Ray Data GA

Ray Data, a scalable data processing library for AI workloads, has been announced as generally available with stability improvements in streaming execution, reading and writing data, better tasks concurrency control, and debuggability improvement with dashboard, logging and metrics visualization. It is built to efficiently use mixed CPU and GPU resources, integrates seamlessly with both the data and AI ecosystems, while offering fault tolerance and resource multiplexing properties of traditional batch processing systems. Ray Data supports unstructured data preprocessing, batch inference, and ingest for ML training workloads. It also integrates with most common tools between the data and AI ecosystems such as ML frameworks, file formats, data sources, and cloud storage.