Upon stepping onto General Intuition’s research and development floor at its New York headquarters, I was immediately guided by the company’s 31-year-old co-founder and CEO, Pim de Witte, toward a monitor on a standing desk. On the screen, someone appeared to be playing Fortnite—but it wasn’t a person. “Our agent has been playing for 100 hours straight,” said Kent Rollins, the chief product officer, with a proud smile. Just as I became captivated by the sight of an AI navigating the game’s virtual landscape, I heard the electronic clatter of a large, four-legged robot approaching. “The same brain powering the agent playing Fortnite 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 clarify that the bot’s default state was “exploration.”

Using that camera as its sole eye, the giant 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 noted that it took only eight minutes of real-world robotics data to fine-tune an AI model for this quadruped. Remarkably, that data was collected on the street, not in the office where the bot was now navigating. An agentic model capable of generalizing from gameplay to simulation to physical embodiment is General Intuition’s core mission. And the model’s ability to understand its place in the world has attracted backing from several major players. On Thursday, General Intuition announced it had raised $320 million at a valuation of $2. This round brings the company’s total disclosed funding to $454 million, following the $134 million round it secured at its launch in October. The startup emerged from de Witte’s other company, Medal, which lets gamers upload and share video game clips. The hundreds of millions of hours of uploaded gameplay provided the initial dataset to train General Intuition’s model in spatial-temporal reasoning—understanding how to move through space and time. However, the crucial element wasn’t the gameplay footage itself; it was the action labels embedded in those clips: precise records of which buttons a player pressed and when. Most competitors, de Witte argues, try to infer actions from video alone, which he believes is insufficient. “We view this as just the next stage of future pre-training,” he 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 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. As I often do when testing world models, I walked straight into a series of walls. In other demos I’ve tried, the agents I control sometimes pass right through, but this one didn’t. From millions of hours of gameplay, it had somehow learned that walls are solid, ladders are for climbing, and shadows lengthen as the sun moves. For General Intuition, this world model isn’t the product itself; it’s the training environment, internally called “the gym.” The company ultimately aims to sell the agentic model, and de Witte argues that the action data embedded in gameplay helps the model distinguish the “self” from the “environment,” giving it a richer understanding of causality. Impressive as General Intuition’s technology appears in demos, the company isn’t the only one tackling this problem. Moreover, getting such a model to function reliably in the physical world at scale hasn’t been achieved yet. Most similar approaches require enormous amounts of real-world data, 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 broadly 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 proprietary 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 the startup’s investors aren’t looking for an exit yet either. The amount and quality of proprietary data General Intuition has through Medal is one of the reasons Khosla believes the startup is a generational bet, not an M&A 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 values. The entrepreneur spent seven 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 limit on military use cases comes as Silicon Valley grows increasingly bullish on war. De Witte says he’s happy for his models to be used for search and rescue missions, though he feels that Silicon Valley’s recent obsession with defense “infects the ecosystem.” 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 quit 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 simply limit what the models won’t do. As a gamer who made $1.5 million by building and hosting a private RuneScape server in his teens, he is 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 be an ecosystem enabler, like Anthropic or OpenAI—a model provider that enables 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 once it gets its API into more customers’ hands, it can test its mettle with a variety of use cases—like 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 experimented with drones and other devices, including testing 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 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 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 got it this far, and its ability to continue collecting data that no one else has will be essential. Especially 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.