Frequently asked questions
Why do you keep saying LLMs—this is AI, right?
Honestly, the short answer (these days) is yes. The long answer is more complicated—AI is a term that has been applied to many different algorithmic techniques and systems over the years. But today (in the mid-2020s) LLM (Large Language Model) A language model trained on a very large amount of text, with billions of parameters. The hand-built models in these lessons are tiny language models; ChatGPT, Claude and Gemini are large ones. The core principles are identical. The difference is scale. View in glossary have kindof sucked all the air out of the room when it comes to AI, so that’s mostly what we’re talking about here. I (Ben) do like to use the term LLM rather than AI whenever I can, because I think it’s more specific and accurate.
You mention ChatGPT and Claude a lot, but Gemini/DeepSeek/etc. is more my jam
None of these resources are specific to any particular LLM product. We sometimes use “ChatGPT” or “Claude” as shorthand because they’re the names most people recognise, but the concepts apply equally to any modern LLM.
Who is this for?
Anyone curious about how language models work. The activities suit learners from primary school age through to adults, with no technical background required. We’ve delivered them to hundreds of participants—primary and high school students, undergraduate students, and senior executives from industry and government—and the hands-on approach lands in all of those contexts.
Did some of this stuff used to be called “My First Language Model”?
Yep, it sure did… and it still is: My First Language Model is the classic LLMs Unplugged lesson. But this website hosts all the LLMs Unplugged resources—other lessons, the modules they’re built from, and the printable materials—not just that one workshop.
Do I need any special materials?
Nope, it’s all stuff you’ll have around the office/house/classroom. Each lesson has a “you will need” section.
Are there printable versions of the lessons?
Not any more—the lessons are now maintained as web pages only, and they print reasonably well straight from your browser if you need hard copies. The printable artefacts for the hands-on activities (pre-generated Booklet A printed dice lookup table for a text: one entry per previous word (or pair of words, in a trigram booklet), listing the possible next words with the d10 range that selects each. A booklet is a pre-trained model you can generate from without having trained it. View in glossary and Cutouts Printed cards, one per word pair in the text, each showing a previous word in a box and the word that followed it. Spread on a table they are the model: to generate, find a card whose boxed word matches your current word and read off its next word. Common pairs appear on more cards, so picking by eye samples in proportion. View in glossary ) are on the tools page.
Can I use these materials in my school classroom?
Yes. All materials are released under CC BY-SA 4.0, so you can use, adapt, translate and share them with attribution. The one obligation is ShareAlike: if you distribute a modified version, it goes out under the same licence.
Can I use these materials in a paid workshop?
Yes, and you don’t need to ask. The licence used to carry a non-commercial clause, which made this murky for anyone charging a fee; it doesn’t any more. Schools, universities, non-profits, consultants and commercial training providers can all run paid workshops off these materials on the same terms. Credit the source, and if you hand out an adapted version, licence it the same way. The lessons each come with suggested session structures and timings.
I’m a corporate client, and I’d love to have some experts come and deliver this workshop for us
Good news—that’s one of the things we do here at the School of Cybernetics. Drop us a line to discuss how we can make it happen.
Honestly, this stuff is just as fun as a Christmas party/team bonding activity, but the learning is very real. Learning can be fun.
Why dice and cutouts instead of computers?
Using physical randomness makes the probabilistic nature of text generation tangible. When you roll dice and look up words in a table, or pick matching cutouts from a spread on the table, you’re doing exactly what a computer does—just slower. This builds genuine understanding rather than treating AI as a black box.
How do these activities relate to ChatGPT, Claude, and other LLMs?
Modern LLMs use the same fundamental principle: predict the next Token A single unit of text that the model works with. In our activities each word and punctuation mark is a token. Modern LLMs use subword tokens, so a long or unusual word may be split into several. View in glossary based on Context window How many previous tokens the model can consider when it predicts the next one. A bigram has a context window of one word and a trigram of two; modern LLMs can consider hundreds of thousands or even millions of tokens. View in glossary . The differences are scale (billions of Parameters The numbers a model stores to encode what it has learned. Each cell of your grid, holding the count for one word pair, is a parameter. A modern LLM has billions of them, and a frontier model on the order of a trillion. View in glossary vs dozens) and learned vs hand-counted statistics. The core mechanism— Weighted random sampling Choosing the next token with probability proportional to its count. A d10 roll against the counts does this, and so does letting your eye land on one of the matching cutouts, because common words appear on more of them. View in glossary based on patterns in Training data The text a model is trained on. In our activities this is the passage you tally, or the book a set of cutouts, a booklet or a set of search sheets was generated from. Modern LLMs are trained on trillions of words from books, websites and other sources. View in glossary —is identical.
Can I generate my own booklets from custom text?
Yes. You can generate booklets online directly in your browser—no installation required. Just upload or paste your text, choose your options, and download a PDF. Your text is processed entirely in your browser and never sent to any server.
If you prefer working offline or want to modify the tools, the source code includes a command-line tool that provides the same functionality.
Is there a research paper about LLMs Unplugged?
Yes. LLMs Unplugged was presented at the 28th Australasian Computing Education Conference (ACE 2026) in Melbourne, Australia. Download the paper here.
BibTeX
@inproceedings{swift2026llmsunplugged,
author = {Swift, Ben},
title = {{LLMs Unplugged: Teaching Resources for a ChatGPT World}},
booktitle = {28th Australasian Computing Education Conference (ACE 2026)},
year = 2026,
month = feb,
address = {Melbourne, VIC, Australia},
publisher = {ACM},
doi = {10.1145/3786228.3786237},
url = {https://doi.org/10.1145/3786228.3786237}
}I found an error in the materials.
Please open an issue on GitHub or contact us. We appreciate corrections and suggestions.
