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The clang of metal, breathtaking speed and tons of adrenaline! Watch a futuristic video of battle robots in ultimate fighting in Moscow. The iron warriors are clashing without mercy for the right to face foreign competitors.

The Russian capital is holding an international competition ‘Bronebot-2016’ for battle robots, February 21–23. “Attention! The show contains scenes of total robot carnage,” the banner reads.

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Whether in the brain or in code, neural networks are shaping up to be one of the most critical areas of research in both neuroscience and computer science. An increasing amount of attention, funding, and development has been pushed toward technologies that mimic the brain in both hardware and software to create more efficient, high performance systems capable of advanced, fast learning.

One aspect of all the efforts toward more scalable, efficient, and practical neural networks and deep learning frameworks we have been tracking here at The Next Platform is how such systems might be implemented in research and enterprise over the next ten years. One of the missing elements, at least based on the conversations that make their way into various pieces here, for such eventual end users is reducing the complexity of the training process for neural networks to make them more practically useful–and without all of the computational overhead and specialized systems training requires now. Crucial then, is a whittling down of how neural networks are trained and implemented. And not surprisingly, the key answers lie in the brain, and specifically, functions in the brain and how it “trains” its own network that are still not completely understood, even by top neuroscientists.

In many senses, neural networks, cognitive hardware and software, and advances in new chip architectures are shaping up to be the next important platform. But there are still some fundamental gaps in knowledge about our own brains versus what has been developed in software to mimic them that are holding research at bay. Accordingly, the Intelligence Advanced Research Projects Activity (IARPA) in the U.S. is getting behind an effort spearheaded by Tai Sing Lee, a computer science professor at Carnegie Mellon University’s Center for the Neural Basis of Cognition, and researchers at Johns Hopkins University, among others, to make new connections between the brain’s neural function and how those same processes might map to neural networks and other computational frameworks. The project called the Machine Intelligence from Cortical Networks (MICRONS).

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Russia’s NextGen Robots are coming.


Russian military institutions are working on a program of robotization of the army that will introduce combat robots able to act independently on the battlefield, deputy head of the Defense Ministry Pavel Popov said in an interview with the Moskovsky Komsomolets newspaper.

Special military units of robots will be operated by a united control system, Popov said, adding that many robotic and pilotless vehicles are already employed in the Russian military.

Military expert Viktor Murakhovsky confirmed that Russia is actively developing new robotic machinery, though the concept is not widely discussed, Moskovsky Komsomolets reported.

The jury may still be out on the usefulness of the Internet of Things, but payments giant Visa is 100 percent sure that it doesn’t want to miss out. Today, it announced plans to push Visa payments into numerous fields. We’re talking “wearables, automobiles, appliances, public transportation services, clothing, and almost any other connected device” — basically anything that can or will soon connect to the internet.

Visa imagines a future where you’ll be able to pay for parking from your car dashboard or order a grocery delivery from your fridge. It makes sense, then, that Samsung is one of the first companies to sign up to the Visa Ready Program, alongside Accenture, universal payment card company Coin and Fit Pay. Chronos and Pebble are also working to integrate secure payments inside their devices.

To show off the technology, which works with any credit card, Visa or otherwise, the company has teamed up with Honda to develop an in-car app that helps automate payments. Right now they have two demos, the first of which concerns refueling. It warns the driver when their fuel level is low and directs them to the nearest gas station. Once the car arrives at the pump, the app calculates the expected cost and allows the driver to pay for the fuel without having to leave the vehicle.

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This story reminds me of the building of ancient pyramids in Egypt as well as the building of ancient temples and cities in Mexico and India.

China has relocated 9K people to build their new giant telescope — in 2000 years from now the robots and Ray Kurzweil (who plans never to die) will be looking at the ancient telescope. And, Ray (the grand earth historian) can tell them all about the process and the reason why it was built.


The Chinese government plans to relocate some 9,000 people to make space for the world’s largest radio telescope. Photo: ChinaPhotoPress.

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Does the connected self driving car, mean a connected work car as well?


SAN FRANCISCO — In the balancing act between business and pleasure, the modern connected car is mostly about pleasure. Drivers can easily stream music from the Internet and dictate text messages to friends, but staying connected to the office is still cumbersome, as anyone who has tried to join a teleconference while driving can attest.

People tired of checking corporate email around the clock may prefer it that way. After all, a request from the boss can still be reasonably deflected with a simple: “Sorry, I’m driving.”

Yet for Microsoft Corp., which dominates the workplace software market with its Office 365 suite, in-car productivity is a huge, untapped opportunity. Many people use cars as mobile offices, and as cars become more automated, putting together a slide deck behind the wheel may go from unsafe to commonplace.