Northwestern University and University of California, Los Angeles (UCLA) scientists have developed a new process-based ...

The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

Understanding and predicting complex physical systems remain significant challenges in scientific research and engineering. Machine learning models, while powerful, often fail to follow the ...

Aramide’s paper titled, ‘Quantum-Safe Networking for Critical AI/ML Infrastructure’, investigates the implications of quantum ...

TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, ...

Introduction The integration of artificial intelligence (AI) into our daily lives has rapidly accelerated, changing the way ...

Despite the AI hype, ML tools really are proving valuable for leading-edge chip manufacturing. More aggressive feature ...

The gradient boost model achieves the best performance for predicting no-shows and late cancellations in primary care practices, according to a study published in the July/August issue of the Annals ...

QBTS unveils quantum AI and blockchain tools aimed at enterprise adoption, fueling optimism around its system sales strategy.

Ionic liquids (ILs) are a class of molten salts with a collection of exciting properties, which have been employed for ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Aman Sardana's research leverages his FinTech architecture expertise to design secure payment intelligence, focusing on ...