Salut a tous les amis ! On se retrouve aujourd’hui pour une nouvelle map nommé Burning Hotel with Ted !
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Unboxing and installation of Cambridge Consultants' NVIDIA DGX-1 Deep Learning Supercomputer
And here comes the wave or Dwave of individual quantum computers in every college, labratory etc. all tied together in a daisy chain to help usher in entities that couldnt otherwise enter our physical realm, yeah Science.
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This video is about The Hive Annual Summit - Rand Hindi
Dr. Animashree Anandkumar is a Bren Professor at the California Institute of Technology and Director of Machine Learning Research at NVIDIA. She develops machine-learning algorithms that enable computers to process dimensional data using tensors. She finds ways to make these algorithms scale more effectively. She earned several prizes for her work including the Alfred P. Sloan Research Fellowship, NSF Career Award, and faculty fellowships from Adobe, Google, and Microsoft. Additionally, Anandkumar was nominated to the World Economic Forum’s network of experts for many fields including academia, business, and the arts. Dr. Animashree Anandkumar is a Bren Professor at Caltech and Director of Machine Learning Research at NVIDIA. She develops machine-learning algorithms that enable computers to process dimensional data using tensors. She finds ways to make machine learning algorithms scale more effectively. She earned several prizes including the Alfred P. Sloan Research Fellowship, NSF Career Award, and faculty fellowships from Adobe, Google, and Microsoft. Anandkumar was nominated to the World Economic Forum’s network of experts for many fields including academia, business, and the arts. 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
Medical diagnosis often is based on information visible from medical images. But what if machine learning and artificial intelligence could help our doctors gain more knowledge from medical images and therefore predict diseases earlier? New research indicates this is indeed possible, and the implications for preventive medicine and several disease types are large. Learn about it in this talk.
Laura Montoya is the Founder and Managing Partner of Accel Impact, including Accel.AI, a global Non-Profit Institute lowering the barriers to entry in engineering artificial intelligence, and LXAI (www.latinxinai.org) an initiative to create opportunity for Latinx in AI. She has been described as a natural and versatile leader with a passion for AI, Computer Science, Research, and Psychology. Her talk explores modeling AI algorithms for social impact through theory, applications, and correlations to real world experience. She describes concepts in reinforcement learning and deep learning, with analogies to evolution of the individual and societies.
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
Consider Our Merchandise! ► http://bit.ly/Corridor_Store
WATCH HOW WE MADE THIS (Amazing) ► https://www.youtube.com/watch?v=gCuG-KJacp8
I'm going to build a medical imaging classification app called SmartMedScan! The potential customers for this app are medical professionals that need to scale and improve the accuracy of their diagnoses using AI. From ideation, to logo design, to integrating features like payments and AI into a single app, I'll show you my 10 step process. I hope that by seeing my thought process and getting familiar with the sequence of steps I'll demonstrate, you too will be as inspired as I am to use this technology to do something great for the world. Enjoy!
Drastic improvements in automation and artificial intelligence over the last decade or so, and wary comments from high-profile tech industry tycoons like Elon Musk and Bill Gates, have led to rumblings of uncertainty about economic displacement. Veteran New York Times science writer John Markoff admits to having contributed to rising concerns in recent years, but says he now sees the issue from a more Keynesian perspective.
Many people view the triumph of the computer Watson over the world’s best Jeopardy players in 2011 as the leading edge of a new age of smart machines. Since then, we have seen self-driving cars, smart search engines, and increasingly able robots moving from the realm of science fiction to deployed technology. As this occurs, we increasingly hear dystopian futurists bemoan a world where drones will replace pilots, computers will replace doctors, and scientists will be put out of work as intelligent computers increasingly replace the knowledge workers in modern society. They worry whether, as scientist Steven Hawking stated, “The development of full artificial intelligence could spell the end of the human race.” In this talk, Dr. Hendler will explore that position and contrast with another approach — that “social machines,” which bring together humans and increasingly intelligent computers, may not be something to fear, but rather the best hope to solve the complex problems facing our world.
An excerpt from the 1968 film "2001: A Space Odyssey" directed by Stanley Kubrick.
Our solar system now is tied for most number of planets around a single star, with the recent discovery of an eighth planet circling Kepler-90, a Sun-like star 2,545 light years from Earth. The planet was discovered in data from NASA’s Kepler space telescope.
The DARPA Challenge is a competitive obstacle course that allows robotics teams to win millions in prize money. More than that, the challenge displays the future benefits of general purpose robots that could aide in future disaster relief.
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.
There are more than 800 million people victims of addictions in the world and Gabe Zicherman shares how we've always used technology to make things more addictive but it has become more extreme because of the use of algorithms. At the same time he explains how these very same algorithms can be used to conquer addictions.
Gabe Zichermann is the CEO & Co-Founder of Onward and the principal experience architect of the company’s scalable, AI-driven approach to conquering addiction. Gabe is a serial entrepreneur, author of three books and speaker with over a decade of experience building systems for behavior change. He is also the world’s foremost expert on engaging design and technology whose work in creating the Gamification movement has changed government, large enterprise and startup workplaces, products and business processes. After watching family and friends battle their addictions, Gabe’s vision is to foster a world where balanced relationships between “real life" and technology make everyone healthier, happier and more truly connected. 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
LIVING UNIVERSE is an interstellar adventure that seeks to answer the most profound question of all: are we alone? Based on the latest scientific knowledge, we will take a journey to a planet beyond our solar system in search of life.
Video Compilation on Artificial Intelligence, Computational Neuroscience, and Machine Learning.
Believe it or not, its a robot named Jiajia.Jia Jia has the long flowing locks and rosy red cheeks as a human, but is being taught deep learning abilities.This life-like cyborg is the brain child of Chen Xiaoping and his colleagues at the University of Science and Technology of China.
When most of us look at A.I. we see magical capabilities. When economists look at A.I. they see something very different. Economist Ajay Agrawal explains: "What economists bring to the conversation is that they are able to look at a fascinating technology like artificial intelligence and strip all the fun and wizardry out of it and reduce A.I. down to a single question, which is, 'What does this technology reduce the cost of?'" Never has one person taken such delight in stripping the fun from something awesome. But what does A.I. lower the cost of? Predictions, says Agrawal. Intelligent machines can take information we have and use it to generate information we need. Uncertainty is the single biggest hurdle in good decision making, and A.I. can drastically increase certainty in many areas, like automated vehicles, language translation, human resources and medical diagnostics. As A.I. becomes a cheaper technology, its use will become even more widespread. "Where I think it’s really interesting is that when it becomes cheap, we’ll start using it for things that weren’t traditionally prediction problems but we’ll start converting problems into prediction problems to take advantage of the new, cheap prediction." Ajay Agrawal is the co-author of Prediction Machines: The Simple Economics of Artificial Intelligence.