AI Design Glossary

All the AI design terms you need to know, explained simply and clearly

All Basic Concepts (5)Generation Techniques (10)Model Architectures (7)Advanced Techniques (3)General Concepts (3)

C D E G L T V7 terms

CLIP

Model Architectures

A multimodal AI model developed by OpenAI that can represent text and images in the same vector space. Used as a prompt understanding layer in image generation tools.

Diffusion Model

Model Architectures

A deep learning model that generates images by gradually denoising. It starts from random noise and step by step creates a meaningful image.

Embedding

Model Architectures

The process of converting text, images, or other data types into dense, fixed-size numerical vectors. Used for semantic similarity calculation and model input representation.

GAN (Generative Adversarial Network)

Model Architectures

A deep learning model where two neural networks are trained against each other: a generator and a discriminator. The generator tries to produce realistic data, while the discriminator tries to distinguish between real and fake data.

Latent Space

Model Architectures

A multidimensional space where data is compressed and mathematically represented. Diffusion models perform image generation in this compressed space for computational efficiency.

Transformer

Model Architectures

A deep learning architecture based on the attention mechanism with parallel processing capability. It forms the foundation of both language and visual models.

VAE (Variational Autoencoder)

Model Architectures

A probabilistic deep learning model that encodes data into a compressed latent space and can generate new data from this space. Used in the image encoding layer of diffusion models.