Quiz: PLE - Kickstart into LLMs + Agentic AI Concepts

What does LLM stand for in AI?

• Limited Logic Memory

• Large Language Model

• Low Latency Module

• Local Language Machine

What is a Large Language Model trained to do?

• Drive a car

• Understand and generate human-like text

• Resize images

• Play music files

What does an “AI Agent” typically do in an application?

• Monitors CPU and memory

• Takes user input, plans a task, and uses tools like APIs or functions to complete it

• Encrypts all network traffic

• Acts as a database replication agent

How do LLMs generate answers to user inputs?

• By querying a database

• Using fixed rule-based logic

• By predicting the most likely next words based on training data

• From handwritten instructions

What makes LLMs “large”?

• Their screen size

• Their price

• The amount of data and parameters they are trained on

• The size of the cloud server

What kinds of tasks can LLMs assist with in modern applications?

• Monitoring network throughput

• Summarizing documents, writing code, creating chatbot responses

• Installing browser plugins

• Resetting system passwords

In agent-based AI, what does MCP stand for?

• Model, Compute, Predictor

• Memory, Code, Prompt

• Model, Context, Planner

• Machine, Command, Program

What is a common role of the “Planner” in an AI Agent architecture?

• Translate text

• Break down a user request into sub-tasks and choose which tools to invoke

• Render UI components

• Store logs for audit

In Agentic AI, what is a “tool” typically used for?

• Styling user interfaces

• Running animations

• Performing real-world actions like calling APIs or functions

• Storing historical prompts

Why are AI Agents considered more powerful than simple chatbots?

• They work offline

• They can reason, plan, and take actions using APIs or tools

• They cost less to run

• They have better spelling