This document discusses the future of artificial intelligence on the Java Virtual Machine (JVM). It outlines how machine learning frameworks are currently monolithic and make assumptions about data. The document proposes a micro-services approach to machine learning that separates out concerns like data pipelines, scoring, model training, and evaluation. This would help reduce lock-in and allow greater flexibility. It also discusses how new hardware like GPUs are better suited for deep learning and the role frameworks like Spark and Akka could play in distributed, real-time machine learning applications on the JVM.