5. On-Premises LLM: Myth, Reality, and Conditions for Success
Objective: to debunk myths; to establish the factual conditions.
On-premise LLM has become, in some committees, the knee-jerk response to: “ChatGPT is banned.”
As if hosting the system in-house automatically solved all issues: security, sovereignty, and control. In practice, this oversimplification doesn’t hold up for long.
A major industrial group launched an on-premise LLM project with great enthusiasm: budget approved, GPUs ordered, ambitious presentations. Twelve months later, the model was still running, but only for three pilot users, within a fixed scope, and without any real business value. Not because the technology didn’t work. But because technical feasibility had been confused with industrial sustainability.
An on-premises LLM isn’t a default option. It’s a major,...
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On-Premises LLM: Myth, Reality, and Conditions for Success
Decide without getting bogged down: a pragmatic approach
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