AI-Centered Partnership Between OMRON and Kyoto University Targets Cardiovascular Diseases

Researchers at the US-based Lawrence Berkeley National Lab (LBNL) recently reported a new approach to error mitigation in a quantum computer (QC) that targets error-producing noise, a ubiquitous problem that can severely limit the performance and utility of existing and near-future quantum computers. The method developed at LBNL consists of taking an initial noisy target circuit and constructing an analogous estimation circuit that is configured specifically for accurate noise characterization. The information gathered from running the estimation circuit is then applied to correct the noise in the original target circuit.

Recently, the Barcelona Supercomputing Center (BSC) trained the first large artificial intelligence (AI) model designed to understand, speak, and write in the Spanish language. The system, named MarIA, was trained on the MareNostrum supercomputer at the BSC, leveraging 59 TBs of language data from the Biblioteca Nacional de España, one of the world's largest public libraries. The model is said to be an expert in both writing and understanding the Spanish language and is free to use by any developer, company, or entity. The system has a wide variety of potential applications including summarization applications, chatbots, smart searches, translation engines, and automatic subtitling chatbots.