At a keynote at the GPU Technology Conference in Munich today, Nvidia, the video/graphics company turned Artificial Intelligence (AI) juggernaut, is today going another step forward in the AI direction. This time though, Nvidia isn't announcing a new Graphics Processing Unit (GPU) platform, or a new proprietary SDK for deep learning, but is instead announcing new a set of new open source libraries for GPU-accelerated analytics and machine learning (ML). Rapid AI movement Dubbed RAPIDS, the new library set will offer Python interfaces similar to those provided by Scikit Learn and Pandas, but which will leverage the company's CUDA platform for acceleration across one or multiple GPUs. According to Nvidia CEO Jensen Huang, who briefed a number of technology journalists by phone on Tuesday, Nvidia has seen 50x speed up in training times when using RAPIDS versus a CPU-only implementation. Integrations and partners RAPIDS apparently incorporates in-memory columnar data technology Apache Arrow, and is designed to run on Apache Spark.