GPT

Large Language Model

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

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.

A text generation strategy that restricts the model to sampling from the K most probable next tokens.

The process of producing coherent and contextually relevant text using AI language models.

The classification of user utterances into predefined categories representing the user's goal or purpose, a fundamental component of conversational AI and chatbot systems.

The task of identifying all expressions in text that refer to the same real-world entity.

The technology that converts spoken language into text, also known as automatic speech recognition.

The process of automatically extracting structured information from unstructured or semi-structured text sources.

The component of conversational systems that tracks conversation state, determines the next system action, and maintains coherent multi-turn interactions with users.

An NLP task that identifies and classifies named entities in text into categories like person, organisation, and location.

Transformer

A neural network architecture based entirely on attention mechanisms, eliminating recurrence and enabling parallel processing of sequences.

Token

A digital asset created and managed on a blockchain, representing value, utility, or ownership rights.