AI explained without the jargon
Understand AI concepts in plain English. Search any term below, or follow our free Learning Path to build your confidence.
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Learn AI with a practical, beginner-friendly pathway
Start with the basics of AI, discover how it applies to work, build better prompting habits, and learn how to use AI tools responsibly.
What you’ll find
- • AI fundamentals and core vocabulary
- • Workplace use cases and practical examples
- • Prompting basics and responsible use
- • Role-based guidance for everyday work
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Categories
AI Basics
Fundamental concepts for understanding artificial intelligence.
27 terms
Machine Learning
Algorithms and methods that enable systems to learn from data.
391 terms
Deep Learning
Neural networks with many layers that learn hierarchical representations.
94 terms
Natural Language Processing
AI techniques for understanding and generating human language.
45 terms
Computer Vision
Teaching machines to interpret and understand visual information.
17 terms
Large Language Models
AI models trained on vast text data to understand and generate language.
151 terms
AI Agents
Autonomous systems that perceive, decide, and act to achieve goals.
40 terms
Prompt Engineering
The craft of designing effective inputs for AI models.
49 terms
Reinforcement Learning
Learning through trial and error with rewards and penalties.
25 terms
AI Hardware
Specialised chips and infrastructure for running AI workloads.
8 terms
AI Companies
Organisations building and deploying artificial intelligence.
2 terms
AI Models
Specific AI systems, architectures, and model families.
10 terms
Featured
Featured Terms
LLM
BeginnerA type of AI model trained on vast amounts of text to understand and generate human language.
Read more →RAG
IntermediateA technique that combines AI language models with external knowledge retrieval for more accurate answers.
Read more →Transformer
IntermediateThe neural network architecture that revolutionised AI by enabling models to process entire sequences at once.
Read more →Agent
IntermediateAn AI system that can perceive its environment, make decisions, and take actions to achieve goals autonomously.
Read more →GPT
BeginnerA family of large language models developed by OpenAI that generate human-like text.
Read more →New
Recently Added
- unsupported-claim rate→
The rate at which a language model produces responses that are not supported by evidence or facts
- uplift modeling→
A type of predictive modeling that estimates the incremental impact of a specific intervention or treatment on an outcome
- upweighting→
A technique used in machine learning to give more importance to certain data points or samples
- user matrix→
A table or matrix that represents the interactions between users and items in a system
- validation→
The process of evaluating a model's performance on a test dataset to ensure it generalizes well
- validation loss→
A measure of how well a machine learning model performs on unseen data during training
- validation set→
A subset of data used to evaluate the performance of a machine learning model
- value imputation→
A technique used to fill missing data with predicted or estimated values
Popular
Trending Terms
- 1 unsupported-claim rate
The rate at which a language model produces responses that are not supported by evidence or facts
- 2 uplift modeling
A type of predictive modeling that estimates the incremental impact of a specific intervention or treatment on an outcome
- 3 upweighting
A technique used in machine learning to give more importance to certain data points or samples
- 4 user matrix
A table or matrix that represents the interactions between users and items in a system
- 5 validation
The process of evaluating a model's performance on a test dataset to ensure it generalizes well
- 6 validation loss
A measure of how well a machine learning model performs on unseen data during training
- 7 validation set
A subset of data used to evaluate the performance of a machine learning model
- 8 value imputation
A technique used to fill missing data with predicted or estimated values
Why AIExplainer?
Making AI understandable
Artificial Intelligence is filled with confusing jargon. AIExplainer exists to make AI understandable through clear explanations, analogies, examples, and structured definitions — just like a traditional dictionary, but for the world of AI.