AI glossary
Plain-English definitions of the artificial intelligence terms you meet in tutorials, tool reviews and release notes. No jargon for the sake of it.
9 terms.
C
- Computer Vision Models & Architectures
- The field of teaching computers to interpret images and video.
D
- Diffusion Model Models & Architectures
- A generative model that creates images by starting from noise and progressively removing it.
F
- Foundation Model Models & Architectures
- A large model pre-trained on broad data that can be adapted to many downstream tasks.
L
- Large Language Model Models & Architectures
- A neural network trained on massive text corpora to predict the next token, enabling it to generate and understand language.
M
- Multimodal AI Models & Architectures
- AI that understands and generates more than one type of data, such as text, images and audio together.
N
- Neural Network Models & Architectures
- A computing model made of connected nodes organised in layers that learn by adjusting the strength of their connections.
P
- Parameters Models & Architectures
- The internal numbers a model learns during training; their count is a rough measure of model size.
R
- Retrieval-Augmented Generation Models & Architectures
- A technique that lets a model look up relevant documents and include them in its answer, improving accuracy and freshness.
T
- Transformer Models & Architectures
- A neural network architecture that uses self-attention to weigh the importance of every word in a sequence relative to every other word.