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

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

6 months — it grew slowly at first before viral spread 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

Why does an AI model perform better on common tasks than on rare or highly specialized knowledge?

AI models are intentionally limited on specialized topics to avoid replacing experts Common tasks are hard-coded into AI models; rare tasks require internet access Common tasks appear more frequently in training data, so the model has seen more examples to learn from — rare or specialized topics have fewer training examples, increasing error and hallucination risk Rare topics require more parameters, and models have a fixed number available

What happens when a conversation exceeds an AI's context window limit?

The AI stops responding and requires a new conversation to be started Exceeding the context window triggers an automatic upgrade to a larger model The AI stores the overflow in external memory and retrieves it when needed The AI loses access to text that falls outside the window — it effectively 'forgets' earlier parts of the conversation and may give inconsistent responses

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

The size of the screen where AI output is displayed The time window during which a conversation is saved before being deleted The number of different topics an AI can discuss in a single session 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

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 Technologies that enter the trough of disillusionment never recover and should be abandoned The Hype Cycle predicts AI will be replaced by a completely different technology by 2027 The trough of disillusionment only applies to hardware technologies, not software like AI