The BigQuery ML
ML.GENERATE_EMBEDDING function
now supports the output_dimensionality argument for text-embedding and
text-multilingual-embedding models. The output_dimensionality argument lets
you specify the number of dimensions to use when generating embeddings.
Feature
Analytics Hub data egress controls are now generally available (GA). Publishers can now enforce egress restrictions on Analytics Hub listings to prevent subscribers from copying or exporting the shared data.
Feature
The slot recommender for editions analyzes historical usage data to recommend optimal capacity purchasing for edition and on-demand workloads. This feature is generally available (GA).
Changed
The BigQuery ML
ML.GENERATE_EMBEDDINGfunction now supports theoutput_dimensionalityargument fortext-embeddingandtext-multilingual-embeddingmodels. Theoutput_dimensionalityargument lets you specify the number of dimensions to use when generating embeddings.Feature
Analytics Hub data egress controls are now generally available (GA). Publishers can now enforce egress restrictions on Analytics Hub listings to prevent subscribers from copying or exporting the shared data.
Feature
The slot recommender for editions analyzes historical usage data to recommend optimal capacity purchasing for edition and on-demand workloads. This feature is generally available (GA).
https://cloud.google.com/bigquery/docs/release-notes#June_05_2024