2021 Trends in Artificial Intelligence and Machine Learning: The ModelOps Movement - insideBIGDATA

Everything Artificial Intelligence has ever been, hopes to be, or currently is to the enterprise has been encapsulated in a single emergent concept, a hybrid term, simultaneously detailing exactly where it is today, and just where it's headed in the coming year. The ModelOps notion is so emblematic of AI because it gives credence to its full breadth (from machine learning to its knowledge base), which Gartner indicates involves rules, agents, knowledge graphs, and more. ModelOps is about more than simply operationalizing and governing AI models. Moreover, it involves doing so onsite while leveraging the advantages of the cloud and, when it comes to AI's machine learning prowess, with a range of approaches rooted in supervised, unsupervised, and even reinforcement learning. Implicit to these capabilities is the need to position machine learning models at the edge, supersede their traditional training data limitations (and methods), and imbibe everything from streaming to static data for a predictive exactness based on the most current data possible.