Foundation models
Foundation models are large general-purpose models adapted to many tasks, rather than built for one.
AI for Kids · Class 10 · Module 1 of 9
Understanding Modern AI
Know the landscape and you stop being impressed by everything equally.
8 sessionsSessions 1–8
4 weeksTypical pace
AppliedLevel
Class 10Artificial Intelligence
The big idea
Students build a working map of modern AI: what foundation models are, how multimodal systems differ, and how to evaluate a capability claim rather than accepting a headline.
Why it matters
Board-year students are making subject and career decisions. An accurate map of the field is genuinely useful information.
Unpacked
What you will actually learn
Three core ideas, each taught with worked examples and then practised until it feels obvious.
Multimodal systems
Multimodal systems handle text, image, audio and video together, which changes what applications are even possible.
Capability evaluation
Capability evaluation means testing claims yourself on tasks you can verify, rather than trusting benchmark headlines.
Did you know?
Benchmark scores can be inflated when test material has leaked into training data — a known problem called contamination.
Common mix-up
“Benchmarks show which model is best.” They show performance on specific tests. Your task is not those tests.
Session by session
Your 8-session journey
Sessions 1–8 of the 72-session year, at two one-hour sessions per week.
- 1
Warm-up and big picture
Where this module fits, what you will build, and a hands-on starter that gets everyone curious about foundation models.
- 2
Foundation models
Guided teaching on foundation models, worked through together with the teacher.
- 3
Foundation models — practice lab
Independent practice, small challenges and one deliberate mistake to diagnose.
- 4
Multimodal systems
Guided teaching on multimodal systems, building directly on the previous two sessions.
- 5
Multimodal systems — practice lab
Applied tasks that combine foundation models and multimodal systems in one piece of work.
- 6
Capability evaluation
Capability evaluation introduced and practised, completing the toolkit needed for the project.
- 7
Project build
Guided build session for the module project: AI landscape briefing.
- 8
Test, present and reflect
Finish, test against the checklist, present the work and explain the decisions behind it.
Project lab
AI landscape briefing
Every module ends with something the student built themselves and can demonstrate. This is the piece that goes into their portfolio and gets explained out loud at the end of session 8.
Try this at home
Design your own five-task benchmark from problems you can check, and run it on every model you have access to.
It is finished when
- It works from start to finish without breaking
- You can explain every part of it in your own words
- You tested it and improved at least one thing afterwards
- Someone else used or understood it without your help
By the end of this module
Students finishing Module 1 can:
- Explain and use foundation models without prompting
- Explain and use multimodal systems without prompting
- Explain and use capability evaluation without prompting
- Build and finish ai landscape briefing
- Test your own work and correct what you find
- Talk an adult through what you made and why
Word bank
The vocabulary introduced here, in plain language:
- foundation model
- A large general model adapted to many tasks.
- multimodal
- Handling several input and output types together.
- contamination
- Test data leaking into training data.
Module challenge
Think you have got this?
0 XPLevel 1 · Curious Beginner
6 quick questions drawn from this module — vocabulary, the project you build, and a myth-or-fact round. Every wrong answer explains itself, so a mistake still teaches you something.
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