glossary

Key terms and definitions

Agent

An AI system that uses an observe-think-act loop with tool calling to autonomously accomplish tasks.

Attention

A mechanism that allows neural networks to focus on relevant parts of the input when producing output.

BERT

Bidirectional Encoder Representations from Transformers — an encoder-only model pre-trained on masked language modelling and next sentence prediction.

Embedding

A learned dense vector representation that maps discrete tokens to continuous vector spaces.

GPT

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

GRU

Gated Recurrent Unit — a simplified RNN variant with fewer gates than LSTM that achieves comparable performance with less computation.

JSON Schema

A vocabulary for annotating and validating JSON documents, used to define tool interfaces for language models.

LSTM

Long Short-Term Memory — an RNN variant with gating mechanisms that can learn long-range dependencies in sequential data.

NLP

Natural Language Processing — the field of AI concerned with enabling computers to understand, interpret, and generate human language.

Prompt Injection

An adversarial attack where malicious input manipulates a language model into performing unintended actions.

RNN

Recurrent Neural Network — a neural network architecture that processes sequences by maintaining a hidden state across time steps.

Tool Calling

A mechanism that allows large language models to invoke external functions and APIs by generating structured requests.

Transformer

A neural network architecture based on self-attention mechanisms, introduced in 'Attention Is All You Need' (2017).