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

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

Temperature only affects response speed, not content — lower is faster, higher is slower Higher temperature always produces better quality — you should maximize it for all tasks Temperature controls language formality: low for formal writing, high for casual writing 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

Even the most capable AI models in 2026 cannot do which of the following?

Write code that executes correctly in common programming languages Summarize a long document into key bullet points Produce grammatically correct text in English Reliably verify whether their own output is factually correct — models can produce false information with the same confidence as true information

What made ChatGPT feel fundamentally different from previous AI products like Siri or Alexa?

ChatGPT was a general-purpose system — one interface could write, analyze, code, and answer questions across any domain, unlike assistants built for narrow command-response tasks ChatGPT was the first AI ever to understand English language ChatGPT was different because it ran on quantum computers unavailable to earlier AI ChatGPT was the first AI to use the internet in real time to answer questions

According to McKinsey's 2025 survey, approximately what fraction of organizations report regular AI use in at least one business function?

About 50% — half of organizations have started; half remain uninvolved Less than 10% — AI is still primarily used only by technology companies About 25% — AI adoption is still in early phases for most organizations 88% — AI is now mainstream in organizations, not experimental

Which of the three habits of effective AI users is most important for working with AI in a professional context?

Using AI for every task, no matter how simple, to build maximum fluency Keeping the judgment — AI generates options and drafts; the human remains accountable for decisions and final outputs Delegating final decisions to AI to remove human bias from the process Never verifying AI output to avoid slowing down the productivity gains

Why is 'Artificial Intelligence' considered a misleading name by many researchers?

The name is misleading because AI is more intelligent than humans in every domain There is no controversy about the name — it accurately describes how the systems work AI is misleading because the system is not artificial — it uses real human data AI systems don't think or understand — they perform sophisticated pattern recognition and statistical prediction, which produces human-seeming outputs without human-like comprehension

Which of these everyday products uses machine learning or AI?

A basic alarm clock — it does only what it's explicitly programmed to do A standard calculator — it follows fixed mathematical rules with no learning 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

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

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 is for small companies; general-purpose AI is only for enterprise use Narrow AI is cheaper; general-purpose AI is always more expensive per use Narrow AI runs on phones; general-purpose AI requires large servers

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

The size of the screen where AI output is displayed 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 time window during which a conversation is saved before being deleted

What does the Gartner Hype Cycle predict about technologies that go through a 'trough of disillusionment'?

Most eventually reach a 'plateau of productivity' where real, consistent value is delivered — the trough represents reality calibration, not permanent failure The trough of disillusionment only applies to hardware technologies, not software like AI The Hype Cycle predicts AI will be replaced by a completely different technology by 2027 Technologies that enter the trough of disillusionment never recover and should be abandoned