Researchers developed a novel annealing processing system that scales both the number of spins and interaction bit width simultaneously Combinatorial optimization problems (COPs) arise in various fields such as shift scheduling, traffic routing, and drug development. However, they are challenging to solve using traditional computers in a practical timeframe. Alternatively, annealing processors (APs), which are specialized hardware for solving COPs, have gained significant attention. They are based on the Ising model, in which COP variables are presented as magnetic spins…

Atomic imaging and AI offer new insights into motion of parasite behind sleeping sickness Millions of people worldwide are affected by African sleeping sickness, Chagas disease and other life-threatening infections caused by microscopic parasites borne by insects such as the tsetse fly. Each of the underlying single-celled parasites — Trypanosoma brucei and its relatives — has one flagellum, a whiplike appendage that is essential for moving, infecting hosts and surviving in different environments. Now, a research team at the California NanoSystems…

In two commentaries, researchers at the University of Maryland School of Medicine say combining modeling methods—and ethically sharing health data—could transform treatment With the advent of artificial intelligence (AI), predictive medicine is becoming an important part of healthcare, especially in cancer treatment. Predictive medicine uses algorithms and data to help doctors understand how a cancer might continue to grow or react to specific drugs—making it easier to target precision treatment for individual patients. While AI is important in this work,…

Neural networks are one typical structure on which artificial intelligence can be based. The term ›neural‹ describes their learning ability, which to some extent mimics the functioning of neurons in our brains. To be able to work, several key ingredients are required: one of them is an activation function which introduces nonlinearity into the structure. A photonic activation function has important advantages for the implementation of optical neural networks based on light propagation. Researchers in the Stiller Research Group at…