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In this issue

Often in RHRQ, we look at the work of people discovering new frontiers in technology, but what I hope makes us different from other technology journals is that we’re also asking how open source and open practices can make these discoveries accessible to people in the...

Developing AI telemetry, digital twins, and other data-driven websites with SPINE Programming Theory

Developers using SPINE Programming have drastically cut manual coding time while maintaining full control over their data. SPINE Programming Theory (SPT) is a form of on-device, local AI code indexing and generation that accelerates software development while ensuring...

Enhanced observability makes optimizing LLM inference performance easier

More metrics and more dashboards mean more ways for researchers to identify actionable improvements. Optimizing the performance, stability, and resource utilization of large language model (LLM) deployments is a challenge for both users and cluster administrators. The...

Where AI meets secure coding: inside SEMLA’s ambition for more resilient software

The industry-academia collaboration aimed at using LLMs to help generate more secure code builds on its success to expand research into infrastructure. In an era when software underpins everything from critical communications and global financial systems to lifesaving...

RISC-V AI workshop with Red Hat, DeepComputing hosted in Boston

RISC-V is an increasingly prevalent hardware architecture in embedded systems, and it’s beginning to serve as the base architecture for many new AI accelerators. It is an instruction set architecture (ISA) with roots similar to Arm and other RISC-based architectures,...
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