In their own words.
Our plain version above is ours. This is the official or expert wording we based it on.
“the cumulative amount of computation used for its training measured in floating point operations”
Regulation (EU) 2024/1689. Text as reproduced by artificialintelligenceact.eu (Future of Life Institute); the official text is on EUR-Lex.
The EU AI Act presumes a general-purpose model has 'high impact capabilities' above 10^25 FLOP of training compute.
Related words.
Fine-tuning
Extra training given to an already-trained model to make it better at a particular job, style or subject.
Distillation
Training a smaller, cheaper model to copy the behavior of a bigger one, so it runs faster at some loss of ability.
Parameters (weights)
The numbers inside a model that are adjusted during training and hold what it has learned. Big models have hundreds of billions or more.
Training data
The text, images, code and other material a model learns from during training.
Training run
One long job, often lasting weeks to months on thousands of chips, in which a model learns from its training data. Its size is usually measured in FLOP of compute.
FLOP (floating-point operation)
One basic arithmetic step on decimal numbers. The total FLOP used to train a model (e.g. 10^25) is a standard way to say how big a training run was.