Explore resources available for popular AI frameworks optimized on Intel® Architecture, including installation guides and other learning material. We are continuously expanding our list of supported frameworks.
Intel continues to accelerate and streamline PyTorch on Intel architecture, most notably Intel® Xeon® Scalable processors, both using Intel® Math Kernel Library for Deep Neural Networks (Intel® MKL-DNN) directly and making sure PyTorch is ready for our next generation of performance improvements both in software and hardware through the nGraph Compiler.
Healthcare workloads, particularly in medical imaging, may use more memory than other AI workloads because they often use higher resolution...
Intel, Dell, and researchers at the University of Florida have collaborated to help data scientists optimize the analysis of healthcare...
The AWS DeepComposer keyboard announced at AWS re:Invent 2019. The machine learning-enabled keyboard helps developers in the field of generative...
Most inference applications today require low latency, high memory bandwidth, and large compute capacity. With the increasing use and growing...
In my over 20 years of working with Intel, I’ve learned something very important: moving an industry forward is not...
We began the Computer Vision Annotation Tool (CVAT) project a few years ago in order to speed up the annotation...
The Apache MXNet community recently announced the v1.5.0 release of the Apache MXNet* deep learning framework. This version of Apache...
With an all-new architecture that maximizes the re-use of on-die data, the Intel® Nervana™ NNP-T was purpose-built to train complex...