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

No degree? No Problem: US Employers Shifting Hiring Mentality for Data Skills

Job seekers owning demonstrable experience with data might soon overtake those with data science degrees when it comes to the candidates global enterprises are seeking, according to a major survey of global business decision makers commissioned by data and analytics firm Qlik, on behalf of the Data Literacy Project.

Streaming Cloud Integration: Key Data Considerations for Hybrid and Multicloud Architectures

A new white paper from Striim explores why hybrid-cloud, multicloud, or inter-cloud architecture strategies all need a modern, real-time data integration solution that keeps up with the speed of business. Striim is uniquely qualified to help make the journey to cloud fast and smooth. Striim simplifies moving real-time data across a diverse set of data sources and cloud targets with high-performance, security, and reliability.

Interview: KDD2019 Co-General Chairs Ankur Teredesai & Vipin Kumar

During my trip to KDD2019 in August, I had the pleasure of sitting down to chat with the co-chairs of the conference, Ankur Teredesai and Vipin Kumar. In the interview that follows, we discuss the growth of the KDD conference over the years, and also it’s changing focus. KDD is touted as being “the premier interdisciplinary conference bringing together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.”

Research Highlight: Compressing Neural Networks with Minimal Sacrifice in Accuracy

Most data scientists soon realize that deep learning models can be unwieldy and often impractical to run on smaller devices without major modification. Our friends over at deeplearning.ai recently communicated about a group of researchers at Facebook AI Research determined a new technique to compress neural networks with minimal loss in accuracy.

Digital Transformation Projects Continue to be at Risk, Couchbase Research Finds

Despite rising optimism in digital transformation, the vast majority of organizations are still suffering failure, delays or scaled back expectations from digital transformation projects, research from Couchbase has found. In the survey of 450 heads of digital transformation in enterprises across the U.S., U.K., France and Germany, 73 percent of organizations have made “significant” or better improvements to the end-user experience in their organization through digital innovation. Twenty-two percent say they have transformed or completely “revolutionized” end-user experience, representing a marked increase over Couchbase’s 2017 survey (15 percent).

Using Artificial Intelligence to Track Birds’ Dark-of-Night Migrations

On many evenings during spring and fall migration, tens of millions of birds take flight at sunset and pass over our heads, unseen in the night sky. Though these flights have been recorded for decades by the National Weather Services’ network of constantly scanning weather radars, until recently these data have been mostly out of reach for bird researchers.

Composable Multi-Threaded Parallelism in Julia

JuliaCon 2019, held July 22-26, 2019 at the University of Maryland in Baltimore, was the biggest and best JuliaCon to date. The JuliaCon session below, “Composable Multi-Threaded Parallelism in Julia,” was presented by Jeff Bezanson and Jameson Nash (Julia Computing). The talk discusses the release of a preview of an entirely new threading interface for Julia programs: general task parallelism.

How Big Data Is Changing the Job Market

In this contributed article, Magnolia Potter explains how big data has had a significant impact on the way candidates look for jobs, as well as on how employers make hiring decisions. Also provided are some of the ways in which big data has changed the job market.

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