Anthropic does scaling laws research to predict empirically what properties emerge in language models at various sizes.

True if, as of 2022, Anthropic was doing scaling-laws research aimed at empirically predicting how language-model properties or behaviours change with model size, as shown by papers such as 'Predictability and Surprise in Large Generative Models' (2022) or similar work. Mostly true if the research existed but focused mainly on predicting loss or performance rather than emergent properties more broadly. Mixed if such research was only marginal. Mostly false if Anthropic's scaling work did not aim at prediction. False if Anthropic did no such research at that time.

Set before the research began.

1. E1 Predictability and surprise in large generative models Anthropic · 15 February 2022 Own record

   “Namely, these generative models have an unusual combination of predictable loss on a broad training distribution (as embodied in their "scaling laws"), and unpredictable specific capabilities, inputs, and outputs.”

2. E2 Anthropic's core views on AI safety Anthropic · 8 March 2023 Own record

   “In the best case, we aim to build detailed quantitative models of how these tendencies vary with scale so that we can anticipate the sudden emergence of dangerous failure modes in advance.”

3. E3 Anthropic's core views on AI safety Anthropic · 8 March 2023 Own record

   “In 2019, several members of what was to become the founding Anthropic team made this idea precise by developing scaling laws for AI, demonstrating that you could make AIs smarter in a predictable way, just by making them larger and training them on more data.”

E1 is Anthropic's published February 2022 paper 'Predictability and Surprise in Large Generative Models', which the resolution criteria name as an example of qualifying work. Its quoted text analyses how models scale, contrasting the predictable loss described by scaling laws with specific capabilities that are hard to predict. E3 says that people who went on to found Anthropic developed scaling laws in 2019. E2 (2023) states the aim of modelling how model tendencies change with scale so that emerging behaviours can be anticipated. All of this evidence comes from Anthropic itself, but E1 is the published research, so it counts as an official record that Anthropic was doing this work in 2022.