The following AlloyDB AI features are now generally available (GA)

## Feature Feature The following AlloyDB AI features are now generally available ([GA](https://cloud.google.com/products#product-launch-stages)): * [Auto vector embeddings](https://cloud.google.com/alloydb/docs/ai/generate-manage-auto-embeddings-for-tables) provide a scalable, automated solution for managing the lifecycle of vector embeddings for large-scale datasets, eliminating the need for manual reindexing or custom scripts. This feature keeps embeddings in sync with transactional data and now supports incremental refresh in `manual` mode, ensuring that embeddings are only generated for new or updated rows. Additionally, you can perform incremental table refreshes or migration up to 100x faster than traditional row-by-row processing using `bulk` mode, improving efficiency for semantic search and Retrieval Augmented Generation (RAG). * [AI functions](https://cloud.google.com/alloydb/docs/ai/ai-query-engine-landing) integrate LLMs like Gemini to bring 'world knowledge' to your AlloyDB data and incorporate advanced semantic search and ranking capabilities directly into your SQL workflows. This feature includes out-of-the-box functions for filtering (`ai.if`), semantic ranking (`ai.rank`), generation (`ai.generate`), and forecasting (`ai.forecast`). * Experience higher performance in AlloyDB AI by utilizing array-based AI functions. You can perform batch processing of natural language prompts directly within your SQL queries, significantly improving efficiency for large-scale AI operations. For more information, see [Perform intelligent SQL queries using AI functions](https://cloud.google.com/alloydb/docs/ai/evaluate-semantic-queries-ai-operators).