#nlp

Dense vector representations that capture the semantic meaning of text, images, or other data in a numerical space where proximity reflects conceptual similarity.

Massive neural networks based on the Transformer architecture, trained on enormous text corpora to understand and generate natural language with emergent capabilities like reasoning, translation, and code generation.

Information retrieval technique that uses vector embeddings to find results by meaning, not just exact keyword matching.

Process of splitting text into discrete units (tokens) that language models can process numerically, fundamental to how LLMs understand and generate text.