A. The function can be directly integrated into a dynamic table's 'SELECT statement to provide continuous, automated embedding updates for new data.

B. If the function is not natively available in the account's primary Snowflake region, cross-region inference cannot be enabled, thus preventing its use.

C. The 'VECTOR' data type, which stores the output of is fully compatible with all Snowflake features, including being used as a primary key in hybrid tables for fast lookups.

D. When is invoked within a Snowpark Python User-Defined Function (UDF) on Snowflake data, the data remains within Snowflake's network boundary during the embedding generation process.

E. To support diverse embedding dimensions from different models, the 'VECTOR data type can be stored efficiently within a 'VARIANT column, which automatically handles schema variations.