MODELOPS VS MLOPS: HERE IS WHAT YOU NEED TO KNOW

One area marked by confusion today is understanding the differences between ModelOps vs. MLOps. ModelOps is the missing link for today's approach, connecting together existing data management solutions and model training tools to the value delivered via business applications. By incorporating ModelOps into your AI pipeline, you'll move past last-mile challenges with operationalizing AI and begin to see the return on your investments in the form of reduced costs, increased revenues, and better risk management. Recently, ModelOps has emerged as the critical link to addressing last-mile delivery challenges for AI deployments. ModelOps is a superset of MLOps, which refers to the processes involved to operationalize and manage AI models in use in production systems.