25 results for “Amazon”
Anthropic opened a research preview of the Model Hardware Standard, a specification that lets AI agents safely control lab and factory equipment. The standard cuts device integration from months to minutes and is being tested by Genentech, AWS, and robotics vendors.
Nvidia has reportedly agreed to acquire Hugging Face for $12.9 billion, giving the chipmaker control of the leading open-source AI model hub. The deal would protect Nvidia's hardware dominance by keeping open-source AI dependent on its silicon while providing a cloud distribution channel.
Amazon and Nvidia expanded their partnership with a 2 million GPU order for 2027-2028 delivery, tripling the previous commitment. The deal spans Blackwell Ultra, Rubin, and Vera CPUs while Amazon simultaneously builds competing Trainium chips.
NVIDIA launched NVLink Fusion with NVHBM on August 26, 2026, giving hyperscalers a standardized path to deploy custom XPUs alongside NVIDIA GPUs. The co-designed memory and interconnect stack promises 30% higher bandwidth, 25% more compute area, and 15% lower HBM power versus standard HBM4e.
NVIDIA unveiled NVLink Fusion, letting hyperscalers plug custom XPUs into its 72‑XPU NVLink domain and MGX rack architecture. The program cuts non‑differentiated engineering so silicon teams can ship custom accelerators faster while reusing proven power, cooling, and cluster software.
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.
Hugging Face is exploring a sale that could value the AI developer platform at $13 billion or more. The potential deal highlights how essential neutral model hubs have become to the AI ecosystem.
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 released Nemotron 3.5 Lightning, a 30B MoE model with 3B active parameters built for high-volume agent execution. The open model cuts inference cost for always-on agents by handling routine tool calls while frontier models focus on planning.
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.
Harvard and MIT researchers released MatrAIx, an open-source system that simulates 8.3 billion AI personas across 1,290 behavioral dimensions. The platform lets product teams stress-test features and AI systems against a planetary-scale synthetic population overnight.