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Causal AI adapts in real time, learning from every shift. Here’s why it outperforms static models when the market won’t sit ...
South Florida TV forecaster John Morales said he was not confident he could predict the paths of storms this year, touching a nerve amid concerns about how federal cuts could affect hurricane season.
More information: Katja Schlegel et al, Large language models are proficient in solving and creating emotional intelligence tests, Communications Psychology (2025). DOI: 10.1038/s44271-025-00258-x.
The model was then asked to supply a short-term forecast (one step, five minutes ahead), a medium-term forecast (30 steps, 2.5 hours ahead), and a long-term forecast (96 steps, eight hours ahead).
The model presents its forecasts probabilistically, drawing from a set of 50 or more predictions to generate its results. All of this occurs far more quickly than with traditional forecasting methods.
Home > Computing Microsoft's AI Weather Model Is More Accurate, Less Expensive Than Traditional Forecasting That's according to a research paper written largely by Microsoft employees, at least.
A Microsoft model can make accurate 10-day forecasts quickly, an analysis found. And, it’s designed to predict more than weather.
In real-life scenarios, long sequence time series forecasting (LSTF) has broad applications, such as electricity demand planning and abnormal weather prediction. In recent years, transformer-based ...
Photovoltaic Energy Production is a basic element of current energy systems. The transition to decentralized energy production which characterizes fast dynamics in the change of electricity ...
The new system, Aardvark Weather, was developed by researchers at the University of Cambridge in collaboration with the Alan Turing Institute, Microsoft Research, and the European Centre for ...
WeatherNext was trained using 40 years of data from past weather events stretching from 1979 to 2018. To test the model's performance, Price and his colleagues had it produce "forecasts" for 2019.