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

Computational Storage Reinvigorates Storage in a Novel Way

In this special guest feature, Scott Shadley, VP at NGD Systems, discusses the SNIA Computational Storage (CS) working group’s technical progress since its inception and how they plan to make computational storage mainstream over the next year. The group just finished a long, painstaking process to establish formal definitions and terminology to properly categorize and standardize computational storage technologies. This work was done by the body’s over 40 participating companies and 148 individual members.

10 Kubernetes Features You Must Know About

In this contributed article, technology writer Gilad David Maayan provides some of the more advanced functionalities and features of Kubernetes to help you get more from your configuration. Kubernetes (k8s) has become key to some of the biggest operations in the world, including Google, Shopify, and Slack. K8s has enabled companies to take advantage of cloud computing in a way that was previously not possible, and it might be able to do the same for big data.

2nd Generation Intel® Xeon® Platinum 9200 Processors Offer Leadership Performance, and Advance AI

Simulation, modeling, data analytics, and other workloads commonly use high performance computing (HPC) to advance research and business in many ways. However, as converged workloads involving AI grow in adoption, HPC systems must keep pace with evolving needs. 2nd Generation Intel® Xeon® Platinum processors, with built-in AI acceleration technologies, offer leadership performance to speed the most demanding HPC workloads.

Using Artificial Intelligence to Revolutionize Art Discovery

AI has touched just about every industry and discipline known to mankind, but how about the arts? Enter Artrendex and its ArtPI, a new interface or API driven by artificial intelligence that’s poised to transform the way art gets discovered, displayed, and sold. It promises to transform art discovery the way Shazam transformed music discovery.

How to Ensure Data Quality for AI

In this special guest feature, Wilson Pang, CTO of Appen, offers a few quality controls that organizations can implement to allow for the most accurate and consistent data annotation process possible. When we talk about quality training data, we’re talking about both the accuracy and consistency of those labels. Accuracy is how close a label is to the truth. Consistency is the degree to which multiple annotations on various training items agree with one another.

Infographic: AI and the Future of Consumer Goods

AI for consumer goods starts in the supply chain. Since 2016, the use of AI in retail grew by 600%; and by 2021, customer service interactions handled by AI will grow by 400%. Are you ready for the impact of AI on your business? By 2023 we estimate that 95% of supply vendors in the consumer goods space will be leveraging AI learning – will you be one of them? The infographic below from our friends over at Noodle.ai outlines the emergence of AI in retail.

Healthy Hives: Cloud Analytics Helps Save the World’s Bee Population

In this machine learning cast study, we describe how cloud analytics technology is being applied to the Global Hive Network, an initiative to collect billions of individual data points from around the world and analyze them to understand the honeybee population’s overall health and its relationship with environments, weather patterns, forage, diseases, parasites, predator species, and pesticides.

Getting Data Scientists to Live in an IT World

In this special guest feature, Dale Kim, Senior Director, Product Marketing at Hazelcast, discusses how data scientists are a bit unique in that they have technical skills and deal heavily with data yet are not necessarily tightly integrated with the rest of the IT team. Many do not consider themselves to be coders, and do not naturally embed themselves into the IT culture and the software development lifecycle.

Interview: Tammy Wang, VP of Data Science and Engineering at Riviera Partners

I recently caught up with Tammy Wang, VP of Data Science and Engineering at Riviera Partners to discuss her company’s partnering with the University of Virginia Economics department to build an AI-powered application that can help people successfully navigate STEM career paths, with a focus on developing a long-term career trajectory in tech. The solution has the potential to impact U.S. labor supply by addressing the increasing demand for technology talent, which has resulted from the rapid digitization and automation of the labor market.