AI Terms
Here you will find key AI terms you may come across, explained in plain language. You do not need to know all of these terms to use AI, but knowing some of them may help you understand AI better.
Artificial Intelligence (AI)
Technology that allows computers to perform tasks that usually require human intelligence, such as understanding language, recognising images, making decisions, or providing recommendations.
Bias
Patterns in AI outputs that reflect imbalances or assumptions in the data it learned from. For example, hiring AI that favours certain genders or ages.
Deep Learning
A type of AI that uses large neural networks with many layers to learn patterns in data.
Ethical AI
AI that is developed and used in ways that are fair, transparent, accountable, and inclusive.
Generative AI
AI that can create new content such as text, images, music, or code. For example. writing a story, generating a poster, or composing music.
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Hallucination
When an AI model generates information that sounds plausible but is incorrect or not based on real data.
Human-in-the-Loop
When humans guide or check AI outputs before they are used in real situations.
Inference
The moment when a trained AI model generates an output in response to a user’s input.
Large Language Model (LLM)
A type of AI model trained on vast amounts of text to understand and generate human-like language.
Machine Learning
A branch of AI where systems learn from data instead of following fixed rules. Models improve as they are exposed to more examples.
Model
A trained AI system that processes input and produces output. Different models are designed for tasks such as writing, analysis, or creative generation.
Multimodal
AI systems that can work with multiple types of input and output, such as text, images, and audio.
Neural Networks
A type of machine learning model inspired by the human brain. Neural networks consist of interconnected layers of “neurons” that process information and learn patterns.
Prompt
The text or instructions given to an AI model to guide its output. For exmaple, “Explain diabetes in simple Punjabi.”
Tokens
Small units of text (words or parts of words) that AI models use to process and generate language. For example, longer inputs use more tokens, which may affect the AI’s output length.
Training Data
The data used to teach an AI model. The quality and diversity of this data affects how well the AI works and whether it is fair.
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Digital Divide
The gap between people who have access to digital technologies and those who do not For example. some communities cannot access AI tools due to lack of internet, devices, or digital literacy.