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Raquel Urtasun on Level-4 Autonomous Trucks

View original at spectrum.ieee.org
IEEE Spectrum - Technical Title: Raquel Urtasun on Level-4 Autonomous Trucks Date: 2026-03-13 13:01 Source: https://spectrum.ieee.org/level-4-autonomous-trucks <img src="https://spectrum.ieee.org/media-library/an-adult-white-woman-with-short-dark-hair-and-crossed-arms-leaning-her-back-against-the-door-of-a-semi-truck.j…
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  • Level 2+ passenger car systems are not verifiable black box architectures unsuitable for Level 4 autonomy

    60% confidence
  • There are 2 million deaths on the road globally per year

    60% confidence
  • Waabi Driver is a shared brain that can scale across full range of vehicles, geographies and environments

    60% confidence
  • Waabi's verifiable end-to-end AI enables driving on local streets with unprotected lefts, traffic lights, and tight turns all the way to end customer

    60% confidence
  • Waabi World is the only simulator where you can mathematically prove that testing in simulation is the same as driving in the real world

    60% confidence
  • Autonomous trucking adoption will create more jobs than removed

    60% confidence
  • Human error causes between 90 percent and 96 percent of accidents

    60% confidence
  • Autonomous haulers could be responsible for 15 percent of total U.S. trucking miles as early as 2030

    60% confidence
  • Everybody who's a truck driver today and wants to retire as a truck driver will be able to do so

    60% confidence
  • Global autonomous trucking business could be worth more than $600 billion per year by 2035

    60% confidence
  • Snowstorms still create a no-go zone for Waabi Driver

    60% confidence

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Two significantly different EPS values (10.21 vs 2.68 USD_per_share) are reported for Morgan Stanley on the same observation date (2025-12-31). Fact A specifies FY 2025, while Fact B's 'N/A' fiscal period is ambiguous. If both represent FY 2025 annual EPS, these values directly conflict. The magnitude of the difference (3.8x) is too large to attribute to rounding or minor calculation variations. The missing fiscal period in Fact B raises data quality concerns, but same-date observation + same attribute should reference the same period.
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