General Intuition has raised $320 million at a $2.3 billion valuation, putting a large new financing round behind a bet that gameplay can become a training ground for more capable AI agents.

The company says it is building foundation models for environments that require spatial and temporal reasoning. The practical claim is narrow but important: models trained on interactive game data may learn how objects, spaces, goals, and timing relate to one another in ways that text-only systems cannot capture.

TechCrunch reported that the round was led by Khosla Ventures and brings General Intuition's disclosed funding to $454 million, after a $134 million launch round last year. GamesBeat also reported the $320 million raise and $2.3 billion valuation, describing the company's focus as frontier models based on gameplay data.

General Intuition was spun out of Medal, the gaming clip platform, giving it access to a large pool of recorded player behavior. The company is using that data to train models that can reason across games, simulation, and embodied systems, including robotics.

The funding is notable because it shifts the "world model" race toward interactive data rather than only web text, images, or passive video. The hard test will be transfer: whether agents that learn from games can reliably perform in messy physical settings, not just controlled demos.