In the last five years, significant advances were made in the fields of computer vision, speech recognition, and language understanding. In this talk, Jeff Dean discusses why and how these advances have come about, what the implications are for areas as diverse as robotics, healthcare, human creativity and computer hardware design, and why these possibilities are so exciting. Jeff Dean is a Senior Fellow in Google’s Research Group, where he leads the Google Brain project. His areas of interest include large-scale distributed systems, performance monitoring, compression techniques, information retrieval, application of machine learning to search and other related problems, microprocessor architecture, compiler optimizations, and development of new products that organize existing information in new and interesting ways. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
“The actual path of a raindrop as it goes down the valley is unpredictable, but the general direction is inevitable,” says digital visionary Kevin Kelly — and technology is much the same, driven by patterns that are surprising but inevitable. Over the next 20 years, he says, our penchant for making things smarter and smarter will have a profound impact on nearly everything we do. Kelly explores three trends in AI we need to understand in order to embrace it and steer its development. “The most popular AI product 20 years from now that everyone uses has not been invented yet,” Kelly says. “That means that you’re not late.” TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and much more. Find closed captions and translated subtitles in many languages at http://www.ted.com/translate Follow TED news on Twitter: http://www.twitter.com/tednews Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector
http://www.ted.com The news that Chinese artist Ai Weiwei has been detained by authorities has prompted significant concern here at TED-HQ. We had shown a film of him at last month’s conference, an unexpected and courageous statement about his treatment by the government, social change, the power of the web, and his hope for the future of China. The film, which was shown as Ai Weiwei himself watched live over the web in the middle of the night, prompted a huge standing ovation from the TED audience. Read the news story: http://www.bbc.co.uk/news/world-asia-pacific-12954811 TED is a non-partisan, nonpolitical organization and we understand the Chinese authorities concern at anything which might provoke social unrest. But for anyone who believes in the power of ideas, of human imagination, it is heartbreaking to see one of the world’s great artists shackled in this way. We will be tracking developments carefully. Here is the film.
Machine learning isn’t just for simple tasks like assessing credit risk and sorting mail anymore — today, it’s capable of far more complex applications, like grading essays and diagnosing diseases. With these advances comes an uneasy question: Will a robot do your job in the future? TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and much more. Find closed captions and translated subtitles in many languages at http://www.ted.com/translate Follow TED news on Twitter: http://www.twitter.com/tednews Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector
L’Ecole Dynamique est une micro-société démocratique où les enfants sont libres de faire leurs propres choix concernant leurs apprentissages et tous les autres domaines de la vie. Elle est ainsi libérée des programmes scolaires, des emplois du temps et des classes d’âges. La Sudbury-Valley School adopte cette approche depuis 1969 et connaît des résultats qui défient toute sagesse conventionnelle. Elle renoue au final avec la tradition socratique d’admettre notre ignorance de ce qu’est une bonne éducation pour la jeunesse, laisser l’enfant être qui il est, sans le juger, sans projeter sur lui celui que nous aimerions qu’il soit. Risible folie ou révolution copernicienne ? Anciennement consultant en direction générale d’entreprise au BCG, Ramïn renoue à 26 ans avec son rêve depuis toujours, celui d’enseigner. Avide de recherches en innovation pédagogiques, son parcours de prof l’amènera à questionner l’école conventionnelle en profondeur et adopter une pratique éducative méconnue et pourtant d’une efficacité redoutable : ne rien faire ! Offrir à l’enfant un cadre sécure, bienveillant, riche en ressources, où il pourra librement épanouir son potentiel dans les domaines qui l’intéressent. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
We’re on the edge of a new frontier in art and creativity — and it’s not human. Blaise Agüera y Arcas, principal scientist at Google, works with deep neural networks for machine perception and distributed learning. In this captivating demo, he shows how neural nets trained to recognize images can be run in reverse, to generate them. The results: spectacular, hallucinatory collages (and poems!) that defy categorization. “Perception and creativity are very intimately connected,” Agüera y Arcas says. “Any creature, any being that is able to do perceptual acts is also able to create.” TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and much more. Find closed captions and translated subtitles in many languages at http://www.ted.com/translate Follow TED news on Twitter: http://www.twitter.com/tednews Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector
Tanmay Bakshi wishes and works towards changing the lives of those who are living with disabilities; those who are living, yet NOT living as we are, and those who are NOT able to even communicate as we do. In his talk, Tanmay shares his passion of working in the field of Healthcare through Artificial Intelligence, a path very few have chosen. Twitter: @TajyMany LinkedIn: Tanmay Bakshi YouTube: tanmay bakshi Facebook: Tanmay Bakshi Tanmay Bakshi is a Software/Cognitive Developer, Keynote Speaker, Algorithm-ist, IBM Champion for Cloud, Honorary IBM Cloud Advisor and author of Hello Swift! Tanmay is host of an IBM Facebook Live series called Watson Made Simple with Tanmay and has over 12,000 followers of his YouTube channel Tanmay Teaches, with a resolve to help 100,000 children and other beginners on their journey to innovate through coding. Tanmay supports initiatives like STEAM, Everyone Can Code, Girls Who Code and Kids Can Code. At the impressive young age of 9, his app tTables, which helps practice multiplication tables, was accepted into the iOS app store; at the age of 12, he presented one of his many algorithms, AskTanmay, the world’s first web-based NLQA (Natural Language Question Answering) System to be powered by IBM Watson, at IBM InterConnect 2016. Tanmay has been exploring and experimenting with cognitive computing and creating his own, custom-built Machine Learning algorithms in the fields of Audiology, Electroencephalogram Pattern Recognition and bridging numeric with image patterns. Twitter: @TajyMany LinkedIn: Tanmay Bakshi YouTube: tanmay bakshi Facebook: Tanmay Bakshi This [More]
This talk was given at a local TEDx event, produced independently of the TED Conferences. In his talk, Andre will explain the current and future impacts of Artificial Intelligence on industry, science, and how it will benefit and accelerate human progress. With almost 20 years of business experience, André has a track record of success with multiple multi-million dollar ventures in multiple industries that have spanned the continent. His latest company works in the field of Artificial Intelligence (AI) and has created a one-of-a-kind neural network that simulates a growing neocortex. This system of neurons uses evolutionary concepts to self-organize to complete tasks only previously achievable by humans. Most futurists and experts believe that by 2035, AI will match and eventually surpass human intelligence. About TEDx, x = independently organized event In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
We’re building an artificial intelligence-powered dystopia, one click at a time, says technosociologist Zeynep Tufecki. In an eye-opening talk, she details how the same algorithms companies like Facebook, Google and Amazon use to get you to click on ads are also used to organize your access to political and social information. And the machines aren’t even the real threat. What we need to understand is how the powerful might use AI to control us — and what we can do in response. Check out more TED Talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
Imagine a global “Hive Mind” that can tap the knowledge, wisdom, insights, and intuitions of millions of people, and produce a super-intelligence that is much smarter than any individual person. A new technology called Artificial Swarm Intelligence is making this possible and it could be our best defense against the emerging dangers of AI. Louis Rosenberg, PhD is a researcher, entrepreneur, and writer. He is currently Founder & CEO of Unanimous AI, an artificial intelligence company that amplifies human intelligence by building “hive minds” modeled after biological swarms. A prolific inventor, Rosenberg has been awarded over 350 patents worldwide for his work in Virtual Reality, Augmented Reality, and Human-Computer Interaction. Rosenberg was also the creator of the Virtual Fixtures system for the U.S. Air Force in the early 90’s, the first immersive Augmented Reality system. Prior to his current role at Unanimous AI, Rosenberg was founder and CEO of Immersion Corporation (NASDAQ: IMMR) and Outland Research, and has worked as a tenured professor at California State University (Cal Poly). This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
View full lesson: http://ed.ted.com/lessons/the-turing-test-can-a-computer-pass-for-a-human-alex-gendler What is consciousness? Can an artificial machine really think? For many, these have been vital considerations for the future of artificial intelligence. But British computer scientist Alan Turing decided to disregard all these questions in favor of a much simpler one: Can a computer talk like a human? Alex Gendler describes the Turing test and details some of its surprising results. Lesson by Alex Gendler, animation by Patrick Smith.
When a very young child looks at a picture, she can identify simple elements: “cat,” “book,” “chair.” Now, computers are getting smart enough to do that too. What’s next? In a thrilling talk, computer vision expert Fei-Fei Li describes the state of the art — including the database of 15 million photos her team built to “teach” a computer to understand pictures — and the key insights yet to come. TEDTalks is a daily video podcast of the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and much more. Find closed captions and translated subtitles in many languages at http://www.ted.com/translate Follow TED news on Twitter: http://www.twitter.com/tednews Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: http://www.youtube.com/user/TEDtalksDirector
Watch the talks we loved in 2016 and discover the year’s most powerful ideas. To watch the full talks, check out the playlist: http://go.ted.com/2016 Can we build AI without losing control over it? | Sam Harris (https://www.youtube.com/watch?v=8nt3edWLgIg) Gene editing can wipe out mosquitoes forever | Jennifer Kahn (https://www.youtube.com/watch?v=OI_OhvOumT0) The secret to effective nonviolent resistance | Jamila Raqib (https://www.youtube.com/watch?v=OIpgrZ8yS-Q) Here’s how we can fix the refugee system | Alexander Betts (https://www.youtube.com/watch?v=kLIfeGflNp8) A prosecutor’s vision for justice | Adam Foss (https://www.youtube.com/watch?v=H1fvr9rGgSg) What do you think when you look at me? | Dalia Mogahed (https://www.youtube.com/watch?v=wzkFoetp-_M) Inside the mind of a master procrastinator | Tim Urban (https://www.youtube.com/watch?v=arj7oStGLkU) The discovery of gravitational waves | Allan Adams (https://www.youtube.com/watch?v=jMVAgCPYYHY) Hunting for dinosaurs showed me our place in the universe | Kenneth Lacovara (https://www.youtube.com/watch?v=o1Z4F4e2Bw4) The visual history of social dance | Camille A. Brown (https://www.youtube.com/watch?v=dpCBMwAweDI&t=4s)
Salut a tous les amis ! On se retrouve aujourd’hui pour une nouvelle map nommé Burning Hotel with Ted ! L’objectif : Survivre le plus longtemps possible dans un hôtel qui prend feu à cause de TED ! ►La map : http://www.minecraftforum.net/forums/mapping-and-modding/maps/2677725-burning-hotel-with-ted ►Clique ici pour t’abonner : http://bit.ly/1MBz710 ►Rejoins moi sur Twitter : https://twitter.com/FuriousJumper ►Rejoins moi sur facebook : https://www.facebook.com/FuriousJumper?notif_t=page_new_likes ►Rejoins moi en live ici : http://leveldown.fr/stream/furiousjumper J’apprécie énormément vos encouragements et je suis très attentif à vos suggestions donc n’hésite pas à aimer la vidéo et à la partager et à t’abonner pour suivre mes aventures . Merci !
What do you get when you give a design tool a digital nervous system? Computers that improve our ability to think and imagine, and robotic systems that come up with (and build) radical new designs for bridges, cars, drones and much more — all by themselves. Take a tour of the Augmented Age with futurist Maurice Conti and preview a time when robots and humans will work side-by-side to accomplish things neither could do alone.
Maurice Conti, Director of Applied Research and Innovation, shares Autodesk’s perspective on how humans and robots will work together in the future.
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Mark Seifter This mega-recitation covers the boosting problem from Quiz 4, Fall 2009. We determine which classifiers to use, then perform three rounds of boosting, adjusting the weights in each round. This gives us an expression for the final classifier. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Mark Seifter We begin by discussing neural net formulas, including the sigmoid and performance functions and their derivatives. We then work Problem 2 of Quiz 3, Fall 2008, which includes running one step of back propagation and matching neural nets with classifiers. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston This lecture begins with a brief discussion of cross-modal coupling. Prof. Winston then reviews big ideas of the course, suggests possible next courses, and demonstrates how a story can be understood from multiple points of view at a conceptual level. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Mark Seifter In this mega-recitation, we cover Problem 1 from Quiz 1, Fall 2009. We begin with the rules and assertions, then spend most of our time on backward chaining and drawing the goal tree for Part A. We end with a brief discussion of forward chaining. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston We begin with a review of inference nets, then discuss how to use experimental data to develop a model, which can be used to perform simulations. If we have two competing models, we can use Bayes’ rule to determine which is more likely to be accurate. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
MIT 6.868J The Society of Mind, Fall 2011 View the complete course: http://ocw.mit.edu/6-868JF11 Instructor: Marvin Minsky In this lecture, students use readings of M.A. Bozarth and Carl Sagan to discuss pleasure systems in the brain and human problem solving. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In this lecture, we consider the nature of human intelligence, including our ability to tell and understand stories. We discuss the most useful elements of our inner language: classification, transitions, trajectories, and story sequences. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In this lecture, we consider cognitive architectures, including General Problem Solver, SOAR, Emotion Machine, Subsumption, and Genesis. Each is based on a different hypothesis about human intelligence, such as the importance of language and stories. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Mark Seifter We start by discussing what a support vector is, using two-dimensional graphs as an example. We work Problem 1 of Quiz 4, Fall 2008: identifying support vectors, describing the classifier, and using a kernel function to project points into a new space. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
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