Genesis AI, a startup that aims to build a foundational model for powering all kinds of robots, has emerged from stealth with a giant $105 million seed round co-led by Eclipse Ventures and Khosla Ventures. Founded last December by Zhou Xian (pictured above, left), who holds a PhD in robotics from Carnegie Mellon University, and Théophile Gervet (pictured above, right), a former research scientist with the French AI lab Mistral, the startup wants to build a general-purpose model that will enable robots to automate a wide range of repetitive tasks, from lab work to housekeeping. Large language models are trained on vast datasets of text, but AI models for robotics must be trained on data on the physical world. However, acquiring that real-world data makes for a costly and time-consuming endeavor. To overcome that, Genesis is turning to synthetic data, which it generates using a proprietary physics engine that, it says, is capable of accurately modeling the physical world. Genesis’ synthetic data engine originated from an academic project that Xian led in collaboration with researchers from 18 universities. Several participants from that project have since joined Genesis, making up its current staff of over 20 researchers who specialize in robotics, machine learning, and graphics.

Full report : Genesis AI, which generates synthetic data for training an AI model meant to power robots, emerges from stealth with a $105 million seed co-led by Eclipse and Khosla.