A generative model that learns to reverse a gradual noising process, turning random noise into an image step by step.
Read definitionA generative model that learns to reverse a gradual noising process, turning random noise into an image step by step.
Read definitionTwo networks trained against each other — one generating fakes, one detecting them — until the fakes are convincing.
Read definitionWriting the input to a model deliberately — with context, examples and constraints — to get a more reliable output.
Read definitionA setting that controls how much randomness goes into choosing each token — low is predictable, high is varied.
Read definition8 subject areas across 32 definitions — start wherever you already are.
The core ideas behind systems that learn patterns from data.
7 termsNeural networks with many layers, and the machinery that trains them.
5 termsHow machines read, generate and reason about human language.
7 termsModels that produce new text, images, audio or code.
4 termsMaking sense of images and video.
1 termDatasets, labelling, evaluation and the training loop itself.
1 termAlignment, bias, interpretability and the limits of these systems.
3 termsServing, scaling and running models in production.
4 terms