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The latest research from Google

Generative AI to quantify uncertainty in weather forecasting

Accurate weather forecasts can have a direct impact on people’s lives, from helping make routine decisions, like what to pack for a day’s activities, to informing urgent actions, for example, protecting people in the face of hazardous weather conditions. The importance of accurate and timely weather forecasts will only increase as the climate changes. Recognizing this, we at Google have been investing in weather and climate research to help ensure that the forecasting technology of tomorrow can meet the demand for reliable weather information. Some of our recent innovations include MetNet-3, Google's high-resolution forecasts up to 24-hours into the future, and GraphCast, a weather model that can predict weather up to 10 days ahead.

AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks

Computer-aided diagnosis for lung cancer screening

Using AI to expand global access to reliable flood forecasts

ScreenAI: A visual language model for UI and visually-situated language understanding

SCIN: A new resource for representative dermatology images

MELON: Reconstructing 3D objects from images with unknown poses

HEAL: A framework for health equity assessment of machine learning performance

Cappy: Outperforming and boosting large multi-task language models with a small scorer

Talk like a graph: Encoding graphs for large language models

Chain-of-table: Evolving tables in the reasoning chain for table understanding