Hyperscaler Capex keeps rising on price hikes and shortages; pricier AI racks drive server value growth over volume.
US hyperscalers keep expanding, but midterm-driven backlash may raise costs and delay permits for later-stage projects.
NVIDIA shipments stay Blackwell-led as Rubin's ramp slips into next year on HBM4 snags, keeping HBM the key bottleneck.
AI chip makers weigh downgrading HBM capacity, hitting capacity for KV cache, lifting offload memory demand, as 8hi stays mainstream.
AI compute surges in 2026 as ASICs rise, NVIDIA defends its ecosystem, and bandwidth becomes the bottleneck.
Optical interconnects in AI data centers are shifting from legacy pluggable optics toward LPO, CPO and OCS. LPO streamlines the signal chain to improve power while keeping a pluggable model, CPO co‑pa...
AI server demand surges on hyperscale and inference workloads, lifting CSP rack-scale buildout amid grid constraints.
NVIDIA expands its AI factory via integrated GPU, CPU, and LPU racks for training and inference, securing its market lead.
Contract DRAM prices are expected to surge significantly, with Micron leading. Spot market sellers are holding back due to strong outlook, causing DDR4 scarcity and DDR5 price hikes. AI's evo...
TrendForce notes surging AI inference drives high-capacity storage demand. HDD shortage pushes CSPs to Nearline SSDs. NAND Flash vendors accelerate QLC validation & expansion. Future sees...
Geopolitical constraints and import controls curb RTX PRO in China, with a special edition awaiting broader demand; CPX adopts GDDR7 memory with increased capacity, complementing Rubin GPUs that rely...
Amazon is rapidly expanding its self-developed AI ASIC servers to bolster AWS's cloud AI training competitiveness. The new generation Trainium chips feature diversified designs ca...
TrendForce forecasts uncertain growth for AI server shipments in 2025, influenced by US export controls, the rise of DeepSeek, and GB rack preparation progress. The base case projects 28% growth; the...
1. End-to-End Model 2. Analysis of Key Players in End-to-End Models 3.The Deployment and Challenges of Computational Power for Training 4. TRI’s View
The expectation that AI would introduce immense benefits to the commercial market has prompted major suppliers to engage in AI training, which yielded the demand for hardware equipment. AI is currentl...
