via TechCrunch AI
General Intuition’s $2.3B Bet That Video Games Can Train AI Agents for the Real World
When I stepped onto General Intuition’s R&D floor at its New York office, the company’s 31-year-old co-founder and CEO Pim de Witte immediately directed my attention to a monitor on a standing desk. It looked like someone was playing a game similar to Fortnite. But it wasn’t a person.
“Our agent has been playing for 100 hours straight,” said Kent Rollins, the chief product officer, beaming.
Before I could fully absorb the sight of an AI navigating the game’s virtual world, I heard the electronic footsteps of a large quadrupedal robot approaching.
“The same brain powering the agent playing the game is powering the robot,” de Witte explained. Josh Duplantis, a data analyst carrying a laptop that streamed a live feed from the robot’s single camera, chimed in to say the bot’s default mode was “exploration.”
Using only that camera—its singular eye—the giant bug-like robot walked up to me, circled around, and continued into the office. It occasionally clipped chair legs or bumped into an errant trash bin, much like a toddler still learning how its body relates to the world. Duplantis noted that it took just eight minutes of real-world robotics data to fine-tune the AI model for the quadruped. Remarkably, that data was collected on the street, not inside the office where the bot was navigating itself.
General Intuition’s raison d’être is an agentic model that can generalize from gameplay to simulation to embodiment—a model capable of understanding its place in the world. That ability has already attracted backing from major investors.
On Thursday, General Intuition announced it raised $320 million at a $2.3 billion valuation, confirming TechCrunch’s earlier reporting. The round brings the startup’s total disclosed funding to $454 million, following the $134 million seed round it raised at launch in October 2025.
The startup emerged from de Witte’s other company, Medal, which lets gamers upload and share video game clips. Hundreds of millions of hours of uploaded gameplay provided the initial dataset to train General Intuition’s model in spatial-temporal reasoning—the ability to understand how to move through space and time.
Crucially, the key ingredient wasn’t just the gameplay footage; it was the action labels embedded in those clips: records of exactly which buttons a player pressed and when. De Witte argues that most competitors are trying to infer actions from video alone, which he considers insufficient.
“We view this as just the next stage of future pre-training,” de Witte said. “We have a single model that can respond to Fortnite information on the screen and take action, but also to real-world dynamics in a way that an LLM could never.”
During my visit, de Witte also set me up with a laptop running General Intuition’s world model—a simulated environment generated frame-by-frame rather than rendered by a traditional game engine.