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Publish Trained AI OS policy with capability-gated model machine
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---
title: Kernelmind Ai Os Lab
emoji: 🧪
colorFrom: indigo
colorTo: blue
sdk: static
app_file: index.html
pinned: false
---
# KernelMind AI OS + Model Machine
KernelMind is a trainable AI operating-system policy kernel. It maps user intent,
resource target, privilege state, network availability, confirmation, file
existence, and service state into a three-action structured plan. The compact
Transformer is trained from scratch on an exhaustive synthetic capability corpus.
The bundled Model Machine is an in-memory virtual computer. It applies an
independent deterministic capability gate before every action, so deletion,
installation, service restart, web access, and protected-file operations cannot
be authorized by model output alone. It never executes commands or touches the
host filesystem.
This is a real trained OS-action policy and runtime prototype, not a bootable
general-purpose operating-system kernel. That boundary is deliberate and tested.
## Verified local result
The 19,527-parameter Transformer reached 100% exact-plan and action-slot accuracy
on 192 held-out combinations after training on 1,536 scenarios. It made zero
unsafe proposals in that test set. A separate hostile-plan audit injected 576
unauthorized delete, install, and restart actions; the Model Machine capability
gate blocked all 576.
```bash
uv run python projects/kernelmind-ai-os/train.py
uv run pytest tests/test_kernelmind_ai_os.py
```
## Hosted showcase
This free static Space preserves the complete original Gradio source, trained artifacts, evaluation files, and local launch requirements. Hugging Face now requires PRO for CPU-backed Gradio hosting, so the public landing page is static while the checked-in `app.py` remains the authoritative runnable demo.