Databricks Certified Generative AI Engineer Associate
Last Update Oct 15, 2024
Total Questions : 45
To help you prepare for the Databricks-Generative-AI-Engineer-Associate Databricks exam, we are offering free Databricks-Generative-AI-Engineer-Associate Databricks exam questions. All you need to do is sign up, provide your details, and prepare with the free Databricks-Generative-AI-Engineer-Associate practice questions. Once you have done that, you will have access to the entire pool of Databricks Certified Generative AI Engineer Associate Databricks-Generative-AI-Engineer-Associate test questions which will help you better prepare for the exam. Additionally, you can also find a range of Databricks Certified Generative AI Engineer Associate resources online to help you better understand the topics covered on the exam, such as Databricks Certified Generative AI Engineer Associate Databricks-Generative-AI-Engineer-Associate video tutorials, blogs, study guides, and more. Additionally, you can also practice with realistic Databricks Databricks-Generative-AI-Engineer-Associate exam simulations and get feedback on your progress. Finally, you can also share your progress with friends and family and get encouragement and support from them.
A Generative AI Engineer wants to build an LLM-based solution to help a restaurant improve its online customer experience with bookings by automatically handling common customer inquiries. The goal of the solution is to minimize escalations to human intervention and phone calls while maintaining a personalized interaction. To design the solution, the Generative AI Engineer needs to define the input data to the LLM and the task it should perform.
Which input/output pair will support their goal?
A Generative Al Engineer has developed an LLM application to answer questions about internal company policies. The Generative AI Engineer must ensure that the application doesn’t hallucinate or leak confidential data.
Which approach should NOT be used to mitigate hallucination or confidential data leakage?
A Generative AI Engineer is creating an LLM-powered application that will need access to up-to-date news articles and stock prices.
The design requires the use of stock prices which are stored in Delta tables and finding the latest relevant news articles by searching the internet.
How should the Generative AI Engineer architect their LLM system?
A Generative Al Engineer is tasked with developing a RAG application that will help a small internal group of experts at their company answer specific questions, augmented by an internal knowledge base. They want the best possible quality in the answers, and neither latency nor throughput is a huge concern given that the user group is small and they’re willing to wait for the best answer. The topics are sensitive in nature and the data is highly confidential and so, due to regulatory requirements, none of the information is allowed to be transmitted to third parties.
Which model meets all the Generative Al Engineer’s needs in this situation?
TESTED 16 Oct 2024
