Grounding

Large Language Model

A neural network trained on massive text corpora that can generate, understand, and reason about natural language.

GPT

Generative Pre-trained Transformer — a family of autoregressive language models that generate text by predicting the next token.

BERT

Bidirectional Encoder Representations from Transformers — a language model that understands context by reading text in both directions.

Tokenisation

The process of breaking text into smaller units (tokens) such as words, subwords, or characters for processing by language models.

Language Model

A probabilistic model that assigns probabilities to sequences of words, enabling prediction of the next word in a sequence.

Contextual Embedding

Word representations that change based on surrounding context, capturing polysemy and contextual meaning.

Word2Vec

A neural network model that learns distributed word representations by predicting surrounding context words.

GloVe

Global Vectors for Word Representation — an unsupervised learning algorithm for obtaining word vector representations from aggregated word co-occurrence statistics.

Instruction Tuning

Training a language model to follow natural language instructions by fine-tuning on instruction-response pairs.

RLHF

Reinforcement Learning from Human Feedback — a technique for aligning language models with human preferences through reward modelling.

Hallucination Detection

Techniques for identifying when AI language models generate plausible but factually incorrect or unsupported content.

Prompt Injection

A security vulnerability where malicious inputs manipulate a language model into ignoring its instructions or producing unintended outputs.

A parameter controlling the randomness of language model outputs — lower values produce more deterministic text.

A measure of how closely the meanings of two text passages align, computed through embedding comparison and used in duplicate detection, search, and recommendation systems.

The capability of language models to accurately interpret and execute natural language instructions, a core skill developed through instruction tuning and alignment training.

Identifying semantic relationships between entities mentioned in text.

The subfield of NLP concerned with producing natural language text from structured data or representations.

A generative probabilistic model for discovering topics in a collection of documents.

AI systems designed to engage in natural, context-aware dialogue with humans across multiple turns.

A computer system designed to converse with humans, encompassing task-oriented and open-domain conversation.