In autonomous driving (AD) tasks, data-driven deep reinforcement learning (DRL) outperforms rule-based methods in terms of continuous decision-making and adaptability. However, traditional DRL relies ...

This study has proposed a detection framework, and implemented it using quantum machine learning (QML) approach by applying Support Vector Machine (SVM) enhanced with quantum annealing solvers.

Key Takeaways Zero Trust is a fundamental shift in how we think about protecting our networks. If you’ve been in the industry long enough, you probably hear the term thrown around all the time, but ...

Microsegmentation limits exposure, and threat detection provides constant vigilance. Organizations that implement a layered Zero Trust framework benefit from stronger breach containment, faster ...

The MI350 and ROCm 7 deliver high-performance AI acceleration.

The US National Institute of Standards and Technology (NIST) has published new practical guidance on implementing zero trust architecture (ZTA). While previous NIST guidance on zero trust in 2020 ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.