1. Generative AI is revolutionizing application development, enabling developers to create new user experiences previously not possible.
2. Cloud SQL for MySQL now supports vector search using ScaNN libraries, allowing for similarity searches by indexing and searching vector embeddings generated by large language models.
3. Upgrading to Cloud SQL for MySQL Enterprise Plus edition with 99.99% SLA for high availability and higher read throughput can enhance user experiences, such as recommending e-books to library patrons based on their preferences.
Generative AI is revolutionizing application development by enabling developers to create innovative user experiences previously impossible. Companies like Linear are utilizing Google Cloud databases to build AI-powered applications, with Cloud SQL for MySQL now offering similarity searches using vector embeddings generated by large language models. By storing vectors in Cloud SQL for MySQL instances, developers can search using nearest neighbor techniques such as KNN or ANN, supported by Google’s ScaNN libraries. This capability allows for more meaningful and relevant user experiences by combining vector search with real-time data.
To illustrate the practical application of this technology, let’s consider a library website using Cloud SQL for MySQL’s Enterprise Plus edition for high availability and increased read throughput. Enabling the cloudsql_vector MySQL flag allows developers to turn data into embeddings and store them in catalog tables for similarity searches. By following steps to get embeddings, store and index them, and perform similarity searches, developers can enhance their website’s functionality for users to find e-books they might enjoy. Adding a column like item_embedding with vector data type to the catalog table, developers can update the library’s catalog to include vector embeddings for all items in circulation, improving the website’s user experience.
In conclusion, Cloud SQL for MySQL’s vector search capabilities enable developers to leverage generative AI for more advanced application development with enhanced user experiences. This technology offers new possibilities for industries seeking to create innovative solutions that integrate AI-powered functionalities like similarity searches using vector embeddings. Requesting access to this preview feature opens up opportunities to explore and implement these capabilities in diverse application development scenarios.