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Best of arXiv.org for AI, Machine Learning, and Deep Learning – February 2019

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.

AI Goes Mainstream

According to a recent Gartner survey, Artificial intelligence (AI) learning has moved from a specialized field into mainstream business use with 37 percent of respondents reporting their enterprises either had deployed AI or would do so shortly. WekaIO’s Barbara Murphy explores the path of artificial intelligence from the fringe to mainstream business practices. Find out what is driving AI growth and adoption.

Who is Recruiting for AI?

In this contributed article from our friends over at RS Components, we look at the important questions: The rise of AI and who’s hiring? Are you at risk of losing your job? Over the next few years we will see the impact new AI roles will have, as new developments will find their way into the home and workplace. The question is, are you ready for this technological wave artificial intelligence continues to bring?

Alegion Outlines the 4 Most Prevalent Types of AI Bias

AI systems are becoming more and more of the norm as machine and deep learning gain grown — especially within the data center and colocation markets. That said, Artificial Intelligence systems are only as good as their underlying mathematics and the data they are trained on. Download a new report from Alegion to further understand the bias behind machine learning and how to avoid four potential pitfalls.

E-Learning and Your Big Data – Effective Analysis

In this contributed article, tech blogger Katrina Hatchett discusses how Big Data can make a sizeable impact in eLearning and it can be used as part of a long term approach for problem solving in the sector. However, competently managing this valuable information will significantly enhance your organization’s ability to provide eLearning effectively.

Infographic: The Typical Data Scientist 2019

It’s hardly a surprise to anyone in the tech and related industries that “data scientist” is the best job to have these days. After all, this has been what sources like the Harvard Business Review and Glassdoor report for what is now four years in a row. And even if we take the base salary of $108,000 out of the equation, the position is still plenty attractive on all other dimensions. The infographic below, produced by our friends over at 365DataScience, suggests that the field is evolving and, with it, the typical professional evolves as well.

Global Artificial Intelligence Patent Survey

In this contributed article, Aaron Gin, Ph.D., partner and Margot M. Wilson, associate, with McDonnell Boehnen Hulbert & Berghoff LLP, explore AI-related patenting trends in various international jurisdictions and provides information on recent developments, common patentability issues, and tips for navigating similar trends in United States patent prosecution.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – January 2019

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.

Dremio Launches Free Online Training Courses for Data Engineers, Analysts, and Data Scientists

Dremio, the Data-as-a-Service Platform company, announced Dremio University, a free online training program for data engineers, analysts, and data scientists. Each Dremio University track is designed to solve today’s data challenges and help maximize the potential of Dremio’s Data-as-a-Service platform.

Field Report: H2O World 2019 San Francisco

I was pleased to be on-hand for the recent (Feb. 4-5) H2O World 2019 conference in beautiful San Francisco. This was my first H2o.ai conference and I was looking forward to drilling down into their popular open source solutions for data scientists including the H2O machine learning platform, Sparkling Water machine learning platform on Spark, H2O4GPU accelerated AI for GPUs, as well as the groundbreaking Driverless AI automatic machine learning (AutoML) platform. With all this leading-edge technology and resulting industry buzz, I can see why the company recently ranked #9 on insideBIGDATA’s IMPACT 50 list of the industry’s most impactful companies.