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Develop Multiplatform Computer Vision Solutions with Intel® Distribution of OpenVINO™ Toolkit

Realize your computer vision deployment needs on Intel® platforms—from smart cameras and video surveillance to robotics, transportation, and much more. The Intel® Distribution of OpenVINO™ Toolkit (includes the Intel® Deep Learning Deployment Toolkit) allows for the development of deep learning inference solutions for multiple platforms.

The AI Opportunity

The tremendous growth in compute power and explosion of data is leading every industry to seek AI-based solutions. In this Tech.Decoded video, “The AI Opportunity – Episode 1: The Compute Power Difference,” Vice President of Intel Architecture and AI expert Wei Li shares his views on the opportunities and challenges in AI for software developers, how Intel is supporting their efforts, and where we’re heading next.

Fast-track Application Performance and Development with Intel® Performance Libraries

Intel continues its strident efforts to refine libraries optimized to yield the utmost performance from Intel® processors. The Intel® Performance Libraries provide a large collection of prebuilt and tested, performance-optimized functions to developers. By utilizing these libraries, developers can reduce the costs and time associated with software development and maintenance, and focus efforts on their own application code.

Supercharge Data Science Applications with the Intel® Distribution for Python

Intel® Distribution for Python is a distribution of commonly used packages for computation and data intensive domains, such as scientific and engineering computing, big data, and data science. With Intel® Distribution for Python you can supercharge Python applications and speed up core computational packages with this performance-oriented distribution. Professionals who can gain advantage with this product include: machine learning developers, data scientists, numerical and scientific computing developers, and HPC developers.

DarwinAI Generative Synthesis Platform and Intel Optimizations for TensorFlow Accelerate Neural Networks

DarwinAI, a Waterloo, Canada startup creating next-generation technologies for Artificial Intelligence development, announced that the company’s Generative Synthesis platform – when used with Intel technology and optimizations – generated neural networks with a 16.3X improvement in image classification inference performance. Intel shared the optimization results in a recently published solution brief.

Using Converged HPC Clusters to Combine HPC, AI, and HPDA Workloads

Many organizations follow an old trend to adopt AI and HPDA as distinct entities which leads to underutilization of their clusters. To avoid this, clusters can be converged to save (or potentially eliminate) capital expenditures and reduce OPEX costs. This sponsored post from Intel’s Esther Baldwin, AI Strategist, explores how organizations are using converged HPC to combine HPC, AI, and HPDA workloads.

Intel’s AI Lab Presents Several Ground-breaking Research Papers

Researchers at Intel’s AI Lab recently presented several compelling research papers at the International Conference on Machine Learning (ICML) (June 10-15) and the Conference on Computer Vision and Pattern Recognition (CVPR) June 16-20.

Intel IT Serves Up Innovative Applications of AI, Analytics and Collaboration

One telling sign that AI industry leading companies truly believe in the technologies they promoting across the globe is how much they’re using these same technologies internally. An excellent case-in-point is Intel IT, the IT services arm of giant Intel Corp.

Redis Labs Delivers the Fastest Multi-Model Database on Intel® Optane™ DC Persistent Memory

Redis Labs, the home of Redis and provider of Redis Enterprise, announced that Redis Enterprise is now available for Intel® Optane™ DC persistent memory across multiple cloud services or as downloadable software for supported hardware from companies participating in Intel’s hardware beta program.

Exploring the Convergence of AI, Data and HPC

The demand for performant and scalable AI solutions has stimulated a convergence of science, algorithm development, and affordable technologies to create a software ecosystem designed to support the data scientist. A special insideHPC report explores how HPC and the data driven AI communities are converging as they are arguably running the same types of data and compute intensive workloads on HPC hardware, be it on a leadership class supercomputer, small institutional cluster, or in the cloud.