Inrecent years, few technologies have evolved at the speed of Artificial Intelligence, and in particular at that of Neural Networks. This exponential growth has been achieved mainly due to two factors:

Decisions made by machines based on AI have already been shown to be discriminatory or racist. This is due to the fact that the algorithms draw on data originating from humans, and this data is frequently biased – among other things with sexist prejudices.

MIT researchers have developed a new method to find out what is going on inside materials. To do this, they need data from the material's surface alone.

Researcher Lukas Tuggener and app developer Florian Seibold intend to revolutionize the world of professional music. They are digitizing sheet music using a completely new deep learning method: Deep Watershed Detection.

Geneva researchers have discovered a molecule that indicates diabetes even before the first symptoms appear. To identify it, they used machine learning methods to analyse thousands of molecules.

The factory of the future: Humans use brain-machine interfaces to control production processes through the power of their minds. This vision was presented to the public on the campus of the EPFL Swiss Federal Institute of Technology in Lausanne within the framework of the “Mental Work” project. At the same time, a unique data set was collected.

Doctors often query the electronic patient record for information that helps them make treatment decisions. But searching for an answer to a single question can take several minutes. A machine learning model could help professionals find information more efficiently.

Proteins control most processes in living cells and are vital for humans. If it were possible to precisely determine all proteins in an organism, diseases such as Alzheimer's or cancer could be treated better and more individually.

Researchers at MIT have developed a method that helps users understand how a machine learning model thinks and compare it to how a human thinks.

For AI systems, learning in “superposition” pays off. It allows them to simultaneously pursue multiple paths and thus learn faster.