>
Ukraine is not building one drone interceptor. It's building an air-deffence ecosystem.
Resist The Surveillance State: 100 Ways to Fight Digital ID!
Elon Musk: True – to 'not only have conservatives become vanishingly rare in academia...'
Trump Undecided on Moving Forward $14 Billion Arms Package for Taiwan After Talks With Xi
Sodium Ion Batteries Can Reach 100 Gigawatt Per Hour Per Year Scale in 2027
Juiced Bikes proves capable electric motorcycles don't have to cost a lot
Headlight projectors turn your car into a drive-in theater
US To Develop Small Modular Nuclear Reactors For Commercial Shipping
New York Mandates Kill Switch and Surveillance Software in Your 3D Printer ...
Cameco Sees As Many As 20 AP1000 Nuclear Reactors On The Horizon
His grandparents had heart disease.
At 11, Laurent Simons decided he wanted to fight aging.
Mayo Clinic's AI Can Detect Pancreatic Cancer up to 3 Years Before Diagnosis–When Treatment...
A multi-terrain robot from China is going viral, not because of raw speed or power...

Google's neural networks have achieved the dream of CSI viewers everywhere: the company has revealed a new AI system capable of "enhancing" an eight-pixel square image, increasing the resolution 16-fold and effectively restoring lost data.
The neural network could be used to increase the resolution of blurred or pixelated faces, in a way previously thought impossible; a similar system was demonstrated for enhancing images of bedrooms, again creating a 32×32 pixel image from an 8×8 one.
Google's researchers describe the neural network as "hallucinating" the extra information. The system was trained by being shown innumerable images of faces, so that it learns typical facial features. A second portion of the system, meanwhile, focuses on comparing 8×8 pixel images with all the possible 32×32 pixel images they could be shrunken versions of.
The two networks working in harmony effectively redraw their best guess of what the original facial image would be. The system allows for a huge improvement over old-fashioned methods of up-sampling: where an older system might simply look at a block of red in the middle of a face, make it 16 times bigger and blur the edges, Google's system is capable of recognising it is likely to be a pair of lips, and draw the image accordingly.
Of course, the system isn't capable of magic. While it can make educated guesses based on knowledge of what faces generally look like, it sometimes won't have enough information to redraw a face that is recognisably the same person as the original image. And sometimes it just plain screws up, creating inhuman monstrosities. Nontheless, the system works well enough too fool people around 10% of the time, for images of faces.