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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.

Growth in Machine Learning: Accessibility of MLaaS and the Future of the Industry

In this special guest feature, Mateusz Czajka, Head of Technology and Product Design at Netguru, discusses how Machine Learning as a Service, or MLaaS, is completely breaking down barriers and has the potential to completely change the way we do business and make decisions –and it’s here now!

Big Data Platforms and AI Tools for Your Small Business

In this contributed article, Sheza Gary, a technical director at Algoworks, discusses how small businesses can start to seamlessly incorporate AI and big data to help reduce business overheads and increase profitability. Implementing big data and AI platforms doesn’t need to involve hiring teams of data scientists or analysts. At this point in 2019, small businesses have a wealth of out-of-the-box solutions available to them, covering a variety of use cases.

AI for Sales: Friend, Not Foe

In this contributed article, Haggai Levi, co-founder and CEO of SetSail, believes that for sales teams navigating in today’s era of ongoing technological disruption and digital transformation, to be truly successful requires a combination of machine and human intelligence.

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.

Artificial Intelligence and Natural Language in M&A: When Context Matters

In this contributed article, Ned Gannon, President of DFIN’s eBrevia subsidiary, explores how AI is proving invaluable in the legal world of mergers and acquisitions, especially in contract analysis. For large deals, the amount of time required to review decades worth of legal documentation to find an anomaly or problematic contractual provision is daunting, and something AI solutions are much better suited for.

“Above the Trend Line” – Your Industry Rumor Central for 8/27/2019

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.

Develop Multiplatform Computer Vision Solutions with Intel® Distribution of OpenVINO™ Toolkit

Realize your computer vision deployment needs on Intel® platforms—from smart cameras and video surveillance to robotics, transportation, and much more. The Intel® Distribution of OpenVINO™ Toolkit (includes the Intel® Deep Learning Deployment Toolkit) allows for the development of deep learning inference solutions for multiple platforms.

Actian Survey of IT Decision Makers Reveals Top Data Management Challenges and Industry Shift to Hybrid Data

Actian, the hybrid data management, analytics and integration company, announced the results of an IT Decision Maker (ITDM) survey. The “Actian Datacast 2019: Hybrid Data Trends Snapshot” polled over 300 IT professionals with key decision-making power in a company of at least 250 employees and asked them what their critical data management pains are.