Items tagged with neural network
PC gamers who have been around, or who have downloaded the original 1993 Doom, will remember the pixelated Doom guy avatar that was a hallmark of that game. I'd wager a bunch of players wondered at some point what that guy would look like in real life. The answer to that question is here with someone employing an AI-trained neural network and having it turn the Doom guy's pixelated likeness into a high-resolution photo. It's hard to see any details in those pixelated images from Doom, but somehow the high-resolution images produced by the neural network look exactly as you would expect them to look. As for how the image came to be, it's said to be the final product of several AI systems that...
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Artificial intelligence has the potential to change lots of things (in good ways) for humanity. Some people, notably Elon Musk, fear an AI arms race could lead to another world war. AI has shown that it is capable of beating humans in games that humans have mastered over many years, such as Google's AlphaGo AI defeating Go world champion Lee Sedol. Now, AI has invented an entirely new sport using data from 400 existing sports. The new sport is called Speedgate, and it was created after design agency AKQA feed the AI neural network data on 400 existing sports. The AI came up with some wacky ideas for sports; one of them was exploding Frisbees making it a good thing that the AI can't force...
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AI can be a good thing or a bad thing, depending on what the AI is designed to do. Many AIs are meant to do things like help doctors diagnose disease, though other AI technologies can be turned towards more nefarious deeds. For example, a team of IEEE researchers has devised a method of harnessing an AI to generate fake fingerprints that work like a master key, to bypass the biometric locks that are employed on smartphones. The team notes that the attack using their AI-driven method can be issued against random devices "with some probability of success." OnePlus 6T In-Display Fingerprint Scanner The technique is known as DeepMasterPrints, and the researchers liken them to a master key for...
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After taking a measured, wait-and-see approach to machine learning, Arm is ready to jump into the fold full throttle. Today, the company is following up on its Project Trillium announcement from back in February with new details surrounding its machine learning processor, also known as the neural-network processing unit or NPU. To quickly recap, Project Trillium encompasses Arm’s push to leverage machine learning and neural network operations across their line-up of processors – whether that processing takes place on the CPU, GPU, or its new NPU. Arm’s goal is to make machine learning feasible “on the edge.” The edge largely describes standalone devices such as smartphones...
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Imagine playing a game like Skyrim or a sports title where the characters you encounter look like real people or creatures, and not rendered graphics. If implemented correctly, it could add a new level of immersion to gaming. It may not be far off, either. NVIDIA released a paper over the weekend detailing a new training methodology for generating unique and realistic looking faces using a generative adversarial network (GAN).Everyone of these faces are machine-rendered... The result is the ability to render photorealistic faces of "unprecedented quality." How NVIDIA achieves this is by using an algorithm that pairs two neural networks—a generator and a discriminator—that compete against each...
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A lot has been accomplished with Google's DeepMind artificial intelligence subsidiary, and it looks like the progress train isn't about to slow down anytime soon. As a quick recap, this year alone we've seen DeepMind take down a Go player, get started on an AI kill switch, attempt to cure blindness, improve speech generation, and even slash a mammoth power bill. What's next? Completely self-contained learning. We wouldn't be shocked if you started having ideas of Skynet running through your head right now. With a new hybrid system called Differentiable Neural Computer (DNC), a neural network is paired with external storage (aka: a large external dataset), and the computer's AI is smart enough...
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We've no doubt all listened to a PC "speak" to us at some point in our lives. Today, technologies are advanced enough to make it so that understanding this speech is not an issue, though we're sure many would prefer that solutions sounded less robotic, or so stitched-together. Google's DeepMind works on developing incredibly smart computers, and one of its projects involves recreating human speech as naturally as possible. You might appreciate the fact that DeepMind has developed its WaveNet model, which improves upon existing solutions by roughly 50%. It still underperforms human speech (but not by much, in our opinion), but it's nonetheless a massive improvement. Given where...
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If you're a fan of travel, you're probably going to love what Google has been up to lately. As we've covered many times, Google is no stranger to machine-learning and developing complex and powerful neural networks of computer resources. Now, the company has decided to focus on geography as well as testing you, not only its own neural network. Google's Tobias Weyand, with the help of other engineers, has developed a neutral network that helps pinpoint exactly where in the world a photograph was taken. For things like landmarks, this wouldn't be too complicated. But what about inside someone's home? Inside a shopping mall? On an ordinary road like the one below? The image above was pulled...
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Netflix has long chased after methods of improving its movie recommendation algorithms, once even awarding a $1M prize to any team of people who could substantially improve on the then-current design. As part of that process, the company has been researching neural networks. Conventional neural networks are created with vast nodes of CPU clusters, often with several thousand cores in total. Netflix decided to go with something different, and built a neural network based on GPU cores. In theory, GPU cores could be ideal for building neural nets -- they offer huge numbers of cores already linked by fast internal interconnects and with relatively large pools of onboard memory. Whether or not the...
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