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Field Report: KDD 2019

As a very long time member of the ACM and their SIGKDD group, I’d always wanted to attend a KDD conference (first one occurred in 1995). This year I received a gracious invitation to attend KDD2019 in Anchorage, Alaska, August 4-8. It satisfied two of my bucket list items: witnessing a KDD first-hand and also […]

TOP 10 insideBIGDATA Articles for July 2019

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.

The AI Opportunity

The tremendous growth in compute power and explosion of data is leading every industry to seek AI-based solutions. In this Tech.Decoded video, “The AI Opportunity – Episode 1: The Compute Power Difference,” Vice President of Intel Architecture and AI expert Wei Li shares his views on the opportunities and challenges in AI for software developers, how Intel is supporting their efforts, and where we’re heading next.

Fast-track Application Performance and Development with Intel® Performance Libraries

Intel continues its strident efforts to refine libraries optimized to yield the utmost performance from Intel® processors. The Intel® Performance Libraries provide a large collection of prebuilt and tested, performance-optimized functions to developers. By utilizing these libraries, developers can reduce the costs and time associated with software development and maintenance, and focus efforts on their own application code.

What Happened to Hadoop? And Where Do We Go from Here?

Apache Hadoop emerged on the IT scene in 2006 with the promise to provide organizations with the capability to store an unprecedented volume of data using cheap, commodity hardware. Hadoop facilitated data lakes were accompanied by a number of independent open source compute engines – and on top of that, “open source” meant free! What could go wrong?

“Above the Trend Line” – Your Industry Rumor Central for 8/5/2019

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.

ThetaRay 4.0 with IntuitiveAI Gives Banks a Powerful New Weapon Against Financial Cybercrime

ThetaRay, a leading provider of AI-based Big Data analytics, announced Version 4.0 of the company’s namesake advanced analytics platform. The update includes major capability upgrades to help global banks detect and prevent financial cybercrime. ThetaRay’s IntuitiveAI solutions replicate the powerful decision-making capabilities of human intuition to detect “unknown unknowns” that cannot be identified by first-generation AI or legacy products.

AI for Legalese

Have you ever signed a lengthy legal contract you didn’t fully read? Or have you every read a contract you didn’t fully understand? Contract review is a time-consuming and labor-intensive process for everyone concerned — including contract attorneys. Help is on the way. IBM researchers are exploring ways for AI to make tedious tasks like contract review easier, faster, and more accurate.

How Companies Can be Ethical with AI

One big question in the industry these days is about the safeguards companies can take to ensure their AI is fair and ethical. Stakeholders are trying to determine how enterprises can ensure that their employees, investors and customers trust their AI technology. With AI advancing at the incredible rate that it is and being applied to diverse use cases such as criminal detection, this is an important and timely topic.

Supercharge Data Science Applications with the Intel® Distribution for Python

Intel® Distribution for Python is a distribution of commonly used packages for computation and data intensive domains, such as scientific and engineering computing, big data, and data science. With Intel® Distribution for Python you can supercharge Python applications and speed up core computational packages with this performance-oriented distribution. Professionals who can gain advantage with this product include: machine learning developers, data scientists, numerical and scientific computing developers, and HPC developers.