Intel® DevCloud: Edge Workloads
Choose Your Environment
Intel® DevCloud for Edge Workloads has two primary pathways designed to help you evaluate, experiment with, and prototype AI and Edge solutions on Intel® hardware for free.
Interactive Prototyping & Benchmarking Environment Using JupyterLab
Follow tutorials to interactively learn to create, tailor, and benchmark computer vision and edge AI applications optimized for Intel hardware.
Explore sample applications for illustrations of market-specific solutions and methods for optimizing, tuning, and accelerating applications at the edge.
Quickly get started with the following resources in the edge development sandbox:
- Jupyter* Notebook-based tutorials and sample applications
- Pretrained models
- Sample data
- Executable code from the Intel® Distribution of OpenVINO™ toolkit
- Tools for tuning and optimizing your models
- Code snippets for rapid prototyping
- Ability to run your workload on a wide range of hardware configurations consisting of CPUs, GPUs, VPUs, and FPGAs
Containerized Environment
Launch and experiment with containerized workloads on a wide range of Intel hardware in the Container Playground, a Kubernetes* environment.
Training & Documentation
Container Playground
Learn how to build, import, and launch cloud-native container applications on a variety of target hardware for your prototyping and testing goals.
Container-based Workloads
Documentation
Videos
Get Started with the Container Playground for Intel DevCloud
Evaluate Containers on the Latest Intel Hardware
Run Workloads with JupyterLab
Learn how to use a bare metal sandbox environment to develop, prototype, and test workloads with JupyterLab.
Documentation
Prototype and Benchmark with JupyterLab* on Bare Metal Infrastructure
Videos
Learn More about AI at the Edge
Optimize your machine-learning solutions for Intel hardware.
Advance your career and get recognized for your new, marketable skills with Intel® Edge AI Certification.