An important update has been made to the "Looking Similar" feature in Recommend. Previously, this feature could only fetch a maximum of 500k items, which prevented the model from being trained if the catalog exceeded this limit. This posed a challenge for customers with larger indices. With this update, Algolia now accepts indices of all sizes, still fetching up to the maximum number of items. Records are browsed and ordered by Custom Ranking to prioritize the most relevant items based on your business criteria. For example, training on a catalog of 3 million book items now completes in 5 hours using the top 500k records. Next, the limit will be tested at 1 million items, enhancing flexibility and usability for larger datasets.