To learn more about how to build next-generation machine learning applications, check out the session "Building reinforcement learning applications with Ray" at the AI Conference in San Francisco, September 4-7, 2018. Hurry--best price ends June 8. We are in an empirical era for machine learning, and it's important to be able to identify tools that enable efficient experimentation with end-to-end machine learning pipelines. Organizations that are using and deploying machine learning are confronted with a plethora of options for training models and model inference, at the edge and on cloud services. To that end,MLPerf, a new set of benchmarks compiled by a growing list of industry and academic contributors,was recently announced at the recent Artificial Intelligence conference in NYC.