dRISK CEO Chess Stetson & COO Rav Babbra
How AI Happens
English - June 30, 2023 18:04 - 35 minutes - 32.3 MB - ★★★★★ - 10 ratingsTechnology Science Mathematics autonomous computer science computer vision big data training data artificial intelligence machine learning Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
dRisk uses a unique approach to increasing AV safety: collecting real-life scenarios and data from accidents, insurance reports, and more to train autonomous vehicles on extreme edge cases. With their advanced simulation tool, they can accurately recreate and test these scenarios, allowing AV developers to improve the performance and safety of their vehicles. Join us as Chess and Rav delve into the exciting world of AVs and the challenges they face in creating safer and more efficient transportation systems.
Key Points From This Episode:
Introducing dRisk Founder and CEO, Chess Stetson, and COO, Rav Babbra.dRisk’s mission to help autonomous vehicles become better drivers than humans.The UK government’s interest in autonomous vehicles to solve transportation problems.Rav’s career background; how the CAVSim competition put dRisk on his radar.How dRisk’s software presents real-life scenarios and extreme edge cases to test AVs.Chess defines extreme edge cases in the AV realm and explains where AVs typically go wrong.How the company uses natural language processing and AI-based techniques to improve simulation accuracy for AV testing.The metrics used to ensure the accuracy of the simulations.What makes AI different from humans in an AV context.The benchmark for the capability of AVs; the tolerance for human driver error versus AV error.Why third-party testing is a necessity for AI.dRisk’s assessment process for autonomous vehicles.The delicate balance between innovation and regulation.Examples of AV edge cases.Tweetables:
“At the time, no autonomous vehicles could ever actually drive on the UK's roads. And that's where Chess and the team at dRisk have done such great piece of work.” — Rav Babbra [0:07:25]
“If you've got an unprotected cross-traffic turn, that's where a lot of things traditionally go wrong with AVs.” —Chess Stetson [0:08:45]
“We can, in an automated way, map out metrics for what might or might not constitute a good test and cut out things that would be something like a hallucination.” —Chess Stetson [0:13:59]
“The thing that makes AI different than humans is that if you have a good driver's test for an AI, it's also a good training environment for an AI. That's different [from] humans because humans have common sense.” — Chess Stetson [0:15:10]
“If you can really rigorously test [AI] on its ability to have common sense, you can also train it to have a certain amount of common sense.” — Chess Stetson [0:15:51]
“The difference between an AI and a human is that if you had a good test, it's equivalent to a good training environment.” — Chess Stetson [0:16:29]
“I personally think it's not unrealistic to imagine AV is getting so good that there's never a death on the road at all.” — Chess Stetson [0:18:50]
“One of the reasons that we're in the UK is precisely because the UK is going to have no tolerance for autonomous vehicle collisions.” — Chess Stetson [0:20:08]
“Now, there's never a cow in the highway here in the UK, but of course, things do fall off lorries. So if we can train against a cow sitting on the highway, then the next time a grand piano falls off the back of a truck, we've got some training data at least that helps it avoid that.” — Rav Babbra [0:35:12]
“If you target the worst case scenario, everything underneath, you've been able to capture and deal with.” — Rav Babbra [0:36:08]
Links Mentioned in Today’s Episode: