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State of Data Science, Engineering & AI Report – 2019

Our friends over at Diffbot, using the Diffbot Knowledge Graph, and in only a matter of hours, conducted the single largest survey of machine learning skills ever compiled in order to generate a clear, global picture of the machine learning workforce. All of the data contained in the “State of Data Science, Engineering & AI Report – 2019” was pulled from the company’s structured database of more than 1 trillion facts about 10 trillion entities (and growing autonomously every day).

The insideBIGDATA IMPACT 50 List for Q3 2019

The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting the enterprise through leading edge products and services. We’re happy to publish this evolving list of the industry’s most impactful companies!

Algorithms: Not Evil, Helpful

INFORMS member Gah-Yi Ban of the London Business School breaks down what algorithms are and how they are useful in a unique talk at a TEDx event. She compares algorithms to evil beings and says it’s a common misconception. Ban helps people understand the role of algorithms in our present lives and how we can shape their role in our future.

Book Review: AI Blueprints by Dr. Joshua Eckroth

Having just finished teaching a couple of introductory data science classes this past academic quarter, I came to the realization that it’s hard for newbie data scientists to get started on a project of reasonable complexity. Many students got frustrated in establishing a framework (or “blueprint”) with which to start building their machine learning applications for their class project. A new title from Packt Publishing, “AI Blueprints,” by Dr. Joshua Eckroth, helps solve this problem by laying out six real-life business scenarios for how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow.

Machine Learning Beyond Predefined Recipes

The next evolution in human intelligence is automating the creation of machine learning models to not follow predefined formulas, but rather adapt and evolve according to the problem’s data. While machine learning has enabled massive advancements across industries, it requires significant development and maintenance efforts from data science teams. Enter Darwin, a machine learning tool that automates the building and deployment of models at scale.

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?

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.

Mind Foundry Launches Machine Learning Platform to Transform Business Problem Owners into Citizen Data Scientists

Mind Foundry, a technology spin-out from the University of Oxford’s Machine Learning Research Group (MLRG), announced the commercial launch of a revolutionary humanized machine learning platform. For the first time the new cloud-based platform allows anyone, of any technical ability and in any size of organization, to swiftly unlock the full value of ever increasing volumes of data to make decisions on complex business issues without the need for data scientists.