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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.

NVIDIA’s New Data Science Workstation— a Review and Benchmark

This new whitepaper from NVIDIA Partner firm PNY Technologies, tests and reviews the recently released Data Science Workstation, a PC that puts together all the Data Science hardware and software into one nice package. The workstation is a total powerhouse machine, packed with all the computing power—and software—that’s great for plowing through data.

Will Advanced Earth Observation Data Come to the Rescue When Climate Change Leads to Food Shortages?

Satellite data enables ongoing monitoring of the situation on Earth, creating models to support agriculture, and managing the risk related to climate change. More and more companies and institutions take advantage of this data, also within the framework of the state administration, where satellite images are increasingly used e.g. to analyze soil moisture and identify areas likely to yield worse crops.

Interview: Felix Dorrek, Ph.D.

I recently caught up with Felix Dorrek to discuss his research in the area of deep generative networks. The interview touches on the technology’s power, practical applications, importance to business in 2020, as well as generating synthetic data. Felix holds a Ph.D. in mathematics from the Vienna Technical University where he conducted research in the field of Convex Geometry.

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

Survey Finds SMBs Aren’t Fully Leveraging Business Analytics

Despite spending hundreds of hours and thousands of dollars on their data analytics solutions annually, 86% of SMB managers and executives surveyed by Onepath said their companies could be making better use of these technologies.

State of AI Decision-Making

Our friends over at Interactions worked with The Harris Poll to survey mid-to-high level executives regarding their thoughts and observations around how their own companies have adopted AI, and what to keep in mind during the planning process. Read on to explore the key findings from the study, as prepared by The Harris Poll.

Teacher Pay is Stagnating. Data and Analytics Could Give it a Boost

In this special guest feature, University of San Diego Assistant Professor in Economics, Alison Sanchez, argues that economic questions like how to increase teachers’ pay can be answered through large-scale data analysis. There is not one single answer or explanation behind the widespread salary drop for teachers, but data and analytics can reveal individual causes of teacher pay stagnation and provide customized solutions to address them.

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

Researcher Develops Algorithm to Make Artificial Intelligence Fairer

A researcher from Queen’s University Belfast has developed an innovative new algorithm that will help make artificial intelligence (AI) fairer and less biased when processing data. Companies often use AI technologies to sift through huge amounts of data in situations such as an oversubscribed job vacancy or in policing when there is a large volume of CCTV data linked to a crime.