AI Basics Quiz: What Do You Actually Know About AI?

Which of the following is an example of AI that predates ChatGPT and has been running invisibly for years?

A basic spreadsheet formula that calculates the sum of a column A dropdown menu that shows you your most recently visited websites ChatGPT Plus, which was the first commercial AI product available to consumers A credit card fraud detection system that flags unusual transaction patterns — a classic machine learning application deployed by banks for over a decade

Which of the following is the correct relationship between AI, machine learning, and generative AI?

Generative AI came before machine learning, which came before AI Generative AI is a type of machine learning, which is a type of AI — they are nested categories, not separate things Machine learning and generative AI are the same thing with different names AI is only about robots; machine learning is about software; generative AI is a marketing term

What is 'hallucination' in the context of AI?

When AI becomes confused and stops responding to questions Hallucination is a technical term for when AI models become overloaded and crash When AI generates plausible-sounding but factually incorrect information — because the model predicts likely text, not verified facts When AI produces visual hallucinations or images instead of text

When would you want a LOWER temperature setting for an AI task vs. a HIGHER temperature?

Higher temperature always produces better quality — you should maximize it for all tasks Lower for precise tasks (data extraction, code, factual answers) where consistency matters; higher for creative tasks (brainstorming, varied options, creative writing) where variation is desirable Temperature only affects response speed, not content — lower is faster, higher is slower Temperature controls language formality: low for formal writing, high for casual writing

How quickly did ChatGPT reach 1 million users after its release in November 2022?

ChatGPT has never reached 1 million users — it is primarily used by researchers 1 year — mainstream adoption in consumer AI has historically been slow 5 days — the fastest product in history to that point to cross 1 million users 6 months — it grew slowly at first before viral spread

Which of these everyday products uses machine learning or AI?

Netflix's recommendation engine — it uses machine learning to predict what content you'll enjoy based on your viewing patterns A physical thermostat with a timer — it executes pre-set rules without learning A standard calculator — it follows fixed mathematical rules with no learning A basic alarm clock — it does only what it's explicitly programmed to do

What is the recommended approach when starting with AI tools for the first time?

Pick one tool and use it consistently on real work for 30 days, building habits through hands-on experimentation rather than reading about AI or switching between tools Take a certification course before using any AI tool in a professional context Try every major AI tool simultaneously to quickly determine which is best Wait until AI tools become more mature and reliable before starting to use them

What usage pattern consistently predicts high-value AI adoption?

Waiting for AI tools to mature further before integrating them into real workflows Starting with a specific, recurring real problem; using AI for first drafts with human review; building task-specific prompting habits; knowing which tasks to keep fully human Trying every new AI tool as soon as it launches to stay current Using AI to replace human involvement in all written tasks entirely

What is the key difference between 'narrow AI' and 'general-purpose AI'?

Narrow AI is cheaper; general-purpose AI is always more expensive per use Narrow AI is for small companies; general-purpose AI is only for enterprise use Narrow AI is designed for one specific task (spam filtering, recommendations); general-purpose AI handles many different tasks through a single model that users direct with language Narrow AI runs on phones; general-purpose AI requires large servers

What does a 'context window' determine in an AI conversation?

How much text the AI can 'see' and refer to at once — including your messages, shared documents, and the AI's own replies. Text outside the window is effectively forgotten The number of different topics an AI can discuss in a single session The size of the screen where AI output is displayed The time window during which a conversation is saved before being deleted