Large Language Model

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.

Grounding

Connecting language model outputs to real-world knowledge, facts, or data sources to improve factual accuracy.

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.

The application of models trained in one language to perform tasks in another language, leveraging shared multilingual representations learned during pre-training.

The artificial production of human speech from text, also known as text-to-speech.

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

A fine-grained sentiment analysis approach that identifies opinions directed at specific aspects or features of an entity, such as a product's price, quality, or design.

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

A summarisation technique that identifies and selects the most important sentences from a source document to compose a condensed version without generating new text.

AI systems that extract structured information from unstructured documents by combining optical character recognition, layout analysis, and natural language comprehension.

The field of AI focused on enabling computers to understand, interpret, and generate human language.

Neural Network

A computing system inspired by biological neural networks, consisting of interconnected nodes that process information in layers.