RAG Model

What is Generative AI?

• An AI system that only analyzes existing data without producing new content.

• An AI system that creates new content such as text, images, and music based on learned patterns.

• A rule-based AI system that requires explicit programming for every task.

• An AI system exclusively designed for analyzing numerical data

What is a key difference between a RAG model and an LLM?

• RAG models integrate external knowledge retrieval with language generation, while LLMs rely only on pre-trained knowledge.

• RAG models are smaller and less efficient than LLMs.

• LLMs require external databases to function, while RAG models do not.

• RAG models are designed only for text summarization tasks.

Which of the following is NOT a type of chunking?

• Fixed-Size Chunking.

• • Semantic Chunking.

• Recursive Chunking.

• Dynamic Vector Chunking.

Given the text divided as follows, what type of chunking is used?

Chunk 1: "Cats are popular pets."

Chunk 2: "Dogs are loyal companions."

Chunk 3: "Birds can make excellent pets too."

• Fixed-Size Chunking

• Semantic Chunking

• Recursive Chunking

• Randomized Chunking

Which pair of words is likely to have the least cosine similarity in their embeddings?

• • Artificial Intelligence and Machine Learning.

• Cat and Dog.

• Artificial Intelligence and Swimming.

• Mathematics and Calculus.

What type of database is commonly used in RAG models?

• Relational Database.

• Vector Database.

• • Graph Database.

• Time-Series Database.

What is the primary function of a RAG model?

• To generate outputs solely based on its training data.

• To retrieve relevant information from external sources and generate context-aware responses.

• To classify and tag data points based on pre-defined categories.

• To enhance computational efficiency in multi-modal data processing.