The rise of Big Data I want to take you back to 2012 . In those early years, our focus was big data, and everyone else was looking at the cloud. We were pioneering, but in a world that was still beginning to understand the value of data.
MLOps — bringing AI models to production Developing a machine learning model is often the first step in creating an AI solution, but never the last. In order to make a model actionable, it needs to be served and its predictions delivered to an application. But what if suddenly many users send requests at the same time or when the system becomes unresponsive? And what if the data on which the model was trained is no longer representative of current real-world data, and the performance of the model starts to deteriorate? This is where Machine Learning Operations (MLOps) come in: a combination of tools and processes to create and automatically maintain a robust and up to date AI system.