Rapidata emerges to shorten AI model development cycles from months to days with near real-time RLHF

Rapidata treats RLHF as high-speed infrastructure rather than a manual labor problem. Today, the company exclusively ...
IEEE

Parallel Collaborative ADMM Privacy Computing and Adaptive GPU Acceleration for Distributed Edge Networks

Abstract: Distributed computing has been widely applied in distributed edge networks for reducing the processing burden of high-dimensional data centralization, where a high-dimensional computational ...
IEEE

NetPlacer+: Model Parallelism Based on Load Balance in Distributed Deep Learning

Abstract: The importance of Model Parallelism in Distributed Deep Learning continues to grow due to the increase in the Deep Neural Network (DNN) scale and the demand for higher training speed.
Frontiers

Post-traumatic growth and rehabilitation adherence in lower extremity fracture patients: a parallel mediation model

Background: Previous studies have shown that psychological factors such as post-traumatic growth (PTG), self-efficacy, and social support may be associated with rehabilitation behaviors in patients ...