12 Terms Defined
Every AI term explained in plain English — with analogies, examples, and the technical detail when you want it.
Core Concept
An AI system that can take autonomous actions to achieve goals — planning steps, using tools, and adapting based on results.
Technique
A prompting technique that improves AI reasoning by asking the model to work through problems step by step before giving an answer.
Core Concept
The maximum amount of text an AI model can consider at once — including your prompt, conversation history, and the response being generated.
Technique
A way of representing text (or other data) as lists of numbers that capture meaning, enabling similarity search and semantic operations.
Technique
A technique where you give the AI a few examples of the task you want it to perform, improving accuracy without any training.
Technique
The process of further training a pre-trained AI model on specific data to specialize its behavior for a particular task or domain.
Limitation
When an AI generates information that sounds plausible but is factually incorrect, fabricated, or not grounded in reality.
Core Concept
A neural network trained on massive text data to understand and generate human-like language.
Practice
The skill of writing instructions to AI models to get the best possible output.
Technique
A technique that lets AI models look up information before answering, improving accuracy and reducing hallucinations.
Core Concept
The basic unit AI models use to process text — roughly corresponding to word parts, common words, or character sequences.
Architecture
The neural network architecture behind modern AI — introduced by Google in 2017 and now powers ChatGPT, Claude, and most other LLMs.
A neural network trained on massive text data to understand and generate human-like language.
The basic unit AI models use to process text — roughly corresponding to word parts, common words, or character sequences.
The maximum amount of text an AI model can consider at once — including your prompt, conversation history, and the response being generated.
An AI system that can take autonomous actions to achieve goals — planning steps, using tools, and adapting based on results.
A technique that lets AI models look up information before answering, improving accuracy and reducing hallucinations.
The process of further training a pre-trained AI model on specific data to specialize its behavior for a particular task or domain.
A way of representing text (or other data) as lists of numbers that capture meaning, enabling similarity search and semantic operations.
A prompting technique that improves AI reasoning by asking the model to work through problems step by step before giving an answer.
A technique where you give the AI a few examples of the task you want it to perform, improving accuracy without any training.
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