Announcing our $320M Series A at a $2.3B valuation, led by @khoslaventures, with @generalcatalyst, @ericschmidt and @JeffBezos. General Intuition is the frontier lab for acting in space and time. We build large action foundation models trained on billions of ground truth action-labeled gameplay clips from 17M monthly active users on Medal, and push the frontier of world models to generate infinite training environments.

Play the four-player demo now.

We're proud to finally share this. Thanks to our partners at Kyutai and Epic for pushing the frontier of the World Models together, and towards open source. It's a new paradigm, we can choose to do things differently. Today marks an important step in that direction.

Introducing MIRA. A playable, multiplayer world model. A dream of Rocket League. Trained on 10k hours of data collected with publicly available bots, MIRA learns the dynamics of a four-player game. The model runs in real time at 20 fps, based on the keys you and the other players press. Built by General Intuition and @kyutai_labs, in collaboration with Epic Games. Not used to develop Rocket League. ▶️ Play the demo, read the technical report, and explore the open-source code at generalintuition.com/mira At ICML? Find us at Booth 111 to try it yourself and dig into the results with the team.

Join the team for a Korean lunch in Seoul this Friday. ICML 2026.

Event registration here: luma.com/owkha7u2 - ping @pallipau with any questions!

ICML 2026! 🇰🇷 We're heading to Seoul next week. Come find our research team at Booth 111 to talk world models and action models - the core of what we're building at General Intuition. We're also hosting a party on Wednesday, July 8th for a curated group of researchers working at the frontier. If that's you, the event RSVP is linked on the thread. See you there!

In all seriousness, the name @gen_intuition comes from this @demishassabis talk, as the north star of the lab is a general agent, where "Play the World" applies to scientific problems that can become games too! Another example: youtube.com/watch?v=JMAv0NS6…

.@gen_intuition CEO @PimDeWitte discusses using data from gamers to train AI & broader implications for the labor market: cnb.cx/3QHDIXj

General Intuition CEO @pimdewitte, who's building foundation models trained on video game controller input data ("action-labeled gameplay clips"), says general intelligence won't "taste like an LLM": "We have a scale of data that's going to allow us to jump to the frontier in one capability — which is any system that can be controlled with a game controller (which is most robots) — and then, you can use that to create a sufficiently general intelligence." "As humans, the decision to talk or type is a very, very small subset of the actions that we can actually take." "So in order to create a sufficiently general intelligence to play 10,000 video games, the model has to be able to predict across the entire action space of human cognition when they're interacting with these environments. Which are 2D and 3D environments, interfaces, long-horizon tasks, short-horizon tasks, [etc.]." "It has to be a sufficiently general intelligence in order to predict actions. Therefore, the type of model you get out is not going to taste like an LLM. This model is going to be incredibly good at navigating unforeseen environments. It's going to be incredibly good at zero-shotting any task that can be done with a game controller."

Read more about world models and our journey in @ScienceMagazine - Thanks @SilverJacket. science.org/content/article/…

@gen_intuition is hiring, reach out on our website.

ARC Prize Foundation General Intuition We’re grateful to announce that @gen_intuition has donated $1,001,337 to support the development of ARC-AGI-4 Thank you @PimDeWitte, @EloiAlonso1, @AdamJelley2, and @micheli_vincent for helping push open AGI benchmarking forward

If you’re curious about world models, policies, and why games may be the next frontier for AI, this conversation with @PimDeWitte on founding @gen_intuition is worth a listen!

Good to chat with @MTSlive on World Models & General Agents - youtu.be/z34F4XhEKGU - as it is becoming increasingly clear the frontier is shifting towards these capabilities. Thanks @packyM for the intro! :)

SITUATION EXPLAINED: A new generation of AI labs are betting that world models are the path to general intelligence that can interact with the real world. We had General Intuition CEO @PimDeWitte on MTS to explain what world models are, and why intuitively world models offer a clearer path towards general intelligence than LLMs. For humans, text is a technology for compressing information about the unfolding, three-dimensional world around us and communicating it to other people. When LLMs reason about the world, they do so by reconstructing the world through text. World models work by modeling the three-dimensional world at the architecture level and then allowing agents to interact with that world. Unlike an LLM, which understands space and time through text, world models perform spatial and temporal reasoning natively. General Intuition hopes to use world models to create embodied AI—machines that can reason and act in the real world. But other companies are also pushing the frontier in this space. Odyssey ML today announced a multi-agent world model, Agora-1. Their launch video shows four participants interacting with a real-time world model simulation of GoldenEye, a first-person shooter for the N64. A playable preview of the GoldenEye simulation is available on their site.

The real world is - or was - uncomputable. If language and code, two of mankind’s most powerful inventions, are inadequate to represent our real world, what do we have left? The Answer is World Models They offer a way to do non-deterministic compute efficiently, and to run simulations that shouldn’t be possible under traditional compute constraints. @packyM

Everyone says they’re building a world model. Very few actually are. Most AI learns to see the world. A world model learns to predict what happens in it — specifically, what happens when people do things. That’s a different problem. Seeing is passive. Consequences require understanding cause and effect Any AI can learn to read a scene. A world model learns INTUITION about what changes it. @gen_intuition

Packy and I spent the past month unpacking world models from first principles. This piece is the result of that exploration. We go into why, what, how, and look out into the future on the implications of our work.