TL;DR
Google DeepMind has connected its Project Genie world model to Google Street View’s 280 billion images, letting users explore AI-generated simulations of real locations. Announced at Google I/O, the feature is rolling out to Google AI Ultra subscribers in the US, with Waymo already using Genie 3 to train self-driving cars on rare scenarios.
Google DeepMind has connected its Project Genie world model to 20 years of Street View imagery, allowing users to wander through AI-generated simulations of real places. The integration, announced at the Google I/O developer conference on Monday, marks one of the most tangible demonstrations yet of what generative world models can do when paired with a colossal real-world dataset.
Project Genie, the company’s general-purpose system for creating interactive environments, can now draw on more than 280 billion images captured across 110 countries and all seven continents. The result is a tool that lets you drop into a simulated version of, say, a New York City block covered in snow, or a London street bathed in rare sunshine, and navigate it in real time.
From research preview to consumer product
Genie 3, the latest iteration of the model, first appeared as a research preview in August 2025, part of a broader push by Google to embed AI across its platform stack. In January 2026, DeepMind opened access to Google AI Ultra subscribers in the United States. The Street View integration is now rolling out to some Ultra users in the US, with a global expansion planned over the coming weeks.
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Jack Parker-Holder, a research scientist on DeepMind’s open-endedness team, framed the feature as serving two distinct audiences. On one hand, robotics developers could use it to train agents in simulated environments that mirror actual locations. On the other, ordinary users could simply explore for fun.
Waymo is already a customer
The robotics angle is not theoretical. Genie 3 already powers one of Waymo’s simulators, where the self-driving car company uses it to train on rare events that would be dangerous or impractical to stage in real life, things like tornadoes or unexpected encounters with elephants on a road. The ability to ground these simulations in actual Street View geography adds another layer of realism.
This kind of simulation-to-reality pipeline is becoming a critical bottleneck in physical AI. Companies including Nvidia and Cadence have been racing to close the gap between what robots learn inside computers and how they perform once deployed, and DeepMind’s approach of layering generative models on top of real-world imagery offers a distinctive route.
Impressive, but far from photorealistic
Diego Rivas, a product manager at DeepMind, cautioned that the Street View integration remains experimental. The generated environments look closer to a video game than to a photograph, and the model is not yet physics-aware. In one demonstration, a character ran straight through a row of cacti without consequence.
Parker-Holder acknowledged the gap directly, estimating that interactive world generation trails video generation by roughly six to 12 months in terms of accuracy. For context, Google’s own Veo model already understands basic physics, and its Nano Banana tool can render perfect text in infographics. Genie is not there yet.
The spatial continuity trick
What does work well, according to Jonathan Herbert, director of Google Maps, is spatial continuity. Turn 360 degrees inside a Genie-generated environment, and the AI remembers what was behind you. It maintains a coherent model of the space rather than regenerating it from scratch with every viewpoint shift.
Herbert described this spatial awareness as the real breakthrough. Google has spent two decades capturing the world through Street View, and the Maps team has long considered how to build richer models on top of that data. Genie, it seems, is the answer, or at least the beginning of one.
What comes next
The launch fits within a broader pattern at Google, where the company is steadily threading AI capabilities into products that already have massive user bases. Street View’s dataset is a competitive moat that no other AI lab can easily replicate, and connecting it to a generative world model turns a passive mapping tool into something altogether more dynamic.
Whether Genie’s simulated streets will eventually rival the fidelity of dedicated game engines or professional video production remains to be seen. For now, the feature is a compelling proof of concept, one that hints at a future where the line between navigating a map and exploring a living, AI-generated world becomes increasingly difficult to draw.
