Memory requirements are the most obvious advantage of reducing the complexity of a model's internal weights. The BitNet b1.58 ...

While deepfake generation advances in complexity, it also becomes more computationally demanding. In contrast, detection is learning to do more with less.

A new editorial was published in Oncotarget, Volume 16, on April 4, 2025, titled “Deep learning-based uncertainty ...

Using these datasets, 72 models with varying configurations – including different convolutional neural network architectures ... also indicating that classic and GAN-based augmentation approaches had ...

105 RISnet: a Dedicated Scalable Neural Network Architecture for Optimization of Reconfigurable Intelligent Surfaces B. Peng, etal. 106 Deep Reinforcement Learning for Secrecy Energy-Efficient UAV ...

This collaboration was undertaken as part of Smiths Detection’s Ada Initiative, the company’s structured framework for accelerating responsible open architecture in security screening.

This solution enables tighter synergy between hardware design, protocols, architectures, and AI training algorithms, boosting system performance.

A new technical paper titled “Thermal Boundary Resistance Reduction by Interfacial Nanopatterning for GaN-on-Diamond Electronics Applications” was published by researchers at University of Bristol, ...