Understanding LLM Ops

LLM Ops, or large language model operations, has emerged as a critical framework for managing the deployment and lifecycle of large language models. This paradigm builds upon the foundations of traditional DevOps and ML Ops but is tailored to accommodate the unique challenges posed by foundation models. Unlike traditional machine learning models where data and training processes are well-defined, LLMs operate more as black boxes, necessitating new approaches for customization and evaluation. Key considerations in LLM Ops include prompt engineering and rigorous evaluation metrics to ensure models produce responsible and accurate outputs, particularly in sensitive applications such as finance and healthcare.