Penny Liang's book, "Understanding Large Models for Humanities Students (1.0)," explains the core technologies of large ...

In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...

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, ...

Opeyemi Adeniran, an AI researcher, has hinted on an AI-powered solution for early detection of Alzheimer’s disease through accurate MRI analysis. According to a statement, she asserts that the ...

This FAQ talks about how attention mechanisms work at their core, how they are used in automatic speech recognition systems, ...

More recently, deep learning and evolutionary algorithms have enabled long-term ecological forecasting, carbon emission ...

“They say, ‘We're going to throw out everything in my memory that's very old. For instance, they’ll cut off everything beyond ...

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 ...

CISPA researcher Sarath Sivaprasad, together with Hui-Po Wang and Mario Fritz from CISPA and other colleagues from HIPS, has ...

A module now brings big AI power to edge devices, running LLMs and vision tasks with low energy use and added security. Want ...

“Nanos flip the deployment model,” said Liquid AI Chief Executive Ramin Hasani. “Instead of shipping every token to a data ...