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
Flow Lenia: Mass conservation for the study of virtual creatures in continuous cellular automata
Proceedings of WIVACE 2022, Communications in Computer and Information Science, Springer (2022)
SyConn2: dense synaptic connectivity inference for volume electron microscopy
Nature Methods, vol. 19 (2022), 1367–1370
Estimates of broadband upwelling irradiance from GOES-16 ABI
Remote Sensing of Environment, vol. 285 (2023)
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