The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

The company says its new architecture marks a shift from training-focused infrastructure to systems optimized for continuous, low-latency enterprise AI workloads. 2026 is predicted to be the year that ...

SAN JOSE, Calif.--(BUSINESS WIRE)--Arrcus, the leader in distributed networking infrastructure, today announced it will showcase its carrier grade 5G ready Arrcus Inference Network Fabric (AINF) at ...

As AI workloads shift from centralized training to distributed inference, the network faces new demands around latency requirements, data sovereignty boundaries, model preferences, and power ...

Adapting to the addressee is crucial for successful explanations, yet poses significant challenges for dialog systems. We adopted the approach of treating explanation generation as a non-stationary ...

Abstract: Since the introduction of Dynamic Bayesian Networks (DBNs), their efficiency and effectiveness have increased through the development of three significant aspects: (i) modeling, (ii) ...

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. We’re at an inflection point with artificial intelligence today, and it’s filtering into ...

Microsoft has come swinging in the battle of custom hyperscale silicon, debuting its “AI inference powerhouse” Maia 200 accelerator. Built on Taiwan Semiconductor Manufacturing Company's (TSMC) 3nm ...

Google researchers have warned that large language model (LLM) inference is hitting a wall amid fundamental problems with memory and networking problems, not compute. In a paper authored by ...

Abstract: Gaze-based object manipulation intention inference is pivotal to natural and intuitive human-robot interaction. Existing methods confine spatial regularity to independent object selection ...