Train and deploy your own open-source humanoid in Python
Hi HN, I’m Ben, founder of K-Scale Labs (YC W24). Last year, I wanted to buy a humanoid robot that I could hack on, but the few options for sale were either too expensive, proprietary, or had a limited SDK. We set out to build an affordable humanoid robot using off-the-shelf components that can be built and shipped today, capable of running modern machine learning models, and make it completely open-source for developers like me. Today, we’re releasing our reinforcement learning library and sim2real pipeline for people who want to train policies for humanoid robots. If you have a computer,…
Train and deploy your own open-source humanoid in Python launched on May 18, 2025 with 30 votes, #703 of 7,905 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
K-Scale Labs provides an open-source platform for training and deploying humanoid robots using Python. The system includes a reinforcement learning library and sim2real pipeline that allows developers to train robot policies on their computers before transferring them to physical hardware built from off-the-shelf components. Designed for developers who want affordable, hackable humanoid robots with modern machine learning capabilities, the platform can be tested in under five minutes and is entirely open-source.
written from the facts on this page · September 2026
From the sources
K-Sim Gym: Making robots useful with RL. Built on top of K-Sim. - kscalelabs/ksim-gym
You can use this repository as a GitHub template or as a Google Colab. You can quickly try out the humanoid benchmark by running the training notebook in Google Colab. git clone [email protected]: < YOUR USERNAME > /ksim-gym.git cd ksim-gym Create a new Python environment (we require Python 3.11 or later and recommend using conda ) Install the package with its dependencies: pip install -r requirements.txt pip install ' jax[cuda12] ' # If using GPU machine, install JAX CUDA libraries python -c " import jax; print(jax.default_backend()) " # Should print "gpu" Train a policy: Your robot should be walking within ~80 training steps, which takes 30 minutes on an RTX 4090 GPU. Training runs…from github.com
In the maker’s words, at launch
Hi HN, I’m Ben, founder of K-Scale Labs (YC W24). Last year, I wanted to buy a humanoid robot that I could hack on, but the few options for sale were either too expensive, proprietary, or had a limited SDK. We set out to build an affordable humanoid robot using off-the-shelf components that can be built and shipped…
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