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DAOS Delivers Exascale Performance Using HPC Storage So Fast It Requires New Units of Measurement

Forget what you previously knew about high-performance storage and file systems. New I/O models for HPC such as Distributed Asynchronous Object Storage (DAOS) have been architected from the ground up to make use of new NVM technologies such as Intel® Optane™ DC Persistent Memory Modules (Intel Optane DCPMMs). With latencies measured in nanoseconds and bandwidth measured in tens of GB/s, new storage devices such as Intel DCPMMs redefine the measures used to describe high-performance nonvolatile storage.

Interview: Terry Deem and David Liu at Intel

I recently caught up with Terry Deem, Product Marketing Manager for Data Science, Machine Learning and Intel® Distribution for Python, and David Liu, Software Technical Consultant Engineer for the Intel® Distribution for Python*, both from Intel, to discuss the Intel® Distribution for Python (IDP): targeted classes of developers, use with commonly used Python packages for data science, benchmark comparisons, the solution’s use in scientific computing, and a look to the future with respect to IPD.

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.

New Stack Overflow Study of Developer Attitudes, Salaries and Demographics

Stack Overflow, the online community for developers to learn, share their knowledge and build their careers, today released the Stack Overflow Annual Developer Survey results . With more than 100,000 responses from coders in 184 countries and dependent territories, it is the most extensive survey of the programmer workforce to date.

The Difference Between Data Science and Data Analytics

In this contributed article, tech writer Rick Delgado, examines the differences between the terms: data science and data analytics, where people working in the tech field or other related industries probably hear these terms all the time, often interchangeably. Although they may sound similar, the terms are often quite different and have differing implications for business.

Ask a Data Scientist: Unsupervised Learning

Welcome back to the “Ask a Data Scientist” article series. This week’s question is from a reader who asks for an overview of unsupervised machine learning.