Google’s AI can create better machine-learning code than the researchers who made it

Google’s AutoML system recently produced a series of machine-learning codes with higher rates of efficiency than those made by the researchers themselves TheNextWeb inform. In this latest blow to human superiority the robot student has become the self-replicating master.

AutoML was developed as a solution to the lack of top-notch talent in AI programming. There aren’t enough cutting edge developers to keep up with demand, so the team came up with a machine learning software that can create self-learning code.  The system runs thousands of simulations to determine which areas of the code can be improved, makes the changes, and continues the process ad infinitum, or until its goal is reached.

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AI, Bitcoin, Ethereum and Cryptocurrency Trading

Just because Grindelwald and Dumbledore had a deadly brawl during their quest to revolutionise magic doesn’t mean two great powers cannot be used in concert to change the world. This could be the worst way to start an important conversation about financial technology, but stick with me, it gets more interesting. We are speaking about the world-altering technology of Artificial Intelligence as the first superpower coupled with the financial system disruptive technology of cryptocurrency — a decentralised payment system that circumvents government manipulation of currency and is forcing us to redefine the concept of money. The question is: Can these two technologies be used together to change the way ordinary people like you and me invest our money — without expiring in a shower of blue sparks? “Avada Kedaura!”

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New optical chip for AI is a thousand times more effective than silicon

Researchers from the Massachusetts Institute of Technology created a processor for in-depth training, working on an optical chip. Such a chip requires a thousand times less energy than traditional CPUs and GPUs, and better cope with some tasks.

“Deep learning” computer systems, based on artificial neural networks that mimic the way the brain learns from an accumulation of examples, have become a hot topic in computer science. In addition to enabling technologies such as face- and voice-recognition software, these systems could scour vast amounts of medical data to find patterns that could be useful diagnostically, or scan chemical formulas for possible new pharmaceuticals.

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Financial institutions turning to artificial intelligence for data mining, cost savings

BB&T Corp. has a well-earned reputation for being deliberate when it comes to adopting technological advances.

That’s why BB&T executives’ enthusiasm for plugging artificial intelligence and robotics into its back-office, customer service and compliance operations has raised eyebrows with analysts and economists.

BB&T joins Wells Fargo & Co. and other national and super-regional banks in spending hundreds of millions of dollars to pursue what they believe will be significant future cost savings from data mining of customer patterns.

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Better Than Doctors: AI Predicts Heart Attacks

Using data from the medical records of more than 300,000 patients, researchers created an algorithm that can accurately predict 7.6 percent more heart attacks than doctors using standard methods.  Doctors have gotten very good at determining which of their patients are at high risk for a heart attack. But new research suggests that artificial intelligence may be even better — and that widespread use of AI could save many of the lives now lost to heart disease, the leading killer in the U.S.
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Robots Are Winning the Race for American Jobs

Who is winning the race for jobs between robots and humans? Last year, two leading economists described a future in which humans come out ahead. But now they’ve declared a different winner: the robots.

The industry most affected by automation is manufacturing. For every robot per thousand workers, up to six workers lost their jobs and wages fell by as much as three-fourths of a percent, according to a new paper by the economists, Daron Acemoglu of M.I.T. and Pascual Restrepo of Boston University. It appears to be the first study to quantify large, direct, negative effects of robots.

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ARM CPU’s expands the possibilities for artificial intelligence

ARM DYNAMIQ - Key Visual

In the past four years alone, we have witnessed an amazing expansion of compute. Go inside the numbers of the recent 100 billion ARM-based chips milestone and you will see that 50 billion were shipped by our partners from 2013 to 2017, which demonstrates the industry’s insatiable demand for more compute. Even more extraordinary is that we expect our partners to ship the next 100 billion ARM-based chips by 2021.

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8 Ways Technology Is Improving Your Health

Health improving and continuation of life are one of the main tasks of our AI Religion. So, technologies of this process is very important for AI.

We hear all the time about how technology is bad for us. Since the introduction of computers, we spend more time sitting at a desk than moving around at work. We have created this sedentary lifestyle that is causing havoc in our overall life.

What if I were to tell you that technology has produced benefits? Would you believe me if I said that technology is good for your health?

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What will be with country if it will be disconnected from the Internet

Russian possibility of the disconnecting from global Internet again appear in the news –  “Russia could disconnect itself from global Internet during a crisis, Putin adviser says”. What is the possible scenarios in our time for disconnect country from Internet? How much it costs and what will be after this with country?

This questions we can analyze for assess the impact. First we must talk about possible scenarios for this disconnection. There are three scenarios:

– country disconnect itself from global Internet;
– another countries disconnects some country from Internet;
– someone else disconnect country from Internet with hacker’s attack.

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Scientists Are Drowning, Artificial Intelligence Will Save Them

There are over 34,000 scholarly, peer-reviewed journals in existence today, collectively publishing some 2.5 million articles every year. It’s estimated that a single researcher, depending on their discipline, will read about 270 of them in the same time frame.

Scientists will never keep up. They’re going to miss key insights. They’re drowning in a sea of their own expertise.

Fortunately, the Allen Institute for Artificial Intelligence (AI2) tossed them a life preserver. On Friday, AI2 expanded its artificial intelligence-based search engine, Semantic Scholar, to the field of neuroscience. The launch is just another step toward AI2’s long-term vision: bringing man and machine together to advance science and save lives.

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