New York-based AI startup General Intuition is negotiating a $300 million funding round that would place its valuation just above $2 billion, according to sources familiar with the matter. The financing comes approximately eight months after the company spun out of Medal, the video game clip-sharing platform, which previously secured a $134 million seed investment. The new capital will be directed toward expanding computational infrastructure to support the launch of a new product expected by late summer or early fall. Co-founded by Medal’s original creator Pim de Witte and led by researchers Eloi Alonso, Adam Jelley, and Vincent Micheli, General Intuition specializes in developing foundation models designed to train embodied artificial intelligence agents. The company’s core advantage stems from Medal’s proprietary dataset, which comprises two billion videos annually generated by ten million monthly active users. This collection of interactive, first-person gameplay footage provides a unique training environment for teaching machines advanced spatial-temporal reasoning, enabling real-time perception, anticipation, and interaction within simulated environments. The startup’s data assets have drawn significant interest from major technology firms. OpenAI previously attempted to acquire Medal, and industry sources indicate that the company’s capabilities continue to attract attention from leading artificial intelligence laboratories. General Intuition operates within a rapidly expanding market for generative world models, competing alongside firms such as Runway, Decart, and World Labs, while Google recently expanded its Genie 3 capabilities with integrated mapping data. Unlike competitors that focus on licensing generative models, General Intuition’s strategy centers on delivering trained AI agents as its primary product, positioning gaming and robotics as immediate commercial applications. Backed by prominent investors including Jeff Bezos, Eric Schmidt, Khosla Ventures, and General Catalyst, the company is leveraging this financial injection to accelerate its development pipeline. The funding round underscores growing institutional confidence in foundational spatial-temporal modeling and its practical applications in autonomous system training.