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Category: robotics/AI

Companies like to flaunt their use of artificial intelligence to the point where it’s virtually meaningless, but the truth is that AI as we know it is still quite dumb. While it can generate useful results, it can’t explain why it produced those results in meaningful terms, or adapt to ever-evolving situations. DARPA thinks it can move AI forward, though. It’s launching an Artificial Intelligence Exploration program that will invest in new AI concepts, including “third wave” AI with contextual adaptation and an ability to explain its decisions in ways that make sense. If it identified a cat, for instance, it could explain that it detected fur, paws and whiskers in a familiar cat shape.

Importantly, DARPA also hopes to step up the pace. It’s promising “streamlined” processes that will lead to projects starting three months after a funding opportunity shows up, with feasibility becoming clear about 18 months after a team wins its contract. You might not have to wait several years or more just to witness an AI breakthrough.

The industry isn’t beholden to DARPA’s schedule, of course. It’s entirely possible that companies will develop third wave AI as quickly on their own terms. This program could light a fire under those companies, mind you. And if nothing else, it suggests that AI pioneers are ready to move beyond today’s ‘basic’ machine learning and closer to AI that actually thinks instead of merely churning out data.

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“The eyes are the window of the soul.” Cicero said that. But it’s a bunch of baloney.

Unless you’re a state-of-the-art set of machine-learning algorithms with the ability to demonstrate links between eye movements and four of the big five personality traits.

If that’s the case, then Cicero was spot on.

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Machine learning is everywhere these days, but it’s usually more or less invisible: it sits in the background, optimizing audio or picking out faces in images. But this new system is not only visible, but physical: it performs AI-type analysis not by crunching numbers, but by bending light. It’s weird and unique, but counter-intuitively, it’s an excellent demonstration of how deceptively simple these “artificial intelligence” systems are.

Machine learning systems, which we frequently refer to as a form of artificial intelligence, at their heart are just a series of calculations made on a set of data, each building on the last or feeding back into a loop. The calculations themselves aren’t particularly complex — though they aren’t the kind of math you’d want to do with a pen and paper. Ultimately all that simple math produces a probability that the data going in is a match for various patterns it has “learned” to recognize.

The thing is, though, that once these “layers” have been “trained” and the math finalized, in many ways it’s performing the same calculations over and over again. Usually that just means it can be optimized and won’t take up that much space or CPU power. But researchers from UCLA show that it can literally be solidified, the layers themselves actual 3D-printed layers of transparent material, imprinted with complex diffraction patterns that do to light going through them what the math would have done to numbers.

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Russia is planning to blast two robot astronauts into space to work on the international space station.

Scientists have developed the advanced machines, named FEDOR, to conduct rescues — even though they have recently been recently trained to use firearms.

According to RIA Novosti, the robots could be blasted into space as soon as August 2019.

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Humanoid Robot torsos, legs, and arms are about where they need to be. But the robot hands are not quite where they need to be yet if we really want them to take all the jobs. The government is dumping a lot of money into robotic hand’s for amputees, which i’m sure they plan to eventually put on the humanoid robots, but it should be pushed along faster.

Imagine, for a moment, the simple act of picking up a playing card from a table. You have a couple of options: Maybe you jam your fingernail under it for leverage, or drag it over the edge of the table.

Now imagine a robot trying to do the same thing. Tricky: Most robots don’t have fingernails, or friction-facilitating fingerpads that perfectly mimic ours. So many of these delicate manipulations continue to escape robotic control. But engineers are making steady progress in getting the machines to manipulate our world. And now, you can help them from the comfort of your own home.

UC Berkeley and Siemens researchers have launched something called Dex-Net as a Service, a beta program that computes how and where a robot should grip objects like vases and turbine housings. You can even upload designs of your own objects. The goal: to one day get the robot in your home to call up to the cloud for tips on how to manipulate novel objects. Maybe we can even keep them from destroying the delicates.

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