Waabi's AI-First Approach to Autonomous Trucking Secures $200M Funding Amid AV Industry Setbacks Image credit: Waabi website |
Raquel Urtasun, founder and CEO of Waabi, has spent two decades developing AI systems capable of human-like reasoning. After her tenure as chief scientist at Uber ATG, she launched Waabi in 2021 to accelerate the deployment of autonomous vehicles, starting with long-haul trucks, using an "AI-first approach."
Waabi differentiates itself from companies like Tesla by employing lidar sensors and a unique training method. Unlike Tesla’s imitation learning, which relies on vast amounts of real-world driving data, Waabi uses a simulator called Waabi World. This simulator creates digital twins, performs real-time sensor simulations, stress tests scenarios, and enables learning without human intervention.
Within four years, Waabi has initiated commercial pilot programs in Texas and plans a fully driverless launch by 2025. The startup aims to expand its technology beyond trucking to applications like robotaxis and warehouse robotics.
Waabi recently raised $200 million in a Series B funding round, bringing total funding to $283.5 million. This is significant given recent setbacks in the AV industry, with companies like Embark Trucks and Argo AI shutting down, and others like Waymo and Cruise facing regulatory and operational challenges.
Urtasun emphasizes that Waabi’s AI can generalize from limited data, making it more efficient and scalable. Unlike traditional AI systems, Waabi's AI can perceive, abstract, and reason about the world in real time, ensuring safety and adaptability. The company plans to leverage Nvidia’s Drive Thor for enhanced computational power, further supporting its autonomous driving systems. Urtasun believes Waabi's technology can be adapted for various autonomous applications, highlighting its versatility and potential for broad impact.
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