Arize has released new features, including the ability to run tasks once on historical data and filter experiments based on dataset attributes or experiment results. Users can now test a task by running it once on existing data or apply evaluation labels to older traces. Additionally, users can view logs and check if a task is set to run continuously or just once. Experiment filters allow for more precise tracking of experiment progress and identification of areas for improvement. The latest content includes video tutorials, paper readings, ebooks, self-guided learning modules, and technical posts on topics such as tracing LLM function calls, intro to LangGraph, exploring Google's NotebookLM, OpenTelemetry and LLM observability, object detection modeling, and building better AI.