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Archive for the ‘information science’ category: Page 271

Sep 9, 2017

The Artificial Intelligence Race: The AI Documentary

Posted by in categories: education, information science, mobile phones, robotics/AI

https://youtube.com/watch?v=0YzoEBCjsIw

Artificial Intelligence (AI) is a science and a set of computational technologies that are inspired by—but typically operate quite differently from—the ways people use their nervous systems and bodies to sense, learn, reason, and take action. While the rate of progress in AI has been patchy and unpredictable, there have been significant advances since the field’s inception sixty years ago…

Toby Walsh, Professor Artificial Intelligence, University of NSW Sydney “There’s lots of AI already in our lives. You can already see it on your smartphone every time you use Siri, every time you ask a lexer a question, every time you actually use your satellite navigation. You are using one of these algorithms. You are using some AI that’s recognizing your speech, answering questions, giving you search results recommending books for you to buy on Amazon. They’re the beginnings of AI everywhere in our lives.”

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Sep 7, 2017

This earpiece will allow you to understand new languages

Posted by in categories: futurism, information science

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Sep 6, 2017

IBM and MIT partner on artificial intelligence research

Posted by in categories: cybercrime/malcode, economics, health, information science, robotics/AI

BOSTON (AP) — IBM is planning to spend $240 million over the next decade to create an artificial intelligence research lab at MIT.

Massachusetts Institute of Technology on Thursday announced the formation of the new MIT-IBM Watson AI Lab. It will support joint research by IBM and MIT scientists.

Its mission will include advancing the hardware, software and algorithms used for artificial intelligence. It also will tackle some of the economic and ethical implications of intelligent machines and look at its commercial application for industries ranging from health care to cybersecurity.

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Sep 3, 2017

Artificial Intelligence and Smart Journalism

Posted by in categories: information science, robotics/AI

How is Artificial Intelligence actually thinking? Even their creators often don’t really fully understand. But if AI becomes more and more important you should at least have an idea of how algorithms get to results. And they think totally different to how human beings do, says Sara M. Watson, tech critic and writer at the Digital Asia Hub, Hong Kong. How can literature and journalism help to find a new perspective on AI?

“The biggest problem AI has is that even the engineers can’t really explain certain outcomes or certain decisions that go through an artificially intelligent system.”

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Aug 26, 2017

Scientists Finally Prove Strange Quantum Physics Idea Einstein Hated

Posted by in categories: information science, mathematics, particle physics, quantum physics, space

The equations of physics are things that we humans created to understand the Universe, and it can be hard to disentangle them from the Universe’s innate properties. It turns out that one of the weirdest things scientists have come up with, what Albert Einstein derisively called “spooky action at a distance,” is more than just math: It’s a fact of reality.

That concept is also known as entanglement, and it’s what allows particles that have once interacted to share a connection regardless of the separation between them. A team of physicists in the United Kingdom used some dense mathematics to come to their Einstein-angering conclusion, taking an important step towards proving whether quantum mechanics’ weirdness is just the math talking, or whether it speaks to innate physical requirements. Their mathematical proof’s main assumption is that any new physics theory should be backward-compatible with the physics you learned in high school.

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Aug 15, 2017

Inside DARPA’s Push to Make Artificial Intelligence Explain Itself

Posted by in categories: information science, robotics/AI

The research arm of the U.S. Department of Defense is marshalling an international effort to overcome what many say is the biggest obstacle to widespread adoption of artificial intelligence: teaching algorithms to explain their decision-making to humans.

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Aug 9, 2017

Why Neuroscience Is the Key to Innovation in AI

Posted by in categories: information science, neuroscience, robotics/AI

Demis Hassabis, founder of DeepMind, says the future of AI lies in neuroscience. Aspects of neuroscience are key in artificial intelligence algorithms.

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Aug 8, 2017

AI Will Make Fake News Video — and Fight It As Well

Posted by in categories: engineering, finance, information science, robotics/AI

Just weeks after one research team appeared to put words in a leader’s mouth, here comes a new tool that can check questionable video for a pulse.

A recent demonstration showing how easy it is to spoof video of a world leader recently made headlines, foretelling a future where robot-created videos cause political and financial havoc. But now comes word of an antidote. On Monday, a group of computer scientists from Carnegie Mellon University’s Software Engineering Institute published new research showing how algorithms can tell whether the person on-screen has a human heartbeat. The technique will help future intelligence analysts, journalists, or just scared television viewers detect the difference between spoofed video and the real thing.

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Jul 31, 2017

The first machine to study the Dance Dance Revolution video game now choreographs its own dances

Posted by in categories: entertainment, information science, media & arts, robotics/AI

Intelligent Machines

Machine-learning algorithm watches dance dance revolution, then creates dances of its own.

A machine learns to choreograph by studying a famous 1990s music video game.

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Jul 28, 2017

Scientists discover nature’s algorithm for intelligence

Posted by in categories: biotech/medical, genetics, information science, mathematics, neuroscience

But if there is some kind of unifying computational principle governing our grey matter, what is it? Dr. Tsien has studied this for over a decade, and he believes he’s found the answer in something called the Theory of Connectivity.

“Many people have long speculated that there has to be a basic design principle from which intelligence originates and the brain evolves, like how the double helix of DNA and genetic codes are universal for every organism,” Tsien said. “We present evidence that the brain may operate on an amazingly simple mathematical logic.”

The Theory of Connectivity holds that a simple algorithm, called a power-of-two-based permutation taking the form of n=2i-1 can be used to explain the circuitry of the brain. To unpack the formula, let’s define a few key concepts from the theory of connectivity, specifically the idea of a neuronal clique. A neuronal clique is a group of neurons which “fire together” and cluster into functional connectivity motifs, or FCMs, which the brain uses to recognize specific patterns or ideas. One can liken it to branches on a tree, with the neuronal clique being the smallest unit of connectivity, a mere twig, which when combined with other cliques, link up to form an FCM. The more complex the idea being represented in the brain, the more convoluted the FCM. The n in n=2i-1 specifies the number of neuronal cliques that will fire in response to a given input, i.

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