Intel quietly launched a free Android app over the weekend, that lets you use your phone as a keyboard and trackpad for your PC. Intel Remote Keyboard was designed for use with mini PCs that are about the size of a flash drive and don't ship with peripherals — but you can use it on any system run...
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Source: http://www.engadget.com/2015/06/20/facebook-and-google-ai-image-creation/
For Facebook and Google, it's not enough for computers to recognize images... they should create images, too. Both tech firms have just shown off neural networks that automatically generate pictures based on their understanding of what objects look like. Facebook's approach uses two of these networks to produce tiny thumbnail images. The technique is much like what you'd experience if you learned painting from a harsh (if not especially daring) critic. The first algorithm creates pictures based on a random vector, while the second checks them for realistic objects and rejects the fake-looking shots; over time, you're left with the most convincing results. The current output is good enough that 40 percent of pictures fooled human viewers, and there's a chance that they'll become more realistic with further refinements.
Google's take heads in the opposite direction. Instead of striving for realism, it's producing art by letting the neural network run wild and decide on the visual elements that it wants to emphasize. If you give the machine a photo of the sky and it thinks there are birds in the scene, it'll keep amplifying those avian traits until they're impossible to miss. The finished work is more than a little trippy, especially if you give it random noise as its source material -- as you can see above, the results give impressionist and surrealist painters a run for their money. You're not likely to see these Facebook and Google programs replacing human artists and photographers, but they're skilled enough to draw images you might enjoy.
Filed under: Science, Internet, Software, Google, Facebook
Via: The Next Web, Singularity Hub
Source: Facebook (ArXiv.org), Google Research Blog
Source: http://www.engadget.com/2015/06/21/light-based-battery/
Sure, you can make solar-powered devices that store their excess energy in a battery, but what about the battery itself? Unfortunately, it's still behind the times -- the lithium-ion cells you see today have to be connected to another device to charge, and they're occasionally very dangerous thanks to their chemical makeup. A team of Indian researchers may have just licked those problems, though. They've developed a battery whose titanium nitrate anode (where current flows into the device) is driven by light, both natural and artificial. In a well-lit area, a prototype can recharge itself without using either an external source or unstable chemicals.
The existing technology isn't ready for prime time yet. While it tops up in 30 seconds, it's barely powerful enough to run an LED light or a small fan, let alone your phone. If the technology improves, however, you could see more gadgets that not only don't have to be plugged in, but won't ignite if you drop them a certain way.
Filed under: Science
Source: ACS
Hunting for extremely dim galaxies is especially difficult with single-lens telescopes. That's because, no matter how technologically advanced, the device's design cannot fully eliminate detail-obscuring scattered light from the resulting images. The University of Toronto's Dragonfly Telephoto Array, however, deftly avoids that issue. This array -- one of the smallest multi-lens astronomy telescopes in use today -- is comprised of 10 Canon 400mm f/2.8 L IS II USM telephoto lenses, each costing $10,000. What's more, each lens is coated in a unique subwavelength nanomaterial that drastically reduces light reflection within the optic. And, like its insect inspiration, the Dragonfly's ten eyes can work in concert with one another to further reduce unwanted illumination in the resulting image, bringing out otherwise unseen detail in cosmic structures. According to the University of Toronto spokesman Roberto Abraham, this $100,000 system is ten times as accurate as its nearest rival.
[Image Credit: U of Toronto]
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