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apple developer account:Deepfaking AIs are inventing faces and bringing the dead to life

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,This woman does not exist. Her face is purely the product of artificial intelligence, and one of countless more on websites showcasing deepfaked faces. — dpa It's hard to believe: refresh, refresh, refresh - a different person every time you reload the page. Are all these people okay with their faces being online in high resolution? Or is this some strange database of wanted criminals? None of these faces are real, a prompt soon tells you - even though you could have sworn otherwise. You're on the website ThisPersonDoesNotExist.com, where developer Phil Wang showcases fake faces - computer-generated images of people who simply do not exist. The photos are known as deepfakes, and this is by far not the only website of its kind. Several other projects are bringing faces to life - both real and imaginary. There's the smiling visages of Altered Qualia, whose eyes will eerily follow your cursor, with plenty more examples on alteredqualia.com. Some people are even bringing deceased loved ones and famous personalities to life using a similar technology. A glance at the #DeepNostalgia posts being shared on Twitter right now shows countless videos of animated faces in black and white, from Anne Frank to late grandparents. Many of them come from a genealogy portal that has recently started offering its customers the opportunity to bring their own uploaded portraits to life. Some videos show people shocked at the sight of a photo of a dead parent being reanimated with a moving head, blinking eyes and a smile or two. It's called Deep Nostalgia, and it's surprisingly realistic, even with faces from paintings or sculptures. Meanwhile over on ThisPersonDoesNotExist.com, the deepfaked, imagined faces come from two interconnected neural networks that are continuously trained with photos of real people to create these impressively realistic portraits. One neural network calculates entirely new faces from all the possible human features it has memorised during learning, from face shapes to skin characteristics and eye colours to hairstyles. The other neural network then evaluates the result with its own empirical values. If the fake face passes the "reality check", it's published. Otherwise, the first network has to rework everything. More than 90% of the results are so realistic that if you didn't know how the portrait came about, you'd have no doubts about its authenticity. But here and there, you'll notice a glitchy face, which is somehow reassuring. There might be something wrong with the symmetry of the face, the peak of a baseball cap is growing out of someone's forehead or there are texture errors on the skin. – dpa
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