APAC Data Center Power Crisis: Solutions for 200 TWh AI Energy Demand
APAC faces 165% power demand increase by 2030. Singapore restricts data centers, Malaysia faces blackouts. Solutions from microgrids to SMRs for AI infrastructure.
Blog
Insights on GPU infrastructure, AI, and data centers.
NVIDIA NIM and Inference Microservices: Deploying AI at Enterprise Scale
Deploying a large language model used to require weeks of infrastructure work, custom optimization scripts, and a team of ML engineers who understood the dark arts of inference tuning. NVIDIA changed
NVIDIA Blackwell Ultra and B300: what the next GPU generation demands
The NVIDIA Blackwell Ultra GPU delivers 15 petaflops of dense FP4 compute, 50% more memory than the B200, and 1.5 times faster performance.¹ A single GB300 NVL72 rack achieves 1.1 exaflops of FP4
GPU Virtualization Performance: Optimizing vGPU for Multi-Tenant AI Workloads
Alibaba Cloud discovered their vGPU deployment achieving only 47% of bare-metal performance despite marketing claims of 95% efficiency, costing them $73 million in over-provisioned infrastructure to
How DeepSeek and Qwen change AI infrastructure economics
DeepSeek claims to have trained its R1 model for just $5.6 million using 2,000 NVIDIA H800 GPUs.¹ Comparable Western models required $80 million to $100 million and 16,000 H100 GPUs.² The January
CXL Memory Expansion: Breaking the Memory Wall in AI Data Centers
Memory bottlenecks kill AI performance. Large language models routinely exceed 80 to 120GB per GPU for KV cache alone, overwhelming even the most expensive HBM-equipped accelerators.¹ Compute Express
Google TPU vs NVIDIA GPU: An Infrastructure Decision Framework for 2025
Anthropic closed the largest TPU deal in Google's history in November 2025—committing to hundreds of thousands of Trillium TPUs in 2026, scaling toward one million by 2027.¹ The company that built
Object Storage for AI: Implementing GPU Direct Storage with 200GB/s Throughput
Meta achieved a 3.8x improvement in model training speed by implementing GPUDirect Storage across their research clusters, eliminating the CPU bottleneck that previously limited data loading to
The AI PC revolution: what on-device AI means for data center strategy
AI PCs will represent 31% of the total PC market globally by the end of 2025, with shipments projected at 77.8 million units.¹ Eight out of ten IT decision makers plan to invest in AI PCs this year.²
Model Serving Optimization: Quantization, Pruning, and Distillation for Inference
A single GPT-3 inference request costs $0.06 at full precision but drops to $0.015 after optimization, a 75% reduction that transforms AI economics at scale. Model serving optimization techniques
Germany's industrial AI transformation confronts infrastructure gaps
Europe's largest economy faces a defining moment. Germany committed €5.5 billion to make AI account for 10% of domestic economic output by 2030.¹ Google announced €5.5 billion in German data center
GPU Depreciation Strategies: Optimizing Asset Lifecycles
Microsoft's Satya Nadella revealed a crucial insight about GPU infrastructure planning: "I didn't want to go get stuck with four or five years of depreciation on one generation."¹ The comment