The platform consists of tools for every step in the modern machine learning lifecycle--from developing machine-learning models to building intelligent applications to integrating machine learning outputs into business intelligence and visualization tools--so it's accessible by business teams. The platform features a portfolio of data management solutions which offer unmatched ability to store and process data at any scale--and data integration tools to ensure data in any format can be accessed for machine learning model building. The platform runs on top of Oracle Cloud Infrastructure, which is optimized for running AI workloads, offering high-speed network fabric and a wide range of GPU and CPU compute options for small- to large-scale model building, training, and production deployments.

Machine learning and its artificial intelligence parent are probably most often regarded by regular-ass people as kind of opaque and esoteric subjects. Or even just tech buzzwords, which is a shame because it doesn't have to be like that. These things are just tools and as tools they can be employed for extremely complex, inscrutable-seeming tasks found in fields like neuroprosthetics or machine perception, or they can be used for everyday things like classifying spam. In other words, machine learning doesn't have to be brain surgery, though it can be useful for that. At the same time, getting into something like Google's TensorFlow open-source machine learning library is pretty daunting.