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Heard on the Street – 5/19/2022

Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.

insideBIGDATA Latest News – 5/11/2022

In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.

Intel’s Habana Labs Launches Second-Generation AI Processors for Training and Inferencing

Intel announced that Habana Labs, its data center team focused on AI deep learning processor technologies, launched its second-generation deep learning processors for training and inference: Habana® Gaudi®2 and Habana® Greco™. These new processors address an industry gap by providing customers with high-performance, high-efficiency deep learning compute choices for both training workloads and inference deployments in the data center while lowering the AI barrier to entry for companies of all sizes.

Heard on the Street – 5/10/2022

Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.

Increase Speed-to-Value with Data Science as a Service

In this contributed article, Tom Martin, data science team leader at E Source discusses Data Science as a Service (DSaaS), a comprehensive package of data science resources and capabilities – think people, algorithms, data, and a cloud-based platform for starters – that enables companies who want to become more data-driven to accomplish that in partnership with experts in a flexible, organic way that accelerates speed-to-value. 

Introducing Innodata’s New AI Data Marketplace

Innodata is excited to announce its new Innodata AI Data Marketplace – an e-commerce portal where users can purchase on-demand datasets to accelerate AI/ML model building and training. With easy access to curated, industry-leading datasets, data science teams can now overcome persistent data challenges that often hamper AI initiatives, such as volume, variety, and privacy constraints. 

Research Highlights: Transformer Feed-Forward Layers Are Key-Value Memories

In this regular column, we take a look at highlights for important research topics of the day for big data, data science, machine learning, AI and deep learning. It’s important to keep connected with the research arm of the field in order to see where we’re headed. In this edition, if you (like me) have wondered what the feed-forward layers in transformer models are actually doing, this is a pretty interesting paper on that topic. Enjoy!

“Above the Trend Line” – Your Industry Rumor Central for 5/5/2022

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

Galileo Launches to Give Data Scientists the Superpowers They Need for Unstructured Data Machine Learning

Galileo emerged from stealth with the first machine learning (ML) data intelligence platform for unstructured data that gives data scientists the ability to inspect, discover and fix critical ML data errors 10x faster across the entire ML lifecycle – from pre-training to post-training to post-production. The platform is currently in private beta with the Fortune 500 and startups across multiple industries.

New Streamlined Statistical Method Provides Improved Pattern Detection and Risk Prediction for Disease

Researchers from the Renaissance Computing Institute (RENCI) at UNC-Chapel Hill, Perspectrix, the UNC School of Medicine, and the WVU Rockefeller Neuroscience Institute have collaborated to develop a new method for finding patterns in data which arguably surpasses the performance of a generally accepted “gold standard.”