What is Transformer?
A type of AI architecture that processes text by paying attention to relationships between all words at once, rather than reading sequentially.
Why It Matters
Transformers are the foundation of modern AI language models and have dramatically improved how machines understand text.
Real-World Example
GPT, Claude, and BERT are all built on the transformer architecture.
“Understanding terms like Transformer matters because it helps you have better conversations with developers and make smarter decisions about your software. You do not need to be technical. You just need to know enough to ask the right questions.”
Related Terms
Large Language Model (LLM)
An AI system trained on massive amounts of text that can understand and generate human language.
Attention Mechanism
A technique that lets AI models focus on the most relevant parts of the input when generating output.
Neural Network
A computing system inspired by the human brain, made up of layers of connected nodes that learn patterns from data.
Self-attention
A mechanism where each word in a text considers its relationship to every other word in the same text.
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Related Terms
Large Language Model (LLM)
An AI system trained on massive amounts of text that can understand and generate human language.
Attention Mechanism
A technique that lets AI models focus on the most relevant parts of the input when generating output.
Neural Network
A computing system inspired by the human brain, made up of layers of connected nodes that learn patterns from data.
Self-attention
A mechanism where each word in a text considers its relationship to every other word in the same text.
Tokenisation
The process of breaking text into smaller pieces called tokens that an AI model can process.
Embeddings
A way of representing words, sentences, or other data as lists of numbers that capture their meaning.