Lifeboat Foundation

Jianxiong Xiao aims to make self-driving cars as widely accessible as computers are today. He’s the founder and CEO of AutoX, which recently demonstrated an autonomous car built not with expensive laser sensors but with ordinary webcams and some sophisticated computer-vision algorithms. Remarkably, the vehicle can navigate even at night and in bad weather.

AutoX hasn’t revealed details of its software, but Xiao is an expert at using deep learning, an AI technique that lets machines teach themselves to perform difficult tasks such as recognizing pedestrians from different angles and in different lighting.

Growing up without much money in Chaozhou, a city in eastern China, Xiao became mesmerized by books about computers—fantastic-sounding machines that could encode knowledge, logic, and reason. Without access to the real thing, he taught himself to touch-type on a keyboard drawn on paper.

Continue reading “AutoX demonstrates how to build an autonomous car without expensive laser sensors” »

While physicists have managed to wrap their minds around chaos theory in the macroscopic world, chaos also has its way at the quantum scale. And in many ways quantum chaos is even more perplexing than its large-scale counterpart.

Which is why it’s such a big deal that researchers have now presented a single equation that can predict how quantum chaos behaves.

This equation effectively explains the patterns within quantum chaos at the atomic level, and it could contribute to our understanding of everything from brain surgery to string theory.

Continue reading “We Now Have an Equation That Explains How The Hell Quantum Chaos Behaves” »

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.”

Continue reading “The Artificial Intelligence Race: The AI Documentary” »

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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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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.”

Continue reading “Artificial Intelligence and Smart Journalism” »

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.

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.

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