Databricks-Generative-AI-Engineer-Associate試験無料問題集（75題）「Databricks Certified Generative AI Engineer Associate 認定」

出題：1

A Generative Al Engineer is building an LLM-based application that has an important transcription (speech-to-text) task. Speed is essential for the success of the application Which open Generative Al models should be used?

A. whisper-large-v3 (1.6B)

B. DBRX

C. MPT-30B-lnstruct

D. L!ama-2-70b-chat-hf

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：2

A Generative Al Engineer is ready to deploy an LLM application written using Foundation Model APIs. They want to follow security best practices for production scenarios Which authentication method should they choose?

A. Use an access token belonging to any workspace user

B. Use a frequently rotated access token belonging to either a workspace user or a service principal

C. Use an access token belonging to service principals

D. Use OAuth machine-to-machine authentication

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：3

A Generative AI Engineer developed an LLM application using the provisioned throughput Foundation Model API. Now that the application is ready to be deployed, they realize their volume of requests are not sufficiently high enough to create their own provisioned throughput endpoint. They want to choose a strategy that ensures the best cost-effectiveness for their application.
What strategy should the Generative AI Engineer use?

A. Change to a model with a fewer number of parameters in order to reduce hardware constraint issues

B. Throttle the incoming batch of requests manually to avoid rate limiting issues

C. Deploy the model using pay-per-token throughput as it comes with cost guarantees

D. Switch to using External Models instead

正解：C 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：4

A Generative AI Engineer is testing a simple prompt template in LangChain using the code below, but is getting an error.

Assuming the API key was properly defined, what change does the Generative AI Engineer need to make to fix their chain?

A.

B.

C.

D.

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：5

A Generative Al Engineer is deciding between using LSH (Locality Sensitive Hashing) and HNSW (Hierarchical Navigable Small World) for indexing their vector database Their top priority is semantic accuracy Which approach should the Generative Al Engineer use to evaluate these two techniques?

A. Compare the cosine similarities of the embeddings of returned results against those of a representative sample of test inputs

B. Compare the Bilingual Evaluation Understudy (BLEU) scores of returned results for a representative sample of test inputs

C. Compare the Recall-Onented-Understudy for Gistmg Evaluation (ROUGE) scores of returned results for a representative sample of test inputs

D. Compare the Levenshtein distances of returned results against a representative sample of test inputs

正解：A 解答を投票する

出題：6

A Generative AI Engineer has been asked to design an LLM-based application that accomplishes the following business objective: answer employee HR questions using HR PDF documentation.
Which set of high level tasks should the Generative AI Engineer's system perform?

A. Split HR documentation into chunks and embed into a vector store. Use the employee question to retrieve best matched chunks of documentation, and use the LLM to generate a response to the employee based upon the documentation retrieved.

B. Calculate averaged embeddings for each HR document, compare embeddings to user query to find the best document. Pass the best document with the user query into an LLM with a large context window to generate a response to the employee.

C. Use an LLM to summarize HR documentation. Provide summaries of documentation and user query into an LLM with a large context window to generate a response to the user.

D. Create an interaction matrix of historical employee questions and HR documentation. Use ALS to factorize the matrix and create embeddings. Calculate the embeddings of new queries and use them to find the best HR documentation. Use an LLM to generate a response to the employee question based upon the documentation retrieved.

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：7

A Generative AI Engineer is developing a patient-facing healthcare-focused chatbot. If the patient's question is not a medical emergency, the chatbot should solicit more information from the patient to pass to the doctor's office and suggest a few relevant pre-approved medical articles for reading. If the patient's question is urgent, direct the patient to calling their local emergency services.
Given the following user input:
"I have been experiencing severe headaches and dizziness for the past two days." Which response is most appropriate for the chatbot to generate?

A. Headaches can be tough. Hope you feel better soon!

B. Please call your local emergency services.

C. Here are a few relevant articles for your browsing. Let me know if you have questions after reading them.

D. Please provide your age, recent activities, and any other symptoms you have noticed along with your headaches and dizziness.

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：8

A Generative Al Engineer is building a system that will answer questions on currently unfolding news topics. As such, it pulls information from a variety of sources including articles and social media posts. They are concerned about toxic posts on social media causing toxic outputs from their system.
Which guardrail will limit toxic outputs?

A. Use only approved social media and news accounts to prevent unexpected toxic data from getting to the LLM.

B. Log all LLM system responses and perform a batch toxicity analysis monthly.

C. Implement rate limiting

D. Reduce the amount of context Items the system will Include in consideration for its response.

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

Databricks-Generative-AI-Engineer-Associate試験無料問題集「Databricks Certified Generative AI Engineer Associate 認定」