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The Next Wave of Cognitive Analytics: Graph Aware Machine Learning

In this contributed article, editorial consultant Jelani Harper discusses a number of compelling and timely topics including manifold learning, graph embeddings, and cognitive computing.

Oracle to PostgreSQL? 6 Reasons to Make Your Open Source Migration

[SPONSORED CONTENT] In this sponsored post, Kirk Roybal, PostgreSQL Database Reliability Engineer at Instaclustr, outlines how Postgres offers some especially enticing advantages for enterprises looking to trim (if not downright slash) costs without impacting database performance. Here’s a half-dozen reasons enterprises should consider the fully open source version of Postgres as a more-than-capable Oracle replacement.

Keys to a Successful AI Program Launch

In this special guest feature, Jerry Kurtz, EVP of Insights & Data at Capgemini North America, discusses how laying the right foundation early is essential to scale AI programs in the long-term. He provides some key examples of important areas AI leaders should prioritize when kicking off their AI programs to ensure they are positioned to scale in the future.

Why Even Marketers Should Understand the Value of Machine Learning

In this contributed article, Dr. Peter Day, Chief Technology Officer at Quantcast, discusses how leading marketers are making use of widely available machine learning and AI-powered solutions that can do the hard work of spotting signals in the noise. In doing so, they are elevating the quality of their decision making and driving better results.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2021

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org 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.

The One Thing You Don’t Want to Leave Behind on Your Digital Transformation Journey: Your Data

In this special guest feature, Kevin Campbell, CEO of Syniti, argues that digital transformation is data transformation, and for enterprises to have a successful digital transformation, their data transformation must be a priority. Through trust and assurance of data, organizations will set themselves up for more efficient business outcomes, strategic planning, and positive returns.

Competitive Tech Companies Lead with Culture to Land Top Talent

In this contributed article, Danielle Jones, Director of Service Operations with Insperity, discusses how competing for high-caliber talent is one of the biggest challenges faced by tech companies of all sizes. With a strategy to prioritize company culture and cultivate a meaningful and positive employee experience, small and midsized data companies can get a head start when it comes to competing with their Big Tech counterparts.

Coming Next in Smart Farming Agronomy —Digitizing the Microbiome

In this contributed article, Bob Gunzenhauser, Agronomy Science Manager for Granular, part of Corte, explores how AI-driven tools are digitizing the soil microbiome and will eventually become another layer of data to drive precision farming. Bob shares his insights as a fifth generation farmer in Iowa who has been involved in the development of Decision Agriculture over the last 25 years, from its early days of yield monitors to today’s predictive analytics and crop modeling.

Lessons Learned: Training and Deploying State of the Art Transformer Models at Digits

In this blog post, we want to provide a peek behind the curtains on how we extract information with Natural Language Processing (NLP). You’ll learn how to appy state-of-the-art Transformer models for this problem and how to go from an ML model idea to integration in the Digits app.

A Hitchhiker’s Guide to AI that Actually Works for Business

In this special guest feature, Alex Hoff, Senior VP of Product Management & Marketing at Vendavo, believes that if you want an AI or ML solution that will be of any practical use, it needs to be a white-box model that is explainable, interpretable, and it will be both more usable and effective if it allows for human insights and intelligence to be combined with the artificial intelligence and insights – a centaur, or perhaps a cyborg.