GenCast, a new AI model from Google DeepMind, is accurate enough to compete with traditional weather forecasting ... which is why it takes less time and computational power to produce a forecast.

Abstract: Reliable interval forecasting of uncertain load with cyberattacks is ... model is employed to extract long- and short-term temporal dependencies of load time series. Then, an optimal ...

DeepMind reports that GenCast dramatically outperforms the best traditional forecasting model ... In addition, the confidence values, based on the uncertainty obtained from the ensemble, were ...

“GenCast could be incorporated as part of operational weather forecasting systems, offering valuable insights to help decision makers better understand and prepare for upcoming weather events.

@inproceedings{jin2023time, title={{Time-LLM}: Time series forecasting by reprogramming large language models}, author={Jin, Ming and Wang, Shiyu and Ma, Lintao and Chu, Zhixuan and Zhang, James Y and ...

In July, it published details of NeuralGCM, a model that combined AI with physics-based methods like those used in existing forecasting ... 97% of the time, and it was better at predicting wind ...

This caught many by surprise and left some shocked, especially market analysts and economists who make a living by forecasting and ... broader question of the confidence with which such forecasts ...

Devised by the search engine firm’s AI division, DeepMind, the “GenCast” model can tell if it’s going to rain 15 days ahead of time at a ... s top operational forecasting system, per ...