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Research Highlights: MIDAS – Real-time Anomaly/Fake News/Intrusion Detection

In the insideBIGDATA Research Highlights column we take a look at new and upcoming results from the research community for data science, machine learning, AI and deep learning. Our readers need to get a glimpse for technology coming down the pipeline that will make their efforts more strategic and competitive. In this installment we review MIDAS – Real-time Anomaly/Fake News/Intrusion Detection developed by Ph.D. candidate Siddharth Bhatia and his team at the National University of Singapore.

A Computational Analysis of Constitutional Polarization

A new paper, “A Computational Analysis of Constitutional Polarization” by Columbia Law School’s David Pozen and Eric Talley found that the U.S. Constitution has come to enable, or even exacerbate, partisan strife. The researchers recently examined the evolution of constitutional rhetoric on the floor of Congress from 1873 to 2016.

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

New Study Details Importance of TCO for HPC Storage Buyers

Total cost of ownership (TCO) now rivals performance as a top criterion for purchasing high-performance computing (HPC) storage systems, according to an independent study published by Hyperion Research. The report, commissioned by our friends over at Panasas®, a leader in HPC data storage solutions, surveyed data center planners and managers, storage system managers, purchasing decision-makers and key influencers, as well as users of HPC storage systems.

New Salesforce Research AI Simulates Millions of Years of Economic Data Using RL

Salesforce Research published a groundbreaking paper, The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies, which applies AI and reinforcement learning to create tax policy for the first time.

AI Under the Hood: Playform

In this installment of “AI Under the Hood” I introduce recently launched Playform (Artrendex Inc.), a generative AI collaborative tool for artists. The company’s tech publicist reached out to me around when the global pandemic became serious, so it’s taken a while for me to write this review. But I was impressed with all the materials the company provided me for making a technology assessment. As a previous researcher myself, I’m always excited when a company sends me a link to an arXiv.org paper written by a founder. Nice touch!

Video Highlights: Machine Learning for Seeing and Hearing More

With COVID-19 keeping everyone indoors, this is the perfect opportunity to brush up your data science skills. Data science is a field that is booming and is playing a huge role in society. Instead of just reading a book, in this regular feature column, I will provide some great video learning resources. You can follow these YouTubers and gain insights and advice from their years of experience in the field. Plus you can learn how to code by following through their tutorials and pick up a new skill. So, fire up YouTube below and start learning!

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

Columbia University DSI Alumni Use Machine Learning to Discover Coronavirus Treatments

Two graduates of the Data Science Institute (DSI) at Columbia University are using computational design to quickly discover treatments for the coronavirus. Andrew Satz and Brett Averso are chief executive officer and chief technology officer, respectively, of EVQLV, a startup creating algorithms capable of computationally generating, screening, and optimizing hundreds of millions of therapeutic antibodies. They apply their technology to discover treatments most likely to help those infected by the virus responsible for COVID-19.

Intel + Cornell Pioneering Work in the “Science of Smell”

Nature Machine Intelligence published a joint paper from researchers at Intel Labs and Cornell University demonstrating the ability of Intel’s neuromorphic test chip, Loihi, to learn and recognize 10 hazardous chemicals, even in the presence of significant noise and occlusion. The work demonstrates how neuromorphic computing could be used to detect smells that are precursors to explosives, narcotics and more.