Ars Technicast special edition, part 1: Machine learning assimilates athletics
Artificial Intelligence, machine learning, and other technologies are changing the world in which we live and work in some subtle, and not-so-subtle, ways. And we’re diving into just a few of them in this podcast series produced in association with Darktrace.
One of the most visible places where analytics based on AI and machine learning are working their way into our popular awareness is in the realm of professional sports. From the virtual lines drawn on a football field to show the line of scrimmage and first-down markers, to Major League Baseball stat casts predicting the probability of successful base stealing, AI has become part of how we consume sports.
In this episode, Ars editors Sean Gallagher and Lee Hutchinson talked with Tim Wade, vice president at NTT’s Advanced Technology Group, about how NTT provides AI-based analytics for the Tour de France, the iconic 21-stage cycling competition. Wade’s team uses wireless communications, helicopters, and a data center in a truck to turn sensor data from each of the competitors’ bicycles into live statistics and analysis of the race—including an algorithm that predicts pile-ups in the peloton.
This special edition of the Ars Technicast podcast can be accessed in the following places:
iTunes:
https://itunes.apple.com/us/podcast/the-ars-technicast/id522504024?mt=2 (Might take several hours after publication to appear.)
RSS:
http://arstechnica.libsyn.com/rss
Stitcher
http://www.stitcher.com/podcast/ars-technicast/the-ars-technicast
Libsyn:
http://directory.libsyn.com/shows/view/id/arstechnica
