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insideBIGDATA Latest News – 9/12/2020

In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.

The Zenith of Natural Language Technologies: Conversational AI

In this contributed article, editorial consultant Jelani Harper discusses how the junction of natural language capabilities enables what Arria NLG CEO Sharon Daniels termed “answers on demand”, which is pivotal for interacting with analytics, Business Intelligence, and workflows in a rapid, conversational manner that’s influential for setting the pace of business today.

MLOps Graduates to Enterprise Model Management (and what that means for global enterprise)

In this special guest feature, Mrinal Chakraborty, DISC Solution Leader at Pactera EDGE, discusses six core aspects of MLOps which are augmenting Enterprise Model Management. The MLOps market will be over $4 Billion in just a few years, and promises to be a major component of the AI solution landscape shortly – but many enterprises are slow to evolve to machine learning lifecycle management which promises to make ML more reliable by defining the processes of its development and deployment.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2020

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.

HuBMAP Inaugural Data Release Puts Detailed Anatomical Data about Seven Human Organs at the Service of Scientists, Public

HuBMAP (the Human BioMolecular Atlas Program) has released its inaugural data for use by the scientific community and the general public. Included in this release are detailed, 3D anatomical data and genetic sequences of healthy tissues from seven organ types, at the level of individual cells as well as many bulk tissue data sets. HuBMAP’s ultimate goal is to provide the framework required for scientists to create a 3D atlas of the human body.

Starting A Successful AIOps Initiative

In this special guest feature, Hari Miriyala, VP Software Engineering at cPacket Networks, discusses how many enterprises are considering or deploying AI/ML tools to make their IT team more efficient, reduce troubleshooting time, or improve their organization’s security. But without the right foundation of accurate, precise and consistent input data, this move to AIOps provides little value.

Video Highlights: BigQuery + Notebooks: Building an Analytics Pipeline on Kaggle

Your architecture choices impact how efficiently you’re able to use your data. In this “Snapshots” video produced by Kaggle, Data Scientist Wendy Kan demonstrates how she incorporates BigQuery and Kaggle Notebooks into her workflow. Watch her create an interactive network analysis graph that explores the most commonly installed Python packages!

“Above the Trend Line” – Your Industry Rumor Central for 9/4/2020

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.

TOP 10 insideBIGDATA Articles for August 2020

In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels.

How Do We Make It Easier To Trust?

In this contributed article, Sean Beard, Vice President at Pariveda Solutions, discusses how automating trust presents a new set of challenges to an organization due to the subject nature of trust. Businesses must develop a better understanding of bias in their data and how different business contexts are applied to that data. With ample misinformation surrounding us all of the time, using AI machine learning, and human oversight, organizations can gain a clearer understanding of what information they can trust and what they can’t.