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The latest big data news and articles

“Above the Trend Line” – Your Industry Rumor Central for 9/17/2018

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.

Alegion Announces Next-Generation Training Data Platform for Enterprise AI Initiatives

Alegion, a training data platform for artificial intelligence (AI) and machine learning initiatives, announced the release of its next-generation platform with new features designed to enhance the quality and efficiency of large-scale machine learning initiatives and deliver model confidence for enterprise AI systems.

SAP Helps Business Users Make Fast, Confident Decisions with One Simple Cloud for All Analytics

SAP SE (NYSE: SAP) announced SAP Analytics Cloud is now available with new machine learning features to uncover correlations in an organization’s data and help users make faster, more confident decisions.

Pure Storage Introduces Data Hub Architecture

Pure Storage (NYSE: PSTG), the all-flash storage platform that helps innovators build a better world with data, introduced a data hub, the company’s vision to modernize storage architecture for unstructured, data-intensive workloads. Built on Pure Storage FlashBladeTM, Pure’s data hub is designed to be truly data centric and enable organizations to effectively utilize today’s most critical currency – data.

Ethics and the Pursuit of AI

In this contributed article, marketing specialist Sophie Ross discusses the center-stage question: What are the ethical implications of artificial intelligence and its applications? She suggests that there has to be a balanced approach to any technology. Humans should have ultimate control over the use, misuse and abuse of the technology so that the ultimate accountability can be fixed for any excesses.

Neural Attention Please, or How Attention Models Can Work for You

In this contributed article, Mikhail Konstantinov, a Data Scientist at ELEKS, discussed the real and potential business uses of the neural attention – a mechanism that enabled machine learning algorithms to select and work with certain pieces of data at a certain moment.

Automation Promises to Pull Big Data Out of Its “Dial-Up” Phase

In this special guest feature Ramesh Menon, Head of Products at Infoworks, discusses how big data is in a predicament, with great promise, and with plenty of innovation at work. But much of it is behind the scenes, and much of that is still surprisingly limited. In a way, big data is trying to break out of the “for developers only” mold the same way ARPANET—the precursor to the web—had to evolve to appeal to more than just computer scientists.

Best of for AI, Machine Learning, and Deep Learning – August 2018

In this recurring monthly feature, we will filter all the recent research papers appearing in the preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

Fundamentals in the Oil Field Matter Even More with Big Data

In this contributed article, Shiva Rajagopalan, President and CEO of Seven Lakes Technologies, discusses how big data is being used and what the opportunities are in the billion dollar oil & gas industry. The objective for success is straightforward for the oil and gas operations: bring the usefulness of data out of the office and make it all about the field.

FICO Makes Artificial Intelligence Explainable with Latest Release of its Analytics Workbench

Leading analytics firm FICO announced the latest version of FICO® Analytics Workbench™, a cloud-based advanced analytics development environment that empowers business users and data scientists with sophisticated, yet easy-to-use, data exploration, visual data wrangling, decision strategy design and machine learning.