Published as an arXiv preprint, the paper details how unsupervised and self-supervised AI models are matching or surpassing supervised systems while uncovering biological patterns that traditional ...

Traditional approaches to autonomous vehicles (AVs) rely on using millions of miles of driving data in conjunction with even more miles of simulated data as inputs to supervised machine learning ...

6G visions include immersive extended reality, holographic communications, tactile internet applications, and large-scale digital twins. Supporting these services will demand fully autonomous network ...

Federated Learning (FL) has gained significant attention as a novel distributed machine learning paradigm that enables collaborative model training while preserving data privacy. However, traditional ...

Artificial Intelligence (AI) and Machine Learning (ML) are becoming core technologies across industries. Organizations are using these technologies to improve ...