Bob Gourley, co-founder and CTO of the cybersecurity consultancy OODA and former CTO at the Defense Intelligence Agency, says ...

Most people are likely familiar with complicated “deep learning” models, like ChatGPT. Models to process small earthquakes ...

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

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

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

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

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 ...

KAIST (President Kwang Hyung Lee) announced on the 20th that a research team led by Professor Sungjin Ahn in the School of Computing has developed a new technology that significantly improves the ...

For drones to expand their activities, a self-localization method for indoor flying drones is required to complement GPS. We have investigated indoor drone positioning based on Wi-Fi RTT (Round Trip ...

Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior performance compared to conventional non-machine learning approaches when ...

Machine learning (ML) tools have revolutionized protein structure prediction, engineering, and design, but the best ML tool is only as good as the training data it learns from. To obtain high-quality ...

In a breakthrough for artificial intelligence (AI) and finance, computer scientists from Texas A&M University have developed a machine learning based method called Symbolic Modeling to handle ...