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    Home»Tech News»Waymo Catches World Model Fever, and the Only Prescription Is More World Models
    Tech News

    Waymo Catches World Model Fever, and the Only Prescription Is More World Models

    Michael ComaousBy Michael ComaousFebruary 7, 20263 Mins Read
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    Waymo Catches World Model Fever, and the Only Prescription Is More World Models
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    Waymo vehicles have reportedly racked up more than 200 million miles of autonomous driving on public roads. But it’s yet to run into a tornado or an elephant, and odds are that it’d respond poorly if it did. To try to help with those once-in-a-billion-miles scenarios, Waymo announced Friday that it is introducing Waymo World Model, a generative AI model that it will use to run near-endless situations to try to make sure its cars are prepared for the unpredictable, which also just happens to fit into the latest trend in the AI space.

    To be clear, Waymo’s world model makes about as much sense as any use case for the technology. The company has a ton of high-definition data that it has collected from its time on the road that it can use to generate realistic re-creations of roads. But, the company said, instead of building a model based only on that information, it’s going to use Google’s Genie 3 model to put its cars in simulated situations that extend beyond what is already in its data set collected from cameras and lidar sensors.

    We’re excited to introduce the Waymo World Model—a frontier generative mode for large-scale, hyper-realistic autonomous driving simulation built on @GoogleDeepMind’s Genie 3.

    By simulating the “impossible”, we proactively prepare the Waymo Driver for some of the most rare and… pic.twitter.com/Pl80OMDqLC

    — Waymo (@Waymo) February 6, 2026

    Google made a splash last month when it released a beta version of Genie 3 to the public, allowing a subset of paid subscribers to generate 3D worlds with realistic physics. Unlike a large language model (LLM)—the underlying technology that powers most AI tools including Google’s own Gemini—which use the vast amount of training data they are given to predict the most likely next part of a sequence, world models are trained on the dynamics of the real world, including physics and spatial properties, to create a simulation of how physical environments operate.

    Genie 3 🤝 @Waymo

    The Waymo World Model generates photorealistic, interactive environments to train autonomous vehicles.

    This helps the cars navigate rare, unpredictable events before encountering them in reality. 🧵 pic.twitter.com/m6rlmkMFJH

    — Google DeepMind (@GoogleDeepMind) February 6, 2026

    Waymo plans to tap into that to put its cars through a gauntlet of scenarios that they likely wouldn’t find themselves in until it’s too late. That includes extreme weather conditions and natural disasters, so the cars can figure out how to navigate a tornado or flood waters; sudden safety emergencies like falling tree branches or an accident with lots of debris; and run-ins with the unexpected, like an elephant on the road. “By simulating the ‘impossible,’ we proactively prepare the Waymo Driver for some of the most rare and complex scenarios,” the company said.

    The theory is certainly sound, though world models aren’t without their drawbacks. The early feedback on the consumer version of Genie 3 was a bit spotty, and world models are still susceptible to hallucinations. We’re still in the earliest stages of seeing these models deployed, and they have lots of room to iterate.

    And Waymos have definitely had their issues in edge-case scenarios in the real world. Late last year, a Waymo ran over a beloved bogeda cat named Kit Kat, and last month, one ran into a kid in a school zone. Those interactions aren’t even particularly rare for a driver to find themselves in, so hopefully Waymo can refine its responses in those scenarios on top of prepping for the most unlikely situations.

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    Source: gizmodo.com

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    Michael Comaous
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    Michael Comaous is a dedicated professional with a passion for technology, innovation, and creative problem-solving. Over the years, he has built experience across multiple industries, combining strategic thinking with hands-on expertise to deliver meaningful results. Michael is known for his curiosity, attention to detail, and ability to explain complex topics in a clear and approachable way. Whether he’s working on new projects, writing, or collaborating with others, he brings energy and a forward-thinking mindset to everything he does.

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