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Akridata Launches Edge Data Platform for ‘Data-Centric AI’

SILICON VALLEY, Calif., Oct. 5, 2021 – Akridata, which calls itself a category-maker in Data-Centric AI, today announced the launch of the Akridata Edge Data Platform, which creates and manages smart data pipelines and AI workflows spanning Edge-Core-Cloud resources – an industry first. The Akridata software solves the problems that emerge when streams of rich […]

MLCommons Releases MLPerf Inference v1.1 Results 

San Francisco – September 22, 2021 – Today, MLCommons, an open engineering consortium, released new results for MLPerf Inference v1.1, the organization’s machine learning inference performance benchmark suite. MLPerf Inference measures the performance of applying a trained machine learning model to new data for a wide variety of applications and form factors, and optionally includes […]

LLNL Reports on Inaugural ML for Industry Forum

LLNL held its first-ever Machine Learning for Industry Forum (ML4I) on Aug. 10-12. Co-hosted by the Lab’s High Performance Computing Innovation Center (HPCIC) and Data Science Institute (DSI), the virtual event brought together more than 500 participants from the Department of Energy (DOE) complex, commercial companies, professional societies and academia. Industry sponsors included ArcelorMittal, Cerebras Systems, Ford Motor Company, […]

DOE Funds $16M for Scientific ML Research

Sept. 9, 2021 — Today, the U.S. Department of Energy (DOE) announced $16 million for five collaborative research projects to develop artificial intelligence (AI) and machine learning (ML) algorithms for enabling scientific insights and discoveries from data generated by computational simulations, experiments, and observations. The research projects range from single Principal Investigator (PI) to multi-PI, […]

Accelerate Artificial Intelligence Initiatives with DDN and NVIDIA at Any Scale

[Sponsored Post] In this whitepaper, DDN and NVIDIA invited ESG to interview several of their joint customers that have been running production AI environments to better understand their needs and to confirm the value that DDN and NVIDIA are providing. ESG research sheds light on the rapid rise of AI initiatives among businesses, including how businesses are leveraging AI to create value. Business have been rapidly investing in AI and ML projects because they work.

Putting Data in The Driver Seat Can Change Everything

[Sponsored Post] When you have data in the driver’s seat, it’s a smooth ride. Any other operator, you risk a bumpy experience. The explosion of Digital Transformation is driving a rapid increase in investment in artificial intelligence (AI) and machine learning (ML) technologies as enterprises seek a competitive edge.

Accelerate Artificial Intelligence Initiatives with DDN and NVIDIA at Any Scale

In this whitepaper, DDN and NVIDIA invited ESG to interview several of their joint customers that have been running production AI environments to better understand their needs and to confirm the value that DDN and NVIDIA are providing. ESG research sheds light on the rapid rise of AI initiatives among businesses, including how businesses are leveraging AI to create value. Business have been rapidly investing in AI and ML projects because they work.

Authors of AI/ML White Paper Win Annual Si2 Power of Partnerships Award

AUSTIN – July 28, 2021 – Authors of a groundbreaking Silicon Integration Initiative white paper identifying a common data model as the most critical need to accelerate artificial intelligence and machine learning in semiconductor electronic design automation are winners of the 2021 Si2 Power of Partnerships Award. The annual awards recognize the Si2 volunteer team that has […]

Registration Open for LLNL-sponsored Industrial ML Forum

Registration is open through July 29 for the first Machine Learning for Industry Forum (ML4I), a three-day virtual event starting Tuesday, Aug. 10. The event is sponsored by Lawrence Livermore National Laboratory’s High Performance Computing Innovation Center and the Data Science Institute. The forum aims to foster adoption of machine learning methods for practical industrial […]

insideHPC Guide to HPC Fusion Computing Model – A Reference Architecture for Liberating Data (Part 3)

This insideHPC technology guide, “insideHPC Guide to HPC Fusion Computing Model – A Reference Architecture for Liberating Data,” discusses how organizations need to adopt a Fusion Computing Model to meet the needs of processing, analyzing, and storing the data to no longer be static. Fusion computing provides a reference architecture with multiple configurations. “We went back to evaluate the first principles of why we store and move data. The Fusion Computing Model looks at a broader integration of capabilities to put agility back at the data center model.”