Genesis AI's open simulation platform for physical AI: one Pythonic API over a multi-physics engine (rigid, FEM, MPM, PBD, SPH, Stable Fluid, IPC), the Nyx path tracer, and Quadrants, a cross-platform Python-to-GPU compiler. It is built to be the evaluation engine for robot foundation models rather than a data factory: 30,000 parallel environments at 43M FPS, and under a zero-shot real-to-sim protocol, sim-vs-real evaluation agreement of Pearson 0.8996 with mean maximum rank violation 0.0166. Apache 2.0, 29.9k stars.
A small Python + C++ library from Kevin Zakka that steps thousands of MuJoCo simulations in parallel on the CPU through a single Batch object: C++ thread pool execution with the GIL released, bind() giving live array views across the whole batch, and expand() for per-simulation model parameters. Memory scales with thread count rather than simulation count, so 4096 simulations stay under 256MB; on a 24-thread machine with a Unitree G1 scene it measured 10.3x over a serial mj_step loop, reaching 676,019 sim-substeps per second with ten substeps batched per call. The repo ships six self-contained solver examples spanning iLQR, predictive-sampling MPC, PPO reinforcement learning, CEM hardware co-design and damped Gauss-Newton system identification, including a Go1 joystick controller that learns to walk in under a minute on a five-year-old M1 laptop.