BigQuery vector search and embedding generation

Опубликовано 25 апреля 2024, 4:00

Discover the power of semantic search! With BigQuery's vector search capabilities, you can analyze unstructured data like text, images, and videos based on their underlying meaning. Explore how machine learning transforms your data into numerical representations called embeddings, making it possible to find connections that traditional keyword searches often miss.

In this video, you'll learn how BigQuery seamlessly generates embeddings from unstructured objects and enables semantic search using familiar SQL functions. See a real-world example as we use these techniques to search a non-labeled product image catalog with text.

Vector search resources:
Learn more in the vector search documentation → goo.gle/bq-vector-search
Read the vector search blog here→ goo.gle/bq-vector-search-blog

Embedding generation resources:
Learn more in the embedding generation with BigQuery documentation → goo.gle/bqml-generate-embeddin...

Subscribe to Google Cloud Tech → goo.gle/GoogleCloudTech