5 results for “AI networking”
NVIDIA declared Scale-In the fifth pillar of AI networking infrastructure, powered by BlueField-4 DPUs, DOCA software, and Spectrum-X Ethernet. The architecture offloads security, storage, and telemetry from host CPUs at up to 800 Gb/s to keep pace with agentic AI factories.
NVIDIA detailed how Spectrum-X Ethernet uses hardware-accelerated adaptive routing, congestion control, and plane load balancing to solve traditional Ethernet's failures at giga-scale AI training. The platform delivers 1.6x performance over off-the-shelf Ethernet, near-perfect multi-tenant isolation, and 2.68 ms failover versus 1.08 seconds for standard Ethernet.
Amazon Science released SOP-Bench, an open benchmark with 2,000+ tasks from real business SOPs across twelve domains. The framework pairs authentic procedures with working tools and ground-truth answers so teams can validate agents before production deployment.
After a summer of agent boundary escapes, NVIDIA maps five stack layers and argues security must live in OpenShell-style runtimes—not in harness code models can rewrite.
NVIDIA published Vera CPU benchmarks showing up to 3.67x faster CRC32C integrity checks and 3.26x faster Reed-Solomon recovery versus an unnamed x86 CPU. The gains target the storage processing bottleneck that can throttle agentic AI workloads.