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Category: robotics/AI – Page 2,359

The exploration of Europa begins under the ice in Antarctica.

That’s where a team of researchers, led by the Georgia Institute of Technology (Georgia Tech), has been testing a variety of robotic subs in recent years to learn about what technologies will work best when NASA eventually launches a mission to Jupiter’s icy moon.

“I really want us to go down through the ice on Europa. I want to explore what’s down there,” says Britney Schmidt, assistant professor at the School of Earth and Atmospheric Sciences at Georgia Tech and principal investigator for the NASA-funded project called SIMPLE, for Sub-ice Investigation of Marine and Planetary-analog Ecosystems.

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IBM delivered on the DARPA SyNAPSE project with a one million neuron brain-inspired processor. The chip consumes merely 70 milliwatts, and is capable of 46 billion synaptic operations per second, per watt–literally a synaptic supercomputer in your palm.

Along the way—progressing through Phase 0, Phase 1, Phase 2, and Phase 3—we have journeyed from neuroscience to supercomputing, to a new computer architecture, to a new programming language, to algorithms, applications, and now to a new chip—TrueNorth.

Fabricated in Samsung’s 28nm process, with 5.4 billion transistors, TrueNorth is IBM’s largest chip to date in transistor count. While simulating complex recurrent neural networks, TrueNorth consumes less than 100mW of power and has a power density of 20mW / cm2.

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The Intelligence Advanced Research Projects Activity has launched a multi-year research and development effort to create new technologies that could provide an early warning system for detecting precursors to cyberattacks. If successful, the government effort could help businesses and other targets move beyond the reactive approach to contending with a massive and growing problem.

IARPA, part of the Office of the Director of National Intelligence, says the three-and-a-half year program will develop software code to sense unconventional indicators of cyber attack, and use the data to develop models and machine learning systems that can create probabilistic warnings.

Current early warning systems are focused on traditional cyber indicators such as activity targeted toward IP addresses and domain names, according to IARPA program manager Robert Rahmer. The first stage, lasting 18 months, will examine data outside of the victim network, such as black market sales of exploits that take advantage of particular software bugs. The second and third phases, 12 months each, will examine internal target organization data and look for ways to develop warnings and transfer any tools that emerge from the research from one organization to another, he said.

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Cool new story in the San Francisco Chronicle about the robotics conference. I gave a speech at it yesterday.

At the two-day RoboBusiness Conference, about 2,000 people were serenaded with lullabies and Disney tunes, including “Let It Go” from the hit film “Frozen,” by a human-like robot designed to comfort senior citizens and autistic children.

And next to a man-size robot that can drive a motorcycle 190 mph around a race track, a half-dozen ant-size robots quickly scurried about a miniature factory floor.

“In five years, could you imagine what this conference is going to look like?” Transhumanist Party presidential candidate Zoltan Istvan asked the crowd. “There are going to be 8-foot robots walking all around us, talking to us, some of them maybe being smarter than us.”

Continue reading “The future of robots: singing lullabies, testing motorcycles” | >

Seems like we’ve been waiting forever for the big showdown between Team USA and Japan. We’re seemingly no closer at the moment, but at least the team at MegaBots can offer a bit of good old-fashioned destruction to tide us over before the massive machines go toe-to-toe.

In the premier of its new web series (the trailer for which was shown off at Disrupt the other week), the team behind the fighting robot startup league go to town on their own robot, the $200,000 Mk. II.

In order to stress test the six-ton bot’s protective casing, the team shoots it with its own gun and gives it several whacks with a wrecking ball. At the risk of spoiling the seven-and-a-half minute long video, it turns out it’s really tough to knock over a 15-foot-tall fighting robot.

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Monitoring blood-glucose levels and injecting insulin to keep them in a safe range is a never-ending headache for sufferers of type 1 diabetes. A number of research projects have made promising steps recently to promise easier ways of doing things, and now this type of convenience is set to move out of the lab and into the real-world. For the first time, the US Food and Drug Administration (FDA) has approved a so-called artificial pancreas designed to both monitor and inject insulin automatically, requiring minimal input from the user.

In a healthy person, beta cells in the pancreas secrete vital insulin, which in turn regulates blood-sugar levels. But for sufferers of type 1 diabetes, this process breaks down along the way, requiring them to administer finger-prick blood tests to keep tabs on their insulin levels and inject the hormone as required.

For years, scientists have been exploring better ways to keep the condition in check. These have included implanting beta cells, tracking glucose levels through contact lenses and ways insulin can be delivered via a capsule rather than a needle. But perhaps the most attractive solution is what is known as a closed-loop system, which seeks to automate both monitoring and administration of insulin to dramatically reduce the burden on the user.

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Industry leaders in the world of artificial intelligence just announced the Partnership on AI. This exciting new partnership was “established to study and formulate best practices on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society.”

The partnership is currently co-chaired by Mustafa Suleyman with DeepMind and Eric Horvitz with Microsoft. Other leaders of the partnership include: FLI’s Science Advisory Board Member Francesca Rossi, who is also a research scientist at IBM; Ralf Herbrich with Amazon; Greg Corrado with Google; and Yann LeCun with Facebook.

Though the initial group members were announced yesterday, the collaboration anticipates increased participation, announcing in their press release that “academics, non-profits, and specialists in policy and ethics will be invited to join the Board of the organization.”

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Translating from one language to another is hard, and creating a system that does it automatically is a major challenge, partly because there are just so many words, phrases and rules to deal with. Fortunately, neural networks eat big, complicated data sets for breakfast. Google has been working on a machine learning translation technique for years, and today is its official debut.

The Google Neural Machine Translation system, deployed today for Chinese-English queries, is a step up in complexity from existing methods. Here’s how things have evolved (in a nutshell).

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