Today we’re introducing UniversalAGI. Airplanes take 20 years to build. Cars take 5. Drones take 1. None of that is required by physics. It’s required by how we test. Engineers can’t test every design, so they test almost none. Simulation was supposed to fix this. It didn’t. Complex setups, hours-long runs, and compute costs mean most of the design space never gets looked at. The best machine you could build is usually the one you never had time to try. We’re building the physics AI that ends that. Our first architecture is LIFT, the Latent Interaction Field Transformer. It predicts industry-grade, 4D high-fidelity surface and volume fields across physical domains. The conditions on an object and the flow around it are learned together in a shared latent space, not separately. It’s faster and more accurate. In a controlled comparison, LIFT delivered 6.27× the inference throughput of AB-UPT and 1.72× that of Transolver’s separate surface-and-volume models. In one aircraft design search, LIFT evaluated 5,800 candidates in 19 minutes. CAD upload to optimized design. Every candidate screened before a single high-fidelity run or physical test. Customers loved using LIFT in their design workflows, rockets, ships, drones, cars, oil & gas reservoirs, bioreactors, batteries and turbo-machinary. We’re building foundation models for the physical world. Aerospace, defense, energy, manufacturing, maritime, automotive. The time to build something new should be set by ambition, not compute. Architecture and results: universalagi.com/research/li…