University of Waterloo researchers have developed new artificial intelligence (AI) technology that can accurately analyze pitcher performance and mechanics using low-resolution video of baseball games. The system, developed for the Baltimore Orioles by the Waterloo team, plugs holes in much more elaborate and expensive technology already installed in most stadiums that host Major League Baseball (MLB), whose teams have increasingly tapped into data analytics in recent years. Waterloo researchers convert video of a pitcher's performance into a two-dimensional model that PitcherNet's AI algorithm can later analyze. Those systems, produced by a company called Hawk-Eye Innovations, use multiple special cameras in each park to catch players in action, but the data they yield is typically available to the home team that owns the stadium those games are played in. To add away games to their analytics operation, as well as use smartphone video taken by scouts in minor league and college games, the Orioles asked video and AI experts at Waterloo for help about three years ago.

Fighting fake news has become a growing problem in the past few years, and one that begs for a solution involving artificial intelligence. Verifying the near-infinite amount of content being generated on news websites, video streaming services, blogs, social media, etc. is virtually impossible There has been a push to use machine learning in the moderation of online content, but those efforts have only had modest success in finding spam and removing adult content, and to a much lesser extent detecting hate speech. Fighting fake news is a much more complicated challenge. But they have limited reach. It would be unreasonable to expect current artificial intelligence technologies to fully automate the fight against fake news.

This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. Fighting fake news has become a growing problem in the past few years, and one that begs for a solution involving artificial intelligence. Verifying the near-infinite amount of content being generated on news websites, video streaming services, blogs, social media, etc. is virtually impossible There has been a push to use machine learning in the moderation of online content, but those efforts have only had modest success in finding spam and removing adult content, and to a much lesser extent detecting hate speech. Fighting fake news is a much more complicated challenge. But they have limited reach.

At the point when many people take their time to think about wearables, they commonly consider wristband screens and smartwatches. However, on the other hand, there are things like "smart shirts," real articles of clothing that contain sensors for heart rate, breathing, and movement. Specialists at the University of Waterloo in Ontario, Canada, as of late utilized such shirts to check whether they could build up an algorithm to recognize early indications of future chronic diseases. They initially did their research with the help of 13 healthy men in their 20's in a research facility-based fitness program, making metric benchmarks. The men at that point wore the shirts in their day to day lives for four unsupervised days.