
Emerging from stealth mode, Genesis AI has announced the completion of a substantial $105 million seed funding round, co-led by Eclipse Ventures and Khosla Ventures. Founded in December by Zhou Xian, a robotics Ph.D. from Carnegie Mellon University, alongside Théophile Gervet, a former research scientist from the French AI lab Mistral, the startup is on a mission to develop a comprehensive model that can empower robots to automate a diverse array of repetitive tasks, ranging from laboratory functions to household chores. Unlike traditional large language models that rely on extensive text datasets, Genesis AI focuses on training its robotics models with real-world data. However, the process of gathering such data is often fraught with high costs and time constraints. To address this issue, Genesis is leveraging synthetic data generated through a proprietary physics engine, which claims to accurately replicate the physical environment. This innovative synthetic data engine is the product of an academic initiative that Xian spearheaded, in collaboration with researchers from 18 universities. Many contributors to that project have now joined Genesis, forming a skilled team of over 20 researchers specializing in robotics, machine learning, and graphics. Genesis AI asserts that its unique simulation technology enables faster model development, giving it a competitive edge over rivals who depend on NVIDIA’s software. Other players in the field include Physical Intelligence, which recently secured $400 million in funding, and Skild AI, valued at $4 billion earlier this year. Kanu Gulati, a partner at Khosla Ventures, expressed enthusiasm for Genesis AI's potential, stating, "It’s a big unknown: Will anybody have a large robotics foundation model that will generalize across tasks? That’s a bet we want to go after. Of all the teams we have seen, we like [Genesis’s] approach for going after robotics foundation models." With operations in both Silicon Valley and Paris, Genesis AI is poised to unveil its foundational model to the robotics community by year’s end.
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