HPE GreenLake Partners with AWS for Seamless Hybrid Clouds

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.

Late last month, US Department of Defense (DOD) leadership explored the potential to inculcate artificial intelligence (AI) processes into its overall military operations, signaling a fundamental change in how information and data are used to increase the decision space for leaders both in military and civilian domains. Delivered during the third and most recent iteration of the Global Information Dominance Experiment (GIDE 3), which included representatives from all 11 combatant commands, NORTHCOM Commander Gen. Glen D. VanHerck's remarks on AI were aimed at progressing the ability to maintain domain awareness, achieve information dominance, and provide decision superiority in both competition and crisis.