Scaling laws
Observed relationships showing that model performance improves predictably as training compute, data and parameters increase together. They guided the push towards ever larger models. They describe a trend in measured loss, not a guarantee of any particular capability.
Related terms
The mechanism in a transformer that lets the model weigh how relevant each token is to every other token when working …
BackpropagationThe technique that calculates how much each weight in a neural network contributed to an error, working backwards from…
Base modelA model straight out of pretraining, before it has been tuned to follow instructions or hold a conversation. Given a q…
Chain of thoughtStep-by-step reasoning written out before a final answer, either prompted ('think it through step by step') or built i…
ComputeShorthand for the processing power used to train and run AI models, usually on large clusters of specialised chips in …
Constitutional AIA training approach, published by Anthropic in 2022, in which a model critiques and revises its own responses against …
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