Posts by Noah Monti
Unlocking Sim2Real for a Robotic Arm with RL Accelerated by AMD Instinct GPUs
- 29 September 2026
Training a policy in simulation and transferring those weights to a real robot (sim2real) is a highly desirable goal in physical AI. Simulation scales data collection far beyond what a single robot can provide, but mismatches in physics and in the software stack make transfer difficult. In this blog post, we train a pick-and-lift policy for a UFactory XArm-6 with reinforcement learning on AMD Instinct GPUs, then deploy the same network on the real arm with a classical perception front-end in place of privileged simulator state.
Utilizing AMD Schola and UnrealRoboticsLab with AMD ROCm™ Software to Train a Robotic Arm
- 17 June 2026
A great reinforcement learning (RL) training environment excels along many axes. Unreal® Engine brings a powerful combination of capabilities, including physically based rendering, high-fidelity visual environments, and a mature toolset for building rich interactive scenes. These strengths make it an excellent fit for training tasks that involve complex lighting or rich vision-based observations.
Training a Robotic Arm Using MuJoCo and JAX on AMD Hardware with ROCm™
- 31 March 2026
Training a robotic arm to pick up an object and place it somewhere else may sound straightforward, but teaching a robot to do this reliably in the real world is one of the harder problems in robotics. Traditional approaches rely on hand-tuned motion planning and carefully scripted control logic, which is brittle and time-consuming to maintain as environments change.