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This Week in Startups

The Self-Driving Startup Nobody Saw Coming | E2289

72 min episode · 3 min read
·
Alex Kindel

Episode

72 min

Read time

3 min

Topics

Relationships, Startups, Fundraising & VC

AI-Generated Summary

Key Takeaways

  • World Model Architecture: World models serve dual functions in autonomous driving: they create rich representations of what physically matters on the road (lane markings, traffic signals, intersecting objects) while simultaneously generating photorealistic simulation environments. Training on hundreds of petabytes of data across dash cams, internet video, and OEM fleets, these models now incorporate radar and lidar alongside cameras, enabling adversarial stress-testing without real-world safety consequences.
  • Licensing vs. Fleet vs. OEM Strategy: Three distinct business models exist in autonomous driving. Building proprietary vehicles limits scale to one brand. City-by-city fleet deployment requires high capital expenditure. Licensing AI to existing manufacturers and fleet operators — Wave's and Wabi's shared approach — captures the largest addressable market by leveraging partners' existing manufacturing scale, distribution, and demand aggregation without owning physical assets.
  • L2 to L4 Gap Is Engineering, Not Science: The transition from hands-off highway driving to fully driverless operation is no longer a scientific unknown — it is an engineering execution problem. Required steps include integrating validated hardware into OEM platforms, scaling training data and compute along a predictable curve similar to LLM scaling, and completing safety validation across diverse global domains before regulatory submission.
  • Nissan Partnership Scale: Nissan's commitment to deploy Wave technology across 90% of its vehicle lineup represents approximately 2.7 million units annually by financial year 2027 — roughly double Tesla's total annual production volume. This single partnership illustrates the leverage of the OEM licensing model: one contract generates more deployment volume than an entire competitor's manufacturing capacity.
  • Subscription Pricing Trajectory: Consumer autonomous driving features are moving toward recurring subscription models, mirroring Tesla's $100 monthly FSD charge. OEMs are testing bundled inclusion, one-time fees, and free trials before converting to subscriptions. The recurring model aligns incentives because ongoing software updates, safety improvements, and insurance cost coverage require continuous revenue rather than a single upfront hardware sale.

What It Covers

Two self-driving startup CEOs — Wave's Alex Kendall and Wabi's Raquel Ratzen — detail how end-to-end AI and world models are moving autonomous vehicles from science projects to mass-market products. Wave targets 2.5 million Nissan vehicles annually by 2027, while Wabi pursues a minimum 25,000-robotaxi Uber partnership with Volvo as OEM partner.

Key Questions Answered

  • World Model Architecture: World models serve dual functions in autonomous driving: they create rich representations of what physically matters on the road (lane markings, traffic signals, intersecting objects) while simultaneously generating photorealistic simulation environments. Training on hundreds of petabytes of data across dash cams, internet video, and OEM fleets, these models now incorporate radar and lidar alongside cameras, enabling adversarial stress-testing without real-world safety consequences.
  • Licensing vs. Fleet vs. OEM Strategy: Three distinct business models exist in autonomous driving. Building proprietary vehicles limits scale to one brand. City-by-city fleet deployment requires high capital expenditure. Licensing AI to existing manufacturers and fleet operators — Wave's and Wabi's shared approach — captures the largest addressable market by leveraging partners' existing manufacturing scale, distribution, and demand aggregation without owning physical assets.
  • L2 to L4 Gap Is Engineering, Not Science: The transition from hands-off highway driving to fully driverless operation is no longer a scientific unknown — it is an engineering execution problem. Required steps include integrating validated hardware into OEM platforms, scaling training data and compute along a predictable curve similar to LLM scaling, and completing safety validation across diverse global domains before regulatory submission.
  • Nissan Partnership Scale: Nissan's commitment to deploy Wave technology across 90% of its vehicle lineup represents approximately 2.7 million units annually by financial year 2027 — roughly double Tesla's total annual production volume. This single partnership illustrates the leverage of the OEM licensing model: one contract generates more deployment volume than an entire competitor's manufacturing capacity.
  • Subscription Pricing Trajectory: Consumer autonomous driving features are moving toward recurring subscription models, mirroring Tesla's $100 monthly FSD charge. OEMs are testing bundled inclusion, one-time fees, and free trials before converting to subscriptions. The recurring model aligns incentives because ongoing software updates, safety improvements, and insurance cost coverage require continuous revenue rather than a single upfront hardware sale.
  • Wabi's Per-Mile Revenue Model: Wabi charges carriers and operators on a per-mile basis rather than upfront licensing fees, creating direct alignment between customer value and revenue. Volvo, as Wabi's primary OEM partner, plans hundreds of commercially deployed trucks by 2027 through its Volvo Autonomous Solutions unit. The Uber Freight partnership covers billions of miles of deployment across North America's top carriers.

Notable Moment

When asked whether Uber had attempted to acquire Wabi — given Raquel Ratzen's four-year tenure at Uber ATG, the Uber Freight partnership, and the new Uber robotaxi deal — Ratzen confirmed multiple acquisition approaches over the years from various parties but stated the company remains entirely off the market, with a goal of building a global physical AI powerhouse.

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Episode Transcript

We pioneered end to end learning when it was widely dismissed. Self driving in a way that economically scales the world is not is not solved. Our partnership is not up to 25,000. It's over 25,000 or, in other words, a minimum of 25,000. Volume is, like, double the cars Tesla builds a year, and that's just one of our partners. And if you're a manufacturer selling a car that doesn't have this, I think your demand is really gonna fall off a cliff. Every car is being intelligently driven by a machine that never blinks. Yeah. You'll pay for your own private chauffeur that that that's in your car. Has Uber tried to buy you? Huawei is not for sale for anybody. This Week in Startups is brought to you by I m eight Health. Start feeling like your best self every day. Go to im8health.com/twist and use the code twist to get a free welcome kit, five free travel sachets, and 10% off your order. Squarespace, turn your idea into a beautiful website. Go to squarespace.com/twist for a free trial. When you're ready to launch, use offer code twist to save 10% off your first purchase of a website or domain. And render. Find out why 5,000,000 developers are already using the all in one cloud platform, render. Go to render.com/twist and apply for the render startup program to get $500 to $100,000 in free credits depending on your stage and backers. Hello, everybody, and welcome back to Twist. My name is Alex. And today, we're going deep on one of my absolute favorite topics in the world. And, no, it's not about open clock. No. Today, we're talking about self driving cars. We're bringing back the CEO of a company that we had on the show back in late two thousand twenty four when Wave, a UK based self driving start up, was doing incredibly interesting things, working hard to bring this technology to market. Since then, quite a lot has happened. We're gonna dive into what Wave has done recently, how close it is to changing your life and my life. So please join me in welcoming back to the show its cofounder and CEO, Alex Kindel. Alex, how you doing? Awesome. Hey, Alex. It's so good to have you back. So late two thousand twenty four feels like twenty nine years ago in AI terms. How has the self driving world been progressing as quickly as the kind of general AI landscape? Well, you know, if I go back to when we started in 2017, one of our very first blog posts was about a world model that we put together back then. It was, I don't know, not in today's status. It was like a 20,000 parameter world model. And we were all excited at the time of end to end AI. Hey, it was going to actually, you know, allow us to to really truly scale autonomy. And that pitch has stayed the …

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