Generative AI Fundamentals
Generative AI learns patterns in existing data and uses those patterns to produce new content. It generates plausible outputs—not guaranteed facts.
Learning objectives
What you will be able to do
- Explain generative ai fundamentals accurately in your own words.
- Recognise how the concept appears in real AI products and professional work.
- Identify an important limitation, risk or evaluation requirement.
- Apply the concept through a practical activity and knowledge check.
Core explanation
Build the right mental model
Generative systems model a data distribution: the patterns that make text, images, audio or code resemble their training examples. At use time, sampling and instructions guide the creation of a new output.
Discriminative models separate or predict existing categories; generative models create. The same application may combine both—for example, classifying a request, retrieving documents and generating a grounded response.
Because generation is probabilistic, the same prompt can produce different answers. Quality control must address factual accuracy, copyright, privacy, bias and unsafe content.
Generation
Producing a new sample consistent with learned patterns.
Prompt
Instructions and context supplied at use time.
Sampling
Selecting among possible outputs according to model probabilities.
Grounding
Connecting generation to trusted source material or tools.
Drafting a policy summary
A language model creates a readable summary from supplied policy documents.
Apply your learning
Practical activity
- Choose one safe generative task.
- Write the purpose, source material, output format and verification method.
- List information that must never be pasted into a public AI tool.
Write your answers in a learning journal. The value comes from connecting the concept to your own profession.
Knowledge check
Test your understanding
Q1Does generative AI retrieve a stored answer word for word?
Answer: Not normally. It generates output from learned probability patterns, context and sampling.
Q2What is grounding?
Answer: Providing trusted context or retrieval so the generated answer is connected to evidence.
If you cannot explain the answer without reading it, revisit the core explanation and example before continuing.
Continue with authoritative sources
Important industry resources
These links lead to official organisations, industry laboratories or established open-source learning projects.