This Week In Startups is made possible by:

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Today’s show:

F1 teams spend up to a third of their budgets on aerodynamics, often utilizing wind tunnels to simulate what happens on the track.

But Lyall Davenport of SKN Systems created a sensor-embedded tape that sticks directly to race cars as they drive around the real world, generating 420M data points per hour. And it comes in at roughly 95% less cost than running a full simulator.

Hear about how Lyall’s background in racing helped him develop the concept, plans to expand from motorsports to drones and defense, and his experiences going through Jason’s various programs.

PLUS OpenAI’s new models are so good, you can’t use them. Why Apple’s Vision Pro chief defected to OpenAI (and why their laptops and devices are getting more expensive). A look at the world’s most annoying data center in Sterling, Virginia. And Jason remembers iconic and influential tech journalist Om Malik.

Guest:

Lyall Davenport: https://x.com/Lyalldavenport

SKN Systems: https://www.skn.systems/

Timestamps:

0:00 How SKN uses tape to generate aerodynamic data

4:04 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off!

6:17 How SKN uses tape to generate aerodynamic data

9:55 Sentry - Your team should be focused on shipping features — not chasing down bugs. New users can get $240 in free credits when they go to https://sentry.io/twist and use the code TWIST

17:20 F1 teams are worth HOW MUCH?

19:42 Northwest Registered Agent: Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at https://northwestregisteredagent.com/twist

20:35 Future markets beyond motorsports

30:03 DigitalOcean - Want to see what building on a true AI-native platform looks like? Head to https://do.co/twist to start building on DigitalOcean's AI-Native Cloud today — and cut your AI workload costs by up to 50%.