8 articles
Index of editorial tags and filtered coverage.
On 2 October 2026 (press spotlighted on the 5th), ASUS announced the 64GB Ascent GX10 configuration on the NVIDIA DGX Spark platform with the GB10 Grace Blackwell Superchip, up to 1 petaFLOP, coherent unified memory for 30–35B open-source models, and two-unit clustering toward 128GB and roughly 1.7× throughput.
On September 14, 2026, Forbes and RuntimeWire covered Cognichip’s enterprise launch of Artificial Chip Intelligence (ACI), founded by Faraj Aalaei. The system uses native physics-informed models—not LLM wrappers—for microarchitecture, RTL, verification and PPA; one cited case compressed a 55-page spec into days versus 4–5 months. Public evidence remains company and customer benchmarks.
On July 24, 2026, Jensen Huang used his first X post to share the “Open Weights and American AI Leadership” letter, signed by Nvidia, Microsoft, Meta, Mistral, Hugging Face, the Linux Foundation and about 25 organizations total; OpenAI, Anthropic, Google and Amazon were absent from the original list. In parallel, Huang confirmed Vera Rubin was already in production, with shipments expected in the fall.
Per an internal memo reviewed by Reuters in July 2026, Meta planned to begin manufacturing its Iris accelerator from September within a four-generation MTIA program, with Broadcom on design and TSMC on fabrication. September coverage indicates production has started; infrastructure ambition is ~7 GW in 2026 and double (14 GW) in 2027, supplementing—not replacing—Nvidia and AMD GPUs.
Semiconductor Report in September 2026 describes how AI demand is tightening DRAM/NAND/HBM, PMICs, controllers, and PCB FR-4 materials: PMIC lead times from 6–8 to 12–16 weeks; some suppliers stop taking new orders; copper foil prioritized for high-frequency laminates; FR-4 lead times from 2 to 4–6 weeks. Tightness may persist into 2027.
Qualcomm’s Dragonwing IQ10 Robotics Reference Design targets up to 700 TOPS sparse / 350 dense, 18 Oryon cores, 64GB LPDDR5x ECC, up to 12 GMSL2 cameras, ROS2, EtherCAT/CAN-FD, and -40–70°C. Unveiled at Computex (June 2026); global commercial availability is scheduled for September 2026 versus NVIDIA Jetson Thor. Pricing was undisclosed as of early September—shipping confirmation verification in progress.
New accelerators promise up to 4× better energy efficiency for LLM inference.
NVIDIA launched CUDA, enabling general-purpose GPU programming; without it, modern deep learning would have been impractical.