Abstract: Federated learning is a distributed machine learning paradigm designed to facilitate collaborative model training while preserving user data privacy. However, in practical scenarios, data ...

Abstract: Isokinetic training has been proven to be an effective method in rehabilitative therapy. However, the quantitative relationship between training speed and the biophysical condition of the ...

AI models still lose track of who is who and what's happening in a movie. A new system orchestrates face recognition and staged summarization, keeping characters straight, and plots coherent across ...

Patient digital twins aim to create computational replicas of an individual’s physiology that can predict disease trajectories and treatment response.

“If we can build our models on our chips, we can build them at a fraction of the cost of a pure-play AI model provider,” Amazon’s new artificial intelligence czar, Peter DeSantis, told the news outlet ...

When churches are equipped with proven tools, they can provide the stability and consistent relationships children in ...

Sea level can temporarily change for a variety of reasons—atmospheric pressure shifts and water accumulation from wind and ...

Our new patent-pending BMS has been released on our first two models Z-Viper and Z-Python. Please visit our website for ...

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

Microsoft has announced that the Microsoft Agent Framework has reached Release Candidate status for both .NET and Python. This milestone indicates that the API surface is stable and feature-complete ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

OpenAI wants to retire the leading AI coding benchmark—and the reasons reveal a deeper problem with how the whole industry measures itself.