Understanding LLMOps in the Context of MLOps

LLMOps refers to the operational practices that support large language models, paralleling traditional MLOps for general machine learning. As the demand for LLMs has soared, the focus of companies like Neptune.ai shifted towards scaling their experiment tracking capabilities to meet these needs. With growing complexities in training such models, teams face challenges in effectively managing data and operational scaling that were less pronounced with previous ML models. This advancement emphasizes the integration of research and production environments, where the same teams are now responsible for deploying sophisticated language models.