Sea snot’ blooms threaten marine life, tourism, and fisheries. Researchers used satellite images and AI to rapidly detect ...

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

MasterQuant is launching at a time when AI bots are gaining traction in the financial industry. According to recent reports, the global market for AI-powered trading solutions is expected to grow ...

At a time when conflict and division dominate the headlines, a new study from UCLA finds remarkable similarities in how mice ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a chatbot is more humanlike and aware than it actually is, like believing it's ...

Explore investment strategies, risks, and growth opportunities in the dynamic AI infrastructure space — plus 3 ETFs to watch.

This paper proposes a deep learning framework F-GCN that integrates multiple wavelet bases, and extracts MI brain electrical ...

The problem with Artificial Intelligence (AI) is that nobody is quite sure what it is.

Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...

A deep learning model was able to determine the presence or absence of distinct autoimmune neuroinflammatory disorders.

ORNL researchers developed an AI that links atomic structure to material behaviors, improving efficiency in material science ...