Moore's Law Is Dead, What Comes Next? The world’s most powerful computing machine is perhaps also the most ubiquitous: the human brain. It’s able to perform computations on a scale that even the most advanced supercomputers cannot hope to match. However, the circuitry underpinning our brains is surprisingly sloppy and slow. Neurons act on millisecond timescales – slow when compared to the fastest processors – and can fail to activate; one reason why the brain has so many neurons is this redundancy. “The problem we’re now facing is more fundamental than anything before” What allows the brain to run on this clunky machinery is parallel computing, the ability to solve problems simultaneously using many different parts of the brain. It’s the law that says the number of transistors on a chip will double every two years; it’s the law that accurately described the explosion in computing power that enables the modern world to function; it’s Moore’s Law and it is coming to a grinding halt. Comments
Surveiller les algorithmes De plus en plus souvent, des algorithmes décident de notre rapport au monde. Que ce soit pour nous mettre en relation avec d'autres sur des sites de rencontres ou pour estimer notre capacité de crédit, pour nous diriger dans la ville via nos GPS voir même pour nous autoriser à retirer de l'argent à un distributeur automatique... les algorithmes se sont infiltrés dans notre vie quotidienne sans notre consentement et modulent notre rapport au monde sans que nous soyons vraiment au courant de leur existence, de l'ampleur de leur action, de leur pouvoir et des critères qu'ils utilisent pour décider de nos existences à notre place. Sans que nous ayons non plus beaucoup de possibilités pour réfuter ou intervenir sur ces critères. "Trop souvent, c'est l'ordinateur qui décide !" Comprendre comment fonctionnent les algorithmes qui nous gouvernent n'est pourtant pas du recours des seuls spécialistes, estime le journaliste Frank Swain (@SciencePunk). Frank voyage dans le monde entier...
The Gigaom guide to deep learning: Who’s doing it, and why it matters The field of deep learning is picking up steam to the point that it’s now inspiring a growing list of startups in areas such as natural language processing and image recognition. It’s also commanding a growing percentage of research and acquisition budgets at companies such as Google, Microsoft, Facebook and Yahoo. This post highlights some of the companies involved in this space and the type of products or projects they’re working on. What deep learning is First, though, a little primer: Despite its cognitive moniker, deep learning isn’t really about teaching machines to mimic the human brain a la the BRAIN Initiative President Obama announced in 2012. Rather, it’s about teaching machines to think more hierarchically or more contextually — to see a picture of a mole, for example, and work down from recognizing the features that comprise an animal to recognizing the specific features that make it a mole. One layer of a Google deep learning network for image recognition. The startups
scientists put free text-analysis tool on the web Now anyone can drag and drop text into a linguistic analysis tool powered by machine learning. By Andrew Myers and Tom Abate Ever wondered whether a certain TV show had a slant in favor of a political candidate? Stanford computer scientists have created a website that gives anyone who can cut and paste the ability to answer such questions, systematically and for free. The website is known as etcML, short for Easy Text Classification with Machine Learning. Machine learning is a field of computer science that develops systems that give computers the ability to acquire new understandings in a more human-like way. The etcML website is based on machine-learning techniques that were developed to analyze the meaning embodied in text, then gauge its overall positive or negative sentiment. “All users have to do is copy and paste, or drop their text datasets into their browser and click,” Socher said. Voigt studies what makes a successful pitch. “This is a free and powerful tool,” Socher said.
Full Steam Ahead: Inside Valve's Grand Plan to Replace Game Consoles With PCs | Game|Life Clockwise from left: Anna Sweet, Eric Hope and Greg Coomer, three of the Valve employees at work on the company’s Steam Machines initiative, in the Valve offices in Bellevue, Washington. Photo: Matthew Ryan Williams/WIRED BELLEVUE, WA — Installed base. It’s what every gaming machine needs if it’s to get even a tenuous foothold in this ultra-competitive market. The difficulty of squaring this circle is the reason why the history of the gaming business is strewn with the bodies of failed platforms. Nintendo’s fall from grace might give Sony and Microsoft, the current kings of the living room, more confidence when it comes to the launches of their respective new platforms, PlayStation 4 and Xbox One, later this month. Last week, Valve announced that 65 million people were now active users of Steam, its gaming umbrella service for personal computers. Our customers love all those Steam titles, but they also like their families. Valve doesn’t need to convince anybody to give up their Xbox.
Le premier robot qui s’adapte aux pannes en deux minutes LE MONDE | • Mis à jour le | Par Nathaniel Herzberg Les robots sont partout. Sur les planètes éloignées ou au fond des abysses, dans les salles d’opération ou les salles des marchés, derrière les portes closes des usines ou sous le capot de nos voitures. Seulement voilà : ils tombent en panne. Une équipe française a peut-être trouvé la parade. « Je débranche une des pattes » Au sous-sol de l’institut des systèmes intelligents et de robotique de l’université Pierre-et-Marie-Curie, à Paris, Antoine Cully présente sa merveille avec un mélange de timidité et de fierté. Sur le sol du laboratoire, la grosse araignée mécanique avance ses six membres d’un pas saccadé mais régulier. « Maintenant, je débranche une des pattes », sourit-il. « Il fait comme un chien blessé, il puise dans son expérience et utilise son intuition », explique Antoine Cully. Algorithme Pas de diagnostic, donc. « C’est terriblement difficile, cela nécessite de disposer de nombreux capteurs, et c’est affreusement cher.
World's Fastest Computer Will Operate Like a Human Brain Google in Jeopardy: What If IBM's Watson Dethroned the King of Search? | Wired Opinion Photo: Sam Gustin / WIRED Remember Watson, IBM’s Jeopardy champion? A couple years ago, Watson beat the top two human champions Ken Jennings and Brad Rutter at a game where even interpreting the cue is complex with language nuances. (Not to mention finding answers at lightning speed on any subject matter.) Yet after the initial excitement, most people – except for a notable few – forgot about Watson. Watson was arguably the first computer ever to pass the Turing Test, designed by British mathematician Alan Turing to determine whether a computer could think. Vasant Dhar is co-director of the Center for Business Analytics at the Stern School of Business at NYU and head of its Information Systems Group. If you had a choice between asking a question to a Jeopardy champion and a search engine, which would you choose – Watson or PageRank? Which means there would be no reason for anyone to start their searches on Google. In other words: Google can retrieve, but Watson can create.
The Battle For The Connected Home Is Heating Up Editor’s note: Matt Turck is a managing director of FirstMark Capital. Follow him on Twitter at @mattturck. Almost 15 years ago, a friend of mine at McKinsey spent a few nights writing a document called “The Battle for the Home”. The thesis at the time was that with broadband, the home PC was gradually going to challenge the TV as the core home digital system. Over the following few years, that battle gradually grew more complex, as the home saw the adoption of a new generation of HDTV sets, game consoles, set-top boxes and DVR options. But fundamentally, the discussion was about who was going to control the home entertainment system. Now, the battle has expanded to the rest of the home. The irony of this market, not always acknowledged, is that a number of large companies with big brands and existing “pipes” in our homes, have been unusually innovative. The first battle for the home was not always kind to startups. The new household brands This is a big opportunity. Not so fast