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

Survey Reveals Widespread Lack of IT Planning for AIOps

A recent survey of IT, business, security and operations executives shows that 76 percent of IT teams have not yet implemented artificial intelligence technologies to improve data center operations, despite the benefits of AIOps for business efficiency. In addition, just over half of survey respondents still have no budgets planned for AIOps projects in the next one to three years. Further, the survey reveals that most IT leaders are still struggling to implement effective strategies for AIOps due to a lack of clarity about their own technology expectations and business objectives.

Addressing Governmental Challenges when Engaging AI, ML and Data Analytics

Gartner recently stated that all industries and levels of government agree the top three game-changing technologies today are AI/machine learning, data analytics/predictive analytics and cloud technologies. However, there are some primary sticking points when it comes to innovation in these areas. Government organizations continue to encounter challenges when trying to pursue these initiatives due to complex security and compliance requirements, poor scalability of legacy IT infrastructure, and perceived risks associated with cloud and IT modernization efforts. How can these challenges be addressed?

AI-Driven Data Catalogs: How to Find the Right one for Your Business

The commoditization of data has opened a world of opportunities up for countless enterprises. But as big data explodes, metadata initiatives are failing, and data discovery and retrieval is getting more and more difficult. A new white paper from IO-Tahoe explores data catalogs as a potential answer to this challenge.

GE Introduces New Analytics to Advance Electric Grid Operations

GE (NYSE: GE) announced the availability of three new grid analytics that combine domain expertise with artificial intelligence (AI) and machine learning (ML) to tackle pressing challenges in electric grid operations. The new portfolio uses data from across transmission and distribution networks to help achieve goals for operational efficiency.

“Above the Trend Line” – Your Industry Rumor Central for 6/12/2019

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.

Interview: Atif Kureishy, Global VP, Emerging Practices at Teradata

I recently caught up with Atif Kureishy, Global VP of Emerging Practices at Teradata, during the 2019 edition of the NVIDIA GPU Technology Conference, to get a deep dive update for how Teradata is advancing into the fields of AI and deep learning. He also speaks about the ways Teradata and NVIDIA are accelerating time to value for enterprise AI environments and gathering financial services insights from GPUs.

How AI Technologies Can Put Purpose and Profit into ESG Investments

In this contributed article, Ruggero Gramatica, Founder and CEO of Yewno, discusses how institutional investors can increase financial returns and make better investment decisions in the field of environment, social, and governance (ESG) investing.

AI-Driven Data Catalogs for the Insights-Driven Enterprise: How to Find the Right Data Catalog

Data lakes have turned into data swamps. Metadata initiatives have derailed. As a result, data discovery and retrieval are ongoing, head-banging challenges. In the universal search for a workable solution, data catalogs are quickly rising to the top of the list. Download the new report from Io-Tahoe that outlines some of the major considerations to help you find the AI-driven data catalog that will work best for your organization. 

AI’s Role in Unleashing Intelligent Sensing

The rise of artificial intelligence (AI) is unlocking a wave of new sensor applications and driving market demand for intelligent sensing – the ability to extract insights from sensor data. To guide innovation and investment in this fast-evolving market, the team at Lux Research, a leading provider of tech-enabled research and advisory services for technology innovation, took a deep dive into how and where enhanced AI analytics are rapidly improving the capabilities of software-defined sensors.