Such claims, however, are overdrawn. They rely too heavily on the same old “realist,” “struggle for control” model where conflict between nation-states has loomed large and business interests and communication technologies served mainly as “weapons of politics” and the handmaidens of national interests from the telegraph in the nineteenth century to the internet today. Yet, nation-states and private business interests, then and now, not only compete with one another but also cooperate extensively to cultivate a common global space of economic accumulation. Communication technologies and business interests, moreover, often act independent of the nation-state and via “private structures of cooperation,” that is, cartels and consortia, as the history and contemporary state of the undersea cable networks illustrate. In fact, the internet infrastructure of the twenty-first century, much like that of the industrial information infrastructure of the past 150 years, is still primarily financed, owned, and operated by many multinational consortia, although more than a few submarine communications cables are now owned by a relatively new roster of competitive players, such as Tata, Level 3, Global Cloud Xchange, and so forth. They have arisen mostly in the last 20 years and from new quarters, such as India in the case of Tata, for example.

    #Economie_numérique #Géopolitique #Câbles_sous_marins