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Jeremy Howard: The wonderful and terrifying implications of computers that can learn

Jeremy Howard: The wonderful and terrifying implications of computers that can learn

http://www.ted.com/talks/jeremy_howard_the_wonderful_and_terrifying_implications_of_computers_that_can_learn

Related:  risullyRESSOURCES PÉDAGOGIQUESComputing & AIMachine LearningTECHNODOOM

Légalisation du cannabis : que fait-on ailleurs? 1. La quantité Dans la plupart des États américains, la quantité de cannabis que l’on peut acheter ou avoir sur soi est de 28,5 grammes (1 oz).La capitale fédérale (Washington DC) est un cas particulier, puisqu’on peut posséder jusqu’à 57 grammes (2 oz) de cannabis, mais son achat et sa vente demeurent illégaux. Par contre, on peut transférer à une autre personne, sans recevoir de paiement, jusqu'à 28,5 grammes de cannabis.En Uruguay, on peut acheter 10 grammes de cannabis par semaine pour un maximum de 40 grammes par mois.Au Canada, le projet de loi permettra l’achat et la possession de 30 grammes de cannabis séché ou l’équivalent en autres produits (cannabis frais, liquide, concentré, etc.).

Le « deep learning », une révolution dans l'intelligence artificielle Cette technologie d'apprentissage, basée sur des réseaux de neurones artificiels, a complètement bouleversé le domaine de l'intelligence artificielle en moins de cinq ans. Le Monde.fr | • Mis à jour le | Par Morgane Tual « Je n'ai jamais vu une révolution aussi rapide.

Machine learning Machine learning is the subfield of computer science that gives computers the ability to learn without being explicitly programmed (Arthur Samuel, 1959).[1] Evolved from the study of pattern recognition and computational learning theory in artificial intelligence,[2] machine learning explores the study and construction of algorithms that can learn from and make predictions on data[3] – such algorithms overcome following strictly static program instructions by making data driven predictions or decisions,[4]:2 through building a model from sample inputs. Machine learning is employed in a range of computing tasks where designing and programming explicit algorithms is infeasible; example applications include spam filtering, detection of network intruders or malicious insiders working towards a data breach,[5] optical character recognition (OCR),[6] search engines and computer vision. Overview[edit] Tom M. Types of problems and tasks[edit] History and relationships to other fields[edit]

This Is the First Anti-Drone Weapon Designed for Use in the United States To deal with unwanted drones flying around, several people around the United States have been making do with shotguns. But now there’s a weapon specifically designed to knock drones out of the sky without totally destroying them. The Battelle DroneDefender is a thoroughly dystopian looking gun-type gadget that uses targeted radio pulses to neutralize in-flight drones and force them to land or hover. L’indigestion qui vient, par Benoît Bréville (Le Monde diplomatique, août 2015) Une carcasse artificielle tombe sur la chaîne de production d’une usine aseptisée. Recouverte par une épaisse pâte blanche sortie d’un bras métallique, elle passe ensuite par une machine qui lui donne l’aspect d’un poulet bien en chair auquel on aurait coupé la tête et les pattes. Quelques pulvérisations de colorant plus tard, la volaille est empaquetée, prête à être vendue. Extraites de L’Aile ou la Cuisse, un film populaire dans lequel Louis de Funès interprète un critique gastronomique en guerre contre un géant de la restauration collective, ces images présentaient en 1976 un caractère saugrenu, propre à susciter l’hilarité.

Get Used To It: Quantum Computing Will Bring Immense Processing Possibilities The one thing everyone knows about quantum mechanics is its legendary weirdness, in which the basic tenets of the world it describes seem alien to the world we live in. Superposition, where things can be in two states simultaneously, a switch both on and off, a cat both dead and alive. Or entanglement, what Einstein called “spooky action-at-distance” in which objects are invisibly linked, even when separated by huge distances. But weird or not, quantum theory is approaching a century old and has found many applications in daily life. As John von Neumann once said: “You don’t understand quantum mechanics, you just get used to it.”

Deep Blue (chess computer) Deep Blue After Deep Thought's 1989 match against Kasparov, IBM held a contest to rename the chess machine and it became "Deep Blue", a play on IBM's nickname, "Big Blue".[8] After a scaled down version of Deep Blue, Deep Blue Jr., played Grandmaster Joel Benjamin, Hsu and Campbell decided that Benjamin was the expert they were looking for to develop Deep Blue's opening book, and Benjamin was signed by IBM Research to assist with the preparations for Deep Blue's matches against Garry Kasparov.[9] On February 10, 1996, Deep Blue became the first machine to win a chess game against a reigning world champion (Garry Kasparov) under regular time controls. However, Kasparov won three and drew two of the following five games, beating Deep Blue by a score of 4–2 (wins count 1 point, draws count ½ point). The match concluded on February 17, 1996. In 2003 a documentary film was made that explored these claims.

Des robots qui imitent les muscles Un texte d'Alain Labelle L'équipe du Laboratoire de robotique reconfigurable de l'EPFL (École polytechnique fédérale de Lausanne) explique que ses « soft robots » entrent en mouvement par injection d'air et peuvent être produits à grande échelle. Les robots sont composés d'élastomères comme le silicone. Leurs moteurs sont inspirés des muscles et leur corps est composé de plusieurs « ballons ». Consulter un psychologue à distance grâce à Internet Le reportage de Marie-Pier Bouchard De plus en plus de psychologues offrent des services à distance, que ce soit par courriel ou par Skype. Ces cyberthérapies seraient aussi efficaces qu'une rencontre en personne, selon les résultats préliminaires d'une étude à laquelle l'Université du Québec à Trois-Rivières (UQTR) participe.

Google Just Open Sourced TensorFlow, Its Artificial Intelligence Engine Tech pundit Tim O’Reilly had just tried the new Google Photos app, and he was amazed by the depth of its artificial intelligence. O’Reilly was standing a few feet from Google CEO and co-founder Larry Page this past May, at a small cocktail reception for the press at the annual Google I/O conference—the centerpiece of the company’s year. Google had unveiled its personal photos app earlier in the day, and O’Reilly marveled that if he typed something like “gravestone” into the search box, the app could find a photo of his uncle’s grave, taken so long ago. Google is open sourcing software that sits at the heart of its empire. The app uses an increasingly powerful form of artificial intelligence called deep learning.

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