This metaphorical cat is both dead and alive – and it will help quantum engineers detect computing errors
Peer-Reviewed Publication
Updates every hour. Last Updated: 1-May-2025 11:08 ET (1-May-2025 15:08 GMT/UTC)
A new study from Oxford University has uncovered why the deep neural networks (DNNs) that power modern artificial intelligence are so effective at learning from data. The new findings demonstrate that DNNs have an inbuilt ‘Occam's razor,’ meaning that when presented with multiple solutions that fit training data, they tend to favour those that are simpler. What is special about this version of Occam’s razor is that the bias exactly cancels the exponential growth of the number of possible solutions with complexity. The study has been published today (14 Jan) in Nature Communications.
Researchers at the Department of Energy’s Oak Ridge National Laboratory joined forces with EPB of Chattanooga and the University of Tennessee at Chattanooga to demonstrate the first transmission of an entangled quantum signal using multiple wavelength channels and automatic polarization stabilization over a commercial network with no downtime.
The successful trial of this innovation marks another step toward the eventual creation of a quantum internet that could prove to be more capable and secure than existing networks.
A research team coordinated by the Department of Physics was able to work on the powerful computers of Google's Quantum Artificial Intelligence Lab to conduct a study on confinement in lattice gauge theory. The results of the study have been published in Nature Physics