Project Showcase
Projects, experiments and challenges. No work brief or research goal required — start with curiosity.
Open-source AI projects that aren't products yet but are worth running and studying — agents, coding agents, infrastructure, and Korean open weights.
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Korean open-source AI tools
The Korean-language layer — morphology, NLP, learning resources, and the HWP document format our challenge is trying to crack open.
Fast modern Korean morphological analyzer in C++ with Python bindings — the practical choice for tokenizing Korean text in production pipelines today.
The workhorse of modern Korean text processing
The classic Korean NLP toolkit that unified a generation of morphological analyzers behind one Python API — still the first import in most Korean NLP notebooks.
Where Korean NLP standardized
The most complete Korean-language LLM engineering curriculum on GitHub — hands-on LangChain/RAG/agent notebooks that much of Korea's AI developer community learned from.
Korea's de-facto open LLM textbook
Open-source HWP viewer and parser in TypeScript — one of the few serious open attacks on Korea's closed document format, and directly relevant to our HWP challenge.
Proof the HWP format can be opened
Robotics & embodied AI
Wave 5 in the open: the projects making robot learning reproducible outside big labs — where Korea's manufacturing edge meets open software.
Open robot-learning stack — datasets, imitation and RL policies, and low-cost robot arm designs that made real-robot training accessible to individuals.
Robot learning's Hugging Face moment
Generative physics engine for robotics — ultra-fast parallel simulation designed to train embodied agents at scales physical hardware can't match.
Simulation speed as the new training data
Open vision-language-action model for robot manipulation — the reference open checkpoint for turning camera frames and instructions into robot actions.
The open baseline every VLA paper compares against