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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.

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?

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’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.

NVIDIA Launches Edge Computing Platform to Bring Real-Time AI to Global Industries

NVIDIA announced NVIDIA EGX, an accelerated computing platform that enables companies to perform low-latency AI at the edge — to perceive, understand and act in real time on continuous streaming data between 5G base stations, warehouses, retail stores, factories and beyond. NVIDIA EGX was created to meet the growing demand to perform instantaneous, high-throughput AI at the edge — where data is created – with guaranteed response times, while reducing the amount of data that must be sent to the cloud.

Using Deep Learning for On-demand Expert Service Cloud for Analytics

Rumblings in the industry indicate there is a new on-demand expert service cloud for analytics. BI teams can now tap thousands of experts around the globe to quickly handle ad-hoc queries and eliminate backlog. The new technology creates a pool of analytics experts to add BI team capacity for ad-hoc analytics on data warehouses.

AI Skills — 93% of Organizations Committed to AI but Skills Shortage Poses Considerable Challenge

Most organizations are fully invested in AI but more than half don’t have the required in-house skilled talent to execute their strategy, according to new research from SnapLogic. The study found that 93% of US and UK organizations consider AI to be a business priority and have projects planned or already in production. However, more than half of them (51%) acknowledge that they don’t have the right mix of skilled AI talent in-house to bring their strategies to life.