We aim to transform scientific research itself. Many scientific endeavors can benefit from large scale experimentation, data gathering, and machine learning (including deep learning). We aim to accelerate scientific research by applying Google’s computational power and techniques in areas such as drug discovery, biological pathway modeling, microscopy, medical diagnostics, material science, and agriculture. We collaborate closely with world-class research partners to help solve important problems with large scientific or humanitarian benefit.
Recent publications
Global extreme heat forecasting using neural weather models
Artificial Intelligence for the Earth Systems, vol. 2 (2023), e220035
Multimodal contrastive learning for remote sensing tasks
Self-Supervised Learning - Theory and Practice, NeurIPS 2022 Workshop
Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields
The Journal of Physical Chemistry Letters, vol. 13(43) (2022), pp. 10183-10189
Chimane-Mosetén
Amazonian Languages: An International Handbook, De Gruyter Mouton (2023)
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