“Try before you buy.” The Intel® DevCloud for the Edge allows you to actively prototype and experiment with AI workloads for computer vision on Intel hardware.

No hardware setup required on your end. The Intel® DevCloud for the Edge utilizes Jupyter* Notebooks to execute code directly within the Web browser. Jupyter* is a browser-based development environment which allows you to run code and immediately visualize results.

You have full access to hardware platforms hosted in our cloud environment, designed specifically for deep learning. You can test the performance of your models using the Intel® Distribution of OpenVINO™ Toolkit and combinations of CPUs, GPUs, VPUs such as the Intel® Neural Compute Stick 2 (NCS2) and FPGAs, such as the Intel® Arria® 10. The Intel® DevCloud for the Edge contains a series of Jupyter* notebook tutorials and examples preloaded with everything you need to quickly get started. This includes trained models, sample data and executable code from the Intel® Distribution of OpenVINO™ Toolkit as well as other tools for deep learning. These notebooks are designed to help you quickly learn how to implement deep learning applications to enable compelling, high-performance solutions.

The Intel® DevCloud for the Edge consists of:

• A development environment with which you interact to develop code and submit compute jobs.
• Edge devices, upon which you can run and test edge workloads.
• Storage servers that provide a network-shared filesystem such that all of your data is accessible at the same path from any machine in the cloud.
• Queue server with which you interact to submit compute jobs to edge devices.
• UI software that allows you to access the Intel® DevCloud resources from a web browser.

Sign Up and Try Now!

See exactly what Hardware is currently available here

Ready to get started with your own Intel® devices?

Find out more and deploy your containers through Cloud to Edge flow from Azure ML to the Edge here.

Intel® DevCloud for the Edge now supports ONNX Runtime + Intel® Distribution of OpenVINO™ Toolkit. Learn more here.