Here, we feed the neural network vast amounts of training data, labeled by humans so that a neural network can essentially fact-check itself as it's learning.
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IBM's chips are still too experimental to be used in mass production, but they've shown promise in running a special type of neural network called a spiking neural network.
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These include the size of the neural network being baked, the amount of pretraining data, how that pretraining data is masked and how long the neural network gets to train on it.
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It was cheaper and faster to train the neural network.
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So she's giving the job to a deep neural network.
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This neural network was a very early version of AlphaGo.
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They used something called a graph neural network, or GNN.
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Google's Deep Dream neural network is the most famous example.
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They're all just assemblages of features to the neural network.
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They posted the code for the neural network on Github.
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So you were using deep learning and neural network models?
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Then, the researchers loaded Niki with their new neural network system.
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Cogniac uses what's called a convolutional neural network to process images.
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Take the neural network that can analyze human actions, for example.
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The company also announced Nvidia Drivenet, its own deep neural network.
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But it is slowly bringing deep neural network to more languages.
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One of the really scary things is [the neural network] Word2vec.
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This would be true of an intelligent neural network as well.
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So far, no neural network can beat human performance on it.
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The deep neural network learns on its own, getting better with experience.
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A neural network would obviously be super helpful for large-scale surveys.
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Google Brain's software does this with two stages of neural network training.
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Inside each neural network are layers of artificial neurons connected like webs.
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And it's this aspect that benefits from a "deep neural network" approach.
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The program contains at least one component known as a neural network.
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The second neural network known as the imitation network then takes over.
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But the neural network was tuned to favor his speech whenever possible.
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Neural network pattern recognition opens whole new categories of hitherto insoluble problems.
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Next, they began "training" a neural network to interpret those degraded images.
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In 1951, he built the first randomly wired neural network learning machine.
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The lung-screening neural network is not ready for the clinic yet.
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In fact, I'm a neural network designed to sound like Dr. Peterson.
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He fed the neural network a still he had taken from YouTube.
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The change also made the neural network dramatically more efficient at learning.
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At the core of Pefin's AI is a feed-forward neural network.
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All I have in the hands-on AI/ML/deep-learning/neural-network experience is some time I've spent playing around with TensorFlow, a graduate-level neural-network course I took back in the day, and some book research.
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Shane began the process by feeding a trained neural network a "seed text" to begin with, like the letter B. "Then the neural network has to try to guess the next character in the sequence," she explained to Hyperallergic.
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But mega-efficiency or neural network problem solving might be just as disruptive.
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If there exists a neural network for religion, how did it get there?
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And training a robust neural network requires feeding it the choicest of pictures.
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It pits two machine-brains—each its own neural network—against each other.
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Yahoo does it — with their special-made, smut-trained, porn-detecting neural network.
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From there, Facebook built a generative saliency map using a deep neural network.
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So, to a neural network, that's one obvious difference between divers and snorkelers.
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Nvidia turned to 1 million images on Flickr to train the neural network.
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Well, not to a neural network trained by Google to identify everyday objects.
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The neural network stitches these together using powerful graphics chips hardened against radiation.
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Click here to view original GIF"Beach" photos processed by MIT's neural network.
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The assessment uses a deep neural network trained with data labelled by humans.
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The origin of Wallace's neural network Magic art comes from a practical place.
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Of course, not every DIY neural network will be quite so G-rated.
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"It has intelligence, but not a deep-learning neural network intelligence," Kim said.
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They have a hormonal information-processing system that's homologous to animals' neural network.
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That type of neural network experimentation is where Pikazo's real power might lie.
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In February, Kuyda asked her engineers to build a neural network in Russian.
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But then, research scientist Janelle Shane came around, armed with her neural network.
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The more layers in the neural network, the more complexity it can capture.
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By analyzing CT scans, a neural network can learn to spot lung cancer.
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Instead, they fed the images, and their diagnostic classifications, to the neural network.
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Cohen's neural network wouldn't be able to "see" that structure on its own.
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It is a very basic neural network (not a sophisticated deep learning net).
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But then around the '80s there was a big move in AI away from neural network systems, and people like [AI pioneer Marvin] Minsky proved things about those primitive neural network systems — that they weren't able to do certain tasks.
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And trying to really push that far is what made us come with the Neural Turing Machine, where we introduce this idea of having a big external memory connected to the neural network that the neural network can access and use.
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According to the website, the "Benign" text is generated using a recurrent neural network.
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"Everyone knew me as the guy who lost against the neural network," he says.
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Then they used a second neural network to analyze a picture of a tree.
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Scientists have lately been putting a neural network to good use identifying distant galaxies.
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They trained a neural network on the images in order to identify their similarities.
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"Prior to my paper, they directly fed the image to neural network," said Kurakin.
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Vanderburg and Shallue will continue polishing the neural network to look for more exoplanets.
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Google fed a neural network an image of a sky, and it saw birds!
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He has over 15 years' experience in speech technology and neural network R&D.
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All of this is controlled by a neural network called the autonomic nervous system.
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DeepDrumpf is a Twitterbot that uses a neural network trained on his terrifying transcripts.
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Then, it uses a neural network to learn to identify prey faster and faster.
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Another neural network, Eve, was tasked with reading the communications between the two robots.
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To solve the problem, we leveraged state-of-the-art deep neural network technologies.
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The neural network controlling each hero has a memory component that learns certain strategies.
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This technology is the neural network, which underpins today's most advanced artificial intelligence systems.
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Consider, for example, a neural network with the task of recognizing objects in images.
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A grid of portraits made by a neural network that studied thousands of paintings.
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For example, we could ensure a neural network doesn't have access to Mein Kampf.
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But the trained neural network identified the manipulated images 99 percent of the time.
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Convolutional neural networks; using cameras, GPUs, neural network A.I. to learn as it goes.
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Still not clear on what exactly a deep learning system or neural network is?
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What's the difference between a quantum computer, a neural network, and your Macbook Pro?
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This neural network simulator is the foundation upon which Berenson builds its own tastes.
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It's almost like a bandmate, but you somehow have access to their neural network.
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As with any neural network, the model's output isn't guaranteed to provide correct answers.
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She inputted various laws of physics and refined the parameters of her neural network.
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Nvidia says it trained a "deep learning neural network" on how best to upscale 1080p and even 720p video to 4K, and it runs that neural network in real time whenever you're playing video on the Shield TV and Shield TV Pro.
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There's a lot of data, and lots of scenarios to train a neural network on.
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But it doesn't take an authoritarian state to turn a neural network toward evil ends.
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The neural network produced a building that is a blend of green and blue arches.
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Like Pikazo, the neural network behind Prisma turns videos or stills into works of art.
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The neural network and hyperspectral imager have already been built and tested by KP labs.
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The Open Neural Network Exchange has been released on Github, you can find it here.
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Even Google said it's going to use the neural network more "broadly" throughout the company.
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This enabled them to create a "biomechanically inspired recurrent neural network" that catalogs human movements.
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One of the earliest important theoretical guarantees about neural network architecture came three decades ago.
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He also borrowed some neural network code from an attendee of the RC car meetup.
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How it works: The user takes a selfie, and Google's neural network gets to work.
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The next time I saw her again, I was besotted, my neural network a jumble.
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The neural network returns results skewed by the raw materials it was given to start.
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"When we say the neural network is like the brain it's not true," says LeCun.
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AI Scry uses a well-know neural network AI Scry isn't an entirely new concept.
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Using more than 30 million lines of Russian text, Luka built its second neural network.
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This was done by training a generative neural network to interpret the archive at SALT.
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This trial engages a neural network separate from the language cortex—the executive-function system.
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"It's basically a kind of neural network that can associate data and images," explains Bridle.
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OK, beauty might be a stretch, but these neural network nudes are definitely strangely fascinating.
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For that task, the team is developing a neural network that can recognize known aircraft.
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That's why we've trained a powerful neural network to replace our expensive, cannabis-smoking writers.
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In any event, it's just amusing to see a neural network literally try to play god.
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That part of the chip can handle 2.1 trillion operations per second for neural network inferencing.
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DeepVariant, though, leverages neural network technology to build something more accurate than anything else in existence.
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A serious neural network can have a billion interconnections, all of which need to be tuned.
|
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In the second column, we see Google fed its neural network an image of a tree.
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The app works by taking a color image and passing it through a Convolutional Neural Network.
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The technology behind this new neural network is called "Bidirectional Encoder Representations from Transformers," or BERT.
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In 1951 he built the first randomly wired neural network learning machine, which he called Snarc.
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They're the result of a neural network trained on millions of real reviews taken from Yelp.
|
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Called GauGAN, the software is just a demonstration of what's possible with Nvidia's neural network platforms.
|
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Their works deploys a type of neural network known as a generative adversarial network, or GAN.
|
|
Facebook and Microsoft announced ONNX, the Open Neural Network Exchange this morning in respective blog posts.
|
|
Take, for example, a neural network that's been trained to analyze human actions in a video.
|
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Then, they turned the neural network loose on the data, leaving it to slowly identify patterns.
|
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The neural network, by comparison, ripped through a database of 21,789 images in just 20 minutes.
|
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The satellite will be used to prove that a hardened neural network can survive in space.
|
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"The neural network itself then learns what parts of the face to look at," he says.
|
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Last year, Google's DeepDream program produced similar, albeit freakier, "artwork" using its own artificial neural network.
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He also clarified that the anti-jpeg neural network is intended specifically for removing JPEG artifacts.
|
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Next, Park wants to feed the neural network more spore images, in order to boost accuracy.
|
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"The teacher got a little bit upset because the neural network was extremely profane," he says.
|
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A group of 7-year-olds had just deciphered the inner visions of a neural network.
|
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Google's DeepMind announced today that it was open sourcing Sonnet, its object-oriented neural network library.
|
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And teaching a neural network what exactly constitutes a "good" kitchen could be a long process.
|
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On the left is the original input image and the original prediction of the neural network.
|
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Scroll down and you'll see the images that trained the neural network to recognize that object.
|
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Aided by a rapidly developing neural network, perhaps she could speak with her friend once again.
|
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According to Apple, the neural network behind Face ID was trained on over 1 billion faces.
|
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The neural network learned first by being fed replays of human games, diamond level and above.
|
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With Picbreeder, each image was the output of a computational system similar to a neural network.
|
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In traditional machine learning, as you train a neural network, it gradually gets better and better.
|
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The human brain has a million times more synaptic connections than today's best artificial neural network.
|
|
Last week, Google Research also open-sourced a neural network framework for TensoryFlow, known as SyntaxNet.
|
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In the nude portrait experiment, however, the neural network refused to move past its Dalí period.
|
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"The control is done via a neural network simulator named Prométhé," Vidal tells The Creators Project.
|
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This all starts with a deep neural network that allows Amazon to understand and learn behavior.
|
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By analyzing photos of pedestrians, for example, a neural network can learn to identify a pedestrian.
|
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By analyzing thousands of images, a neural network can, for example, learn to identify a pedestrian.
|
|
Chunks build on chunks, and, she says, the neural network built upon that knowledge grows bigger.
|
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Using computer modeling software with a neural network tool, Yang began programming software of her own.
|
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The tool they had developed was basically an ingenious way of testing a deep neural network.
|
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A neural network can learn tasks largely on its own by analyzing vast amounts of data.
|
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By analyzing thousands of proteins, a neural network can learn to predict the shape of others.
|
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Apps like Prisma use neural network algorithms to apply a particular artistic style to an image.
|
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There isn't exactly a Bible verse that tells you if a neural network is blasphemous or not.
|
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You don't just throw a bunch of data and teach a deep neural network how to drive.
|
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Experts must use instinct and trial and error to discover the right architecture for a neural network.
|
|
She used a neural network that can find patterns across answers rather than analyze each in isolation.
|
|
That is because DeepMind's original neural network could learn to play only one game at a time.
|
|
So we're just as smart as AI. Would you like a neural network installed in your neck?
|
|
Click here to view original GIF This creep machine, called Alter, runs entirely off a neural network.
|
|
As with these earlier examples, the neural network here was trained by imbibing a carefully constructed dataset.
|
|
I do my neural network tutorials and so I understand it and there's a lot of bullshit.
|
|
The solution isn't a neural network or computer vision system, though: For now, it's just elbow grease.
|
|
So by watching Kelp's behavior, the neural network learned these rules without having to be taught them.
|
|
The tool used for this particular research is what's known as a convolutional neural network, or CNN.
|
|
But a byproduct of this approach is a thorough understanding of the way the neural network operates.
|
|
If you're on point, however, the neural network will home in on the object and guess correctly.
|
|
When it comes to images, you can think of a neural network as a pattern recognition system.
|
|
The neural network, by comparison, was able to find the manipulated image 99 percent of the time.
|
|
It played game after game after game versus a (slightly) different version of its own neural network.
|
|
Yet as the Tokai team discovered, leveraging this technique to image a neural network is slightly trickier.
|
|
By analyzing millions of bicycle photos, for instance, a neural network can learn to recognize a bicycle.
|
|
By analyzing thousands of dog photos, for instance, a neural network can learn to recognize a dog.
|
|
By analyzing thousands of car photos, for instance, a neural network can learn to recognize a car.
|
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A neural network can learn to recognize a dog by gleaning patterns from thousands of dog photos.
|
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By metabolizing thousands of cat photos, for instance, a neural network can learn to recognize a cat.
|
|
The robot uses a neural network to automatically teach itself to balance as it climbs the ladder.
|
|
The language is then dumped into a "neural network dialogue model" that learns the characters' language patterns.
|
|
A deep neural network was fed the dataset, creating a model based on the late president's speech patterns.
|
|
Shane's friend Eva Gulotty helped sort the data into groups, after which the neural network did its job.
|
|
Generating a neural-network design from scratch is harder than tweaking the settings of one that already exists.
|
|
And recently, they released their first result: a neural network that sharpens up blurry, noisy images from space.
|
|
The more words, faces, or objects a neural network "sees," the better it gets at spotting those targets.
|
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The more neural network layers the original image goes through, the more trippy the end result will be.
|
|
The training method for Dadabots involves feeding a sample recurrent neural network whole albums from a single artist.
|
|
As it's fed this data, different neurons in the neural network light up in response to each image.
|
|
The deep neural network then scanned these pixel by pixel, looking for the characteristics common to each diagnosis.
|
|
"Our neural network learning approach enables us to continue to iterate and improve functionality over time," Tesla says.
|
|
Those phrases are then analyzed by a neural network, which can detect certain characteristics of a person's voice.
|
|
To accomplish the task, Facebook trained an ever-fashionable deep neural network on tens of millions of photos.
|
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A neural network could provide future rovers and deep-space probes with a better ability to make decisions.
|
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The secret, as with so many other interesting visual computing projects these days, is a convolutional neural network.
|
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But with the help of Perol and his colleagues' neural network, this important work could get a boost.
|
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The resulting neural network trained on this information could predict what a dog would do in certain situations.
|
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The researchers' model is based on teaching a neural network to make a differentiation between foreground and background.
|
|
The task for your neural network is to draw a border around all sheep of the same color.
|
|
By identifying the visual changes, theoretically, the neural network could then reverse engineers the correct sequence of steps.
|
|
A convolutional neural network is just the trick to tease out new and interesting results from that morass.
|
|
The team used a deep neural network to identify crooked 360 photos and reorient them to maintain realism.
|
|
In this case, the neural network being attacked was trained as an ImageNet classifier trained to recognize animals.
|
|
Over time, this neural network will learn from its mistakes and improve as more people play with it.
|
|
Training a neural network involves adjusting the neurons' weights so that a given input produces the desired output.
|
|
Suddenly, training a four-layer neural network, which had previously taken several weeks, took less than a day.
|
|
For the past two years Shane has trained a neural network to come up with Halloween costume suggestions.
|
|
A huge number of pictures are put through an artificial intelligence engine called a deep convolutional neural network.
|
|
For a neural network, images are images, and the data set they're trained on is all that matters.
|
|
Beyond that, AWS could discuss a data warehouse service for storing data that's intended for neural network training.
|
|
Indeed, the ultimate end game is taking a deep neural network and embedding it onto a single chip.
|
|
They then used those images to train a type of neural network known as Generative Adversarial Networks (GANs).
|
|
The end result of repurposing this bio-imaging technique to map a fruit fly's neural network was impressive.
|
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By analyzing millions of retinal photos, a neural network can learn to recognize early signs of diabetic blindness.
|
|
If a neural network sees the world in two dimensions, a capsule network can see it in three.
|
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These are a pair of neural network systems that can automatically generate convincing images or manipulate existing ones.
|
|
"ADR starts with a single, nonrandomized environment, wherein a neural network learns to solve Rubik's Cube," she said.
|
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This makes the task harder, since the neural network must now learn to generalize to more randomized environments.
|
|
He is known for his invention in 1982 of the associative neural network, known as the Hopfield Network.
|
|
First, it's not a fully trained neural network capable of besting human performance right out of the box.
|
|
The animal's neural network had not learned arithmetic; it had learned to detect changes in human body language.
|
|
A neural network — learning software that allows the robot to execute complex functions — enables it to navigate ladders.
|
|
It's an ontological question: Is the deep neural network really seeing a world that corresponds to our own?
|
|
Then the neural network was given new information, including a patient's symptoms as determined during a physical examination.
|
|
This likely will mean convening a group of leading AI experts, such as OpenAI, and establishing a standard that includes explicit definitions for neural network architectures (a neural network contains instructions to train an AI model and interpret an AI model), as well as quality standards to which AI must adhere.
|
|
A deep neural network was then able to decode, or translate, these patterns, allowing the system to reconstruct speech.
|
|
If the neural network gets it wrong, you send it back for more training (a process known as backpropagation).
|
|
Like a brain, a deep neural network has layers of neurons—artificial ones that are figments of computer memory.
|
|
The same tweak will foil a neural network regardless of the particular image that it's been tasked with classifying.
|
|
For some data sets and masking techniques, the neural network success rates exceeded 80 percent and even 90 percent.
|
|
The first way is to feed Google's neural network an image and ask it to look for something specific.
|
|
Previously, the development of a single neural network could take weeks or even months, depending on the hardware setup.
|
|
But the paper does also address the possibility of single-camera creation by way of another convolutional neural network.
|
|
Neural-network translation requires heavy-duty computing power, both for the original training of the system and in use.
|
|
Once the chip is tipped off by someone speaking, the neural network kicks into gear and gets to work.
|
|
Enter Samsung's new research, in which a neural network can turn a still image into a disturbingly convincing video.
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Television Let nature inspire us Our brain is a biological neural network, so companies are building artificial neural networks.
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Large scale neural network training and visual recognition are necessary for Level 4 and Level 5 autonomy, he said.
|
|
"The workings of the neural network are themselves quite abstract and hard to understand," Holden admitted in an email.
|
|
As you can see in the video below, it's the perfect surreal selfie-op for artificial neural network enthusiasts.
|
|
They have new analysis software and a nascent neural network tool to search for more varied types of signals.
|
|
Their measurements were used to train a neural network to tell the difference between normal and abnormal heart rhythms.
|
|
A research paper from January details how just how easy it is to trick an image recognition neural network.
|
|
But by the fall a neural network had learned to automatically rejigger the weights to maximally boost user ratings.
|
|
The company was one of the first to develop tools like "neural network learning" that are still buzzwords today.
|
|
Engineers then trained a deep neural network to identify these abnormal heart rhythms from Apple Watch heart rate data.
|
|
The neural network she uses is roughly equivalent to the brain of an earthworm in terms of neurons employed.
|
|
What's more, the new system is powered by four tensor processing units (TPUS)—specialized chips for neural network training.
|
|
SwiftKey recently launched an Android keyboard that uses a neural network instead of its standard algorithms when predicting words.
|
|
Then they ran those into two systems of artificial intelligence — machine learning and a deep recurrent neural network (RNN).
|
|
Pikazo users simply upload an image, apply the style, then wait as the neural network works its artistic magic.
|
|
There's built-in neural network training software, though many researchers and companies will want to roll their own solutions.
|
|
Ion relies on the deep neural network Eos and Atlas, a number of different modules designed for camera tuning.
|
|
In keeping with the open-source culture of neural network art, Kogan has posted instructions for style transfer technique.
|
|
So they did what any good 2018 coder would do: build a neural network that lets you do it.
|
|
Google has also used DeepMind's WaveNet neural network to generate the Google Assistant voices for US English and Japanese.
|
|
A neural network add-on that will let your HoloPic grow and change is available for an additional $9.99.
|
|
In 2000, Google's DeepMind demonstrated that a single neural network was capable of mastering several different Atari 2100 games.
|
|
Akiyama trained the neural network using 500 ASCII drawings taken from popular Japanese to message boards 5channel and Shitaraba.
|
|
Along with his recordings, Google utilized its WaveNet deep neural network technology to fine tune Legend's voice for Assistant.
|
|
AutoDraw uses similar technology to the puppyslug-generating Deep Dream neural network to act as a spellcheck for sketches.
|
|
Pat's approach of combining role and reference grammar (RRG) with a neural network is just one of those approaches.
|
|
Second is a computationally cheap neural network that uses way more signals than the simple topical similarity mentioned above.
|
|
SAN FRANCISCO — In 2004, Geoffrey Hinton doubled down on his pursuit of a technological idea called a neural network.
|
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By analyzing thousands of eye scans, for instance, a neural network can learn to detect signs of diabetic blindness.
|
|
By pinpointing patterns in thousands of dog photos, for instance, a neural network can learn to recognize a dog.
|
|
In the first iteration of the study, he and the team had started with a totally naïve neural network.
|
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Feed millions of cat photographs into a neural network, for instance, and it can learn to recognize a cat.
|
|
The neural network "I started researching when I was in my second year of high school," she told CNN.
|
|
The neural network detected AFib at an accuracy rate of 97%, with sensitivity of 98% and specificity of 90%.
|
|
According to this paper, Apple has had to train its neural network to detect faces and other objects on photos.
|
|
A neural network called " Nightmare Machine ," introduced by MIT computer scientists in 2016, transformed ordinary photos into ghoulish, unsettling hellscapes.
|
|
Shane noted that not all of the words produced by the neural network were originally found in the dataset provided.
|
|
The online tester will give you detailed feedback on your password based on a neural network of millions of samples.
|
|
The neural network learns from the dataset and imitates the language to generate its own version of candy heart messages.
|
|
Assigning numerical values to the survey let the researchers refine their neural network so it tracked alongside how people felt.
|
|
A convolutional network is a specific kind of neural network well suited to identifying images and sensing patterns in them.
|
|
They collaborated to create this interactive data-visualization that lets users toy around with and design their own neural network.
|
|
"I used Andrej Karpathy's char-rnn, an open-source neural network framework for torch (written in Lua)," Shane told Gizmodo.
|
|
Because that neural network is trained to look for buildings in an image, it spat back a squat, green building.
|
|
When taking that second approach, what the neural network will produce depends on how many layers the image goes through.
|
|
So he and his colleagues designed a neural network that spat out Yelp-style blurbs of about five sentences each.
|
|
The resulting images instead reflect how the background neural network powering the camera interpreted the scene coming through the lens.
|
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The Assistant uses a neural network to analyze the trigger phrases "Ok Google" and "Hey Google" to detect voice characteristics.
|
|
Mark Sullivan Portal's AI has a good deal of film-industry knowledge embedded into the layers of its neural network.
|
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He was the first person to propose that a neural network could learn through implicit learning the way humans do.
|
|
Google's search engine relies heavily on a neural network algorithm that millions of workers are using to perform their job.
|
|
The technology at the heart of this research here is a neural network trained on a dataset of recorded negotiations.
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This is where the final step comes in of "hallucinating" the remainder of the image via a convolutional neural network.
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It is an unfortunate side-effect of the underlying neural network caused by the training set bias, not intended behaviour.
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The trick was to take these recordings and train a machine-learning program, called a neural network, to interpret them.
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A man named Andy Herd fed all of the scripts from the TV show Friends into a recurrent neural network.
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Instead, the sensors inside Tesla vehicles lean on a neural network that's trained by data collected by all Tesla vehicles.
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"What inspired me was I found a post online from someone who'd done neural network cookbook recipes," she told Gizmodo.
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In fact it'll it process up to 2,800 images per second using a neural network-based algorithm to do that.
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"I felt like the first ever film remade by a neural network had to be Blade Runner," Broad told Vox.
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The neural network then labels each sheep with a color and draws a border around sheep of the same color.
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At that developmental period, weaker brain connections are eliminated, leaving a more efficient and more specialized neural network, she said.
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When images of vehicles were flipped over, the deep neural network misclassifed them as "shopping basket"Image: Alcorn et al.
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It's highly possible that this has been an elaborate publicity stunt to promote his company's AI and neural network technologies.
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The results from different algorithms will typically converge, as Cole found when he compared his GPRs to the neural network.
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Head trauma affects the brain's anticipatory neural network which guides human reactions and the tool focuses on analyzing visual response.
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The AI — a neural network — learned to identify planets from 15,000 Kepler signals that had already been labeled by scientists.
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From there, Microsoft employees contributed to the knowledge of the neural network by confirming that tags of photos were correct.
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My favorite example is "How to trick a neural network into thinking a panda is a vulture" by Julia Evans.
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The team started with an existing convolutional neural network architecture, previously trained on 1.28 million images from the ImageNet dataset.
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Just a week later, company researchers announced they training a neural network to edit the photos and improve their stitching.
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Nvidia's Ian Buck standing next to a Big Sur-trained neural network creating art based on more than 12,000 paintings.
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Training a neural network involves adjusting the neurons' weights so that a given input produces the desired output (see diagram).
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The system started with a neural network, which is an arrangement of small computing elements called neurons connected in layers.
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She gives the neural network a long list of what she wants it to imitate, such as names of snakes.
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It's done with a neural network that consumed millions of data points on items, arrangements, and attempts to grab them.
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Stein believes these images will "tune" Anki's neural network, which Vector can then use to better spot detect furry friends.
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In 2016, Google successfully reduced its data center cooling energy use by 40 percent with the "deep mind" neural network.
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Check out this tool based on Chainer, a flexible neural network framework that can support a number of different uses.
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And when that happens, the neural network is ready for prime time and can start identifying apples in pictures professionally.
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That's what I think is powerfully evocative about Auto-encoding Blade Runner—that synthetic leap that the neural network makes.
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At the receiving end, researchers took images of the wall-projected beam and then fed them into their neural network.
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The neural network learned to identify these by using signals that had been vetted and confirmed in Kepler's planet catalog.
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By looking for patterns in millions of dog photos, for example, a neural network can learn to recognize a dog.
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In CLEVR, a neural network would be presented with a suite of simple objects, such as pyramids, cubes and spheres.
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It is an unfortunate side-effect of the underlying neural network caused by the training set bias, not intended behavior.
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The Stanford researchers have developed a system named Genie that simplifies the task of training a so-called neural network.
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This approach takes a lot of computing power up front to generate realistic clouds for the neural network to imitate.
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By looking for patterns in thousands of dog photos, for instance, a neural network can learn to recognize a dog.
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His latest work deals heavily with the neural network, a computer system modeled on the human brain and nervous system.
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But a neural network pretrained with word embeddings is still blind to the meaning of words at the sentence level.
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The result is what Abbeel calls "the Covariant Brain" — a nickname for the neural network shared by the company's robots.
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Advances in machine learning have been made by training a computerized mimic of a neural network on a given task.
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The advantage of a machine learning model is that once a neural network is trained, solutions are delivered almost immediately.
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After training a neural network in the data center, the company runs this algorithm on chips installed on the car.
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As a neural network system, the platform will continue to "learn," tracking any human input to use with future scans.
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Within the sprawling community of neural network development, there is a small group of mathematically minded researchers who are trying to build a theory of neural networks—one that would explain how they work and guarantee that if you construct a neural network in a prescribed manner, it will be able to perform certain tasks.
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Now before I dive into self praise, some context: After the first debate, we did a small experiment based on a random sampling of social media posts using labelled data feeds, a CNN (convolutional neural network; a feed-forward artificial neural network), a Bayesian methods-based network and a variant of word210vec-like algo.
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What the cat paper demonstrated was that a neural network with more than a billion "synaptic" connections — a hundred times larger than any publicized neural network to that point, yet still many orders of magnitude smaller than our brains — could observe raw, unlabeled data and pick out for itself a high-order human concept.
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When images are uploaded to eBay, it uses a deep learning model called a convolutional neural network to process the images.
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The second step is to make the neural network learn the dynamics of the evolving flame front from the input data.
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The researchers trained a neural network on more than 131,000 mainshock–aftershock pairs, then selected unrelated 30,000 pairs for a test.
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When this happens, the part of the neural network with the pretrained model will give the generator a small thumbs up.
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Basically, after feeding the neural network images of simulated galaxies, the researchers were able to get useful information about real galaxies.
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The so-called neural network can sense people&aposs postures and movement even from the outside of a building or room.
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The intent is that the generative neural network will produce a superior result by bouncing its ideas off its adversarial counterpart.
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Then, they gave the neural network a binary task: to tell them which files in Kepler's terabytes of data contained exoplanets.
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The new designs benefit from an improved branch predictor that uses neural network algorithms to improve data prefetching and overall performance.
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That's why full-stack software engineer Zack Thoutt created a neural network to write speculative chapters of the much-anticipated novel.
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It scrapes the web for pictures of faces, and then it morphs their expressions using a deep-learning-powered neural network.
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"We use a deep learning model called a convolutional neural network to process the images," eBay said in a blog post.
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Once a neural network has learned the defining characteristics of a particular artist, it can "transfer" them to a new image.
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Neural networks currently have an issue on objects it was trained on and what the neural network is trained to do.
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Apple's VoxelNet basically compresses these processes into a single neural network, resulting in a system that's more efficient than its predecessors.
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Their device, called Intuition-1, is controlled by a neural network, a form of artificial intelligence modelled on the human brain.
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The company has also developed a customized convolutional neural network to detect objects of interest and label them with bounding boxes.
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Via neural network classification, the Stanford researchers were able to calculate gravitational lens parameters like ellipticity, Einstein radius, and lens center.
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In terms of the core tech, Moiseenkov says the team is using neural network/deep learning algorithms to process the photos.
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Once the element is placed, GauGAN reaches into its neural network and fills in the details to create a beautiful picture.
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Google showed the neural network things like color, texture and style preferences from more than 13793883 fashion experts to train it.
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Then, the neural network fills in the necessary blanks to create just one second of video, seen here as looping gifs.
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So next time you see a photo preview on Twitter that invites you to click remember to thank a neural network.
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Next-generation technology, however, will introduce more efficient chip architectures designed expressly for deep neural network computation rather than graphics processing.
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And a neural network might find those squiggly lines in unexpected places — in someone's haircut, for example, or a rumpled blanket.
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So if you have a specific task in mind, how do you know which neural network architecture will accomplish it best?
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Instead, it employs a neural network so it can skip the intermediate step of translating audio to text and back again.
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ALVINN, which stands for Autonomous Land Vehicle In a Neural Network, was used as a test vehicle well into the 1990s.
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It uses a type of machine learning called a neural network, which is trained to recreate the styles of famous artists.
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"We had no insight into what data the neural network was triggering off in order to make better predictions," Fernandez said.
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While the player doodles, the neural network throws out its best guesses of the subject, stopping mid-sketch if it's correct.
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First, we'd take a neural network and program different layers to identify different elements of a cat: claws, paws, whiskers, etc.
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Herd create a neural network using Google's open source machine learning software TensorFlow and fed it a bunch of Friends scripts.
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This imagery is the work of computer scientist Gabriel Goh, who created a neural network that mashes together two existing programs.
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The software lets users choose from a variety of neural network architectures and then monitor the utilization of available computing resources.
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It involves training a neural network to interact with an environment with only occasional feedback in the form of a reward.
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Standardizing what the ideal neural network architecture should be is somewhat difficult, as some architectures handle certain tasks better than others.
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After training with this vast collection of English, the neural network has presumably learned some useful things about language in general.
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And when the team plugged this neural network into the two-armed robot, it could do the same with physical objects.
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By looking for common patterns in millions of bicycle photos, for instance, a neural network can learn to recognize a bike.
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GPT-2 uses a newly invented neural network design called the Transformer, invented 18 months ago by researchers at Google Brain.
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The neural network compares the data it outputs with the targets and updates the network learns to better mimic the targets.
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The researchers propose training a neural network to power the photo development process that happens inside cameras, so as the sensors are interpreting the light hitting the lens and turning it into a high quality image, the neural network is also trained to mark the file with indelible indicators that can be checked later, if needed, by forensic analysts.
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Take, for example, image recognition, which relies on a particular type of neural network known as the convolutional neural network (CNN) — so called because it uses a mathematical process known as convolution to be able to analyze images in non-literal ways, such as identifying a partially obscured object or one that is viewable only from certain angles.
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The authors of an April paper on generating poems from photographic images conclude that—even when you activate two discriminative networks that train a recurrent neural network, and link them to a deep coupled visual-poetic embedding model consisting of a skip-thought model, a part-of-speech parser, and a convolutional neural network—writing poems is hard.
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Let's say you've built a neural network consisting of thousands of GPUs, each of which has thousands of cores — essentially, a supercomputer.
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The researchers took 4,800 of these tweets, which were "handcoded for moral content," and used them to train a deep neural network.
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This neural network generates an internal impression, or visual roadmap, of an object following a brief visual inspection (typically around 20 minutes).
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As it sifted through the screenshots, the neural network — just like many human YouTube users—developed a fascination with pictures of cats.
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Photo: Leon Neal (Getty)Artificial Intelligence researchers used a neural network to create fake fingerprints that could be a hacker's dream tool.
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The researchers were able to compile a dataset of more than 6,000 optical illusion images that they gave to a neural network.
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For this research, the CSAIL researchers trained their neural network on photos of people doing regular activities like walking, sitting, and talking.
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It relies on an artificial intelligence convolutional neural network to detect how your face moves and map it to a specific emotion.
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Founded in summer 2016, Fabby's platform is based on the neural network to be found under the hood of the modern smartphone.
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The utility of a neural network (and machine learning, in general) is in its ability to make generalizations from large data sets.
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Then, the swap happens, with a neural network synthesizing video of the target individual based on the stick figure movements of source.
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More bullshit coming from Silicon Valley, but any kid, right, can make that effort and learn how to create a neural network.
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At this point in time, it wouldn't be feasible to smash an entire deep neural network (DNN) onto such a small processor.
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The researchers didn't tell the neural network exactly how to spot the different species — the AI figured that out on its own.
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An artificial neural network is a machine-built simulacrum of the functions carried out by the brain and the central nervous system.
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On Wednesday, Carter's team released a paper that offers a peek inside, showing how a neural network builds and arranges visual concepts.
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With minimal preprocessing, they were fed into the neural network, which, after training and testing, generated its best estimates of brain age.
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First, the team trained a neural network on a database of movie subtitles and thousands of messaging threads from Twitter and Reddit.
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ALVINN's neural network was "beautifully implemented, but constrained very much so by the hardware," Cameron wrote in a subsequent post on Medium.
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An artificial intelligence engine, also known as a neural network, is a computing system that can learn and adapt based on inputs.
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This allowed the system to improve and refine its digital brain, known as a neural network, as it continually learned from experience.
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The screenplay is a product of Benjamin being trained on a strict diet of sci-fi scripts via a recurrent neural network.
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To wit: They've created a benchmark system for assessing the performance of several major neural network architectures used for common AI tasks.
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Duplex operates through a complex combination of speech to text, text to speech and Google's own WaveNet audio processing deep neural network.
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The researchers trained the deep neural network on millions of educational YouTube clips with over 100,000 different speakers, according to the paper.
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Researchers created what is essentially an eye-tracking system for a neural network, which records which pixels the computer looks at first.
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The app leverages a neural network (LSTM – Long Short Term Memory) and LSI (Latent Semantic Indexing) to suggest responses to user requests.
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This time, the results aren't just visual, though the animal-based neural network aesthetics are still here and more phantasmagorical than ever.
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Then, the system analyzes the segmentation map with a second neural network, and identifies signs of disease using a separate classification network.
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"It's a neural network imagining what a gazebo or butte looks like," said Mr. Kogan, a resident scholar at New York University.
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In 1989, Carnegie Mellon pioneered a neural network called ALVINN that could be employed in road following tasks in certain field conditions.
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The site uses a neural network to produce the audio and it sounds so much like Jordan Peterson that it's downright spooky.
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Once a neural network is trained for a task, it must perform it, and that requires a different kind of computing power.
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Its first product, which uses a deep-learning convolutional neural network (CNN) to analyze medical images, will apply for regulatory approval soon.
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The subsequent readings showed that the safety signal strategy activated a completely different neural network in humans and mice than behavioral therapy.
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Deep learning "trains" a computer program known as a neural network to look for certain patterns in a large number of images.
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Like LSD and mushrooms, it could lead to neural network reorganization resulting in foggy headedness and flashbacks after excessive, long-term use.
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The Stanford team trained a neural network with data from 200,000 motion samples, including test drives on slippery surfaces like snow and ice.
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The car performed similarly running both the learned and physics-based systems, even though the neural network lacked explicit information about road friction.
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The team says they were encouraged by the results, but stress that their neural network system does not perform well in any environment.
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It relies on a neural-network framework that can anticipate people's movements and change the configuration of a crossing or buffer zone accordingly.
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Your job is to determine if a line is actually from the Bible, or if it's just nonsense generated by a neural network.
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Text that has a verb with an out-of-place "-eth" is probably the neural network trying to speak like an ancient writer.
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This made me wonder: is it disrespectful to "train" a neural network on the Bible, or use them to produce fake religious texts?
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That would involve scanning a brain (possibly destructively), reconstructing the neural network from the scan, and running the simulation on a suitable computer.
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To make this work, Macnish drew on Google's object recognition neural network and the data set created for the game Google Quick, Draw!
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After all, this study alone involved a neural network-trained algorithm using an automated process to detect whether automated Twitter bots were real.
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Earlier studies used eye aspect ratio (EAR) or a convolutional neural network-based (CNN) classifiers to detect if eyes were open or closed.
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Just this week, a team debuted an AI-generated film which required training a neural network on screenplays and videos, Ars Technica reported.
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First, songs are converted into spectrograms — visual representations of audio frequencies, which the neural network uses to identify features like pitch and rhythm.
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The detection algorithm involved is a version of a program called a neural network, a type of software adept at signal-recognition tasks.
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OpenAI then has its vision network — a type of neural network trained on a hundreds of thousands of simulated images — observe the action.
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The filter was swiftly deleted, and FaceApp's CEO, Yaroslav Goncharov apologized for what he told The Guardian was an "underlying neural network" failure.
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Essentially, a multi-layered (ie, "deep") neural network is shown images of a particular face, taken from different angles and with different expressions.
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A neural network will try to infer the colors that likely work best in the photo – like turning the grass green, for example.
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A neural network trained by Google to identify everyday objects was recently tricked into thinking a 3D-printed turtle was actually a gun.
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NSynth Super utilizes Magenta's NSynth, Google's neural network that generates sounds, and directions for building your own NSynth Super are available on Github.
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Once they'd trained a neural network to identify these areas, they needed to optimize it to work in real time on the site.
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Now a freshman in computer science at the University of Georgia, Shaza Mehdi trained a neural network to identify plant diseases on sight.
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Coy and crafty, she had large luminous eyes that reflected the electric thoughts of her neural network and an alluring smile to match.
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Using thousands of hours of TV footage from the BBC, scientists trained a neural network to annotate video footage with 46.8 percent accuracy.
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It's pretty tricky at first, but it's a great way to understand, at an abstract level, how neural network systems sort through information.
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Google has its neural network to make this a possibility, and it's not clear if Amazon is currently able to add something similar.
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Remember when an AI researcher tried to train a neural network to invent new names for paint colors and it went hilariously wrong?
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One of the better-known examples is a neural network created by Google that was fed random YouTube thumbnails from 10 million videos.
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You can check out the entire list, based on the work of the neural network and "data science and machine learning teams," below.
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After that, it was a question of feeding examples of heart MRIs into the neural network and letting it work out the solution.
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The app uses deep learning, or an artificial neural network composed of many layers, to transform the photo into a work of art.
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Part of the app's appeal is the fact that it uses sophisticated neural network processing, or deep learning algorithms, to process the photos.
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Within the community, the word "deepfake" itself is now a noun for the kinds of neural-network generated fake videos their namesake pioneered.
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An image-processing neural network, for example, can be made to highlight the regions of an input image which most influenced its decision.
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Suggesting a neural network writ large, the objects overhead also seem downright heavenly — constellations in the night sky, celestial bodies orbiting on high.
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The visual and tactile information Baxter gathers is sent to a deep neural network, where it's cross-referenced against images in the ImageNet.
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"There is even recent evidence that the representations it finds are not too dissimilar from those discovered by a neural network," Hewitt notes.
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By analyzing millions of retinal scans showing signs of diabetic blindness, a neural network can learn to identify the condition on its own.
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He and his graduate students used a neural network to run an earthquake analysis 500 times faster than they could in the past.
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So, Mr. Eck and his team have fed notes from hundreds of instruments into a neural network, building a vector for each one.
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For a simple artificial neural network of the sort proposed in the 1940s, the attempt to even try to replicate this was unimaginable.
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These kinds of manifolds have no "global" symmetry for a neural network to make equivariant assumptions about: Every location on them is different.
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Dactyl figures out how to manipulate something using reinforcement learning, which trains a neural network to control the hand based on extensive experimentation.
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For it, artist Orestis Herodotou fed macro images of biological lifeforms and satellite images of rivers and mountain ranges into a neural network.
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Success will involve full transparency of the process and not blind faith that a single "black box" deep neural network will work correctly.
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Alexa will switch between languages, and employ new natural-sounding voices modeled using neural network processing to provide more realistic and expressive responses.
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"We expect NVDA to begin shipping its next-gen Volta GPU architecture optimized for neural network training [artificial intelligence] in 3Q17," he wrote.
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DeepNude failed entirely with some photographs that used weird angles, lighting, or clothing that seem to throw off the neural network it uses.
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Infrared image, left, and output of the neural network highlighting areas of interest Infrared image, left, and output of the neural network highlighting areas of interest This footage was then put through a deep learning system trained to recognize the size and intensity of the heat put out by a koala, while ignoring other objects and animals like cars and kangaroos.
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They created a neural network that can enable driverless cars to perform high-speed, low-friction maneuvers just as well as race car drivers.
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He tried an experimental technique to automatically tune its software, which was based on a machine learning technique less complex than a neural network.
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This has enabled the company to create neural network-powered art filters that work on users' phones, transforming photos and videos on the go.
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To train Pythia, the researchers converted the world's largest digital collection of ancient Greek inscriptions into a format that their neural network could understand.
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As first reported by Business Insider, researchers from the University of Chicago have trained a neural network that can churn out convincing fake reviews.
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In addition, a neural network that is trained to spot and resist spoofing defends against attempts to unlock your phone with photos or masks.
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Once trained, Dr Tromer's neural network can identify films with up to 99% accuracy, based on a fingerprint between one and five minutes long.
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First, we need to download VGG16, which is a 16-layer convolutional neural network that's about the state-of-the-art in image recognition.
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Facebook collaborated with Microsoft last year to create the Open Neural Network Exchange (ONNX) which was designed to make movements between frameworks more simple.
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After having been trained, the neural network was able to identify faces, objects and handwritten text with accuracy rates as high as 90 percent.
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Nvidia's new neural network requires a lot of computing power to generate these videos, and most people don't have access to that many GPUs.
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The different parts of the neural network appear on-screen as boxes (called "lobes," naturally), which are joined together by lines like a flowchart.
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It's like a simpler version of Swiftkey's neural network predictive keyboard, only trained in mild racism and abuse rather than your weekly grocery list.
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Related: Lose Yourself in the Eerie GIFs of DarkAngelØne Stereoscopic GIFs Get Trippy Makeovers with Neural Network Imaging Uh Oh, 3D GIFs Infiltrated Reality
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A month ago, Yahoo launched an open-sourced neural network, called "open_nsfw," that rates images on a scale of 0 (SFW) to 1 (NSFW).
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Appropriately, the Files Go team also made a Bad Joke detector, which uses "the first fully decentralized deep neural network" to identify terrible jokes.
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Let's Enhance is an Estonia-based startup that's using a so-called 'hallucinating AI' deep neural network to power a freemium photo upscaling service.
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Broad wanted to teach an artificial neural network how to achieve this video encoding process on its own, without relying on the human factor.
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By inserting a postage-stamp image of a baseball, they found they could confuse the neural network into thinking a whale was a shark.
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The final data set was then used to train a neural network that could predict the depth of a moving object in a video.
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The neural network was designed such that cities with greater distances between them are more likely to be illuminated than channels that are not.
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Just one example is the neural network fine-tuning technique of backpropagation, which was invented in the 1980s but only became really useful recently.
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But it also has what Yandex dubbed "a neural network based 'chit-chat' engine" to allow Alice to have "free-flowing conversations about anything".
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What happens when you feed a neural network some movie scripts, give it a few props and instruct it to write a movie script?
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Certain curves, certain dark spots, certain proportions – the subtle reasoning of the neural network mirrors our own intuitive recognition of familiar shapes and colors.
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Photo: APSoon after Mike Schroepfer was promoted to Facebook CTO, he began recruiting top neural network researchers to build up the company's AI capabilities.
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"I think eventually, given enough data, a big enough neural [network] can be teased into dreaming up many different kinds of scenarios," Wang added.
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But you can't apply the same type of attack on a biological neural network (read: a living creature) that you can on a machine.
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Google researchers solved that problem by incorporating neural network technology, building "value networks" to evaluate board positions and "policy networks" to evaluate individual moves.
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Basically, like other local explanation methods, CEM tries to tell you why a certain neural network has classified your input in a particular way.
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She used the ofxCcv library, which reads each image and labels it using a trained convolutional neural network, according to similarities in the images.
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The artistic process uses the same neural network idea as that which was used by Google Photos to identify images in its search function.
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The winning entry used a so-called convolutional neural network, a form of deep learning designed to emulate the way vision works in animals.
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However, the neural network setup required far less manual configuration and monitoring, and could be more easily extended for deployment on different social networks.
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AliveCor built a deep neural network using EKG results from more than 1,000 patients with congenital LQTS and more than 1,000 patients without it.
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Source: GumGum Source: GumGum So, in its early stages, the neural network spits out a bunch of wrong answers in the form of percentages.
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It is based on the same neural network tech that powers Google's voice search in the Google app and voice typing in Google's Keyboard.
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Melee last year—but it is the first one trained completely on a neural network through reinforcement learning, which closely resembles how humans learn.
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The two researchers built what is called a neural network, a complex mathematical system that can learn tasks by analyzing vast amounts of data.
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And, as the two researchers showed, a neural network can learn to write phishing messages by inspecting tweets, Reddit posts, and previous online hacks.
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By analyzing a database of old customer support phone calls, for example, a neural network can learn to recognize commands spoken into a smartphone.
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An artificial neural network could do something similar, by gradually altering, on a guided trial-and-error basis, the numerical relationships among artificial neurons.
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In 2016, Cohen and Welling co-authored a paper defining how to encode some of these assumptions into a neural network as geometric symmetries.
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But for physicists, it's crucial to ensure that a neural network won't misidentify a force field or particle trajectory because of its particular orientation.
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Bowman points out that it's hard to know how we would ever be fully convinced that a neural network achieves anything like real understanding.
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Training data, such as images or audio, are fed to a neural network, which is gradually adjusted until it responds in the correct way.
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Call it the Hamlet strategy: lending a deep neural network the power of internal monologue, so that it can narrate what's going on inside.
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Olah has been working for the last couple of years on creating new ways to visualize the inner workings of a deep neural network.
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Still, this is an enormously difficult task because of the need to run the multiple layers of a convolutional neural network in real time.
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After training the neural network on this large corpus of statements with metadata, it was then given another 1,000 statements from the quote corpus.
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The island map reflects light only in pieces, suggesting a neural network of floating-yet-connected ideas and emphasizing the sense of ordered chaos.
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In 2011, Caltech bioengineer Lulu Qian created the first artificial neural network out of DNA, but it could recognize only a handful of patterns.
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Prisma, the photo app that applies neural network magic to photos for a wide variety of artistic effects, now also works with 15-second videos.
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The systems reads the map, matches it against the stored image on the phone using a built-in neural network processor, and unlocks the phone.
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Working with researchers from Massachusetts General Hospital, Dina Katabi and her team from MIT used an artificially intelligent algorithm known as a deep neural network.
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Prisma, the mobile app that turns your photos into artworks through neural-network magic, has received what its founders call the biggest update so far.
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If a neural network is studying pictures, it might start by discovering the concept of "edges," sorting out all the edges from the non-edges.
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But the second, perhaps more fun, way to use inceptionism is to feed the neural network an image and let it decide what it sees.
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Schmitt also included a "confidence" number below each image caption, which represents, as a percentage, how certain Microsoft's neural network was of the caption's accuracy.
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We also trained a separate neural network that uses all distances in aggregate to estimate how close the proposed structure is to the right answer.
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Tech Crunch reports from CES that in reality that means it can process up to 2,800 images per second using a neural network-based algorithm.
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In this case, a neural network is trained using recordings and transcripts of someone speaking, so that it learns how they map words onto sounds.
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The list was generated by training a neural network on thousands of band names, and includes must-see acts like "Horse Choir" and "Man Mist".
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For instance, Tesla's new cutting-edge neural network chips, which are a critical piece of Autopilot 3.0, are being made by Samsung in Austin, Texas.
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Swiftkey is best known for its iOS and Android keyboards, which use artificial intelligence (and even a neural network!) to generate predictions that actually work.
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This morning at the WSJ's D.Live event, Intel formally unveiled its Nervana Neural Network Processor (NNP) family of chips designed for machine learning use cases.
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So Erik Bernhardsson decided to see what would happen if he threw 50,000 fonts at a neural network and left it to chew at them.
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This memory sprang to mind with the recent news that the Google Translate engine would move from a phrase-based system to a neural network.
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But researchers at MIT are using GAN to do the holy, blessed work of building a neural network to teach computers how to make pizza.
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Humans helped the neural network refine its over 1,000 suggestions, and ultimately three games were physically tested before AKQA chose Speedgate and finalized its rules.
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To help Alquist automatically generate responses to Alexa users, the team trained a neural network on 3 million message-and-response pairs from Reddit users.
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Specifically, the gig entails building a biological neural network that is trained to classify images and then trying to fool it to misclassify the images.
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Companies will be able to leverage this network, but Nvidia also insisted in saying that car makers would want to control their own neural network.
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The method involves inserting software probes in the various layers of a neural network and monitoring its behavior as it trains on examples and evolves.
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The MIT team made Shelley by training "a neural network of 140,000 horror stories from the r/nosleep subreddit," a collection of original scary stories.
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Using TensorFlow and Theano, you'll learn how to build a neural network while exploring techniques such as dropout regularization and batch and stochastic gradient descent.
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"The neural network of technological advances has made it possible for a multitude of creative solutions and innovations to improve our world," says Dr. Hussein.
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Japan's National Science Museum unveiled a new exhibit last month: a creepy-looking robot that's powered by 42 pneumatic actuators and its own neural network.
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A neural network is then used to compare this scan with an initial scan provided by the user to determine a match and prevent spoofing.
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Researchers from Portugal have had enough, though, and built a neural network that tries to determine whether you or your virtual interlocutor is being sarcastic.
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DeepMind's artificial intelligence technology relies on a "deep neural network" made up of layers of connections, referred to as nodes, which sort through sensory information.
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If you've ever fed photos into Google's trippy DeepDream program or had Facebook automatically tag your friends in a photo, you've encountered a neural network.
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In a way this "diffractive deep neural network" is a lot like that: it uses and manipulates physical representations of numbers rather than electronic ones.
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Among other things, the service offers a drag-and-drop neural network builder that allows even non-programmers to configure and design their neural networks.
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Earlier this week, research scientist Janelle Shane posted the results of an experiment where a neural network generated some less-than-appealing paint swatch names.
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That's exactly what Charles, programmer Harrison Kinsley's self-driving neural network (a computer program that teaches itself to estimate things using input data), does best.
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In the backend, YouTube's sound captioning system is based on a Deep Neural Network model the team trained on a set of weakly labeled data.
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For example, to train a neural network to identify pictures of apples or oranges, it needs to be fed images that are labeled as such.
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Loosely based on the web of neurons in the human brain, a neural network can learn tasks by identifying patterns in vast amounts of data.
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Janelle Shane, a research scientist and blogger, recently worked with one of her readers to train a neural network to come up with fake ailments.
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How can the minutiae of unemployment insurance compete for attention with movies describing the birth of Skynet, the diabolical neural network in the "Terminator" series?
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He and his students soon moved to Google, and the mathematical technique that drove their system — called a neural network — spread across the tech world.
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When the team fed these models into a neural network, it learned to identify a similar point on potentially any digital object with any shape.
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The neural network that found structurally new types of drugs did so without knowing any human-identified patterns in how various molecules tend to function.
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It then utilizes another deep neural network to determine if the detected eye is open or close, using the eye' appearance, geometric features and movement.
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"This bidirectionality is conditioning a neural network to try to get as much information as it can out of any subset of words," Uszkoreit said.
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And thanks to a neural network it will one day share with its fellows in warehouses around the world, anything it learns, they'll learn, too.
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If deep learning could generalize, we'd have had L5 self-driving in 2016, and it would have taken the form of a big neural network.
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You're gonna be sort of a plug-in neural network as a human being that is performing some tasks that right now the robots can't.
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DeepHeart is an artificial neural network — a form of AI — that uses heart rate and step count data collected by wearables to detect medical conditions.
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"With a vanilla neural network you take a set of input data, pass it through the network, and get a set of outputs," said Thoutt.
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According to Motherboard, researchers in Cambridge trained deep neural network algorithms, similar to Google's Deep Dream program, to recognize certain features from conventionally scary images.
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Last Wednesday, researchers at Caltech announced that they created an artificial neural network from synthetic DNA that is able to recognize numbers coded in molecules.
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After isolating individual sound units (known as phonemes) from the recordings, the companies then used the neural network to choose the best examples to stitch together.
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In Altered Carbon this is achieved by having a cortical stack implanted, presumably constantly scanning the brain neural network using some form of nanotechnological fiber network.
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Just when you thought the neural network fad had fizzled, the New York City skyline transforms into a vibrant expressionist painting, and it all begins anew.
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A neural network was set loose on this trove of data, seeking out patterns and connections between images of food and the matching ingredients and recipes.
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When given a collection of labeled data, it builds a neural network layer by layer, testing each addition to the design to ensure it improves performance.
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By running these GIFs through the neural network Pikazo, the artists are creating trippy stylistic mashups which flicker in a new type of psychedelic neural animation.
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The video features three examples of a trained deep neural network trying to understand images coming from a live webcam, based on what it's seen before.
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Blocky noise is automatically removed and some neural network smarts are applied to imagine missing parts of the picture and enlarge it in a smoother way.
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Finally, the images produced from both neural network training sessions are then composited together to create the best approximation of what the original image might be.
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The chatbot uses a neural network to hold an ongoing, one-on-one conversation with its user, and over time, learn how to speak like them.
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Back in November, Google released artificial intelligence experiment that asks you to draw a random object and see if the neural network can identify your doodle.
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Related: Swirling GIF Illusions Look Like the Universe Breathing Lose Yourself in the Eerie GIFs of DarkAngelØne Stereoscopic GIFs Get Trippy Makeovers with Neural Network Imaging
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An infrared hi-def camera captures everyone's motions and faces, and the resulting data — 16 million or so data points — was fed to the neural network.
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This does exactly what it says on the tin: feeding a generative neural network with a bunch of faces and getting it to create similar samples.
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In its latest paper, the Facebook AI Research (FAIR) team dropped some impressive results for its implementation of a modified convolutional neural network for machine translation.
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Some traitors to the species at Carnegie Mellon have applied the ever-applicable neural network approach to create an AI that is literally a killing machine.
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For now, Nvidia's new neural network will probably just be a way for companies to create realistic virtual worlds without as much expense or human effort.
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The team has built a Recurrent Neural Network which takes in a number of data sources to predict what the person behind the wheel might do.
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The team says the deep neural network picked up on the trail 85 percent of the time, while humans nailed it 82 percent of the time.
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This means that even the designer of a neural network cannot know, once that network has been trained, exactly how it is doing what it does.
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It uses what's known as a convolutional neural network to perform its party trick, having been trained on a set of over a million color images.
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DLSS is a method that uses Nvidia's supercomputers and a game-scanning neural network to work out the most efficient way to perform AI-powered antialiasing.
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The main component is a recurrent neural network, a type of program that's particularly good at learning to mimic sequential data, such as writing and music.
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To create the software, engineers trained a neural network on a database of paired faces, containing images both before and after they'd been edited using Liquify.
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Mehdi was particularly inspired by a YouTube video starring a Stanford researcher who built a neural network that rivals board-certified dermatologists at identifying skin cancers.
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Roscoe is no AI expert, but his creation uses neural network software similar to what Waymo's street-legal autonomous minivans rely on to perceive the world.
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This reinforcement learning strategy, which was used extensively by AlphaGo as well, has its roots in psychology: the neural network learns from rewards like humans do.
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In this case, it's all being done by one super-efficient neural network that knows and can combine dozens of styles based on lower-level features.
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How RISE works: It randomly obscures parts of an input image, running them through the neural network to observe how the changes affect the output weights.
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Effectively, the engineers were willing to trade some of the accuracy of the neural network for full visibility and control on how the prediction software worked.
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For example, in a research project from Google, a neural network was used to generate a picture of a dumbbell after being trained on sample images.
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It's also why, when the framing of an alligator swimming was slightly altered, the neural network classified it as a cliff, lynx, and a fox squirrel.
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By 2012, the Hinton-led program came up with a deep learning neural network algorithm that performed more than 40 percent better than what came before.
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Lobster's artificial intelligence engine kicks in by analyzing these images, building a neural network and enabling detailed search methods, thus enabling the discovery of your work.
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At the end of each day, the robots' experiences were sent to a neural network, which was then hooked up to the robots the next day.
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A neural network can quickly learn about a simple concept, but it is dependent on the data that us humans feed it, for better or worse.
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Like most AI systems, the new Semantic Scholar relies on a neural network—a computer architecture inspired by the way real neurons connect to each other.
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Together the pair used 15,000 NASA data points to create a neural network, or artificial intelligence organized in a similar way to neurons in the brain.
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Using one of Google's image recognition algorithms, the teams says they were able to train the neural network to identify both malignant and benign skin lesions.
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Conceptually speaking, you are training the neural network as to what a purpose and a mechanism look like, which is a lot harder than it looks.
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Deep Speech, which debuted in December 2015, is a speech recognition system that uses an artificial neural network to translate audio input directly to transcribed output.
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Fanuc's machines will feed what they learn into a neural network that other robots can learn from and contribute to as well, reported MIT Technology Review.
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The images were cropped further and then processed through a deep neural network, a layered mathematical system capable of identifying patterns in vast amounts of data.
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In about two weeks, a team of Google researchers "trained" a neural network that outperformed technology from the start-up that had taken years to create.
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Like its predecessor, this self-taught Go AI—known as AlphaGo Zero—is a neural network, a type of computing architecture modeled after the human brain.
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A neural network is the same technology that is rapidly improving face recognition services, talking digital assistants, driverless cars and instant translation services like Google Translate.
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Loosely modeled on the web of neurons in the human brain, a neural network is a complex mathematical system that can learn tasks on its own.
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For example, one neural-network language model—similar to the one Aristo uses—was reported in 2019 to capably determine whether one sentence logically implies another.
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The simplest description of a neural network is that it's a machine that makes classifications or predictions based on its ability to discover patterns in data.
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It's a legitimate neural network, borrowed from the open source GPT-2 model created by AI research company OpenAI and trained specifically to write CAH cards.
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Each layer of the neural network makes multiple, parallel connections between certain words while ignoring others — akin to a student diagramming a sentence in elementary school.
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The tool uses a neural network that estimates how "far" each pixel in a photo is from the camera in order to create a "3D photo."
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Engineers train a neural network for a particular task before sending it out into the real world, and it can't learn without enormous numbers of examples.
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And that's entirely orthogonal to throwing 10x more data and compute at a big neural network so that it improves its skill by some small percentage.
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The researchers matched up the GIFs with the frames in their videos of origin and fed them into the neural network, along with their user tags.
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Feed millions of cat photos into a neural network and it can learn to recognize a cat — and later pick out cats by color and breed.
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The phrase "neural network" stems from early efforts to create a computing system that emulated the human brain's individual neurons working together to solve a problem.
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He tested this approach on 36 different handwritten versions of the same numbers and in each instance the DNA neural network was able to recognize them.
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An artificially intelligent system called a deep residual neural network scoured through the data, analyzing weight distribution, gait speed, and three-dimensional measures of each walking style.
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First the team fed in a hundred hours of music into a neural network, which allowed it to create listenable music, complete with melody, instruments and drums.
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Here, the researchers studied fur and converted the mathematics of the light bouncing around to a subsurface scattering model using a rather simple neural network, explained Ramamoorthi.
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They trained a neural network to recognize and then mask the human-made radio interference that comes from satellites, airports, WiFi routers, microwaves, and malfunctioning electric blankets.
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Such neural network–based sentiment analysis can be applied not just to individual conversations, but to the combined activity of every social media user on a platform.
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They used it as, essentially, a single-layer neural network that sorted images into two classes: "car" or "no car" in a library of 20,000 street scenes.
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But in the age of AI, creating targeted malware can become as easy as training a neural network with pictures or voice samples of the intended target.
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They developed a neural network, not unlike the kind that can auto-tag your dog in a photograph, and trained it with 15,000 astronomer-confirmed exoplanet signals.
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Google built on the previous work of a 2013 acquisition, DNNresearch, by setting up a deep neural network trained on data that had been labeled by humans.
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Based on how various sentences are related to one another in the memory space of the neural network, Google's language and AI boffins think that it has.
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OpenAI's algorithm then takes the information gleaned from the vision network and feeds it to a second neural network, called an imitation network, guiding the robotic arm.
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Weighing in at just 11 pounds and roughly the size of a medicine ball, this minute astronaut is equipped with the neural network strength of IBM's Watson.
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As for as those AI performance gains go, Qualcomm is saying the Snapdragon 2855 will big sizable improvements to tasks that rely on neural network-assisted software.
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Places is a convolutional neural network (CNN), a type of program that can learn to recognise features in sets of data, such as images, presented to it.
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The researchers also trained the neural network on videos of people's faces and then used simple sketches to transfer expressions onto the people speaking in the video.
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An animation system powered by a neural network drawing from real motion-captured data may help make our avatars walk, run and jump a little more naturally.
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Using it, they were able to train a neural network that could recognize handwriting (a standard training task for new forms of AI) with 95 percent accuracy.
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It's connected by Wi-Fi to a server that uses artificial intelligence to analyze the object, and a neural network containing 256,000 images of different clothing items.
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It details ways YouTube's "neural network" AI system acted like an "addiction engine," pushing users to consume more videos, regardless of the fringe nature of their content.
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It's actually just the sick and twisted result of a neural network predicting what a still photo of a baby would look like if it were moving.
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Click here to view original GIFWhen you put footage of New York City through a neural network, you get a city that looks like beautiful, moving artwork.
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We'll likely be hearing more from Magic Pony when the details of the neural network — and how it was put together — are presented at CVPR in June.
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Johnson proved that a neural network will fail at this task when the width of the layers is less than or equal to the number of inputs.
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The pool report of the exchanges on Wednesday read like something written by a neural network trained to talk like a president, but, no, they actually happened.
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Apple also specifies that it has trained a neural network to "spot and resist spoofing" to defend against attempts to unlock the device with photos or masks.
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Only last month, scientists built a novel neural network model of time perception, which was based solely on measuring and reacting to changes in a visual scene.
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For example, are you selling a chip, along with design environments, sample neural network frameworks and data sets, that will empower your customers to deliver magical products?
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By showing the figures to the neural network along with the WiFi signals, the network was able to learn which radio signals were made by each movement.
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To do that, it's using a new neural network model that's been trained by analyzing 12,000 ebooks, primarily fiction — with a lot of those being romance novels.
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In total, the system can push up to 8 teraflops and recognize up to 2,800 images per second using the AlexNet neural network-based deep learning algorithm.
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Professor Ken Goldberg, meanwhile, will be demonstrating his lab's Dex-Net system, which utilizes an off-the-shelf industrial robotic gripper trained on a deep neural network.
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This type of AI—the same neural network that identifies faces, animals, and objects in pictures uploaded to Google's online services—has proven adept in medical settings.
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In the case of the semiconductor company, Dhurandhar was able to map the behavior of the neural network on the software structure that the company already used.
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"It is an unfortunate side-effect of the underlying neural network caused by the training set bias, not intended behavior," Goncharov told The Guardian in a statement.
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That's why the neural network classified a candle as a jack-o-lantern with 99.94 percent confidence, even though there were no carved pumpkins in the image.
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In 1951, his first year of postgraduate study, he created what may have been the world's first artificial neural network, a learning machine inspired by biological brains.
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Ultimately, with enough of these things going and contributing data to a central pool in real time, a neural network would be trained to watch for problems.
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There's been a series of major advances in voice synthesis over the last couple of years as neural network technology improves on the old highly manual approach.
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It scraped the closed captioning on every episode of HBO's Silicon Valley and trained the neural network to mimic Richard, Bachman, and the rest of the gang.
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Related: "Computer Thoughts" Projected onto a Giant Dome via Neural Network Watch a Czech Planetarium Transform into a Mythic Light Show Planetariums As Platforms For Immersive Art
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He had trained a neural network to spot chromatic aberrations and other signs of manipulation; the network produces "heat maps" highlighting the suspect areas of an image.
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They were designed instead by a neural network, which crunched doodle data from millions of people and spit out the original art that makes up the embroidery.
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That's why the researchers began with crowd-sourced examples of hundreds of products with their purposes and mechanisms labeled, a solid foundation to train the neural network.
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Related China Becomes a Living Painting in This Neural Network Timelapse A Vietnamese Art Collective Is Making Commercials for Communism What's the Weirdest Sculpture at Art Basel?
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"Could the neural network learn to invent new paint colors and give them attractive names?" she posited, giving examples of existing ones — Tuscan sunrise, Blushing pear, Tradewind.
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Understanding the function of Cloud Index's neural network—called deep convolutional generative adversarial network (DCGAN), described in early 2016 by machine learning researchers—is what interests Bridle.
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Among other things, he built a neural network that learned to write its own Kanji, the logographic Chinese characters that are not so much written as drawn.
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And while it may take humans years to search through so many candidates for that one miracle molecule, a neural network can do the work in days.
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Then, when fed a snippet of text, it will identify events, and use them to shape a continuation of the plot churned out by a neural network.
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Such chips are designed to imitate the network of neurons in the brain, not unlike a neural network but with even greater fidelity, at least in theory.
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The fine-tuning required to perfect an algorithm, by for example searching through different neural network architectures to find the best one, can be especially computationally intensive.
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Deepfake algorithms work the same way: They use a type of machine learning system called a deep neural network to examine the facial movements of one person.
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Related: A Slice-of-Life Stop-Motion Set During an Argentine Dictatorship Stereoscopic GIFs Get Trippy Makeovers with Neural Network Imaging Adventure Time-Worthy Psychedelics | Monday Insta Illustrator
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After feeding it a dataset of almost 50,000 real British place names, the neural network generated a list of over 4,500 fake ones, but how convincing are they?
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Related: 'Pikazo' App Lets You Paint Neural Network Art Masterpieces Dive into Deep Dream Infinity in These Trippy Music Videos [Premiere] Deepdreamed Cronenberg Is the Cronenberg of Deepdreaming
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The team trained a deep neural network on this dataset to classify an image of an iris as taken either while the subject was alive or post-mortem.
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According to a University of California, Berkeley press release, the researchers "trained an algorithm known as a convolutional neural network" to replicate traditional methods of detecting the bursts.
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A neural network could quickly identify the things that stand out that might be of most interest to astronomers, or point out things a human eye might miss.
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The team used a neural network that can analyze complicated scenes in video footage—such as people walking, dancing, playing basketball—and identify which pixels belong to humans.
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Meanwhile, however, the malware uses a facial recognition neural network, tuned to the picture of the intended targeted, to scan the computer's webcam video feed for its target.
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The secret to their success: a neural network trained to identify exoplanets, developed by University of Texas at Austin astronomer Andrew Vanderburg and Google software engineer Christopher Shallue.
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He also likes to say that his startup is based on artificial intelligence — though you won't find it at the deep, complex level of a convolutional neural network.
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Well, you can start by just navigating around Google and OpenAI's example here, built to unspool the innards of a well-known neural network called GoogLeNet or InceptionV1.
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Actual computing time is reduced by limiting the precision of the math involved and using Google's Tensor Processing Units, custom hardware designed with neural network training in mind.
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The latest release from the division's AI experiments series is a new web app that lets you collaborate with a neural network to draw doodles of everyday objects.
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But while a cat looks like a cat no matter if it's grey or pink to us, one can't really say the same for a deep neural network.
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Apple is angling hard through these waters toward a future where the kinds of neural network processing that have to be done remotely can be done on device.
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Of course, every player in the market aims to build chips that enable neural network parameters to be distributed across a large number of chips at high-efficiency.
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Taking the neural network trained on the dog's behavior, they wanted to see if it had learned anything else about the world that they had not explicitly programmed.
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In both cases, the neural network was able to complete these tasks with decent accuracy using just the basic data it had of a dog's movements and whereabouts.
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But it was only recently that Alexander Reben was curious enough to see what a neural network would make of the human equivalent of Ambien: painter Bob Ross.
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They were able to train the neural network quickly and efficiently to identify what most would consider superior photographic elements using what's known as a generative adversarial network.
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The watch runs a distinct model for detection that isn't as large as the full neural network running on the iPhone or as small as the initial detector.
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"The notion of depth in a neural network is linked to the idea that you can express something complicated by doing many simple things in sequence," Rolnick said.
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Reinforcement learning doesn't require humans to label lots of training data; it just requires telling a neural network to seek a certain reward, often victory in a game.
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Currently, switching from an AI designed to recognize faces to one designed to understand human speech would require a complete overhaul of the neural network associated with it.
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" Venetian Snares is no stranger to modular synths himself—he says that his setup is "almost like a bandmate, but you somehow have access to their neural network.
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To determine whether something has been altered, you have to go back to the source, and the NYU researchers believe this can be done with a neural network.
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After pulling the data from these two sources, Estela trained a neural network to recognize patterns based on all the examples in the database and their respective tags.
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The company's AvyScanner uses radar and an AI-powered neural network to locate hazardous avalanche zones and alert skiers to the danger before they find themselves in trouble.
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Every couple of months, photos from FaceApp—a face-editing app that uses neural network to make users look younger, older, more feminine, or more masculine—goes viral.
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Related: This Futuristic Take on the Fauvism Movement Is Trippy as Hell Stereoscopic GIFs Get Trippy Makeovers with Neural Network Imaging Paint-Covered Balloons Burst Like Liquid Jewels
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Colorado-based research scientist Janelle Shane has trained a neural network (a type of machine-learning algorithm) to write its own Christmas carols, and the results are...interesting.
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Trained for a week on a massive data set of portraits, a neural network became capable of mimicking visual patterns and spitting out striking images of nonexistent people.
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They basically trained the deep neural network with all the historical data of the bank and let it figure out for itself the patterns that defined fraudulent transactions.
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It's a thin metaphor that managed to catch on and now whenever I say I'm training a neural network people assume that I'm into some real mystical shit.
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So when you feed Dango a sentence, it uses its neural network to parse through the ideas in the sentence, and plot their vectors in this semantic space.
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For Shane's AI creations, she uses a type of machine-learning algorithm known as a neural network, which is modeled after the way neurons work in a brain.
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Shane trains uses the char-rnn neural network framework to train the computer to "speak" using only beer words, then turns on the creativity and makes it think.
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They thought it was cool to be the first brewery to have a beer named by a neural network, "but the overriding emotion was just bewilderment," said Fritts.
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As far as AI goes, Microsoft also today announced that it will bring its new Brainwave deep neural network acceleration platform for real-time AI to the edge.
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It's less clear whether a reputation for silly and/or uncanny valley neural network effects will translate into lots of paying customers for rather more subtle selfie alterations.
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In the meantime, DeepMind, the British AI company that Google acquired in 2014, has applied psychological tools to analyze how a neural network solved basic image-classification tasks.
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Google also notes that while most architects optimize their chips for convolutional neural networks (a specific type of neural network that works well for image recognition, for example).
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If an actual outcome differs from the computer's predicted outcome, information about what went wrong gets passed back through layers in the neural network, adjusting the system accordingly.
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Loosely based on the network of neurons in the human brain, a neural network is a complex algorithm that can learn tasks by analyzing vast amounts of data.
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What's more, when the team built simulated piles of random objects and fed those into the neural network, it could learn to lift items from physical piles, too.
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By capturing vast quantities of human speech, neural network programs can be trained to recognize spoken language with accuracy rates that in the best circumstances approach 95 percent.
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He then told the neural network to throw away some of the information contained in the image, though he didn't specify what it should or shouldn't throw away.
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A convolutional neural network slides many of these "windows" over the data like filters, with each one designed to detect a certain kind of pattern in the data.
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Neon, a project developed by an independent research group under Samsung named Star Labs, has created a neural network called Core R3 that simulates incredibly lifelike human avatars.
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"Over time, we expect to see DSPs [digital signal processors] specifically designed for neural network inference and training," Burke said at the G I/O conference this year.
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These recordings formed a data set that it used to train an artificial neural network — a computing system whose structure is modeled loosely after neurons in a brain.
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Deep Learning with TensorFlow Master deep learning techniques by enrolling in this course on TensorFlow, an open-source software library for machine learning and deep neural network research.
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After getting the first question wrong (I incorrectly attributed the text to the neural network), I realized a convenient winning strategy: the coherent sentences are probably from the Bible.
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Rosenberg claimed she was training a neural network, a type of computing architecture inspired by the human brain, and needed a large set of browsing data to do so.
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The CV system described in this paper uses a recurrent neural network to create an "attention mask" for every frame, then track relevance of each object as time proceeds.
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"With its new products, Habana has quickly extended from inference into training, covering the full range of neural-network functions," said Linley Gwennap, principal analyst of The Linley Group.
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The basic way to do this is to use a neural network: a computational structure that's broadly similar to the human brain (though it's light-years behind in sophistication).
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How it works: Alhanai used a neural network to find characteristics of speech — like pitch or breathiness — that relate most closely to depression but aren't correlated with one another.
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Related: 'Pikazo' App Lets You Paint Neural Network Art Masterpieces Dive into Deep Dream Infinity in These Trippy Music Videos [Premiere] Google's Psychedelic AI Art Takes Twitter by Storm
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Researchers at the University of Surrey in the U.K. were able to use a deep convolutional neural network to separate vocals from backing instruments in a number of songs.
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Research scientist Janelle Shane fed all the classic messages from candy hearts into a neural network algorithm that then mimicked the word patterns to, uh, varying degrees of success.
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Next, the neural network was tested by being shown a new, never-before-seen trail—and the network was able to identify the trail as such on its own.
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First, the scientists made a dataset to train the neural network with, which meant generating 6 million fake images showing what gravitational lenses do and do not look like.
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Then, we compared Norman's responses with a standard image captioning neural network (trained on MSCOCO dataset) on Rorschach inkblots; a test that is used to detect underlying thought disorders.
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" Speaking to The Verge by email, he noted that the neural network would best apply to "local earthquake monitoring efforts" — as in Oklahoma — "where there are high-seismicity rates.
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Like ag tech or ... Cuban: You have to have some domain knowledge, because the whole idea of building a neural network is identifying what's going to feed what, right?
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In order to train the TOS, we mimic it and have created a neural network e that maps properties such as gender, length of hair, shape of eyes, etc.
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The company touts its Memristive Nanowire Neural Network chip architecture as being able to train larger, more powerful neural networks than any commercial chip that's currently on the market.
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The poster explained that the clip was fake, created by training a neural network to generate images of Gadot's face that matched the expressions of the video's original star.
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The Flo team says they have developed a neural network for the product resulting in a lot more accuracy than usual – up to 50% compared to traditional statistical models.
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They endowed her with an artificial mind, called a neural network, an advanced form of machine learning in which a computer learns a task by relying on training examples.
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In 2012, artificial intelligence researchers revealed a big improvement in computers' ability to recognize images by feeding a neural network millions of labeled images from a database called ImageNet.
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"You can drop a neural network powered car in locations it has never seen before, and have it gracefully perform, using techniques human use [from] past experience," Cameron said.
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Its deep neural network product can be trained to work in a variety of industries, and Clinc currently works with major banks, automakers, quick-service restaurants and healthcare companies.
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The idea behind RISE is to randomly obscure parts of the input image and run it through the neural network to observe how the changes affect the output weights.
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The resulting model did not perform as well as the neural network but managed to improve the performance of the company's original software considerably while also maintaining its interpretability.
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Kepler-90 i is the new planet discovered by Google's neural network, and it had a weaker signal than the ones normally used to identify planets by traditional means.
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Google used TensorFlow to build its Magenta project, which aims to advance machine generated art, and recently released a 90-second piano melody created solely by a neural network.
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Well, Google's engineers took that as a challenge, and set up a convolutional neural network architecture, training it on thousands of labelled images like the one to the right.
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Most of the AI field is focused on manually designing all the building blocks of an intelligent machine, such as different types of neural network architectures and learning processes.
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To get a sense for how well a neural network could write tech and business headlines, I gave Shane over 8,000 CNN Business headlines published over the past year.
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To develop InverseKnit, researchers first created a data set of knitting patterns with matching images that were used to train a deep neural network to generate machine knitting patterns.
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The researchers, who published their findings in the journal Nature this week, first trained a neural network using 129,450 photos representing more than 2,000 different types of skin conditions.
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Intel's Nervana Neural Network Processor lineup, named after Nervana, the company it acquired in 2016, is developed by the Intel AI group led by former Nervana CEO Naveen Rao.
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Gaia spotted these hypervelocity stars with the help of a neural network, which is a type of program inspired by the structure of neural organization in the human brain.
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In the fully connected layer, each reduced, or "pooled," feature map is "fully connected" to output nodes (neurons) that represent the items the neural network is learning to identify.
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Crucially, this neural network had been trained on images of turbulence-distorted beams, so it was able to strip away this distortion to identify just the message being sent.
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But it has been updated several times, and the current version employs a neural network trained to recognize species using images from the rich library compiled by human users.
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DeepMind said neither of these neural network architectures were used to develop AlphaGo Zero, although the neural net developed for AlphaGo Zero will have applications far beyond board games.
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Since the camera on Berkeley's robot could see depth, it captured three-dimensional images that were not unlike the CAD models the team uses to train its neural network.
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"The silicon vendors such as Qualcomm are now moving towards moving what we call a neural network accelerator into those devices," said Simon Bryant, director of research at Futuresource.
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The new system relies on a neural network, a breed of artificial intelligence that is accelerating the development of everything from health care to driverless cars to military applications.
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To search through this treasure trove of astronomical data, researchers at Google trained a neural network on 15,000 examples of exoplanet data that had been labeled by NASA researchers.
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Using deep learning and a dataset of pictures of people wearing various disguises, researchers were able to train a neural network that could potentially identify masked faces with some reliability.
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So using this technology, you can actually take a neural network, an AI algorithm, and you can throw a bunch of data and teach it what Kara Swisher looks like.
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Related: Step Into A Playfully Disorienting Pastel Digital Art World Stereoscopic GIFs Get Trippy Makeovers with Neural Network Imaging Take a Walk in Someone Else's Shoes with POV-Altering Headgear
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Related: Learn How To Make Stereoscopic GIFs With Mr. GIF Stereoscopic GIFs Get Trippy Makeovers with Neural Network Imaging Twitchy GIFs Made From Stereoscopic Photographs Architect Maps Isometric, Stereoscopic Visions
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The researchers designed a dense neural network (DNN) architecture that predicts a blowjob giver's next move based on analysis of past movements, kind of like predictive text on your phone.
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Earlier this week, research scientist Janelle Shane got a fantastically unusual request from the Portland Guinea Pig Rescue, asking if she could build a neural network for guinea pig names.
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In this case, the researchers combined the CNN-based method with a recursive neural network (RNN), an approach that considers previous eye states in addition to individual frames of video.
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Eventually the neural network was able to generate those skeletons by analyzing just the scattered radio signal data, which, it turns out, can easily pass through walls when light can't.
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It took longer than most people thought, with the first real breakthrough coming in 2009 when a neural network based system became better at speech recognition than a human transcriber.
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By mapping out what visual elements are activated in each part of a neural network, time and time again, eventually, you get the atlas: a visual index to its brain.
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The only known successful exit has been that of DeepMind, which was bought by Google and built an AI atop a convolution neural network that plays games on its own.
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It was made in Tensorflow, where the neural network is built and trained—meaning it must analyze lots of pictures first so it knows how to fill in the lines.
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The exhibition, which takes place tonight at the Gray Area Art & Technology Theater in San Fransisco, includes 29 neural network artworks, created by artists at Google and around the world.
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After collecting data from 10 different drivers who covered 1,000 miles of freeway and city over two months, the team annotated the footage in order to train their neural network.
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Martiniani is applying it to machine learning in hopes of building more efficient AI: how many different ways can you wire a neural network and still have it be functional?
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These are crunched, along with live news, by a neural network christened The Underwood, in homage to the devious anti-hero of "House of Cards", a popular political drama series.
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Shane analyzed a list of 7700 paint colors from Sherwin Williams with a neural network called char-rnn, including both the paint names and their red, blue, and green values.
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Redundancy is a natural choice for AV systems, but it's made more palatable by the extreme levels of acceleration and specialization that are possible nowadays for neural network-based computing.
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Scientists trained a neural network to look for patterns in a database of more than 131,000 "mainshock-aftershock" events, before testing its predictions on a database of 30,000 similar pairs.
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Obviously there's still a long way to go before Broad's neural network generates earth-shattering video technology, but we can safely say already — we've seen things you people wouldn't believe.
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At the front of the queue is SwiftKey for Android and iOS, which has long been using advanced neural network AI to work out what you're going to say next.
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If there is an 80% chance of an 'h' following a 'c' and a 20% chance of it instead being an 'e,' the responsible neural network would go with 'h.
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Last year, the company showed off its vision for the connected future of the car — complete with "deep neural network" computer vision — in a presentation so wild it seemed plausible.
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After collecting all the short love notes Shane could find, such as "LOVE YOU" or "CALL ME," she fed them into a neural network to see what it would create.
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But Google may have made them relevant again — or at the very least, interesting — by letting you mix and match them in real time using a single specialized neural network.
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Researchers at Penn State University and the International Institute for Tropical Agriculture in Tanzania have trained a neural network running on a smartphone to spot cassava disease with 93% accuracy.
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Now, the team behind the iOS and Android app Pikazo are bringing neural network imaging to mobile devices, allowing people to apply iconic artist's styles, and customized ones, to images.
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So does neural network deep learning, a type of artificial intelligence where data is fed through layers of simulated neurons in order to train a computer to recognize complex patterns.
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The new release now lets iOS developer to build neural network features directly into apps, like the ability to parse sentence structure and / or recognize people and objects in photos.
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There's a sort-of comparison there in that the "neurons" of a neural network are nodes where input signals are mapped to output signals, but it's mostly a superficial likeness.
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A deep-learning system can be trained using this database, repeatedly working through the examples and adjusting the weights inside the neural network to improve its accuracy in assessing spamminess.
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In the absence of a written description, the neural network generates new text — effectively, an algorithmically written crime report based on the three other features used in the training model.
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First, they spent three days training a neural network — a machine-learning algorithm modeled after the way neurons work in a brain — on replays of human players' StarCraft II games.
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Even earlier, in 1958 The New York Times reported that the Navy was planning to build a "thinking machine" based on the neural network research of the psychologist Frank Rosenblatt.
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Those are promising results, but this neural network has a long way to go before it could be unleashed upon the billions of photos floating around the internet right now.
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At Baidu's Create conference for AI developers in Beijing today, the company and Intel announced a new partnership to work together on Intel's new Nervana Neural Network Processor for training.
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Related: This Is What a Robot Designed by a Neural Network Looks Like Robots Sketch Human Portraits in a Life Drawing Class Japan's Robot Restaurant Is a Futuristic Sensory Overload
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During over 1,000 hours of work over the last six weeks, the group developed a new algorithm that confuses a neural network no matter how the AI looks at it.
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It could be under the influence of ayahuasca that the central neural network system becomes evoked, and those physiological changes could be modified, even for a brief period of time.
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A neural network has the same needs, but its focus is usually more narrow and we don't really socialize with it, so the labels need to be much more precise.
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In the first step, a neural network segments the scan, which is difficult for humans to read in its raw form, into colored areas that represent different types of tissue.
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Cerny said the company could potentially have players upload photos of their ears, which could then filter through a neural network to choose the right HRTF setting for each individual.
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By playing against itself and updating its neural network as it learned from experience, AlphaZero discovered the principles of chess on its own and quickly became the best player ever.
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"This is the first time a neural network specifically has been used to identify a new exoplanet," said Christopher Shallue, a software engineer at Google who helped make the finding.
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If a neural network is trained on images that show a coffee cup only from a side, for example, it is unlikely to recognize a coffee cup turned upside down.
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But they found that if they began with a neural network that had already been trained to recognize some unrelated feature (dogs versus cats, say) it learned faster and better.
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Connecting Broca's area with Wernicke's is a neural network: a thick, curving bundle of billions of nerve fibres, the arcuate fasciculus, which integrates the production and the comprehension of language.
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New hardware has been developed to implement deep neural network models and may provide enough information to decode a listener's focus, but this often happens at lower speeds than preferred.
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Deep learning is a big umbrella term that contains many different sorts of neural network and a couple of other machine learning techniques that are a lot like neural networks.
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The system used a neural network, a breed of artificial intelligence, to digest the electronic health records from more than 1.3 million patient visits at a pediatric hospital in China.
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After training the neural network on these sources, the researchers had a program that could look at an image and make a prediction as to the potential for privacy violation.
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With that foothold established in the market, Goldin hopes that KnuEdge will come to be the foremost provider of technology for the neural-network-powered artificial brains of the future.
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As shown in "Universal Adversarial Perturbations," what fools one neural network 90 percent of the time, may only have a success rate of 50 or 60 percent on a different network.
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Once back at the lab, the researchers used an AI in the form of a Deep Neural Network (DetectNet) to analyze the collage, searching for—and meticulously counting—individual penguin nests.
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So like a recently designed neural network that can't quite figure out how to name paint swatches without sounding like gobbledygook, Janet's easily confused at first (she thinks everything's a cactus).
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But the deep-neural-network software fueling the excitement has a troubling weakness: Making subtle changes to images, text, or audio can fool these systems into perceiving things that aren't there.
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Related: Dive into Deep Dream Infinity in These Trippy Music Videos [Premiere] 'Pikazo' App Lets You Paint Neural Network Art Masterpieces This Artist Is Teaching Neural Networks to Make Abstract Art
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Aman Tiwari, a computer scientist at Carnegie Mellon University, trained the AI by overlaying census data on high-resolution satellite imagery of New York and feeding it through a neural network.
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In particular, the company uses deep learning and neural network algorithms to predict healthcare patterns in patients, and beyond, to reduce preventable hospitalization, and, in turn, save on costs and hassles.
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AI Duet works by taking the notes you play using your computer's keyboard and running it through a neural network that has been trained using machine learning with scores of examples.
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In 2015, their networks were creating pictures like this: In 2016, they're creating pictures like this: To create these images, the neural network is trained on a database of similar pictures.
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But Gerry Zhang, a graduate student at UC Berkeley and part of the Breakthrough Listen project, created a convolutional neural network system that would theoretically scour the data set more effectively.
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You draw a face, and Pix2Pix uses a neural network to create what looks like an approximation of an oil painting of that face (made up of pieces of Rense's face).
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It can also crunch through the massive number sets used by an AI system to improve itself at nearly twice the speed, according to tests conducted on standardized neural network models.
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Others are helping comb through data streams for interesting signals, like a neural network that removes human-made interference from radio telescopes to help scientists home in on potentially exciting signals.
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Shane's previously told us that she does this for fun—essentially, she saw a list of neural network recipes that ended before she wanted it to, so she made her own.
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Original photo: Dorothea Lange; color modification: Richard ZhangThe neural network continues to work away in the background, updating the colorized results every time a new marker is added by a user.
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Meet Teleport: An app that's using a trained neural network to power a selfie-editing feature that lets you change the color of your hair at the touch of a button.
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I write this as large swathes of the industry are moving away from traditional programming and towards the various flavors of AI. How do we formally specify a convoluted neural network?
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Related: If Picasso Painted 'Alice in Wonderland'... We Got an Artificial Neural Network to Name Random Objects in the VICE Office This Artist Is Teaching Neural Networks to Make Abstract Art
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The young man's fluency demonstrated that his 'wetware' – a living neural network, if you will – had been trained well enough to intuit the subtle rules (and exceptions) that make language natural.
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Related: Dive into Deep Dream Infinity in These Trippy Music Videos [Premiere] 'Pikazo' App Lets You Paint Neural Network Art Masterpieces This Artist Is Teaching Neural Networks to Make Abstract Art
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An opera company used lines generated by Shane's neural network and a brewery in Michigan took one of the machine's suggestions of "The Fine Stranger" in naming one of its beers.
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"The way that this Word2vec algorithm works is that you train a neural network model to remove each word and predict what the words next to it will be," Jain said.
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Terrapattern is built on a Deep Convolutional Neural Network (DCNN), and has been trained to recognize geographical features within small squares in four cities — New York, San Fransisco, Pittsburgh, and Detroit.
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Today, Google's newest machine learning project released its first piece of generated art, a 90-second piano melody created through a trained neural network, provided with just four notes up front.
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While the app worked most of the time, for me, the servers occasionally timed out and froze, and other times the neural network seemed unable to distinguish humans from other animals.
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The company's answer is automatic alternative text: a neural network analyses photos, and if it's at least 80 percent confident it understands what's going on, the AI will describe the photo.
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In 2012, Google made headlines when it trained a neural network with 16,000 central processing unit (CPU) chips on 10 million images from YouTube videos and taught it to recognize cats.
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Breakthroughs in machine learning -- especially the deep learning and neural network technologies used by Maven -- have led to a massive expansion in the diversity of activities that can effectively be automated.
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Computer scientists train an artificial neural network (a type of computing architecture loosely based on the human brain) so that it can perform a particular task, like beating a specific game.
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But then she took a cue from a blog reader and fed her neural network paint names with only lowercase letters and added more color names from companies like Benjamin Moore.
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An artificial (as opposed to human) neural network (ANN) is an algorithmic construct that enables machines to learn everything from voice commands and playlist curation to music composition and image recognition.
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It's advertised utility is limited to designing party invitations, but let's not forget that every neural network experiment is, in some capacity, designed to teach computers how to see and think.
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In training a complex model, such as a deep neural network, the use of small data sets can lead to something called overfitting, which is a common pitfall in machine learning.
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Well, that type of functionality isn't just for absurdist poetry, you know; the team behind Sunspring used the same technology — an LSTM Neural network, to be precise — to write a screenplay.
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The company's also added support for TensorFlow Lite and the new Open Neural Network Exchange frameworks, in addition to regular old TensorFlow and Caffe, freeing up developer choice on that front.
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Oh, and speaking of A.I., this is a little awkward but … our bosses spent the past three months training a neural network to replace you as the author of this newsletter.
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Much as a neural network can learn to identify a cat by analyzing hundreds of cat photos, it can learn the musical characteristics of a bassoon by analyzing hundreds of notes.
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For the first time, AI researchers have figured out how to identify brand-new types of antibiotics by training a neural network to predict which molecules will have bacteria-killing properties.
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Hill built a company around the project and made the technology more accurate by switching its conventional image-deciphering algorithms for the neural network technology that started the recent AI boom.
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They did this by placing mathematical constraints on what the neural network could "see" in the data via its convolutions; only gauge-equivariant patterns were passed up through the network's layers.
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"Startup companies trying to launch different things into space are very interested in my work, because it's essentially very low-cost," she adds, comparing her neural network to sensors and radars.
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Details: The system used a neural network, a breed of artificial intelligence, to digest the electronic health records from more than 1.3 million patient visits at a pediatric hospital in China.
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Qualcomm, for example, just announced its 820 chip, known primarily as the compute engine inside many of today's high-end smartphones, can be used for deep learning and neural network applications.
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Researchers used a set of high-powered Tesla V100 GPUs and a deep-learning neural network to generate a nearly perfect, smooth slow-motion video out of any standard video clip.
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Two systems are at play: one neural network (an assemblage of digital nodes that reorganize themselves to accomplish a task) to process real-world images, and another to process imitation data.
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What had happened, essentially, was this: The clock registered the time, which sent the data into the LSTM neural network that Goodwin had trained on one of three corpora of literature.
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