How to Run a Sandboxed LLM in a School Lab With No Cloud Bill
The default way schools adopt AI is to send student work to a vendor's cloud. That choice creates three problems at once, and all three land hardest on the schools with the least money.
First, student data leaves the building. Minors' writing, questions, and mistakes travel to a third party under terms a teacher rarely reads. Second, the bill scales with use, so the more students benefit, the more it costs, which pushes schools to ration access. Third, it requires reliable internet, which many schools do not have in every classroom.
There is a design that removes all three. Run a small open model locally, on hardware the school owns, sandboxed from the internet. I research offline and sandboxed LLMs for secure academic computing, and the architecture that protects sensitive research transfers cleanly to a school lab. The constraints are nearly identical: keep the data in, keep the cost flat,...
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