810-110

810-110 practice questions, page 2 of 4, with answer review and explanations.

Question 6

What is the purpose of a vector database in a RAG architecture?

  1. to allocate resources for response generation
  2. to manage the context window
  3. to perform model weight updates
  4. to store numerical representations of data

Question 7

An analyst needs a model that can analyze a network topology diagram and a set of configuration logs simultaneously. Which type of model should be selected?

  1. multimodal model
  2. diffusion model
  3. embedding model
  4. generative adversarial network

Question 8

A practitioner is estimating the operational cost of integrating a cloud-hosted LLM API into an application. How does tokenization influence the cost of using this API?

  1. Tokenization has no impact because pricing is based on a flat-rate subscription.
  2. Costs are determined by the number of API calls.
  3. Tokenization increases cost by requiring additional GPU run time.
  4. The number of tokens determines the per-request cost.

Question 9

Which generative AI model family should be used for identifying and summarizing technical themes across thousands of unstructured network incident reports?

  1. variational autoencoders
  2. diffusion models
  3. large language models
  4. generative adversarial networks

Question 10

What is an advantage of cloud-hosted API services when comparing cloud-hosted and locally hosted AI models?

  1. rapid elastic scaling for unpredictable inference demand
  2. elimination of per-token operational costs
  3. full control over data residency and privacy
  4. lower network latency for all end users