Ray version 1.6 is released

The new version 1.6 of Ray includes several key updates, including the introduction of Ray Datasets for large-scale data loading, Runtime Environments for better dependency packaging, support for GCP TPU VMs in the Autoscaler, and the addition of Ray Lightning as a plugin for PyTorch Lightning to enable parallel training. These features aim to address interoperability issues, provide high-level abstractions, and simplify the process of running large-scale data processing applications on Ray. The updates are designed to make it easier for users to work with Ray and take advantage of its distributed computing capabilities.