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Earthly Machine Learning

Earthly Machine Learning

Climate Knowledge in Large Language Models

· 12 min · Stagione 2 Episodio 2

Note dell’episodio

Climate Knowledge in Large Language Models
Kuznetsov, I., Grassi, J., Pantiukhin, D., Shapkin, B., Jung, T., & Koldunov, N. (2025). Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research.

LLMs have an internal "map" of the climate, but it is fuzzy: Without access to external tools, Large Language Models (LLMs) can recall the general structure of Earth’s climate—correctly identifying that the tropics are warm and high latitudes are cold. However, their specific numeric predictions are often inaccurate, with average errors ranging from 3°C to 6°C compared to historical…

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