Upon stepping onto General Intuition’s research and development floor at their New York headquarters, I was immediately guided by 31-year-old CEO and co-founder Pim de Witte toward a monitor on a standing desk. On screen, someone appeared to be playing a game reminiscent of Fortnite—but it wasn’t a human. “Our agent has been playing for 100 hours straight,” Kent Rollins, the chief product officer, said with a grin. Before I could fully take in the sight of an AI navigating the game’s virtual world, I heard the electronic footsteps of a large four-legged 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 streaming live footage from the robot’s single camera, chimed in to note that the bot’s default state was “exploration.”

Using only that camera—its singular eye—the oversized insect-like robot approached me, circled around, and then continued through the office. It occasionally bumped into chair legs or knocked over a stray trash bin, much like a toddler still learning how its body relates to the world. Duplantis mentioned that it took just eight minutes of real-world robotics data to fine-tune an AI model for the quadruped. Remarkably, that data was collected on the street, not inside the office where the bot was now navigating. An agentic model capable of generalizing from gameplay to simulation to physical embodiment is the very purpose of General Intuition. And the model’s ability to understand its place in the world has attracted major backers.

On Thursday, General Intuition announced it had raised $320 million at a $2.3 billion valuation. This brings the startup’s total disclosed funding to $454 million, following the $134 million round it secured at its launch last October. The company was spun out of de Witte’s other venture, Medal, a platform where gamers can upload and share video game clips. The hundreds of millions of hours of uploaded gameplay provided the initial dataset for training General Intuition’s model in spatial-temporal reasoning—essentially, understanding how to move through space and time. But the crucial element wasn’t just the video footage; it was the embedded action labels in those clips: precise records of which buttons a player pressed and when. Most competitors, de Witte argues, are trying to infer actions from video alone, which he believes is 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.”

At one point, de Witte handed me a laptop running General Intuition’s world model—a simulated environment generated frame by frame rather than rendered by a traditional game engine. As I often do when testing world models, I walked straight into a series of walls. In other demos I’ve tried, the agents you control sometimes pass right through, but this one didn’t. From millions of hours of gameplay, it had somehow learned that walls are walls, ladders are for climbing, and shadows grow longer as the sun moves. For General Intuition, this world model isn’t the final product; it’s the training environment (internally called “the gym”). The company ultimately aims to sell the agentic model itself, and de Witte argues that the action data embedded in gameplay helps the model distinguish the “self” from the “environment,” giving it a deeper understanding of causality.

Impressive as General Intuition’s technology may appear in demos, the company isn’t alone in tackling this challenge. Moreover, deploying such a model at scale in the physical world hasn’t been accomplished yet. Most similar approaches require massive amounts of real-world data, which is gathered slowly and at great expense. General Intuition’s bet is that gameplay offers a scalable shortcut. Its investors are comfortable with that bet. The latest round was led by Khosla Ventures, with participation from General Catalyst, Jeff Bezos, Eric Schmidt, Nico Rosberg, and researchers at Google DeepMind and MIT. The vast majority of the funding will go toward scaling compute capacity. General Intuition has a deal with CoreWeave and plans to focus on pre-training the next version of the model. A portion has been set aside to make its API more widely available by the end of summer. Vinod Khosla, whose firm led the round, said he was drawn to de Witte’s vision and the company’s exclusive data position. “If you look at LLMs, when reasoning emerged, it was a quantum leap,” Khosla told me in a phone interview. “In world models, I think the quantum leap is the emergence of intuition in the AI, a human intuition-like capability. The human action data and reaction data you have in games is the key part to the emergence of intuition.”

The vision is a generational company.

General Intuition isn’t the only company to recognize that Medal’s human action data is a critical piece of the puzzle for building dynamic world models and general agents. Brianna Martin, the startup’s chief of staff, said the company was born, in part, after Medal turned down an acquisition offer from a major lab. There have been other offers since. De Witte and his co-founders—Eloi Alonso, Adam Jelley, and Vincent Micheli—aren’t interested in being acquired, and neither are the startup’s investors looking for an exit just yet. The volume and quality of proprietary data General Intuition has through Medal is one reason Khosla believes the startup is a generational bet, not a merger target; it could become the backbone for generalized agents and world models in both simulation and the real world. “At this point, it would be a data acquisition, which is sort of uninteresting,” Khosla said.

Part of that bet also involves trusting de Witte’s principles. The entrepreneur spent three years working in the humanitarian space, including with Doctors Without Borders. As a result, he has drawn a clear line for how General Intuition’s technology will be used: no agents will be employed to harm humans. “We don’t want to be an escalatory part of the system,” de Witte said. “Let’s say I were to come out and say, ‘We’re doing lethal autonomy.’ What do you think would happen in other countries?”

That restriction on military applications comes as Silicon Valley grows increasingly enthusiastic about defense, though de Witte says he’s happy for his models to be used for search and rescue missions. De Witte is Dutch, and much of his team is European, which shapes the company’s identity. He says he brought on Martin in part because of her decision to publicly leave Palantir over its work with U.S. Immigration and Customs Enforcement. “I don’t know why Silicon Valley does what it does,” he said. “There’s a reason I’m not there.”

De Witte’s ethics don’t just limit what the models won’t do. As a gamer who earned $1.5 million by building and hosting a private RuneScape server in his teens, he’s also thinking about what happens to people left behind by what AI models can accomplish. General Intuition recently launched a platform called Nerve, a jobs marketplace that lets gamers earn money using their existing setups. Those who sign up start with data labeling and can eventually move toward robot teleoperation and other tasks. Medal’s user base, de Witte noted, is precisely the generation most exposed to AI-driven displacement, and he wants them to have a stake in what’s coming next.

**A data flywheel**

De Witte wants General Intuition to function as an ecosystem enabler, similar to Anthropic or OpenAI—a model provider that allows others to build on top of its technology. Today, the startup has a handful of customers in gaming, simulation, and robotics. “We’re not gonna build a self-driving car company,” de Witte said. “We’re gonna make it 10 times easier for the next person to build a self-driving car company.”

The company says that once its API reaches more customers, it will be able to test its capabilities across various use cases—such as testing a robot in a digital twin of a factory floor, powering a human-like bot inside a gaming studio, or sending a quadruped to navigate hazardous environments. While a quadruped is the first physical embodiment General Intuition has tried in the real world, it has also tested drones and other devices, including evaluating the model in driving games. “It works on anything that you can control using a game controller or a keyboard mouse,” de Witte said.

Building a data flywheel is one of the key goals. “We’ll pick customers where we can diversify the embodiments that this generalized foundation model is serving as the backbone for,” de Witte said. “So we’re going to prioritize picking customers based on whether they can offer real-world data that’s going to be interesting and useful to move the needle on research. And if they’d have an agile internal team where we can be real embedded partners and learn from each other.”

Khosla said that General Intuition’s proprietary data is what brought it this far, and its ability to continue collecting data that no one else has will be essential. This is especially true because, despite impressive demos, whether the simulation-to-real-world transfer can hold at scale is an open question that nobody has fully answered yet.

*Correction: The headline previously misstated how much General Intuition raised in this round. The error has been fixed.*