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Why Your AI Workflow Needs Software-based Secondary Storage

In this special guest feature, Geoff Bourgeois, Co-founder and CEO of HubStor, discusses how one of the chief obstacles to executing AI is managing massive volumes of unstructured data. The trick is keeping this data intact to your AI/ML infrastructure without adding silos and layers of complexity. Secondary, scale-out, and cloud storage components are essential to large-scale AI projects, but they shouldn’t be independent silos that make it challenging to tier and recall data sets as needed.

“Above the Trend Line” – Your Industry Rumor Central for 12/31/2018

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.

Infographic: AI – The Dark Side vs. The Force for Good

There’s a lot of talk about the potential evils of artificial intelligence, but in the right hands AI can do extraordinary good. The infographic below, developed by out friends over at, explores both sides to the story.

Succeeding with AI in a Data Driven World

In this contributed article, Simon Crosby, CTO of SWIM.AI discusses how enterprises can overcome the challenges of moving AI projects from conception to production in today’s landscape. Enterprises are continuing to struggle when implementing AI projects, with an average of 1 in 3 being successful, and often taking more than 6 months to go from development to production. Learn how enterprises can succeed at AI.

Infographic: How AI helps Companies and Job Hunters Connect

The series of infographics below, developed by our friends over at, defines some of the challenges for job seekers and employers, then explains how AI may alleviate or eliminate those challenges. For example, according to an article from the Harvard Business Review, “A vast body of research shows that the hiring process is biased and unfair. Unconscious racism, ageism, and sexism play a big role in who gets hired.” With the help of AI, this bias may be on its way out.

How AI and Machine Learning Will Affect Cybersecurity

In this contributed article, front end developer Gary Stevens discusses how cybersecurity is now more proactive than reactive. A big reason why is the major advancement of artificial intelligence, machine learning, and data science. Computers are getting smarter and keeping us all safer as a result.

Why AI is the Future of Prior Auths

In this contributed article, Ron Wince, Founder/CEO of Myndshft, examines the healthcare industry in light of a powerful argument to be made that both provider organizations and health plans can reap immediate, transformative results with AI by breaking ground on the business and administrative side of healthcare. Optimizing the prior authorization process is perhaps the most compelling example.

Myths of Big Data, Analytics & AI

In this special guest feature, Nikhil Bhatia, Director of Product Management at Riversand Technologies, addresses some of the common myths and misconceptions around the areas of Big Data, Analytics & AI and presents a pragmatic approach and some best practices to apply these technologies in today’s competitive world.

Best of for AI, Machine Learning, and Deep Learning – November 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.

GridGain® Professional Edition 2.7 Introduces TensorFlow Integration, Enhanced Usability, Transparent Data Encryption at Rest

GridGain Systems, provider of enterprise-grade in-memory computing solutions based on Apache® Ignite™, announced the immediate availability of GridGain Professional Edition 2.7, a fully supported version of Apache Ignite 2.7. GridGain Professional Edition 2.7 introduces TensorFlow™ integration for enhanced training of deep learning (DL) models.