📘 Blog · 🎬 Demo Gallery · 📄 Paper
- 2026 April: First open-source release of Neural Computers, starting with the data pipeline for CLI and GUI trajectory generation.
Neural Computers (NCs) are neural networks that unify computation, memory, and I/O in a single latent runtime state. The long-term goal is the Completely Neural Computer (CNC): a general-purpose neural computer that challenges the layered architecture of conventional computers. As an initial step, this project studies whether executable dynamics can be learned solely from collected I/O traces, without access to instrumented program state, using CLI and GUI trajectories as training and evaluation data.
Environment Python 3.9+ · Docker · asciinema · agg · ffmpeg
1. CLI / Asciinema
python3 main.py cligen asciinema record --command "python3 --version"
python3 main.py cligen asciinema cast-to-mp4 workspace/cligen_general/casts2. CLI / VHS
python3 main.py cligen vhs build-image
python3 main.py cligen vhs generate-basic --count 10 --prefix demo
python3 main.py cligen vhs make-manifest
python3 main.py cligen vhs run-manifest3. GUI / Synthetic
pip install -r engine/gui/synthetic_data_collection/requirements.txt
python3 main.py guiworld build-image
python3 main.py guiworld synthetic --count 1 --max-workers 1Using training data generated by the code released in this repository.
CLIGen (general / asciinema)
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CLIGen (clean / vhs)
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GUIWorld (GUI)
Alternating: Conventional Computer / Neural Computer
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Our models (not released here) are built from Wan2.1 and Matrix-Game-2. The data engine for CLIGen (General) is built from Asciinema, the data engine for CLIGen (Clean) is from VHS, the data engine for GUIWorld (Random) is modified directly from Neural-OS, and the data engine for GUIWorld (CUA) is built according to Claude CUA.
| Data Engine | Source |
|---|---|
| CLIGen (General) | Asciinema |
| CLIGen (Clean) | VHS |
| GUIWorld (Random) | Neural-OS |
| GUIWorld (CUA) | Claude CUA |

















