As AI increasingly powers vehicle automation, traditional safety standards are proving insufficient, demanding a broader evaluation of functional behavior beyond simple component failure.
New research demonstrates how combining multiple explainable AI techniques can provide a more complete and trustworthy understanding of deep learning models used in medical imaging.
A new study investigates how artificial intelligence can help healthcare professionals navigate the growing volume of patient-generated health data and improve cardiac risk reduction.
A new study details how machine learning algorithms can automatically classify white dwarf stars from large spectroscopic surveys, accelerating the discovery of rare and unusual systems.
A new review examines how context-aware deep learning is improving network intrusion detection through flow-based telemetry analysis.
Researchers introduce a framework that proactively identifies privacy risks throughout the entire lifecycle of artificial intelligence systems, from data collection to model deployment.
This review explores the burgeoning intersection of large language models and traditional modeling & simulation techniques, offering a practical guide for researchers and practitioners.
New research reveals that even carefully curated datasets can subtly shift the behavior of powerful language models, creating unexpected and potentially harmful outcomes.
A new approach combines graph neural networks and manifold learning to visualize and interpret the complex behavior of Internet of Things devices.
A new language model, FiMI, is being developed to better understand and operate within the unique complexities of India’s financial landscape.