CONNECT WITH US
Aug 24
Nvidia server prices to rise up to 17% as memory costs climb
Prices for some Nvidia-based server systems due for delivery in 2027 are set to rise by more than 15%, with certain flagship configurations increasing about 17%, as higher memory and other component costs feed through to next-generation data center infrastructure.
OmniVision Group reported a sharp drop in first-half 2026 profit as weakness in consumer electronics and automotive electronics weighed on its core image sensor business, even as machine vision, robotics and edge AI emerged as faster-growing sources of revenue.
According to 36Kr, Shanghai Guangyu Xinchen Technology says its TC1000 series of 3D-stacked near-memory-computing AI processors has moved from silicon validation to mass-production deployment, marking a claimed acceleration in the commercialization of memory-centric computing for edge AI.
Nvidia has reportedly notified major customers that server systems using its AI chips will rise by more than 15%, with the new pricing set to apply to models shipping from early 2027, including Grace Blackwell and the next-generation Vera Rubin platform. The move is expected to ripple through the chip and system supply chain, while industry figures say it could also lift the appeal of inference ASICs.

Samsung Electronics and SK Hynix are stepping up equipment spending at their NAND flash plants in China through 2027, upgrading existing production lines even as future access to Western chipmaking tools becomes less predictable.

Chinese analog and mixed-signal chipmaker Novosense Microelectronics has introduced the NSM350x series, a Hall-based magnetic encoder designed for high-precision angular measurement in robot joints and industrial motion-control systems, reports Sina Finance.
Infineon Technologies has agreed to acquire Bangalore-based C2i Semiconductors, a move that strengthens its position in power delivery for AI data centers and highlights India's growing role in chip design. The deal could shape how global operators manage rising energy demand, efficiency pressures, and next-generation computing workloads.

Nvidia said its Groq 3 LPX inference accelerator is now in full production, a move that could speed up agentic AI systems used worldwide for coding, reasoning, and other tasks. The company said the platform is designed to improve responsiveness, lower latency, and support growing demand for real-time AI applications.

SpaceXAI plans to deploy Nvidia's new Vera CPUs to speed up agentic AI workloads, a move that could influence how advanced AI systems are built and run worldwide. The partnership also extends toward orbital computing, signaling a broader shift in where future AI infrastructure may be located.

In an August 24 press release, IBM announced that it is developing the first dual-architecture mainframe processor, a move that could let global enterprises run Arm-native and IBM workloads on the same future systems. The milestone may broaden software choices, accelerate AI adoption, and reshape mission-critical computing for banks, governments, and large cloud operators worldwide.

The AI infrastructure race is entering a phase where access to silicon is no longer the only constraint. As compute demand expands into multi-gigawatt projects, the industry is increasingly confronting a second bottleneck: how to finance hardware and data-center capacity at the scale frontier-model developers now require.
The AI infrastructure race has been marked by a near-fixated drive to expand AI-powered buildouts, as demand for increasingly complex chip configurations pushes against the physical and economic limits of scalability.