In this video from SC16, Dr. Eng Lim Goh from HPE/SGI discusses new trends in HPC Energy Efficiency and Deep Learning for Artificial Intelligence. “Recently acquired by Hewlett Packard Enterprise, SGI is a trusted leader in technical computing with a focus on helping customers solve their most demanding business and technology challenges.”
I recently caught up with Adam Compain, CEO of ClearMetal, to discuss how AI already is being used in the logistics industry to decipher the global supply chain’s many big data complexities.
“Presto is a perfect fit with the Teradata Unified Data Architecture, an integrated analytical ecosystem for our enterprise customers. Presto enables companies to leverage standard ANSI SQL to execute interactive queries against Hadoop data. With Presto, utilizing Teradata’s Query Grid connector for Presto, customers can execute queries that originate in Teradata Integrated Data Warehouse that join data within the IDW and Hadoop leveraging Presto.”
Glint Introduces AI-for-HR™ with Smart Alerts that Predict Business Impact of At-Risk Employee Populations in Real-Time
Glint, the real-time employee engagement platform, introduced AI-for-HR™, delivering real-time intelligence to help organizations make faster, more impactful people decisions.
Today UK startup brytlyt announced an enterprise data platform using Nvidia’s Tegra K1 superchip that offers faster, more efficient and more flexible data processing and analytics.
With the release of Intel® Cloud Edition for Lustre software in collaboration with key cloud infrastructure providers like Amazon Web Services (AWS), commercial customers have an ideal opportunity to employ a production-ready version of Lustre—optimized for business HPDA—in a pay-as-you-go cloud environment.
This week’s lustre 101 article looks at the history of lustre and the typical configuration of this high-performance scalable storage solution for big data applications.
For a long time, the industry’s biggest technical challenge was squeezing as many compute cycles as possible out of silicon chips so they could get on with solving the really important, and often gigantic problems in science and engineering faster than was ever thought possible. Now, by clustering computers to work together on problems, scientists are free to consider even larger and more complex real-world problems to compute, and data to analyze.
Most firms understand that robust enterprise risk management (ERM) will not only improve risk management; it will also help them to measure risk more accurately and develop a more sustainable business model. However, while simple in theory, ERM can sometime be difficult in practice.
“Some c-suite executives have quickly discovered the power of analytics, while others were more reluctant to embrace it. We see companies that embrace analytics across the enterprise as being more successful than their competitors. These observations have also been supported by academic studies that conclude that analytic oriented and metric driven organizations outperform those that do not embrace analytics holistically.”