Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...

Abstract: A general problem in multi-node systems is data synchronization, where the most used method uses synchronous data updating. All changes made by the user are immediately reflected in the data ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Artificial Intelligence, Perceived Objectivity, Decision Authority, Human Resource Management, Algorithmic Governance, ...

Lilian Coral explains the Trump TikTok deal, what it means for users, and what it reveals about the administration’s efforts ...

See how optimizing content differently for LinkedIn, Reddit, and search engines improves reach, relevance, and user ...

Small and dense but filled with vitally important neural fibers, the brainstem has been hard for brain imaging technologies ...

The signals that drive many of the brain and body's most essential functions—consciousness, sleep, breathing, heart rate and motion—course through bundles of "white matter" fibers in the brainstem, ...

Machine learning is helping neuroscientists organize vast quantities of cells’ genetic data in the latest neurobiological cartography effort.

I'll explore data-related challenges, the increasing importance of a robust data strategy and considerations for businesses ...

Abstract: To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes ...