Databricks Certified Generative AI Engineer - Associate

When working with Generative AI applications in Databricks that require vector search, it is crucial to use an indexing method that is optimized for high-dimensional data. Embeddings used in such models are typically high-dimensional vectors, and the search needs to be efficient in terms of both speed and accuracy. Using a vector indexing method such as FAISS or Annoy, which are specifically designed for similarity search in high-dimensional spaces, ensures that the application can perform efficiently. Other methods like relational databases or CSV formats would not be optimized for this purpose and would result in slower and less efficient querying.