Microsoft’s CNTK (Cognitive Toolkit) is one among many platforms that trains computers to learn, and it’s getting an upgrade.
CNTK drives the Microsoft services Cortana and Skype language translation, and it boasts more than 90 percent accuracy in speech recognition tasks. Microsoft will soon release an upgraded CNTK toolkit, and one hardware maker wants to ensure the toolkit works best on its hardware.
Nvidia is partnering with Microsoft to optimize its GPU development tools for CNTK. The companies have created a set of deep-learning algorithms and libraries that will speed up CNTK to perform AI tasks like image and speech recognition on GPUs.
Deep-learning tools like CNTK are sandboxes in which developers can create a model for computers to solve a particular problem. The ultimate objective is to build a well-trained model that can accurately perform a specific task, such as shuffling through loads of medical data to diagnose a disease.
Based on input, researchers are continuously modifying models and tweaking parameters. One such tweak optimizes neural networking connections for better AI capabilities and for scaling the training model over more GPUs and servers.
The training of computer models can run for days and require intense computing horsepower. GPUs power deep learning for companies like Google and Facebook, and Microsoft is allowing some customers to test GPUs as part of its Azure cloud service. The updated CNTK tools will run faster on Microsoft’s Azure N Series cloud offerings, which run on…
click here to read the rest of this story.