https://www.youtube.com/watch?v=YXFh8Um-qxE?rel=0&autoplay=1&autoplay=1&modestbranding=1
What better way to celebrate the onset of the revolutionary 2022 Formula 1 season than to speak to one of the people involved in the very making of the regulations.
Priya Ponnapalli from Amazon Web Services (or AWS) joins Soumil Arora and Kunal Shah in this episode of the Inside Line F1 Podcast.
Priya leads the team of humans and machines (of course!) at AWS that works with Formula 1. AWS’ involvement goes way beyond the TV graphics that Formula 1 fans have witnessed in the past few seasons.
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00:00 Intro
03:31 How and why did this partnership begin?
06:52 How did AWS work on the 2022 regulations?
10:56 The insights that AWS found working on the new cars
16:00 How do they work around without teams sharing data?
17:25 How is the team divided between humans and machines?
18:45 How open have F1 been to change?
19:44 How do the AWS models change with time to match the changes on track?
23:24 What’s next in the pipeline for AWS and F1?
25:08 The learnings from other sports
27:22 Is ML effective for the quick decisions?
28:22 Is AWS working on the F1 VAR?
29:15 Can learnings from F1 be taken to the outside world?
30:37 AWS’s learnings for F1 from NFL
33:22 How has the partnership with F1 been so far?
36:24 Advice for youngsters aiming to ace ML and AI
In this episode of the Inside Line F1 Podcast, Priya explains how the AWS-Formula 1 partnership came about, the areas the partnership has already worked in (F1 2022 regulations along with TV graphics & more) and what areas they could potentially collaborate on in the future (FIA’s VAR?).
What are the main challenges of working with Formula 1? Does AWS take learnings from their sports partnerships into other business areas like finance or healthcare? And finally, do AWS’ machine learning algorithms evolve through a season just the way Formula 1 cars do?
Tune in!
(Season 2022, Episode 09)
Follow our hosts on Twitter: Soumil Arora and Kunal Shah
Image courtesy: Formula 1
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