From the official release notes and blog. Every item points at the concepts worth re-reading.
Automatic change data feed computes row-level changes at query time with row tracking, without manually enabling change data feed on each Delta Lake or Apache Iceberg v3 table. It works with batch queries, Structured Streaming, and Delta Sharing, and requires Databricks Runtime 19 LTS or above with row tracking enabled.
Automatic change data feed reached general availability in Databricks. It computes change data feed at read time from row tracking on Delta Lake tables and row lineage on Apache Iceberg v3 tables, so qualifying Unity Catalog tables can serve row-level changes.
Auto CDF derives inserts, updates and deletes at query time from row tracking, so a table no longer has to have the change data feed enabled before the fact to be read as a stream of changes. Databricks measures MERGE and UPDATE about 15% faster with it. Generally available.
Nothing of that kind yet.