ETH Zurich | Empowering data-driven science

Thanks to a collaboration between CHUV, EPFL – through the Swiss Data Science Center – and UNIL, a predictive platform based on artificial intelligence is under development to improve patient care.

As we endeavor to reduce global CO2 emissions to avoid the worst impacts of climate change, Bühler Group is laying the technical foundations to make real impacts on the industry’s emissions through an innovative approach to optimizing manufacturing operations.

It is difficult to effectively monitor and track progress in urban housing. We attempt to overcome these limitations by utilizing self-supervised learning with over 15 million street-level images taken between 2008 and 2021 to measure change in London.

Not all datasets are images and we need architectures that adapt to other types of data, encoding both domain specific knowledge and data specific characteristics. For instance, at the SDSC, we deal with spherical data, i.e. curved images on a sphere, but without clear borders and arbitrary orientation.

PassGPT is a Large Language Model for password generation trained on leaked passwords, which can outperform existing methods based on generative adversarial networks by guessing twice as many unseen passwords.

The SDSC has developed a dashboard with which parliamentary services can calculate the composition of the committees of the National Council.