After widespread backlash, a disturbing app that uses artificial intelligence to produce fake nude images of women is being taken offline. According to the anonymous creator of the app who goes by'Alberto,' the takedown stems from the app's potential to be abused. 'Despite the safety measures adopted (watermarks) if 500,000 people use it, the probability that people will misuse it is too high,' reads the tweet. Shortly after news of a'deepfaking' app capable of doctoring photos of nude women spread across the media, creators have taken the service offline It is a downloadable offline app which works on Windows and Linux. It is believed the software is based on pix2pix, an open-source algorithm developed by University of California, Berkeley researchers in 2017.

Artificial intelligence can now put itself in someone else's shoes. DeepMind has developed a neural network that taught itself to'imagine' a scene from different viewpoints, based on just a single image. Given a 2D picture of a scene – say, a room with a brick wall, and a brightly coloured sphere and cube on the floor – the neural network can generate a 3D view from a different vantage point, rendering the opposite sides of the objects and altering where shadows fall to maintain the same light source. The system, called the Generative Query Network (GQN), can tease out details from the static images to guess at spatial relationships, including the camera's position. "Imagine you're looking at Mt. Everest, and you move a metre – the mountain doesn't change size, which tells you something about its distance from you,"says Ali Eslami who led the project at Deepmind. "But if you look at a mug, it would change position.

Avatar breakthrough as AI that can create a perfect 3D face from a single picture is revealed (and they've tried it out on Donald Trump, Hillary Clinton and even Muhammad Ali) The stunning maps made from three million satellite images... The'golden cigar' UFO: Strange object flashes red and blue... The future of flying: NASA tests radical new embedded jet... Would YOU grow cannabis in your kitchen? The stunning maps made from three million satellite images... The'golden cigar' UFO: Strange object flashes red and blue...

The stunning maps made from three million satellite images... The'golden cigar' UFO: Strange object flashes red and blue... The future of flying: NASA tests radical new embedded jet... Would YOU grow cannabis in your kitchen? The stunning maps made from three million satellite images... The'golden cigar' UFO: Strange object flashes red and blue...

WWDC16 just ended and Apple left us with new amazing innovative APIs. This year speech recognition, proactive applications, machine learning, user intents, and neural networks have been the most frequent terms used during the conference. So, besides a new rich version 3 of Swift, almost every new addition to iOS, tvOS and macOS is related with artificial intelligence. For example, Metal and Accelerate in iOS 10 provide an implementation of convolutional neural networks (CNNs) for the GPU and CPU respectively. During the keynote, Craig Federighi (Apple's SVP Software Engineering) showed how the Photos app on iOS organizes our photos according to different smart criteria. He highlighted that Photos app uses deep learning to provide such functionality. Also, Federighi showed how Siri, now available to developers, can suggest what we need.

WWDC16 just ended and Apple left us with new amazing innovative APIs. This year speech recognition, proactive applications, machine learning, user intents, and neural networks have been the most frequent terms used during the conference. So, besides a new rich version 3 of Swift, almost every new addition to iOS, tvOS and macOS is related with artificial intelligence. For example, Metal and Accelerate in iOS 10 provide an implementation of convolutional neural networks (CNNs) for the GPU and CPU respectively. During the keynote, Craig Federighi (Apple's SVP Software Engineering) showed how the Photos app on iOS organizes our photos according to different smart criteria. He highlighted that Photos app uses deep learning to provide such functionality. Also, Federighi showed how Siri, now available to developers, can suggest what we need.

WWDC16 just ended and Apple left us with new amazing innovative APIs. This year speech recognition, proactive applications, deep learning, user intents, and neural networks have been the most frequent terms used during the conference. So, besides a new rich version 3 of Swift, almost every new addition to iOS, tvOS and macOS is related with artificial intelligence. For example, Metal and Accelerate in iOS 10 provide an implementation of convolutional neural networks (CNNs) for the GPU and CPU respectively. During the keynote, Craig Federighi (Apple's SVP Software Engineering) showed how the Photos app on iOS organizes our photos according to different smart criteria. He highlighted that Photos app uses deep learning to provide such functionality. Also, Federighi showed how Siri, now available to developers, can suggest what we need.