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Job of the Week: Software Engineer for Perception Infrastructure at Argo AI

Argo AI in Pittsburgh is seeking a Software Engineer for Perception Infrastructure in our Job of the Week. “With offices in Pittsburgh, the Bay Area of California, Southeastern Michigan and Central New Jersey, we are building a high-performance team that is excited by complex engineering challenges and is passionate about making transportation safer, more affordable and accessible for all.”

Can we use Machine Learning to Learn about Machines?

In this special guest feature, Ellexus CEO Rosemary Francis writes that the convergence of HPC and Ai is already changing the landscape in the world of supercomputing. “It is only as machines get faster that they are able to get cleverer. This means that more and more industries are becoming interested in making supercomputers even more powerful and investment in the exascale goal will increase.”

Survey Foretells Explosive Growth in Machine Learning Projects Over Next Two Years

Over at the Univa Blog, Gary Tyreman writes that the company sponsored an industry-wide survey to better understand what key challenges our HPC users are currently facing that are preventing them from moving their machine learning (ML) projects into production. “Our goal is to use this data to help guide our customers and recommend the right set of tools and migration options needed to accelerate value in machine learning.”

How AI is Changing the Media & Entertainment Industry

This insideHPC guide series explores how artificial intelligence is revolutionizing and evolving the media and entertainment industries. To get things started, this post offers up an overview of how AI is impacting the entertainment industry and the future of these sectors. 

Video: How Governments Can Get Involved in Artificial Intelligence

In this episode of Ai News, David Shaw examines the question: is Ai tangible or realistic? “Naveen believes that we have to start at the beginning, in elementary schools, and try to model curriculum with AI in mind. Just as kids learn skills like typing in school, they might also gain some guided computational skills. When it comes to STEM, more schools can try to incentivize students to excel in these fields by providing more grants and scholarships.”

Architectural Considerations for AI Workloads in Technical Computing

New workloads in machine learning and analytics have placed significant burdens on traditional HPC systems. This guest post explores how HPE, Intel and WekaIO are working together to solve potential I/O bottlenecks in machine learning and AI workloads. 

Revolutionizing the Media and Entertainment Industry through Artificial Intelligence

From the creative process behind the scenes, to content delivery and audience engagement, artificial intelligence is having a profound effect on the media and entertainment industry. Download the new insideHPC guide, brought to you by Dell EMC and Nvidia, to learn more about how AI is revolutionizing this sector.

Scale Your HPC Environment for AI Workloads

In this guest post, Intel Data Center Group’s Trish Damkroger covers how to scale your HPC environment for AI workloads. “Intel’s HPC interoperable framework assists developers with tools to modernize applications for advanced workloads and support for development languages like Python, C++, and Fortran.”

New Modular Lenovo ThinkSystem Accelerates Ai Performance

Over at the Lenovo Blog, the company has unveiled a new ThinkSystem based on a modular infrastructure targeted at Ai workloads. “By developing the ThinkSystem SR670 platform with integrated modularity, Lenovo has recognized that technologies around the CPU are evolving rapidly and driving massive performance gains for many types of workloads. System designs need to evolve to provide the capability and flexibility for customers to add more revolutionary technologies to the system faster. Customers shouldn’t be gated by a system that can’t change and grow with them as they build their intelligence platforms of the future.”

Video: Overview of Machine Learning Methods

“Machine learning enables systems to learn automatically, based on patterns in data, and make better searches, decisions, or predictions. Machine learning has become increasingly important to scientific discovery. Indeed, the U.S. Department of Energy has stated that “machine learning has the potential to transform Office of Science research best practices in an age where extreme complexity and data overwhelm human cognitive and perception ability by enabling system autonomy to self-manage, heal and find patterns and provide tools for the discovery of new scientific insights.”