This new release of Ray 1.2 introduces two major features: native support for spilling to external storage and integration with libraries from the Python data processing ecosystem, including PySpark, Dask, Modin, and Mars. The goal is to enable developers to work with distributed data processing more directly within their Python applications, reducing the need for separate clusters or services. This should improve system efficiency and reduce operational overheads, allowing users to focus on writing more expressive code without worrying about setting up and maintaining complex infrastructure.