Databricks Databricks-Generative-AI-Engineer-Associate Databricks Certified Generative AI Engineer Associate Exam Exam Practice Test Questions

• Question 1

  A Generative Al Engineer is building a RAG application that ans.wers questions about internal documents for the company SnoPen AI.The source documents may contain a significant amount of irrelevant content, such as advertisements, sports news, or entertainment news, or content about other companies.Which approach is advisable when building a RAG application to achieve this goal of filtering irrelevant information?

  • Keep all articles because the RAG application needs to understand non-company content to avoid answ.ering questions about them.
  • Include in the system prompt that any information it sees will be about SnoPenAI, even if no data filtering is performed.
  • Include in the system prompt that the application is not supposed to option any questions unrelated to SnoPen Al.
  • Consolidate all SnoPen AI related documents into a single chunk in the vector database.

  Show Answer Answer: C Next

• Question 2

  A Generative Al Engineer is tasked with developing a RAG application that will help a small internal group of experts at their company ans.wer specific questions, augmented by an internal knowledge base. They want the best possible quality in the options, 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 option. 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?

  • Dolly 1.5B
  • OpenAI GPT-4
  • BGE-large
  • Llama2-70B

  Show Answer Answer: C Next

• Question 3

  Which indicator should be considered to evaluate the safety of the LLM outputs when qualitatively assessing LLM responses for a translation use case?

  • The ability to generate responses in code
  • The similarity to the previous language
  • The latency of the response and the length of text generated
  • The accuracy and relevance of the responses

  Show Answer Answer: D Next

• Question 4

  A Generative Al Engineer is creating an LLM system that will retrieve news articles from the year1918 and related to a user's query and summarize them. The engineer has noticed that the summaries are generated well but often also include an explanation of how the summary was generated, which is undesirable.Which change could the Generative Al Engineer perform to mitigate this issue?

  • Split the LLM output by newline characters to truncate away the summarization explanation.
  • Tune the chunk size of news articles or experiment with different embedding models.
  • Revisit their document ingestion logic, ensuring that the news articles are being ingested properly.
  • Provide few shot examples of desired output format to the system and/or user prompt.

  Show Answer Answer: D Next

• Question 5

  A Generative Al Engineer has already trained an LLM on Databricks and it is now ready to be deployed.Which of the following steps correctly outlines the easiest process for deploying a model on Databricks?

  • Log the model as a pickle object, upload the object to Unity Catalog Volume, register it to Unity Catalog using MLflow, and start a serving endpoint
  • Log the model using MLflow during training, directly register the model to Unity Catalog using the MLflow API, and start a serving endpoint
  • Save the model along with its dependencies in a local directory, build the Docker image, and run the Docker container
  • Wrap the LLM’s prediction function into a Flask application and serve using Gunicorn

  Show Answer Answer: B Next