Sentences with phrase «neural network applications»

The company says that the chip is designed specifically for the operation of deep neural network tasks at high speeds and low cost, enabling developers to build the «next generation» of deep neural network applications on Windows clients.

Not exact matches

Neural networks have been around for a while, but it's fair to say that many successful practical applications use at least one convolutional layer.

Alibaba is developing its own neural network chip, the Ali - NPU, which will be used in AI applications, such as image video analysis, machine learning,...

Twitter today is taking another step to build up its machine learning muscle, and also potentially to improve how it delivers photos and videos across its apps: the company is acquiring Magic Pony Technology, a company based out of London that has developed techniques of using neural networks (systems that essentially are designed to think like human brains) and machine learning to provide expanded data for images — used, for example, to enhance a picture or video taken on a mobile phone; or to help develop graphics for virtual reality or augmented reality applications.

«Neural network models are brain - inspired models that are now state - of - the - art in many artificial intelligence applications, such as computer vision.»

Then, for each application, they used a neural network to find correlations between particular neuromuscular signals and particular words.

This goes far beyond recent applications of neural networks in astrophysics, which were limited to solving classification problems, such as determining whether an image shows a gravitational lens or not.

In artificial - intelligence applications, a neural network is «trained» on sample data, constantly adjusting its weights and firing thresholds until the output of its final layer consistently represents the solution to some computational problem.

Such «optical neural networks» could make any application of so - called deep learning — from virtual assistants to language translators — many times faster and more efficient.

Over the past few years, the team has focused on developing new methods in Evolutionary Computation (EC), i.e. designing artificial neural network architectures, building commercial applications, and solving challenging computational problems using methods inspired by natural evolution.

«This is especially relevant when applying deep neural networks to medical tasks where the disease - specific data is often costly to label with a gold standard and where the datasets are relatively small in sample size compared to those for deep learning applications in other fields.»

Coastal physical oceanography, subtidal circulation, ocean observing systems, real - time surface buoy design, towable buoy designs, autonomous vehicles, surface current measurements with HF RADAR, Doppler technology, oceanographic applications of artificial neural networks.

Bioinformatics professors Anthony Gitter and Casey Greene set out in summer 2016 to write a paper about biomedical applications for deep learning, a hot new artificial intelligence field striving to mimic the neural networks...

The major focus is on artificial neural networks, evolutionary algorithms, fuzzy systems and the applications of these methods.

These students have fewer opportunities to discover the connections between isolated facts and to build neural networks of concepts that are needed to transfer learning to applications beyond the contexts in which the information is learned and practiced.

In doing so, they will build confidence about facing uncertainty, strengthen their growing neural networks of EFs through activation and application, and find more pleasure in the adventures of constructing knowledge.

In a recent investor letter, we described why deep learning, and in particular recurrent neural networks, might be well suited to the application of long - term systematic value investing.

Emerging solutions to lawyers» search problems over the coming decade and beyond could likely include a synthesis of «intelligent search engine» applications culled from the areas of artificial intelligence, neural networks, and other forms of information filtering and machine - learning techniques.

Bioinformatics professors Anthony Gitter and Casey Greene set out in summer 2016 to write a paper about biomedical applications for deep learning, a hot new artificial intelligence field striving to mimic the neural networks...

«We developed that system using a deep convolutional neural network approach that others, including Google and Pinterest, have used to develop similar applications.

Facebook has a team of people building neural networks — applications that help machines think and act like humans — and many of those applications are already live inside of M, Schroepfer says.

The software has a feature that will let you use your device as a virtual touchpad and keyboard for a PC, and they will also support Android's neural network API to let developers make full use of hardware acceleration for machine learning applications.

For developers, Android Oreo introduces WebView, Java 8 language APIs (Application Programming Interfaces), a Neural Networks API, Autofill framework, notification channels, AnimatorSet, autosizing TextView, new media features, unified layout margins and padding, speech output, app categories, and fonts in XML format.

More applications and use cases based on Google's AutoML, which uses neural networks to create more neural networks.

The major focus is on artificial neural networks, evolutionary algorithms, fuzzy systems and the applications of these methods.