SnowPro Specialty Gen AI GES-C01Demo

By Snowflake · Question Mode

QuestionQ24

Snowflake Gen AI & LLM Functions

A Gen AI Specialist requires a solution that supports asking questions in natural language and receiving answers based on structured data in Snowflake without using SQL.

How can this be achieved?

Choose two
  • A Create a custom data model, apply the data model to a database, and ask questions from the Snowflake Document AI option in the AI & ML Studio in Snowsight.
  • B Create a custom data model, enhance the model with cross-region inference, and ask questions in a custom-built application that calls the Snowflake Cortex Agent API.
  • C Create a semantic model, upload the semantic model to a stage, and ask questions from the Snowflake Cortex Analyst option in the AI & ML Studio in Snowsight.
  • D Create a semantic model, upload the semantic model to a stage, and ask questions in a custom-built application that calls the Snowflake Cortex Analyst API
  • E Create a Snowflake Cortex Agent in Snowsight, extract data from the database, and ask questions by fine-tuning an LLM with the extracted data.
Explanation

Snowflake Cortex Analyst answers natural-language questions about structured data by using a semantic model to generate the required SQL. A semantic model stored on a stage can be used in the Cortex Analyst experience in Snowsight or supplied to the Cortex Analyst API by a custom application.

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