Generative AI Fundamentals · Lesson 1

What is Generative AI

We explain how generative AI differs from classical algorithms and why an LLM is neither a search engine nor a database.

20 min read2 questions in quizReady prompt includedIn progress

Practical exercise

What to do after this lesson

Open ChatGPT or Claude. Ask one question whose answer you already know. Evaluate accuracy. Then ask about something highly specialized in your field and check the answer against your own knowledge. Note where the model got it wrong.

Task grader

Open ChatGPT or Claude. Ask one question whose answer you already know. Evaluate accuracy. Then ask about something highly specialized in your field and check the answer against your own knowledge. Note where the model got it wrong.

Your answer

Ready-to-use prompt

Template for this lesson

Copy and adapt to your context. Text in angle brackets should be replaced.

Explain <topic> to me as if I'm a smart professional but a complete beginner in this area. Use analogies from everyday life. After the explanation, give me 3 questions I should ask to verify I understood correctly.

Prompt sandbox

Prompt

Common mistakes

What people get wrong

Taking model responses as facts without verification — especially dangerous with numbers, dates, and names.
Assuming confident tone = correct answer. Models write both correct and incorrect content with equal confidence.

How it differs from classical AI

| Classical AI | Generative AI | |---|---| | Rules written by hand | Patterns learned from data | | Returns yes/no or a number | Generates free-form content | | Brittle on new inputs | Generalizes flexibly | | Transparent logic | Hard to explain individual outputs |

A classic example of classical AI: a spam filter that checks for words like "win," "free," "urgent" and blocks the email. It works — but add one new trigger word and you need to manually update the rules.

A generative model trained on labeled spam/not-spam examples learns contextual signals that a human never would have thought to encode.

Why it's not a search engine

A search engine finds existing pages. An LLM generates a response on the fly — based on statistical patterns absorbed during training. This means:

The answer may not exist anywhere online — the model invented it

The answer may be plausible but false (hallucination)

There's no "taken from here" link by default — if you need sources, you need RAG or a search-enabled model

Practical takeaway

Think of an LLM as a very fast, well-read colleague who has read almost everything but occasionally lies with confidence. Their input is valuable — but requires verification for anything critical.

Correct mental model: LLM = draft acceleration + idea generation + concept explanation NOT = authoritative fact source without verification

Report a bug

What is Generative AI

Task grader

Prompt sandbox

Quiz — 2 questions

Discussion

Generative AI: where the name comes from

How it differs from classical AI

What generative AI can do today

Why it's not a search engine

Practical takeaway