Blog
Insights on GPU infrastructure, AI workloads, and bare metal computing.
NovaCore and GPU.ai Partner to Expand Blackwell-Powered GPU Access Across U.S. and India
Our strategic partnership with GPU.ai gives AI teams seamless access to GPU resources across two continents — Blackwell in Hyderabad, A100/H100/H200 on the U.S. east coast.
NovaCore Becomes India's First GPU Cloud to Deploy NVIDIA Blackwell
We've deployed India's first NVIDIA Blackwell-powered GPU cloud in Hyderabad, bringing next-generation AI infrastructure to startups, researchers, and enterprises across India, the U.S., and the Middle East.
India's $200 Billion AI Infrastructure Moment
India is targeting $200B+ in AI infrastructure investment by 2028. Between government incentives, hyperscaler commitments, and domestic conglomerates, the country's compute capacity is about to increase 8x.
DeepSeek and the Open-Source Inference Revolution: Why Hardware Matters More Than Ever
DeepSeek V3 trained for $5.6M on 2,048 GPUs. As open-source models match frontier performance at a fraction of the cost, the bottleneck shifts from model access to inference infrastructure.
Adani's $100 Billion Bet on Sovereign AI Infrastructure
The Adani Group committed $100 billion to build green-energy-powered, hyperscale AI data centers by 2035. What this means for India's position in the global AI compute landscape.
India's Zero-Tax AI Policy Through 2047: What It Means for GPU Infrastructure
India's Union Budget 2026-27 introduced a tax holiday through 2047 for foreign cloud providers operating AI data centers in India. Here's why this changes the math for AI infrastructure decisions.
NVIDIA Blackwell Ultra: What the GB300 NVL72 Means for AI Infrastructure
NVIDIA's Blackwell Ultra architecture delivers 1.5x the performance of B200 with 288GB HBM3e per GPU. Here's what the specs mean in practice for training and inference workloads.
Why Bare Metal Matters for AI Training
Virtualization overhead costs you 10-15% of your GPU compute. At supercluster scale, that's millions in wasted spend.
What to Look for in a GPU Cloud Provider
Not all GPU clouds are equal. Beyond price-per-hour, here are the factors that actually determine whether a provider will work for serious AI workloads.
Training and Inference Need Different Infrastructure
Teams that optimize their GPU clusters for training often find them poorly suited for inference — and vice versa. Here's why the hardware requirements diverge and what to do about it.
The GPU Shortage: What's Real, What's Not, and What Comes Next
H100 lead times have dropped from 52 weeks to under 8. The GPU shortage narrative is outdated — but the market dynamics that replace it are more nuanced than 'supply is fixed.'