Ars Technicast special edition, part 1: Machine learning assimilates athletics

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Expert System, machine learning, and other technologies are altering the world in which we work and live in some subtle, and not-so-subtle, methods. And we’re diving into simply a few of them in this podcast series produced in association with Darktrace.

Click on this link for a records, and click on this link for an MP3 direct download.

Among the most noticeable locations where analytics based upon AI and machine learning are working their method into our popular awareness remains in the world of expert sports. From the virtual lines made use of a football field to show the line of skirmish and first- down markers, to Big league Baseball stat casts forecasting the likelihood of effective base stealing, AI has actually ended up being part of how we take in 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 supplies AI-based analytics for the Trip de France, the renowned 21- phase bikingcompetition Wade’s team utilizes cordless interactions, helicopters, and an information center in a truck to turn sensing unit information from each of the competitors’ bikes into live stats and analysis of the race– consisting of an algorithm that anticipates pile-ups in the peloton.

This special edition of the Ars Technicast podcast can be accessed in the following locations:

iTunes:
https://itunes.apple.com/us/podcast/the-ars-technicast/id522504024?mt=2 (May take numerous 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

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