On your 2026 mid-range gaming workstation, training a high-DoF robot arm and a complex hand for basic pick-and-place tasks via Reinforcement Learning takes roughly 30 to 45 minutes of real-world wall clock time.
Because your GPU can handle massive parallelization, it compresses
over 5 years of trial-and-error training experience into that brief window. Once trained, deploying the resulting policy down to your edge devices (
Raspberry Pi 5 and
Pico 2) requires a specific hardware communication architecture.
I'm not sure if the search engine results are correct, but this seems much better than when I took the Deep RL class 4 years ago.