MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

Google Discover is largely a mystery to publishers and the search marketing community even though Google has published ...

Automotive Market is expected to reach USD 244.4 billion by 2036, driven by growing adoption of autonomous driving, ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

1 Department of Rehabilitation Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China 2 School of Mathematics, South China University of Technology, Guangzhou, ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

1 Institute for Theoretical Physics, University of Bremen, Bremen, Germany 2 Institute of Electrodynamics and Microelectronics (ITEM.ids), University of Bremen, Bremen, Germany Considering biological ...

Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. “smarter than a Nobel Prize winner” in such fields as biology, math, engineering, and ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Abstract: To address the challenges of data sparsity, cold start, and insufficient dynamic adaptability in traditional recommendation systems, this study proposes a personalized recommendation model ...