TechnologyAI & Data
Generative AI: fun facts and quiz
The essentials in 7 ideas, with fun facts, an illustrated story and a quiz to see how much you know.
The essentials
What It Makes
Generative AI creates new content, like text, images, music, voices and video, from a prompt. It learns patterns from huge collections of existing examples.
Key fact
A prompt is the instruction you give it.
Large Language Models
Chatbots run on large language models, trained on vast amounts of text to predict what comes next. That simple trick, at huge scale, produces fluent writing.
Key fact
LLM stands for large language model.
Hallucinations
Generative AI can state false things confidently, like invented quotes or sources. These are called hallucinations, so important facts are worth checking.
Key fact
Fluent doesn’t always mean accurate.
Image Generators
Image generators turn text into pictures. Many start from random noise and refine it step by step into an image that matches the prompt.
Key fact
This method is called diffusion.
Deepfakes
Deepfakes are AI-made videos, images or voices that imitate real people. They can be fun, but they can also be used to mislead.
Key fact
Checking trusted sources helps spot fakes.
AI & Creativity
Generative AI raises new questions: who owns an AI-made picture, and is it fair to train on artists’ work without asking? Courts and lawmakers are still deciding.
Key fact
In the US, purely AI-made works don’t get copyright.
Using It Well
Generative AI is great for brainstorming, drafting and explaining. Clear prompts get better results, and checking the output keeps you in charge.
Key fact
Giving examples in a prompt often improves the answer.
Fun facts
In 2018, a portrait made with AI sold at Christie’s auction house for 432,500 dollars.
Big language models train on so much text that a person reading nonstop would need thousands of years to get through it.
In 2023, US lawyers were fined for citing court cases in a filing that a chatbot had invented.
Early image generators were famously bad at hands, often drawing six or seven fingers.
Early deepfake faces rarely blinked, because the photos they learned from seldom showed closed eyes.
In 2023, an artist turned down a big photography prize after revealing his winning picture was made with AI.
Asking a chatbot to work through a problem step by step can improve its answers.
Story: The Next-Word Game
The Next-Word Game
1948. Mathematician Claude Shannon wants to show how predictable English is. He opens a book at random and notes down a word.

Then he flips to another page, finds that word again, and writes down whatever follows it. Word by word, a strange sentence grows.
His result began: “The head and in frontal attack on an English writer…” Today’s chatbots play the same next-word game, with vastly more text.
True or false?
Tap your answer to see if you got it, and why.
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Question 1 of 10
Generative AI can create images from text.
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True. Describe it, and it draws it.
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Question 2 of 10
Large language models generate text one piece at a time.
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True. Predicting what comes next, over and over.
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Question 3 of 10
AI chatbots can make up false information.
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True. Even when they sound sure.
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Question 4 of 10
Many image generators start from random noise.
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True. And clean it up step by step.
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Question 5 of 10
Deepfakes can imitate real people’s voices.
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True. Sometimes from just a short sample.
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Question 6 of 10
Questions about AI and copyright are still being debated.
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True. In courts and parliaments worldwide.
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Question 7 of 10
Clearer prompts usually give better results.
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True. Say what you want, and give context.
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Question 8 of 10
Generative AI can only copy existing files exactly.
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False. It produces new combinations.
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Question 9 of 10
Language models look up every answer in an encyclopaedia.
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False. They generate answers from learned patterns.
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Question 10 of 10
If a chatbot sounds confident, it must be right.
Show the answer
False. Confidence isn’t accuracy.
Keep going in the app
KnowSoda learns what you know and brings back what you’re about to forget. Generative AI has 6 more ideas at the Advanced and Expert levels.
Sources
- U.S. Copyright Office — Copyright and Artificial Intelligence
- Ho, Jain & Abbeel (2020), denoising diffusion probabilistic models
- Anthropic — Prompt engineering overview
- Reuters (2023) — ChatGPT sets record for fastest-growing user base
- OpenAI — What are tokens and how to count them
- C2PA — Coalition for Content Provenance and Authenticity


