AI Knowledge Information 2

Question 1

Which knowledge representation technique uses probabilistic relationships between variables to model uncertainty?

Accepted Answer

Bayesian network

Answer

Bayesian networks use directed acyclic graphs to represent probabilistic dependencies between variables, enabling inference under uncertainty.

Question 2

In a knowledge graph, what is the primary purpose of an 'ontology'?

Accepted Answer

Define concepts, relationships, and rules within a domain

Answer

An ontology formally defines the concepts, their properties, and relationships within a domain, providing a shared vocabulary and structure for the knowledge graph.

Question 3

What is 'knowledge distillation' in the context of AI model compression?

Accepted Answer

Training a smaller student model to mimic a larger teacher model

Answer

Knowledge distillation transfers knowledge from a large, complex teacher model to a smaller student model by training the student on soft probability outputs from the teacher.

Question 4

Which information retrieval metric measures the fraction of relevant documents returned out of all documents returned?

Accepted Answer

Precision

Answer

Precision measures how many of the retrieved documents are actually relevant, calculated as true positives divided by all retrieved documents.

Question 5

In retrieval-augmented generation (RAG), what role does the 'retriever' component play?

Accepted Answer

Fetches relevant context documents to ground the generator's response

Answer

The retriever searches an external knowledge store for documents relevant to the query and passes them as context to the generative model.

AI - Engineer Practice Test

AI - Engineer Practice Test

AI Knowledge Information 2