On August 21, 2023, a new integration between Comet and Ray was announced, enhancing the capabilities for data scientists to manage and scale machine learning workloads effectively. Ray, an open-source project, simplifies scaling compute-intensive Python tasks such as deep learning and model serving, with a flexible distributed execution framework supporting various libraries. The integration introduces CometLoggerCallback, enabling users to log metrics, hyperparameters, and source code from Ray Trials to the Comet UI, thereby facilitating comprehensive experiment tracking and visualization. The setup involves configuring Comet credentials and installing Ray Tune and Comet via pip, allowing engineers to leverage Comet’s visualization tools to gain insights into their Ray experiments. This collaboration is expected to drive advancements in machine learning, with notable companies like Uber, Amazon, LinkedIn, and OpenAI already utilizing Ray for their ML workflows.