Deploy Your Own Private LLM
What a private LLM deployment means in practice, when it makes sense, and how to evaluate the operational trade-offs beyond simple privacy slogans.
Deployment
Open-Source LLMs You Can Host
A practical overview of hostable open-weight models and how to think about choosing one for real business tasks.
Deployed, Retrained, Repeated: When LLMs Learn From Being Used
Opening — Why this matters now The AI industry likes to pretend that training happens in neat, well-funded labs and deployment is merely the victory lap. Reality, as usual, is less tidy. Large language models are increasingly learning after release—absorbing their own successful outputs through user curation, web sharing, and subsequent fine‑tuning. This paper puts a sharp analytical frame around that uncomfortable truth: deployment itself is becoming a training regime. ...