Image recognition helps find your keys / wallet BBC

Kinsight uses Kinect sensor to find lost keys and wallets Objects tracked by the Kinsight system The team used their system to track a range of objects around a home Continue reading the main story Related Stories Microsoft launches Kinect for PCs Interface controls compete at CES Earthquake rescue with Kinect bot Forgetful geeks need never lose keys, phones or even cutlery at home again. Two computer science researchers have developed a depth-camera based system that keeps track of household objects as they are moved around a building. The project - dubbed Kinsight - relies on several of Microsoft's Kinect sensors attached to a computer running the team's software. Although the project is still at an experimental stage, it has been shown to work in a "real-world scenario". Details of the system were recently outlined at a conference in China and were subsequently reported by New Scientist. "Imagine if we had a system that could keep account of all the objects that we interact with in our daily lives," the researchers said. "By keeping track of the locations of the objects, we could build a smart search engine for our home that could answer queries like - where are my eye glasses, or my TV-remote, or my wallet?" Although alternative solutions, such as the use of radio-frequency identification chips already exists, the men said their system was many times cheaper due to the high cost of RFID readers. What goes where The researchers noted that running a computer program that simultaneously tracked all the owner's objects in real-time would be too processor-intensive. So they based their design around the principle that objects only change locations when humans move them. As a result the system focuses on tracking human figures and then looking for objects that have changed position in their vicinity. Although the Kinect sensor's capabilities are limited - it only sees objects up to 11 feet (3.4m) away and only provides "skeleton data" at 15 frames/second - the Kinsight program has commonsense notions built into it to improve accuracy: so it knows that a coffee cup is most likely to be found at a study desk, or kitchen sink, but not inside a bath. Kinect sensor The researchers say accuracy could be improved if Microsoft releases a more powerful Kinect "This means that, when in doubt, an object recognition algorithm can use this knowledge to identify an object by analysing the likelihood of it being at some location, or looking for the candidate objects in their other locations," the researchers said. On the move Algorithms were also created to help the computer learn the appearance of objects and the context they were likely to be used in by analysing the data gathered. To prove the system worked the two scientists labelled 48 objects - including knives, forks, keys and a Rubik's cube - and identified 80 possible locations around a house. They then asked volunteers to move the items around according to randomly generated patterns. The results suggested room for improvement - errors were more likely if the objects were very small, far away, transparent or placed too closely together - but the team said these problems should be addressed by using more sensors per room and adopting more sensitive depth-cameras. In the meantime, they say that even when the program does lose track of possessions, it can still say were they were last seen which may still prove helpful.

L'offensive secrète d'Obama contre l'Iran

Révélations sur l'extrême implication du président dans les cyberattaques contre le programme nucléaire deTéhéran. Le virus Stuxnet, développé conjointement par les États-Unis et Israël sous le nom de «Jeux olympiques», visait à détraquer le programme nucléaire iranien. Il a réussi au-delà de toute espérance. Dans un livre qui vient de paraître aux États-Unis, la Maison-Blanche reconnaît à mots couverts l'implication extrême du président Barack Obama. À quelques jours de son intronisation, en janvier 2009, Barack Obama est convoqué à la Maison-Blanche pour un aparté très discret avec son prédécesseur, George W. Bush. Ce que dit le quarante-troisième président des États-Unis est sans détour. Il est vital, martèle Bush, de préserver deux actions en cours: l'utilisation de drones au Pakistan dans la lutte contre al-Qaida et la cyberguerre contre l'Iran. Ce qui suit est relaté dans un livre publié mardi aux États-Unis, signé par David Sanger*, rédacteur au New York Times, qui livre des témoignages inédits. Barack Obama découvre qu'une «sale guerre» très secrète se joue depuis 2006 contre le régime chiite de Téhéran. Non pas avec des troupes au sol, mais avec des ordinateurs, des virus et des codes malveillants. Une guerre moins sanglante en apparence, mais tout aussi âpre, et dont l'issue pourrait également «décider de la guerre ou de la paix», comme n'hésite pas à lui confier le président sortant. L'arme fatale, en l'occurrence, est un virus informatique d'une puissance inégalée, nom de code «Olympic Games » («Jeux olympiques»), qui, depuis deux ans, sème le chaos au sein du programme nucléaire iranien. Programme nucléaire souterrain À la surprise générale, Obama va se muer en chef de guerre déterminé, à mille lieues de sa pusillanimité supposée en matière de politique étrangère. Omniprésent dans la conduite des opérations, le président démocrate exige un briefing hebdomadaire sur l'état de l'offensive en cours, donnant son aval à chaque nouvelle cyberattaque contre l'Iran. «Jamais, écrit Sanger, depuis Lyndon Johnson et le choix des cibles à bombarder au Nord-Vietnam, un président n'avait été impliqué d'aussi près dans l'escalade pas à pas d'une attaque contre les infrastructures d'une nation étrangère.» L'origine du programme remonte à 2006, lorsque l'Administration Bush constate l'épuisement des stratégies traditionnelles face à des dirigeants iraniens de plus en plus arrogants. Convenant que des frappes conventionnelles auraient peu d'effets sur un programme nucléaire souterrain et disséminé aux quatre coins du vaste désert iranien, la Maison-Blanche décide de lancer des «cyberattaques» contre le cœur de ce programme, les souterrains de Natanz, à 250 km au sud de Téhéran. «Jeux olympiques» doit pouvoir détruire les très sensibles centrifugeuses de Natanz, en modifiant la vitesse de rotation de leurs moteurs. Dans cette opération américano-israélienne, les programmateurs de la National Security Agency (NSA), à Fort Meade (Maryland), près de Washington, collaborent avec une unité spéciale de guerre électronique de Tsahal, connue sous le nom d'Unité 8200. Initialement baptisé «The Bug» par ses créateurs, le virus va être testé avec succès sur des centrifugeuses libyennes d'un modèle semblable, saisies en 2003. Reste à l'inséminer dans le très secret système informatique du programme nucléaire iranien. Il fallait trouver un ingénieur ou un technicien physiquement rattaché aux installations de Natanz pour y introduire involontairement le virus. «C'était notre Saint-Graal, commente laconiquement l'un des auteurs du projet. Et il s'avère qu'il y a toujours un idiot pour ne pas trop réfléchir à ce que contient la clé USB entre ses mains.» Les résultats vont au-delà des espérances. «Olympic Games» s'infiltre dans les arcanes de Natanz, déclenchant des pannes de centrifugeuses, en apparence bénignes et localisées. Jusqu'à ce que survienne un couac majeur en 2010. Le virus échappe à ses créateurs lorsqu'un ingénieur iranien le libère tout à fait involontairement sur Internet. La menace, détectée durant l'été aux quatre coins du globe, est rebaptisée Stuxnet par les experts en sécurité informatique. Mille centrifugeuses détruites Barack Obama se trouve à la croisée des chemins. Il doit décider de tout arrêter avant qu'il ne soit trop tard, que cette arme d'un genre nouveau désormais révélée au grand jour ne soit décortiquée par les ennemis des États-Unis et ne revienne comme un boomerang sur les infrastructures vitales américaines. Convaincu des dégâts «prometteurs» causés à Natanz, Obama autorise deux nouvelles cyberattaques, à l'aide d'une version perfectionnée de «Jeux olympiques», rebaptisé «Flame» (flamme). Il ne le regrettera pas. «Flame» réussit l'exploit de détruire mille exemplaires de centrifugeuses iraniennes ultramodernes de type Ir-2. Mieux, les interceptions révèlent que l'Iran est en train de perdre confiance en son savoir-faire et ses ingénieurs. Certains d'entre eux sont même limogés sans autre forme de procès. Le chaos est complet dans les souterrains de Natanz et les laboratoires de la capitale iranienne. Les sources consultées par Sanger sont formelles: malgré le fiasco de Stuxnet, «Flame» a sans doute retardé d'un an et demi à deux ans le programme nucléaire iranien dans sa quête de la bombe. Un délai précieux, censé permettre aux sanctions internationales de faire enfin entendre raison au régime iranien. Cet objectif-là n'est pas encore atteint. * David E. Sanger, Confront and Conceal: Obama's Secret Wars and Surprising Use of American Power, Crown publishers, juin 2012.

Big data from social networks take trendwatching to new level WASHpost

‘Big data’ from social media, elsewhere online redefines trend-watching By Ariana Eunjung Cha, Published: June 6 From a trading desk in London, Paul Hawtin monitors the fire hose of more than 340 million Twitter posts flying around the world each day to try to assess the collective mood of the populace. The computer program he uses generates a global sentiment score from 1 to 50 based on how pessimistic or optimistic people seem to be from their online conversations. Hawtin, chief executive of Derwent Capital Markets, buys and trades millions of dollars of stocks for private investors based on that number: When everyone appears happy, he generally buys. When anxiety runs high, he sells short. Hawtin has seen a gain of more than 7 percent in the first quarter of this year, and his method shows the advantage individuals, companies and governments are gaining as they take hold of the unprecedented amount of data online. Traders such as Hawtin say analyzing mathematical trends on the Web delivers insights and news faster than traditional investment approaches. The explosion in the use of Google, Facebook, Twitter and other services has resulted in the generation of some 2.5 quintillion bytes each day, according to IBM. “Big data,” as it has been dubbed by researchers, has become so valuable that the World Economic Forum, in a report published last year, deemed it a new class of economic asset, like oil. “Business boundaries are being redrawn,” the report said. Companies with the ability to mine the data are becoming the most powerful, it added. While the human brain cannot comprehend that much information at once, advances in computer power and analytics have made it possible for machines to tease out patterns in topics of conversation, calling habits, purchasing trends, use of language, popularity of sports, spread of disease and other expressions of daily life. “This is changing the world in a big way. It enables us to watch changes in society in real time and make decisions in a way we haven’t been able to ever before,” said Gary King, a social science professor at Harvard University and a co-founder of Crimson Hexagon, a data analysis firm based in Boston. The Obama campaign employs rows of people manning computers that monitor Twitter sentiment about the candidates in key states. Google scientists are working with the Centers for Disease Control and Prevention to track the spread of flu around the world by analyzing what people are typing in to search. And the United Nations is measuring inflation through computers that analyze the price of bread advertised in online supermarkets across Latin America. Many questions about big data remain unanswered. Concerns are being raised about personal privacy and how consumers can ensure that their information is being used fairly. Some worry that savvy technologists could use Twitter or Google to create false trends and manipulate markets. Even so, sociologists, software engineers, economists, policy analysts and others in nearly every field are jumping into the fray. And nowhere has big data been as transformative as it has been in finance. Wall Street is all about information advantage. Every little bit could mean the difference between a bonanza or a devastating loss, and so big data is being fed into computers to power high-frequency trading algorithms — and directly to traders in every way imaginable. Hedge funds are experimenting with scanning comments on Amazon product pages to try to predict sales. Banks are tallying job listings on Monster as an indicator of hiring. Investment firms are conducting computer analyses of the financial statements of public companies to search for signs of a bankruptcy. Why wait for the government to release official numbers on auto sales, home sales and retail sales when the trends could be gleaned weeks or even months earlier by analyzing publicly available data online? Five years ago, only 2 percent of investment firms were incorporating Twitter analysis and other forms of “unstructured” data into their trading decisions, according to a report by Adam Honore, a research director at Aite, a financial services consulting group based in Boston. By 2010, the share of companies experimenting with this technology jumped to 35 percent. Today, Honore said, that number is closer to 50 percent. “Big data is fundamentally changing how we trade,” Honore said. ‘Data in motion’ Richard Tibbetts, chief technology officer at StreamBase, a Lexington, Mass., company that provides tools for analyzing large amounts of data, calls it “examining data in motion.” The trick is to be able to find the digital smoke signals amid all the other stuff. Traders who were analyzing Twitter for unusual activity, for instance, were able to get the news of Osama bin Laden’s death and a massacre in Norway hours before the information was officially confirmed, giving them a significant jump on their colleagues who learned of the events through traditional news sources. “The new generation of trader expects to have dozens of tools at their fingertips instead of just a Bloomberg terminal,” Tibbetts said. Hawtin began experimenting with trading on a social-media sentiment algorithm in the spring of 2011, tapping $40 million from his now-closed hedge fund. He has repeatedly warned potential investors that there is a high level of risk. “It’s a very new area we don’t fully understand yet,” he said. But the interest in his project was so great that in April he began offering his technology to retail investors. In addition to its efforts to gauge the collective mood of the world, the company now examines messages on Twitter, Facebook and other social-media outlets to create measures for individual stocks and commodities. On a recent weekday, Hawtin was studying his global sentiment monitor when he noticed something troubling, a surge in anxiety after two days of relative calm. After deliberating for a few minutes, he decided it was too early to take any action. If the anxiety continued to trend up the following day, he said, he would probably start selling. “There’s a delay between how you’re feeling about your economic situation and having that sentiment turned into a decision like buying or selling a stock or adjusting your portfolio,” he said. The numbers support Hawtin’s strategy — at least so far. His investors beat the main London stock index by seven-fold in the first quarter of this year. But programs such as Hawtin’s are only as good as the data being entered, and a growing backlash against big data may threaten the flow of that information. Privacy concerns Companies and governments are pushing the envelope in the use and reuse of data in ways not originally intended, and privacy groups are pushing back. Even the basic definition of personal data varies widely from one country to another, making it unclear how it can be used. The regulatory framework has not caught up with the technology. Tim Berners-Lee, a founder of the World Wide Web, has become so concerned about the misuse of personal information by companies and governments that he has warned people to be cautious about what they put online. The data sets are so large that they are normally analyzed in aggregate, but privacy advocates worry that information can still be tied to individuals. Civil liberties groups have sued to stop a U.S. government program that monitors social media data for national security threats, arguing that it could be used to unjustly label people as bad credit risks — or even terrorists — and chill free speech. There is also the danger of what scholars call information asymmetry, where certain parties have an unfair advantage because they have better information than others — a phenomenon that some have argued shakes the foundation of a market economy. “It increases opportunities for those who are already richer and disadvantages those that are poor,” said Jay Stanley, a lawyer with the American Civil Liberties Union in Washington. Beyond the civil liberties issue, data streams can be manipulated. You can spam Twitter streams with positive words about a stock to make it look as if there is a groundswell of optimism about the company. Or you can use the same techniques to try to sink a stock. Vagelis Hristidis, an associate professor of computer science at the University of California at Riverside, is the lead author of a paper detailing another investment strategy based on Twitter. During a four-month simulation, his approach outperformed other baseline strategies and indexes, including the Dow Jones industrial average, by between 1.4 percent and 11 percent. “A model that predicts the stock market,” Hristidis said, “can only be successful as long as people don’t know about it.”