Myths about teaching can hold you back
- Year 10
- OCR
Predictive vs generative AI
I can explain the differences between predictive and generative AI systems.
- Year 10
- OCR
Predictive vs generative AI
I can explain the differences between predictive and generative AI systems.
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Lesson details
Key learning points
- Predictive AI makes predictions by using patterns found in existing data.
- Generative AI is a type of AI that produces new, original content based on the patterns it has learned.
- Predictive AI is typically applied in tasks like forecasting future trends and classifying data into categories.
- Generative AI can be used to produce a wide variety of new outputs, including text, images and code.
Keywords
Predictive AI - machine learning algorithms use data to identify patterns and make guesses about the future
Generative AI - a type of artificial intelligence (AI) designed to generate content, such as text, images or sound
Common misconception
Only generative AI systems require training data to complete tasks.
All AI systems rely on training data to perform tasks by using patterns identified in the data.
To help you plan your year 10 computer science lesson on: Predictive vs generative AI, download all teaching resources for free and adapt to suit your pupils' needs...
To help you plan your year 10 computer science lesson on: Predictive vs generative AI, download all teaching resources for free and adapt to suit your pupils' needs.
The starter quiz will activate and check your pupils' prior knowledge, with versions available both with and without answers in PDF format.
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Explore more key stage 4 computer science lessons from the Data science: AI and machine learning unit, dive into the full secondary computer science curriculum, or learn more about lesson planning.
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Prior knowledge starter quiz
6 Questions
Q1.What is the name for an approach in artificial intelligence where systems improve by learning from data?
Q2.Match each keyword to its definition:
an approach where systems learn from data
following set instructions
using examples to improve over time
updating a model with new data