Core Concepts
Natural Language Processing (NLP)
NLP combines linguistics, computer science, and machine learning to enable computers to read, understand, and generate human language. Core tasks include tokenization, parsing, translation, summarization, and question answering.
The transformer architecture revolutionized NLP from 2017 onward, enabling models to process language at unprecedented scale and quality. Today NLP capabilities are embedded in nearly every major software product.
Authority Links
Related Terms
Core Concepts
Natural Language Understanding (NLU)
AI's ability to understand and interpret human language meaning and intent.
Core Concepts
Natural Language Generation (NLG)
Generating coherent, contextually relevant text from structured data or prompts.
Model Components
Transformer
A neural-network architecture, introduced by Vaswani et al. in 2017, that uses self-attention and parallel computation across all sequence positions — the foundation under virtually every frontier language and multimodal model in production today.
Core Concepts
Token
Smallest processing unit in NLP: a word, word part, or character.