person:sergey brin

  • The Path to Artificial Super Intelligence

    Photo by Tony Webster on Unsplash“The new spring in AI is the most significant development in computing in my lifetime. Every month, there are stunning new applications and transformative new techniques. But such powerful tools also bring with them new questions and responsibilities.”  — Sergey BrinSergey Brin couldn’t have put it more clearly. Dubbed as the technology of the decade, AI has been the catchphrase on every futurist’s tongue. From customer support chatbots to smart assistants, AI has begun to transform numerous industry verticals.If you take a deep dive, you would notice AI has started bettering humans in several tasks. Like detecting cancer better than oncologists or translating languages or beating Go (Chinese Checkers) world champion. These achievements are setting up the tone (...)

    #artificial-intelligence #hackernoon-stop-story #artificial-super-intel #machine-learning #future

  • #google Search — How A Master’s Thesis Became An Idea Worth $70 Billion

    Google Search — How A Master’s Thesis Became An Idea Worth $70 BillionWhat most of you might know is that the Google Search that you currently know and use began as a Master’s thesis that Larry Page and Sergey Brin worked on back in 1996, that revolutionized the way people looked at search engines. However, what most do not know is that their initial idea was not to rank websites, rather to rank annotations on websites.“ One idea Page presented to Winograd, a collaboration with Brin, seemed more promising than the others: creating a system where people could make annotations and comments on websites. But the more Page thought about annotation, the messier it got. How would you figure out who gets to comment or whose comment would be the one you’d see first? For that, he says, “We needed a (...)

    #google-search #google-thesis #google-founders-stanford #google-origin-story

  • Google, Apple, Facebook, Les Nouveaux Maîtres du Monde

    Ils s’appellent Bill Gates, Mark Zuckerberg, Sergey Brin ou encore Larry Page : ces Américains, dont certains n’ont pas encore 40 ans, comptent parmi les hommes les plus riches et les plus puissants de la planète. Leur point commun ? Ils ont créé le monde d’aujourd’hui grâce à une révolution technologique sans précédent : Internet et les réseaux sociaux. Anciens ados visionnaires devenus les dirigeants des plus grandes entreprises du secteur – Google, Facebook, Apple, Microsoft –, ils possèdent (...)

    #Apple #Google #Microsoft #Facebook #domination #GAFAM

  • Before Self-Driving Cars Become Real, They Face These Challenges | WIRED

    OH, THE UNTAINTED optimism of 2014. In the spring of that year, the good Swedes at Volvo introduced Drive Me, a program to get regular Josefs, Frejas, Joeys, and Fayes into autonomous vehicles. By 2017, Volvo executives promised, the company would distribute 100 self-driving SUVs to families in Gothenburg, Sweden. The cars would be able to ferry their passengers through at least 30 miles of local roads, in everyday driving conditions—all on their own. “The technology, which will be called Autopilot, enables the driver to hand over the driving to the vehicle, which takes care of all driving functions,” said Erik Coelingh, a technical lead at Volvo.

    Now, in the waning weeks of 2017, Volvo has pushed back its plans. By four years. Automotive News reports the company now plans to put 100 people in self-driving cars by 2021, and “self-driving” might be a stretch. The guinea pigs will start off testing the sort of semi-autonomous features available to anyone willing to pony up for a new Volvo (or Tesla, Cadillac, Nissan, or Mercedes).

    “On the journey, some of the questions that we thought were really difficult to answer have been answered much faster than we expected,” Marcus Rothoff, the carmaker’s autonomous driving program director, told the publication. “And in some areas, we are finding that there were more issues to dig into and solve than we expected.” Namely, price. Rothoff said the company was loath to nail down the cost of its sensor set before it knew how it would work, so Volvo couldn’t quite determine what people would pay for the privilege in riding in or owning one. CEO Hakan Samuelsson has said self-driving functionality could add about $10,000 to the sticker price.

    Volvo’s retreat is just the latest example of a company cooling on optimistic self-driving car predictions. In 2012, Google CEO Sergey Brin said even normies would have access to autonomous vehicles in fewer than five years—nope. Those who shelled out an extra $3,000 for Tesla’s Enhanced Autopilot are no doubt disappointed by its non-appearance, nearly six months after its due date. New Ford CEO Jim Hackett recently moderated expectations for the automaker’s self-driving service, which his predecessor said in 2016 would be deployed at scale by 2021. “We are going to be in the market with products in that time frame,” he told the San Francisco Chronicle. “But the nature of the romanticism by everybody in the media about how this robot works is overextended right now.”

    The scale-backs haven’t dampened the enthusiasm for money-throwing. Venture capital firm CB Insights estimates self-driving car startups—ones building autonomous driving software, driver safety tools, and vehicle-to-vehicle communications, and stockpiling and crunching data while doing it—have sucked in more than $3 billion in funding this year.

    To track the evolution of any major technology, research firm Gartner’s “hype cycle” methodology is a handy guide. You start with an “innovation trigger,” the breakthrough, and soon hit the “peak of inflated expectations,” when the money flows and headlines blare.

    And then there’s the trough of disillusionment, when things start failing, falling short of expectations, and hoovering up less money than before. This is where the practical challenges and hard realities separate the vaporware from the world-changers. Self-driving, it seems, is entering the trough. Welcome to the hard part.

    Technical Difficulties
    “Autonomous technology is where computing was in the 60s, meaning that the technology is nascent, it’s not modular, and it is yet to be determined how the different parts will fit together,” says Shahin Farshchi, a partner at the venture capital firm Lux Capital, who once built hybrid electric vehicles for General Motors, and has invested in self-driving startup Zoox, as well as sensor-builder Aeva.)

    Turns out building a self-driving car takes more than strapping sensors and software onto a set of wheels. In an almost startlingly frank Medium post, Bryan Salesky, who heads up Ford-backed autonomous vehicle outfit Argo AI, laid out the hurdles facing his team.

    First, he says, came the sensor snags. Self-driving cars need at least three kinds to function—lidar, which can see clearly in 3-D; cameras, for color and detail; and radar, with can detect objects and their velocities at long distances. Lidar, in particular, doesn’t come cheap: A setup for one car can cost $75,000. Then the vehicles need to take the info from those pricey sensors and fuse it together, extracting what they need to operate in the world and discarding what they doesn’t.

    “Developing a system that can be manufactured and deployed at scale with cost-effective, maintainable hardware is… challenging,” Salesky writes. (Argo AI bought a lidar company called Princeton Lightwave in October.)

    Salesky cites other problems, minor technological quandaries that could prove disastrous once these cars are actually moving through 3-D space. Vehicles need to be able to see, interpret, and predict the behavior of human drivers, human cyclists, and human pedestrians—perhaps even communicate with them. The cars must understand when they’re in another vehicle’s blind spot and drive extra carefully. They have to know (and see, and hear) when a zooming ambulance needs more room.

    “Those who think fully self-driving vehicles will be ubiquitous on city streets months from now or even in a few years are not well connected to the state of the art or committed to the safe deployment of the technology,” Salesky writes.

    He’s not the only killjoy. “Technology developers are coming to appreciate that the last 1 percent is harder than the first 99 percent,” says Karl Iagnemma, CEO of Nutonomy, a Boston-based self-driving car company acquired by automotive supplier Delphi this fall. “Compared to last 1 percent, the first 99 percent is a walk in the park.”

    The smart companies, Iagnemma says, are coming up with comprehensive ways to deal with tricky edge cases, not patching them over with the software equivalent of tape and chewing gum. But that takes time.

    Money Worries
    Intel estimates self-driving cars could add $7 trillion to the economy by 2050, $2 trillion in the US alone—and that’s not counting the impact the tech could have on trucking or other fields. So it’s curious that no one seems quite sure how to make money off this stuff yet. “The emphasis has shifted as much to the product and the business model as pure technology development,” says Iagnemma.

    Those building the things have long insisted you’ll first interact with a self-driving car through a taxi-like service. The tech is too expensive, and will at first be too dependent on weather conditions, topography, and high-quality mapping, to sell straight to consumers. But they haven’t sorted out the user experience part of this equation. Waymo is set to launch a limited, actually driver-free service in Phoenix, Arizona, next year, and says it has come up with a way for passengers to communicate they want to pull over. But the company didn’t let reporters test the functionality during a test drive at its test facility this fall, so you’ll have to take its word for it.

    Other questions loom: How do you find your vehicle? Ensure that you’re in the right one? Tell it that you’re having an emergency, or that you’ve had a little accident inside and need a cleanup ASAP? Bigger picture: How does a company even start to recoup its huge research and development budget? How much does it charge per ride? What happens when there’s a crash? Who’s liable, and how much do they have to pay in insurance?

    One path forward, money-wise, seems to be shaking hands with enemies. Companies including Waymo, GM, Lyft, Uber, and Intel, and even seemingly extinction-bound players like the car rental firm Avis, have formed partnerships with potential rivals, sharing data and services in the quest to build a real autonomous vehicle, and the infrastructure that will support it.

    Still, if you ask an autonomous car developer whether it should be going at it alone—trying to build out sensors, mapping, perception, testing capabilities, plus the car itself—expect a shrug. While a few big carmakers like General Motors clearly seem to think vertical integration is the path to a win (it bought the self-driving outfit Cruise Automation last year, and lidar company Strobe in October), startups providing à la carte services continue to believe they are part of the future. “There are plenty of people quietly making money supplying to automakers,” says Forrest Iandola, the CEO of the perception company DeepScale, citing the success of more traditional automotive suppliers like Bridgestone.

    Other companies seize upon niche markets in the self-driving space, betting specific demographics will help them make cash. The self-driving shuttle company Voyage has targeted retirement communities. Optimus Ride, an MIT spinoff, recently announced a pilot project in a new developed community just outside of Boston, and says it’s focused on building software with riders with disabilities in mind.

    “We think that kind off approach, providing mobility to those who are not able-bodied, is actually going to create a product that’s much more robust in the end,” says CEO Ryan Chin. Those companies are raising money. (Optimus Ride just came off an $18 million Series A funding round, bringing its cash pull to $23.25 million.) But are theirs viable strategies to survive in the increasingly crowded self-driving space?

    The Climb
    OK, so you won’t get a fully autonomous car in your driveway anytime soon. Here’s what you can expect, in the next decade or so: Self-driving cars probably won’t operate where you live, unless you’re the denizen of a very particular neighborhood in a big city like San Francisco, New York, or Phoenix. These cars will stick to specific, meticulously mapped areas. If, by luck, you stumble on an autonomous taxi, it will probably force you to meet it somewhere it can safely and legally pull over, instead of working to track you down and assuming hazard lights grant it immunity wherever it stops. You might share that ride with another person or three, à la UberPool.

    The cars will be impressive, but not infallible. They won’t know how to deal with all road situations and weather conditions. And you might get some human help. Nissan, for example, is among the companies working on a stopgap called teleoperations, using remote human operators to guide AVs when they get stuck or stumped.

    And if you’re not lucky enough to catch a ride, you may well forget about self-driving cars for a few years. You might joke with your friends about how silly you were to believe the hype. But the work will go on quietly, in the background. The news will quiet down as developers dedicate themselves to precise problems, tackling the demons in the details.

    The good news is that there seems to be enough momentum to carry this new industry out of the trough and onto what Gartner calls the plateau of productivity. Not everyone who started the journey will make the climb. But those who do, battered and a bit bloody, may just find the cash up there is green, the robots good, and the view stupendous.

    #Uber #disruption

  • Google’s true origin partly lies in CIA and NSA research grants for mass surveillance — Quartz

    Le titre est un peu « clickbait », mais les infos sont intéressantes, quoique parfois elliptiques.

    C’est écrit par : Jeff Nesbit, Former director of legislative and public affairs, National Science Foundation
    Quelqu’un qui doit savoir de quoi il cause.

    In the mid 1990s, the intelligence community in America began to realize that they had an opportunity. The supercomputing community was just beginning to migrate from university settings into the private sector, led by investments from a place that would come to be known as Silicon Valley.

    The intelligence community wanted to shape Silicon Valley’s efforts at their inception so they would be useful for homeland security purposes. A digital revolution was underway: one that would transform the world of data gathering and how we make sense of massive amounts of information. The intelligence community wanted to shape Silicon Valley’s supercomputing efforts at their inception so they would be useful for both military and homeland security purposes. Could this supercomputing network, which would become capable of storing terabytes of information, make intelligent sense of the digital trail that human beings leave behind?

    Intelligence-gathering may have been their world, but the Central Intelligence Agency (CIA) and the National Security Agency (NSA) had come to realize that their future was likely to be profoundly shaped outside the government. It was at a time when military and intelligence budgets within the Clinton administration were in jeopardy, and the private sector had vast resources at their disposal. If the intelligence community wanted to conduct mass surveillance for national security purposes, it would require cooperation between the government and the emerging supercomputing companies.

    Silicon Valley was no different. By the mid 1990s, the intelligence community was seeding funding to the most promising supercomputing efforts across academia, guiding the creation of efforts to make massive amounts of information useful for both the private sector as well as the intelligence community.

    They funded these computer scientists through an unclassified, highly compartmentalized program that was managed for the CIA and the NSA by large military and intelligence contractors. It was called the Massive Digital Data Systems (MDDS) project.
    The Massive Digital Data Systems (MDDS) project

    MDDS was introduced to several dozen leading computer scientists at Stanford, CalTech, MIT, Carnegie Mellon, Harvard, and others in a white paper that described what the CIA, NSA, DARPA, and other agencies hoped to achieve. The research would largely be funded and managed by unclassified science agencies like NSF, which would allow the architecture to be scaled up in the private sector if it managed to achieve what the intelligence community hoped for.

    “Not only are activities becoming more complex, but changing demands require that the IC [Intelligence Community] process different types as well as larger volumes of data,” the intelligence community said in its 1993 MDDS white paper. “Consequently, the IC is taking a proactive role in stimulating research in the efficient management of massive databases and ensuring that IC requirements can be incorporated or adapted into commercial products. Because the challenges are not unique to any one agency, the Community Management Staff (CMS) has commissioned a Massive Digital Data Systems [MDDS] Working Group to address the needs and to identify and evaluate possible solutions.”

    In 1995, one of the first and most promising MDDS grants went to a computer-science research team at Stanford University with a decade-long history of working with NSF and DARPA grants. The primary objective of this grant was “query optimization of very complex queries that are described using the ‘query flocks’ approach.” A second grant—the DARPA-NSF grant most closely associated with Google’s origin—was part of a coordinated effort to build a massive digital library using the internet as its backbone. Both grants funded research by two graduate students who were making rapid advances in web-page ranking, as well as tracking (and making sense of) user queries: future Google cofounders Sergey Brin and Larry Page.

    The research by Brin and Page under these grants became the heart of Google: people using search functions to find precisely what they wanted inside a very large data set. The intelligence community, however, saw a slightly different benefit in their research: Could the network be organized so efficiently that individual users could be uniquely identified and tracked?

    The grants allowed Brin and Page to do their work and contributed to their breakthroughs in web-page ranking and tracking user queries. Brin didn’t work for the intelligence community—or for anyone else. Google had not yet been incorporated. He was just a Stanford researcher taking advantage of the grant provided by the NSA and CIA through the unclassified MDDS program.
    Left out of Google’s story

    The MDDS research effort has never been part of Google’s origin story, even though the principal investigator for the MDDS grant specifically named Google as directly resulting from their research: “Its core technology, which allows it to find pages far more accurately than other search engines, was partially supported by this grant,” he wrote. In a published research paper that includes some of Brin’s pivotal work, the authors also reference the NSF grant that was created by the MDDS program.

    Instead, every Google creation story only mentions just one federal grant: the NSF/DARPA “digital libraries” grant, which was designed to allow Stanford researchers to search the entire World Wide Web stored on the university’s servers at the time. “The development of the Google algorithms was carried on a variety of computers, mainly provided by the NSF-DARPA-NASA-funded Digital Library project at Stanford,” Stanford’s Infolab says of its origin, for example. NSF likewise only references the digital libraries grant, not the MDDS grant as well, in its own history of Google’s origin. In the famous research paper, “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” which describes the creation of Google, Brin and Page thanked the NSF and DARPA for its digital library grant to Stanford. But the grant from the intelligence community’s MDDS program—specifically designed for the breakthrough that Google was built upon—has faded into obscurity.

    Google has said in the past that it was not funded or created by the CIA. For instance, when stories circulated in 2006 that Google had received funding from the intelligence community for years to assist in counter-terrorism efforts, the company told Wired magazine founder John Battelle, “The statements related to Google are completely untrue.”

    Did the CIA directly fund the work of Brin and Page, and therefore create Google? No. But were Brin and Page researching precisely what the NSA, the CIA, and the intelligence community hoped for, assisted by their grants? Absolutely.

    In this way, the collaboration between the intelligence community and big, commercial science and tech companies has been wildly successful. When national security agencies need to identify and track people and groups, they know where to turn – and do so frequently. That was the goal in the beginning. It has succeeded perhaps more than anyone could have imagined at the time.

  • Google Has Quietly Dropped Ban on Personally Identifiable Web Tracking

    Google is the latest tech company to drop the longstanding wall between anonymous online ad tracking and user’s names. When Google bought the advertising network DoubleClick in 2007, Google founder Sergey Brin said that privacy would be the company’s “number one priority when we contemplate new kinds of advertising products.” And, for nearly a decade, Google did in fact keep DoubleClick’s massive database of web-browsing records separate by default from the names and other personally (...)

    #Google #Gmail #terms #publicité #profiling


  • Get Rich U. - The New Yorker (avril 2012)

    If the Ivy League was the breeding ground for the élites of the American Century, #Stanford is the farm system for #Silicon_Valley.


    In 1998, Larry Page and Sergey Brin, who were graduate students, showed Hennessy their work on search software that they later called #Google. He typed in the name Gerhard Casper, and instead of getting results for Casper the Friendly Ghost, as he did on AltaVista, up popped links to Gerhard Casper the president of Stanford. He was thrilled when members of the engineering faculty mentored Page and Brin and later became Google investors, consultants, and shareholders. Since Stanford owned the rights to Google’s search technology, he was also thrilled when, in 2005, the stock grants that Stanford had received in exchange for licensing the technology were sold for three hundred and thirty-six million dollars.

    In 1999, after Condoleezza Rice stepped down as provost to become the chief foreign-policy adviser to the Republican Presidential candidate George W. Bush, Casper offered Hennessy the position of chief academic and financial officer of the university. Soon afterward, Hennessy induced a former electrical-engineering faculty colleague, James Clark, who had founded Silicon Graphics (which purchased MIPS), to give a hundred and fifty million dollars to create the James H. Clark Center for medical and scientific research. Less than a year later, Casper stepped down as president and Hennessy replaced him.

    Hennessy joined Cisco’s corporate board in 2002, and Google’s in 2004. It is not uncommon for a university president to be on corporate boards. According to James Finkelstein, a professor at George Mason University’s School of Public Policy, a third of college presidents serve on the boards of one or more publicly traded companies. Hennessy says that his outside board work has made him a better president. “Both Google and Cisco face—and all companies in a high-tech space face—a problem that’s very similar to the ones universities face: how do they maintain a sense of innovation, of a willingness to do the new thing?” he says.

    #tech_companies #startups #université

  • RAGEMAG | Google Glass : un gadget pour nantis en mal de reconnaissance technologique ?

    A quel moment le portable bascula-t-il de symbole de statut et de pouvoir à celui d’ « émasculation » ? Dès lors qu’il devint plus facile à se procurer que des toilettes, très certainement.

    Si on l’interrogeait, il y a fort à parier que Sergey Brin ferait remonter cette bascule à l’arrivée du smartphone à écran tactile – quand utiliser un portable commença à rimer avec « rester planté à caresser une vitre absolument lisse », les yeux baissés, plutôt que de beugler des ordres dans un mobile digne d’une cabine téléphonique, coude fléchi, biceps saillant, le regard inflexible porté droit devant (ou sur un seconde classe). Un vrai bonhomme ne reste pas « planté » : un vrai bonhomme agit ! Un vrai bonhomme écrase les touches de ses gros doigts autoritaires, et prend les mesures qui s’imposent ! PJ Rey et moi-même avions débattu du smartphone comme expression de notre capacité d’action, mais « caresser » ? Toucher ? Encore un truc de gonzesses. Beurk.

    L’insécurité du nanti

    Sergey Brin, évangéliste des Glass.

    Blague à part, l’insécurité évoquée par Brin à travers le smartphone ne se limite pas à sa fragile surface (vitreuse). Brin considère le smartphone « émasculant » non seulement du fait de l’immobilité demandée pour le caresser, et pas uniquement parce que « même les filles » peuvent le faire, mais aussi parce que son smartphone ne l’associe plus à l’élite au pouvoir. Le concept de masculinité est indissociable de celui d’autorité, et le statut privilégié de Brin s’explique autant par sa classe sociale et son identité professionnelle que par son genre. Les portables symbolisaient l’autorité mâle quand seuls les businessmen pleins aux as pouvaient se les payer. Maintenant que des milliards de quidams en ont un dans la poche, leur capacité à signifier un certain statut s’est éteinte en trois sonneries, plus vite qu’un appel dans un tunnel.

    Rappelez-vous (pour les moins jeunes) le bon vieux temps des gros portables hors de prix, que presque personne n’avait. Lorsque vous fermez les yeux et pensez à celui qui tenait l’une de ces toutes premières briques dans la main, qui voyez-vous ? Un blanc dans un costard, une Rolex au poignet, des lunettes de soleil eighties sur le nez ? Oui, c’est bien ce que je pensais. Les premiers modèles de « téléphone cellulaire » – comme à peu près toute technologie flambant neuve et ultra chère – faisaient office de marqueurs de statut. Un cellulaire signifiait : « Je suis riche, je suis puissant, et je suis tellement important que n’importe qui doit pouvoir me joindre même quand je ne suis ni chez moi ni au bureau. »

    Puis leur taille diminua, leur prix baissa, et ils se démocratisèrent. Les élites furent néanmoins sauvées par l’arrivée du smartphone à écran tactile. Pas aussi chers que les pionniers du cellulaire, les premiers iPhones n’étaient quand même pas donnés, pour ceux capables de s’en dégoter un : à 499 $ pièce avec un contrat de 24 mois chez AT&T, les gens faisaient encore la queue des heures devant les boutiques Apple dans l’espoir de mettre la main dessus. Nous étions en 2007, et l’iPhone devenait instantanément un symbole de statut. Mais accélérons un peu le film : en 2013, qu’en est-il ? On ne compte plus les smartphones à écran tactile disponibles sur le marché. L’iPhone lui-même est aujourd’hui proposé chez les quatre gros opérateurs US (sans déblocage). A un mètre de distance, bien malin qui pourrait distinguer un iPhone 5 à 849 $ neuf d’un vulgaire iPhone 4 d’occas à 90 $. D’excitant, le symbole de statut a plongé dans le plébéien et le mondain.

    #google_glass #iphone #reconnaissance #technologique

  • Dans les nouvelles du matin :

    Google founder splits with wife… Co-founder Sergey Brin and his wife of six years, 23AndMe co-founder Anne Wojcicki, are living apart following Brin’s alleged involvement with a Google employee. Although the couple’s joint assets and projects are substantial, AllThingsD reports that a prenuptial agreement ensures no impact on Google if the couple divorces.

    …as a key executive jumps ship. Top Android executive Carlos Barra is defecting to China’s fast-growing smartphone company Xiaomi. According to AllThingsD, Barra was formerly dating the woman who is now involved with Brin.

    #vie_privée #google

  • Le jour où #Google gagna la première bataille du Net | bluetouff

    Les plus jeunes ne le savent probablement pas, mais la venue de #Microsoft sur le « terrain commercial #Internet » a été douloureuse. Lente, souvent maladroite, l’approche d’Internet proposée à ses clients en terme d’expérience utilisateur a été l’un des challenges les plus difficiles que Microsoft ait du relever. En 1998, date de la création de Google par Larry Page et Sergey Brin, Microsoft se consacre corps et âme à son coeur de métier, le développement et la commercialisation du système d’exploitation Windows 98 et de ses solutions entreprise (NT4). Internet n’était alors pas encore dans tous les foyers, aussi, les utilisateurs arrivaient encore tant bien que mal à faire la différence entre leur sphère privée (leur ordinateur, leur navigateur, leur client email, leurs applications de bureautique….) et la sphère publique d’Internet, le offline, gratuit et le online, affreusement consommateur d’unités téléphoniques. Internet n’avait rien d’illimité à l’époque. C’est aussi avec Windows 98 que la majorité des internautes de l’époque surfaient sur un web encore tout jeune. Il fallut d’ailleurs attendre la seconde édition de Windows 98 pour que le système d’exploitation dispose par défaut du nécessaire pour se connecter à peu près convenablement à Internet une fois fraîchement installé. Le premier (...)

    #A_la_Une #Bienvenue_chez_Google

  • A New and Frightening #Stuxnet |

    ISSSource has learned leaders of the three major software companies, Sergey Brin at Google, Steve Ballmer at Microsoft and Larry Ellison at Oracle have been working with Israel’s top cyber warriors and have now come up with new version of a Stuxnet-like worm that can bring down Iran’s entire software networks if the Iranian regime gets too close to a breakout, according to U.S. intelligence sources.

    Cet article est-il crédible ? il est très flou sur ses sources et références, ce qui est d’ailleurs fortement reproché par Dale Peterson à la plupart des papiers sur Stuxnet

    Stuxnet Reporting Needs Facts and Attribution
    (lire aussi sous cet article le commentaire de Ralph Langner lui-même)

    #iran #cyberguerre #psyops