It is a concept that is at the core of industrial manufacturing. From the second Industrial Revolution to the rise of Lean Manufacturing, industry giants have optimized the manufacturing process. They realized that removing inefficiency and waste from the process enables them to make more components without changing much else. This

On smart speakers and other low-power linked devices, a new technique leverages optics to speed up machine learning calculations. A graphic depicts a revolutionary piece of hardware called a smart transceiver that drastically accelerates one of the most memory-intensive stages of running an ML model by utilizing silicon photonics technology.

We’re putting another year of exciting developments in artificial intelligence (AI) deep learning behind us – one filled with remarkable progress, controversies and, of course, disputes. As we wrap up 2022 and prepare to embrace what 2023 has in store, here are some of the most notable overarching trends that marked this year in

Besides time and cost savings, surrogate models could lead to new scientific discoveries, owing to their ability to handle large volumes of high-dimensional data. New research from the Lawrence Livermore National Laboratory (LLNL) demonstrated deep learning surrogate models performing as well, and sometimes better, than more expensive simulators. The researchers

Omnipose, a deep learning software, is helping to solve the challenge of identifying varied and miniscule bacteria in microscopy images. It has gone beyond this initial goal to identify several other types of tiny objects in micrographs. The UW Medicine microbiology lab of Joseph Mougous and the University of Washington