Natural Language Generation

Natural Language Processing

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

Seq2Seq Model

A neural network architecture that maps an input sequence to an output sequence, used in translation and summarisation.

Latent Dirichlet Allocation

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

Text Embedding

Dense vector representations of text passages that capture semantic meaning for similarity comparison and retrieval.

Semantic Search

Search technology that understands the meaning and intent behind queries rather than just matching keywords.

Vector Database

A database optimised for storing and querying high-dimensional vector embeddings for similarity search.

Constitutional AI

An approach to AI alignment where models are trained to follow a set of principles or constitution.

Natural Language Understanding

The subfield of NLP focused on machine reading comprehension and extracting meaning from text.

Document Understanding

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

Slot Filling

The task of extracting specific parameter values from user utterances to fulfil a detected intent, such as identifying dates, locations, and names in booking requests.

Cross-Lingual Transfer

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

Text Embedding Model

A neural network trained to convert text passages into fixed-dimensional vectors that capture semantic meaning, enabling similarity search, clustering, and retrieval applications.

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

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

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

The maximum amount of text a language model can consider at once when generating a response.

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

Identifying semantic relationships between entities mentioned in text.

An NLP task where a system automatically answers questions posed in natural language based on given context.

The automatic transcription of spoken language into written text using acoustic and language models, foundational to voice assistants and meeting transcription systems.