 The foundation of having that data management platform is absolutely fundamental and necessary to do good machine learning. Without good data, without good data management, you can't do good ML or AI sounds sort of simple, but very true. Hadoop's evolved. The nature and velocity of data has evolved in the last five, six, seven, eight years. It's about going to the edge. It's about leveraging the cloud. It's not about screens taking over the world and being in charge of you and us being dominated by them, as often we say in culture now. It's about having this really beautiful interface between technology and objects. So essentially, why would I need Hadoop? You know, if I can take the traditional tools people are now evolving and using, like Jupyter Notebooks Spark, TensorFlow, you know, those packages with Kubernetes on top of a database as a service and some object store, I have a much easier stack to work with. Enable everyone to make data-driven decisions, but make sure that they're interpreting that data in the right way, right? Give them enough guidance. Don't let them just kind of attack the wildland.