Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI

Advanced warfare platforms are increasingly using unused spectrum, now the Pentagon needs a system to cripple it

The US military is cultivating new electronic warfare technologies that, in real time, use artificial intelligence to learn how to jam enemy systems that are using never-before-seen frequencies and waveforms.

Although this “cognitive electronic warfare” is still in its nascent stages of development, scientists developing these systems told Defense News the technology could appear on the battlefield within the next decade.

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Imagine a five-year-old watching Mum talking to Siri, and Dad talking to Alexa, on a daily basis — what must she think of such interactions? Children nowadays witness computers that seem like they have a mind of their own — and even a personality with which to engage. It can be taken for granted that their perception of machines, and thus of the world itself, differs a lot from our own.

Artificial intelligence is one of the most promising areas of tech today, if not even the one that is likely to entail the most striking changes in our way of living, the way our economy works and how society functions. Thanks to enormous amounts of data, coupled with compute power to analyze it, technology companies are making strides in AI that resembles something of a gold rush.

New approaches, including use of deep neural networks, have led to groundbreaking achievements in AI, some of which weren’t predicted to happen for another decade. Google defeating the world champion at the ancient game of Go is just one prominent example. Many more are to be expected, including advances in deep learning combined with reasoning and planning — or even emulating creativity and artwork.

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Elon Musk has recently hinted that he may be working on a “neural lace,” a mesh of electronics that will allow AI and the brain to work together. This could help human brains keep up with future enhancements in AI.

There’s no doubt that Elon Musk is one busy individual. When not playing on the Tesla factory floor, he may be bringing electric roofs to electric vehicles, or dreaming up the Hyperloop, or toying with the future of AI.

If not any of those, he is apparently busy protecting us from being treated like house pets after the Singularity. To that end, the billionaire polymath has revealed he may be working on something called a “neural lace.”

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The conjunction of Venus and Jupiter just before dawn over the southeastern Caspian sea. Credit: Babak A. Tafreshi (TWAN) http://twanight.org/

Aside from the attention it receives around one of its rare solar transits, Venus hardly makes headlines.

But before our warming sun turned Venus into a poster child for the dangers of a runaway greenhouse, our closest planetary neighbor may have once had oceans capable of harboring complex life.

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A computer’s victory over a human go master this past March reminds us of the pending “singularity” — the rapidly approaching moment in time when artificial intelligence overtakes human intelligence. Machines will learn, and we won’t be their teachers. Are we prepared for it? Can we prepare for it?

We’d better. Many futurists declare it inevitable, probably within a generation, maybe less. Shukan Shincho magazine discusses some hypothetical implications in its Aug. 25 edition. Even the least of them are shocking. For example, in 2045 a computer with the combined intellectual power of the entire human race would cost $100. In short, it’ll be no big deal. What will be a big deal? Should we shudder at the thought, or rejoice?

Francis Bacon (1561−1626) is generally acknowledged as the grandfather of modern science. “Nature, to be commanded, must be obeyed,” he wrote. His fictional “New Atlantis” was a utopia ruled by scientists who, having admitted their ignorance and purged themselves of illusory knowledge, experimented, observed and slowly built up from scratch an ever-expanding store of “true” knowledge — armed with which they “commanded” nature to outgrow her destructive caprices and ease mankind’s lot.

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Ray Kurzweil is a futurist, a director of engineering at Google and a co-founder of the Singularity University think tank at NASA Ames Research Center in Mountain View. He is a nonfiction author and creator of several inventions.

Kurzweil met with the Silicon Valley Business Journal to discuss how technology’s exponential progress is rapidly reshaping our future through seismic shifts in information technology and computing power, energy, nanotechnology, robotics, health and longevity.

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Intel has planted some solid stakes in the ground for the future of deep learning over the last month with its acquisition of deep learning chip startup, Nervana Systems, and most recently, mobile and embedded machine learning company, Movidius.

These new pieces will snap into Intel’s still-forming puzzle for capturing the supposed billion-plus dollar market ahead for deep learning, which is complemented by its own Knights Mill effort and software optimization work on machine learning codes and tooling. At the same time, just down the coast, Nvidia is firming up the market for its own GPU training and inference chips as well as its own hardware outfitted with the latest Pascal GPUs and requisite deep learning libraries.

While Intel’s efforts have garnered significant headlines recently with that surprising pair of acquisitions, a move which is pushing Nvidia harder to demonstrate how GPU acceleration (thus far the dominant compute engine for model training), they still have some work to do to capture mindshare for this emerging market. Further complicating this is the fact that the last two years have brought a number of newcomers to the field—deep learning chip upstarts touting the idea that general purpose architectures (including GPUs) cannot compare to a low precision, fixed point, specialized approach. In fact, we could be moving into a “Cambrian explosion” for computer architecture–one that is brought about by the new requirements of deep learning. Assuming, of course, there are really enough applications and users in a short enough window that the chip startups don’t fall over waiting for their big bang.

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http://www.unz.com/akarlin/sinotriumph/

Nothing illustrates China’s meteoric rise as some well chosen numbers.

By the end of the 1990s, China had come to dominate the mainstays of geopolitical power in the 20th century – coal and steel production. As a consequence, it leapt to the top of the Compositive Index of National Capability, which uses military expenditure, military personnel, energy consumption, iron and steel production, urban population, and total population as a proxy of national power. Still, one could legitimately argue that all of these factors are hardly relevant today. While Germany’s fourfold preponderance in steel production over Russia may have been a critical number in 1914, China’s eightfold advantage in steel production over the US by 2014 is all but meaningless in any relevant comparison of national power. The world has moved on.

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Geordie’s perspective of AI on QC…

By Piper McGowin

Meanwhile as everyone was busy arguing over the bread and circus elections, the CIA was busy funding a computer so powerful that it is described as “tapping into the fundamental fabric of reality” and the man who owns the company says being near one is like “standing at the altar of an alien God.”

What exactly do you suppose they are doing with it?

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Mercedes-Benz Vans and drone tech startup Matternet have created a concept car, or as they’re calling it a Vision Van, that could change the way small packages are delivered across short distances.

The Vision Van’s rooftop serves as a launch and landing pad for Matternet’s new, Matternet M2 drones.

The Matternet M2 drones, which are autonomous, can pick up and carry a package of 4.4 pounds across 12 miles of sky on a single battery charge in real world conditions.

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