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insideBIGDATA Latest News – 2/18/2020

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.

“Above the Trend Line” – Your Industry Rumor Central for 2/17/2020

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.

Teacher Pay is Stagnating. Data and Analytics Could Give it a Boost

In this special guest feature, University of San Diego Assistant Professor in Economics, Alison Sanchez, argues that economic questions like how to increase teachers’ pay can be answered through large-scale data analysis. There is not one single answer or explanation behind the widespread salary drop for teachers, but data and analytics can reveal individual causes of teacher pay stagnation and provide customized solutions to address them.

Why Partnerships Beat Outsourcing In Data Labeling

In this contributed article, Mohammad Musa, Founder & CEO of Deepen AI, discusses how good data labeling leads to better results, whether it’s in autonomous cars, medical imaging, or any other industry where AI thrives. Done poorly, the entire system suffers. Inefficiencies and inaccuracies become inevitable, while major safety risks caused by poor labeling can derail an entire project.

Reality Bites: 3 Misconceptions that Can Lead to Microservice Mayhem

In this contributed article, Eric D. Schabell, Global Technology Evangelist and Portfolio Architect Director at Red Hat, discusses how microservices are core to organizations’ flexibility and agility in the digital world. But that doesn’t mean that microservices are right for every use case or even for every organization—at least, not right now.

Tomorrow’s Machine Learning Today: Topological Data Analysis, Embedding, and Reinforcement Learning

In this contributed article, editorial consultant Jelani Harper highlights how certain visual approaches of graph aware systems will significantly shape the form machine learning takes in the near future, exponentially increasing its value to the enterprise. Developments in topological data analysis, embedding, and reinforcement learning are not only rendering this technology more useful, but much more dependable for a broader array of use cases.

How Analytics is Changing the Game for Sports – and Academia

In this contributed article, Darin W. White, Ph.D., Executive Director, Center for Sports Analytics at Samford University, discusses how big data has given rise to the sports analytics major at Samford University. He explains how students are leveraging data sets to help sports organizations drive team efficiencies by informing recruitment strategy and in-game decision making and increase revenue primarily by better engaging their fans.

Businesses Building AI Applications Are Shifting to Open Infrastructure

In this special guest feature, Ami Badani, CMO of Cumulus Networks, suggests that as AI requires a lot of data to train algorithms in addition to immense compute power and storage to process larger workloads when running these applications, IT leaders are fed up with forced, expensive and inefficient infrastructure, and as a result they are turning to open infrastructure to enable this adoption, ultimately transforming their data centers.

AI Usage in Banking is Forcing the Conversation around the Ethical Use of Data

In this contributed article, Lisa Shields, Founder and Chief Executive Officer at FISPAN, dives into the ethical considerations banks must take into account when developing AI, and how they can do so responsibly. With the right business practices in place, banks can reap the benefits of AI while keeping customers in control of their data and protected from its misuse.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – January 2020

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.