Intel® Developer Cloud for the Edge

Announcements

Deploy and evaluate your AI workloads on the newly hosted Intel® Data Center GPU Flex Series 170. The GPU is optimal for pipelines that include more complex AI models, such as multiple object detection or multiple classification models.

Learn More about Intel® Data Center GPU Flex Series

Launch JupyterLab and Try It Now

Learn to deploy an industrial computer vision model to detect real-world analog pointer meters and extract corresponding digital readings using the Intel® Distribution of OpenVINO™ toolkit.

View Industrial Meter Reader

Deploy and evaluate your AI workloads on the newly hosted Intel® Data Center GPU Flex Series 140. With higher number of video encode and decode engines, this GPU can support a high number of streams for AI inferencing workloads.

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Intel® Deep Learning Streamer (Intel® DL Streamer) code snippets are small blocks of reusable code that can be inserted in a Jupyter* Notebook for detection, classification, and tracking applications on Intel® Developer Cloud for the Edge workloads using the OpenVINO™ toolkit. Use the tag ‘DL Streamer_LTS’ to filter out the Intel DL Streamer code snippets.

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Intel® Developer Cloud for the Edge now features the Intel® Distribution of OpenVINO™ toolkit version 2022.2. 

Note  Deep Learning Workbench is on version 2022.1 of the toolkit. 

View Release Notes

Analyze and evaluate newly added samples: Image Classification Using ResNet-50 and Sequence Classification Using BERT to Accelerate PyTorch* Model Inference Using OpenVINO™ Integration with ONNX* Runtime for PyTorch*. 

View Sample

Deploy and evaluate your AI workloads on the newly hosted Intel® Xeon® D-2712T and Intel Xeon D-2796NT processor systems.

Quickly browse, import, or export your AI models and test data from Amazon S3 buckets to optimize and evaluate inference performance on Intel® hardware within Intel® Developer Cloud for the Edge.

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The tutorial notebook has reusable code snippets to help you quickly create OpenVINO™ applications.

Try It Out

Try your own AI workloads on the newly hosted Intel Core i7 and i9 processor systems.

Accelerate PyTorch model inference using OpenVINO™ Integration with ONNX* Runtime for PyTorch* as an runtime provider to run on Intel® hardware.

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This solution uses the Intel® Deep Learning Streamer and Intel® Distribution of OpenVINO™ toolkit to identify people and determine social distance in crowded public spaces. 

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Try your own AI workloads on the newly hosted Intel Core i5 and i7 processor systems.

Learn the latest inference API for automatic device selection and performance hints to dynamically optimize for latency or throughput.

View Sample

New notebooks demonstrate brain tumor segmentation, classification, object detection, and style transfer in French and German languages.

This incremental update includes support for text classification models, OpenVINO™ API 2.0 enabled in tools, Cityscapes Dataset, and initial support for natural language processing (NLP) models. 

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Code snippets are small blocks of reusable code that can be inserted in a Jupyter* Notebook to aid and accelerate coding of sample applications on Intel® Developer Cloud for the Edge workloads using the OpenVINO™ toolkit.

Launch JupyterLabs and Try It Now

Now you can import and securely launch HELM charts, Docker* Compose images, and containers on Intel® hardware in the new Kubernetes* environment. Explore, edit, and test OpenVINO™ toolkit sample applications with JupyterLab, and optimize AI models with the improved Deep Learning Workbench.

Intel® Developer Cloud for the Edge has been updated with version 2022.1 of the OpenVINO™ toolkit.

Release Notes

Try your own AI workloads or Intel® Developer Cloud for the Edge sample applications on the newly hosted Pentium® processor systems.

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This release adds support for Intel® Distribution of OpenVINO™ toolkit version 2021.4.2, and contains minor bug fixes and usability enhancements.

Get Started  

This latest version allows you to do out-of-the-box benchmarking, measure the accuracy of your model, and perform comprehensive comparison of accuracy between floating point and int8 models and more.  

Get Started

Provides an enhanced experience when working with sample, tutorial and prototype notebooks.

Intel® Developer Cloud for the Edge now features the Intel Distribution of OpenVINO toolkit version 2021.4.2.

Release Notes

This incremental update includes support for explainable AI for classification model types, visualization of inference results, streamlined INT8 calibration flow, and multiple UX improvements. 

Get Started

Seamlessly develop, build, and test cloud-native container applications on various target deployment hardware. 

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Use OpenVINO toolkit optimizations with TensorFlow* inference applications across a wide range of compute devices.

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Intel Developer Cloud for the Edge now supports OpenVINO toolkit version 2021.4.1.

Release Notes

Try your own AI workloads or Intel Developer Cloud for the Edge sample applications on the newly hosted OnLogic* platforms.

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Create datasets and explore the performance benefits of converting models to int8 and TensorFlow. Now includes YOLO* model support.

Try It Now 

Explore constructing media analytics pipelines using Deep Learning Streamer in the Frictionless Retail Sample on Intel Developer Cloud for the Edge.

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Intel® Developer Cloud for the Edge—Developer Journeys

Get Started

The Intel® Developer Cloud for the Edge is designed to help you evaluate, benchmark, and prototype AI and edge solutions on Intel® hardware for free.

To get started, choose the environment or solution that best meets your goals.

Learn, Prototype, and Optimize with JupyterLab on Bare Metal Hardware

Rapidly prototype and test edge software workloads on Intel® CPUs, GPUs, and VPUs using Python* and our preinstalled libraries, code snippets, sample applications, tutorials, and developer tools.

 

Get Started with JupyterLab 
View Tutorials
Browse Sample Applications
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Run Containerized Workloads Powered by Red Hat* OpenShift* Platform

The Container Playground powered by Red Hat* OpenShift* platform enables you to seamlessly develop, build, and test Kubernetes*-based, cloud native container applications on Intel® hardware.

 

  • Import from a prebuilt library, container registry, or Helm* chart
  • Build and run containers from Git repositories
  • Evaluate on Intel® architecture
  • Gain insights through telemetry

 

Get Started
Developer Guide
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Additional Developer Solutions

Edge for Industrial

Speed up development of industrial solutions with pre-validated software packages for machine learning, data analytics, and software-defined control at the edge.

OpenVINO™ Integration with TensorFlow*

This solution is designed for developers who want to use built-in TensorFlow* models in their OpenVINO™ toolkit inferencing applications. In most cases, OpenVINO™ integration with TensorFlow* can be accomplished with just two lines of code.

Deep Learning Workbench

The Deep Learning Workbench simplifies using the Intel® Distribution of OpenVINO™ toolkit to tune, visualize, and compare the performance of deep-learning models on Intel® architecture.

Post-Training Optimization Tool

Accelerate the inference of deep-learning models without retraining. The Post-Training Optimization Tool (POT) offers a suite of tools that let you automate the model transformation process without changing model structure.

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Hardware Available For Edge Workloads

Test your workload performance with combinations of CPUs, GPUs, and accelerators in bare metal and cloud-native container architectures to identify the hardware platform that works best for your inferencing solutions.

Explore All Hardware

Move from Prototype to Production

Take your product from prototype to production with downloadable solutions from the Intel® Developer Catalog, and procure hardware from Intel's ecosystem of hardware partners.

Development Kits

Jump-start your application development with the latest foundational kits with an option to include an Intel® Vision Accelerator Design product.

Browse All Kits

Intel® Developer Catalog

This development resource offers computer vision and deep learning solutions to try in the Container Playground, which uses the Red Hat OpenShift platform, to install and deploy to the network edge.

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Ecosystem Partners

Run your workloads or run a sample from Intel on partner hardware hosted within Intel Developer Cloud for the Edge.

Visit Partner Program