Lifeboat Foundation: Safeguarding Humanity
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Category: supercomputing

https://youtube.com/watch?v=amwyBmWxESA

When people post their emotional responses to social media and through their free email account(s), they are loading their human personal emotional responses, judgments, and biases into a large computer and cloud database? Everything we post and respond to is data somewhere. The truth is, hundreds of millions of people around the planet do this every day, 24 hours a day, seven days a week.

Are we uploading our brains to a cloud on a supercomputer and evolving into an artificially intelligent machine? This question and more…

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The recent efforts to remove Net Neutrality have given many a sense of impending doom we are soon to face. What happens to an Internet without Net Neutrality? Advocates have a vision of the possible results — and it is quite the nightmare! In this segment of Future A to Z, The Galactic Public Archives takes a cheeky, yet compelling perspective on the issue.

Part 1 / Part 2

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Hewlett Packard Enterprise has come a big step closer to launching a computer called The Machine that it’s been talking about, researching, and developing since 2014. On Tuesday, it announced that is has a prototype of this computer that is specifically designed for the big data era.

It uses a new kind of memory to be able to store and instantly analyse mind-boggling amounts of data, potentially even a limitless amount of data. The current prototype that HPE is showing off today contains 160 terabytes (TB) of memory, which is enough to store and work with every book in the Library of Congress five times over, the company says.

Also read: Why Trump’s disclosures to Russia are ‘damaging’.

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Confidential details of a top-secret encryption-breaking supercomputer were left completely exposed on an unsecured computer server belonging to New York University (NYU), according to a new report.

While it’s not uncommon for even critical-level infrastructure to suffer potentially catastrophic security breaches, what makes this event different is that there was seemingly no foul-play or attempts to hack into NYU’s systems.

Instead, it looks like somebody may have just forgotten to secure their classified data properly, exposing hundreds of pages of information on a covert code-breaking machine co-administered by the Department of Defence, IBM, and NYU.

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I can conceive that in saner circumstances, Tesla Model X might never have come to be. But the strongest blades are forged in the hottest fires, and for those that survive the heat, something very special is born.

Model X is special in a way that the automotive industry hasn’t been able to conceive in a very long time. It is an all-electric SUV that can seat up to seven people with bucketloads of cargo space to spare. It is a sporty all-wheel drive car that can throw instant and ungodly amounts of torque at the tarmac. It is a serene cruiser with its silent drive and breathtaking panoramic windshield. It is, in essence, an eight-eyed falcon with a supercomputer brain that dreams of a future of fully autonomous driving. And I had to have it.

As a Model S owner, I had already experienced and enjoyed more than a year of zero emissions Tesla driving. I knew what great things the car was capable of. I’d felt the thrill of instant torque, I’d fallen in love with the one-foot, regenerative braking driving experience, and I’d been chauffeured up and down the M1 by my very own Autopilot. Where the Model S presented itself as an all electric car — a subtle statement and proof of concept about a future of green but powerful motoring, Model X presented itself as a bold vision for what a car could be, if its only blueprint were imagination.

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This is nowhere near the power of the biggest systems, but still allows us to participate in research and development powered by supercomputer.

The idea that a computer could deliver an increase in life expectancy arises for a number of reasons, Prof Desplat says. Major gains are expected from the emergence of personalised medicine, care specifically tailored to match your genetic make-up. This will be driven in the not too distant future by “deep artificial intelligence learning” run on a supercomputer. These will also deliver faster more accurate early diagnosis, he says.

These computers are used in a variety of ways, from weather forecasting and climate modelling to energy usage modelling, statistical processing and seismic analysis when prospecting for oil and gas.

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Goldcorp (NYSE: GG, TSX: G) is teaming up with one of the world’s largest computer companies to help it find more gold at its storied Red Lake mine in Ontario.

Vancouver-based Goldcorp announced on March 3 it is bringing IBM Watson technology to Canadian mining for the first time. Named after IBM’s founder, Thomas J. Watson, Watson is a supercomputer that combines artificial intelligence with analytical software. According to WhatIs, IBM Watson replicates the human ability to answer questions by accessing 90 servers with a combines data storage of 200 million pages of information. Yet it can squeeze into a space that would fit 10 refrigerators. The supercomputer memorized the “urban dictionary” in 2013.

While the High Grade Zone (HGZ) has been the backbone of the Red Lake operation, with an average gold grade over two ounces per tonne, HGZ is expected to be depleted by 2020. Thus the need for more exploration to keep the mine going.

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In an era of maturing artificial intelligence technology, what does the future of the corporation look like? Will the rise of robots help us do our jobs better, or harm them? This dynamic has become a mainstay of the dialogue around AI, with voices from technology visionaries such as Bill Gates and Stephen Hawking weighing in.

But at Fortune’s Most Powerful Women International Summit in Hong Kong on Tuesday, leaders at two of the world’s most powerful tech giants pushed back on those concerns. AI is intended to help—not hinder—the human workforce, they said.

“AI is actually not new for us,” said Vanitha Narayanan, chairman of IBM India, whose Watson supercomputer has risen to global acclaim. But “technology always comes way ahead of policy.”

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In the past, traditional methods to understand the behavior of quantum interacting systems have worked well, but there are still many unsolved problems. To solve them, Giuseppe Carleo of ETH Zurich, Switzerland, used machine learning to form a variational approach to the quantum many-body problem.

Before digging deeper, let me tell you a little about the many-body problem. It deals with the difficulty of analyzing “multiple nontrivial relationships encoded in the exponential complexity of the many-body wave function.” In simpler language, it’s the study of interactions between many quantum particles.

If we take a look at our current computing power, modeling a wave function will need lot more powerful supercomputers. But, according to Carleo, the neural networks are pretty good at generalizing. Hence, they need only limited information to infer something. So, fiddling with this idea, Carleo and Matthias Troyer created a simple neural network to reconstruct such multi-body wave function.

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