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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.

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.

Julia: The Programming Language Of The Future

Keno Fischer, Julia Computing co-founder and CTO (Tools) discussed Julia and Julia Computing in a recent interview. Learn how he became interested in computer science and how Julia was created, and how a 16 year-old German exchange student became a 19 year-old co-founder of Julia Computing. Keno shares stories behind the creation of the popular […]

Why Music Makes Us Feel, According to AI

Your heart beats faster, palms sweat and part of your brain called the Heschl’s gyrus lights up like a Christmas tree. Chances are, you’ve never thought about what happens to your brain and body when you listen to music in such a detailed way. But it’s a question that has puzzled scientists for decades: Why does something as abstract as music provoke such a consistent response? In a new study, a team of USC researchers, with the help of artificial intelligence, investigated how music affects listeners’ brains, bodies and emotions.

AutoML in Practice

The compelling Oct. 15, 2019 presentation below is on behalf of one of my favorite Meetup groups: LA Machine Learning. The talk, “AutoML in Practice,” is by Danny D. Leybzon, a Solutions Architect at Qubole, a cloud-native big data platform. Automated Machine Learning (AutoML) is one of the hottest topics in data science today, but what does it mean? This presentation gives a broad overview of AutoML, ranging from simple hyperparameter optimization all the way to full pipeline automation.

Competition Uses AI to Combat Inequities in Early Childhood Education

Booz Allen Hamilton, Kaggle and PBS KIDS launched the fifth annual Data Science Bowl. This 90-day competition challenges thousands of data scientists and researchers from around the world to apply the power of artificial intelligence to combat inequities in early childhood education (ECE). More specifically, participants will create AI algorithms using anonymous gameplay data from the PBS KIDS Measure Up! App, which helps young children build math skills, to better understand children’s unique learning styles.

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

New Survey: Nearly Two Thirds of Analytics Projects Are Jeopardized Due to Poor Access to the Right Data

According to the 2019 Data Decisions Survey from analytics database provider Exasol, 57% of organizations have suffered because of slow or poor access to the right data, resulting in an inability to access real-time analytics and inaccurate business intelligence (BI). Full results of the survey, recently released, highlight how organizations are leveraging data to make more intelligent and productive business decisions.

Wearable AI Market to Cross USD 180 Billion Frontier by 2025

The Wearable AI Market is set to grow from its current market value of more than USD 35 billion to over USD 180 Billion by 2025; as reported in the latest study by our friends over at Global Market Insights, Inc. The explosive growth of smartwatches has been the primary factor propelling the wearable AI market. Continuous improvements in the design and functionality along with its availability at lower price increased its adoption among consumers.

Atos Unveils North American Google Cloud Artificial Intelligence Lab

Atos, a global leader in digital transformation launched its Google Cloud Artificial Intelligence (AI) Lab at its North American Headquarters in Irving, Texas, as part of a global partnership between Atos and Google Cloud to provide clients and businesses access to the latest analytics technologies. The Atos AI lab in North America is the latest lab and a part of a global network with other labs in London, Paris and Munich.