Intel® Tiber™ Developer Cloud for the Edge
Get started at any stage of edge development with inference applications and deep learning models.
Latest from 2023
Explore the capabilities of newly added and some updated OpenVINO™ notebooks for generative AI (GenAI) on Intel® Developer Cloud for the Edge.
New Notebooks:
- Instruction Following Using Databricks Dolly 2.0 and OpenVINO
- Create an LLM-powered Chatbot Using OpenVINO
Updated Notebooks:
- Image Editing with InstructPix2Pix and OpenVINO
- Text-to-Image Generation with ControlNet Conditioning
- Infinite Zoom Stable Diffusion* v2 and OpenVINO
- Text-to-Image Generation with Stable Diffusion v2 and OpenVINO
- Stable Diffusion Text-to-Image Demo
- Stable Diffusion v2.1 Using Optimum for Intel and OpenVINO
- Stable Diffusion v2.1 Using Optimum for Intel and OpenVINO on Multiple Intel® Devices
Introducing the new cloud version of Deep Learning Workbench on the Intel® Developer Cloud for the Edge that makes it easy to import, optimize, and analyze the performance of AI models with Intel® Distribution of OpenVINO™ Toolkit, PyTorch*, TensorFlow*, and ONNX* (Open Neural Network Exchange).
Try this intuitive tool within your browser to bring your own AI model and visualize model-per-layer performance on the latest Intel® architecture including 4th generation Intel® Xeon® Scalable processors (formerly code named Sapphire Rapids) and Intel® Data Center GPU Flex Series within minutes.
Intel® Developer Cloud for the Edge now features the Intel® Distribution of OpenVINO™ toolkit version 2023.2.0 (the latest version). Experience the upgrade in performance on the latest hardware using the Benchmark App.
Intel® Developer Cloud for the Edge now features Intel® Distribution of OpenVINO™ toolkit version 2023.1.0 (the latest version). Experience the upgrade in performance on the latest hardware through using the Benchmark App.
Note Deep Learning Workbench is included in version 2022.1 of the toolkit.
Using the latest OpenVINO™ toolkit release, this sample application demonstrates how a smart video IoT retail solution may be created to perform a real-time queue management by using YOLOv8* medium model for object detection to enhance business productivity.
Deploy and evaluate your AI workloads on the newly hosted Intel® Core™ i7-1370PE processor.
Try It Now with the Container Playground
Intel® Developer Cloud for the Edge now features the Intel® Distribution of OpenVINO™ toolkit version 2022.3.1 LTS. Experience the upgrade in performance on the latest hardware using the Benchmark App.
Note Deep Learning Workbench is on version 2022.1 of the toolkit.
Deploy and evaluate your AI workloads on the newly hosted processors:
Using the latest OpenVINO™ release, this sample application demonstrates how a smart video IoT solution may be created to perform real-time object detection and instance segmentation with a pretrained YOLO* V8 Nano model.
Explore the capabilities of OpenVINO™ for generative AI with Stable Diffusion Jupyter* Notebook tutorials on Intel® Developer Cloud for the Edge.
Text-to-Image Generation with Stable Diffusion v2 and OpenVINO
Infinite Zoom Stable Diffusion v2 and OpenVINO
Intel® Developer Cloud for the Edge now features the latest Intel® Distribution of OpenVINO™ toolkit version 2023.0. Experience the upgrade in performance on the latest hardware via the Benchmark App
Note Deep Learning Workbench is on version 2022.1 of the toolkit.
Seamlessly develop, build, and test cloud-native container applications on various target deployment hardware. Customers from PRC now have a better user experience with reduced latency for containerized workflows.
Deploy and evaluate your AI workloads on the newly hosted Intel® Core™ i7-13700 with Intel® Arc™ A770 graphics (8 GB).
Intel® Core™ i7-13700 Processor
Analyze and evaluate updated samples or tutorials with improved throughput AI inference performance and streamlined coding.
Updated samples and tutorials with OpenVINO toolkit 2.0 APIs:
- Intruder Detection: Demonstrates how a smart video IoT solution may be created using Intel® hardware and software tools to perform intruder detection.
- Performance Comparison: Demonstrates the impact of data type and hardware selection on model performance.
- Store Aisle Monitor: Demonstrates how a smart video IoT solution may be created using Intel hardware and software tools to perform store aisle monitoring.
- Restricted Zone Notifier: Demonstrates how a smart video IoT solution may be created using Intel hardware and software tools to perform restricted zone notification
- People Counter System: Demonstrates how a smart video IoT solution may be created using Intel hardware and software tools to perform people counting.
Deploy and evaluate your AI workloads on the newly hosted Intel® Core™ i3-12300HL and Intel® Core™ i7-12800HL processors.
Deploy and evaluate your AI workloads on the newly hosted Intel® Xeon® Gold-6338N and Intel® Xeon® Gold 6448Y processors.
Bare Metal Environment: The performance metrics dashboard now adds two new metrics—Total Workload Power Consumption (kW) and Total Workload Energy Consumption (kJ)—to hardware and application-level metrics. These metrics measure workload power and energy use while an application runs to help users decide on efficient computing for their solution.
Deploy and evaluate your AI workloads on the newly hosted i9-13900TE and i7-13700TE processors.
Try It Now with the Benchmark App
Experience the upgrade in performance on our latest hardware through the Benchmark App.
Note The Deep Learning Workbench can be found in version 2022.1 of the toolkit.
Experience the new Electrocardiogram (ECG) Arrhythmia Prediction application. It uses the latest version of the OpenVINO™ toolkit for inference to predict atrial fibrillation by identifying different time-series ECG rhythmic wavelengths.
Deploy and evaluate your AI workloads on the newly hosted Intel® Xeon® Platinum 8480+ Processor.
Launch JupyterLab and Try It Now
Deploy and evaluate your AI workloads on the newly hosted Intel® Core™ i5-1250PE processor.
2022 Archive
Learn to use GStreamer* pipelines for complex media analytics tasks such as detection, classification, and tracking using Intel® Deep Learning Streamer 2022.2.
View the Tutorial
Bare Metal Environment: The performance metrics dashboard adds a new metric called Power Usage (Watts)/Time GMT to hardware and application level metrics. This metric shows CPU power use while the application is running to help users further fine-tune their workload and hardware configuration.
Try It
Analyze and evaluate updated samples or tutorials with improved throughput performance.
Tutorial with Sync OpenVINO 2.0 API:
Samples and tutorials with Async OpenVINO 2.0 APIs:
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 170
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.
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.
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.
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.
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*.
Deploy and evaluate your AI workloads on the newly hosted Intel® Xeon® D-2712T and Intel Xeon D-2796NT processors.
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.
The tutorial notebook has reusable code snippets to help you quickly create OpenVINO™ applications.
Try your own AI workloads on the newly hosted Intel Core i7 and i9 processors.
Accelerate PyTorch model inference using OpenVINO™ Integration with ONNX* Runtime for PyTorch* as an runtime provider to run on Intel® hardware.
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.
Try your own AI workloads on the newly hosted Intel Core i5 and i7 processors.
Learn the latest inference API for automatic device selection and performance hints to dynamically optimize for latency or throughput.
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.
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.
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.
These samples demonstrate Noise Suppression, Time-Series Forecasting, Object Detection with Tiny YOLO* V4 and Neural Network Compression.
Intel® Developer Cloud for the Edge has been updated with version 2022.1 of the OpenVINO™ toolkit.
Try your own AI workloads or Intel® Developer Cloud for the Edge sample applications on the newly hosted Pentium® processors.
This release adds support for Intel® Distribution of OpenVINO™ toolkit version 2021.4.2, and contains minor bug fixes and usability enhancements.
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.
2021 Archive
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.
This incremental update includes support for explainable AI for classification model types, visualization of inference results, streamlined INT8 calibration flow, and multiple UX improvements.
Seamlessly develop, build, and test cloud-native container applications on various target deployment hardware.
Use OpenVINO toolkit optimizations with TensorFlow* inference applications across a wide range of compute devices.
Intel Developer Cloud for the Edge now supports OpenVINO toolkit version 2021.4.1.
Try your own AI workloads or Intel Developer Cloud for the Edge sample applications on the newly hosted OnLogic* platforms.
Create datasets and explore the performance benefits of converting models to int8 and TensorFlow. Now includes YOLO* model support.
Explore constructing media analytics pipelines using Deep Learning Streamer in the Frictionless Retail Sample on Intel Developer Cloud for the Edge.
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.