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Unsupervised Learning

AI is trained with unlabelled data (only inputs, no answers). For example, given thousands of
pictures of dogs and cats without labels, it groups them into clusters based on similarity, though
it does not know their names.
In generative AI, unsupervised learning helps models uncover the natural structure of data, such
as how words or images are organised.

Supervisor
Input Raw Data Supervisor Input Raw Data Output
Labelled Data

Training Dataset Desired Output Dog
Dog Dog
Output
Dog
Dog Processing
Processing
• Unknown Output Cat
Cat • No Training Dataset
Cat Cat

EVERYDAY EXAMPLES OF GENERATIVE AI

Generative AI is already part of many tools and applications you may encounter in daily life.
Some common examples include:
Text generation: Produces human-like text by learning from large amounts of written data. It
is used to create emails, stories, articles, answers and more. Examples: ChatGPT, Jasper AI,
Google Gemini.
Image generation: Creates images or artwork based on text descriptions or sample images.
It uses patterns learned from millions of pictures to generate new visuals. Examples: DALL·E,
MidJourney, Adobe Firefly.
Music and audio creation: Composes music or generates sound effects by analysing
musical styles and patterns. Examples: AIVA, Soundraw, Voicemod AI.

Video generation: AI can turn text into video clips or help edit and enhance videos with
creative effects. Examples: Runway ML, Sora (by OpenAI), Pictory.
Code generation: Writes, completes or debugs code based on a programmer’s instructions or
existing code. Examples: GitHub Copilot, AWS CodeWhisperer, ChatGPT.
Games and storytelling: Creates new stories, characters or game plots, making interactive
content instantly. Examples: AI Dungeon, NovelAI.

BENEFITS OF GENERATIVE AI

Generative AI offers several advantages that make work faster, smarter and more creative.
Some important benefits include:

Content creation: Speeds up writing, designing and editing tasks by generating high-quality
text, images, videos and music.

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