The Agentic AI Infrastructure Blueprint: Bridging the Gap from Pilot to Production in 2026
Most enterprises have a successful pilot. Few have the runway for a successful takeoff in production. Here’s what infrastructure breaks and what to build…
News
Updates, announcements, and coverage from Arc Compute.
Why Investors Are Shifting From AI Startups to AI Infrastructure
Artificial intelligence has triggered one of the largest capital investment cycles in modern technology. Venture funding has flowed into AI startups building foundation models,…
Beyond Blackwell: Preparing Enterprise Data Centers for the NVIDIA Rubin Architecture and the HBM Crunch
Every major NVIDIA architecture transition forces a decision point for enterprise AI teams. The shift from Hopper to Blackwell was disruptive enough. What comes…
Jensen Huang’s GTC 2026 Keynote: The $1 Trillion AI Factory Era Has Arrived
The Inference Inflection Point Is Real, and It’s Already Here Jensen spent real time explaining why demand has multiplied so dramatically. His argument comes down to…
Data Sovereignty in AI: Why Cloud-Only Strategies Fall Short
It’s common to think of data sovereignty in AI as compliance checkboxes and audit trails. Those matter, but they’re line items on a much longer…
A CEO’s Guide to AI Inference Economics
Why enterprise AI infrastructure investments often fail to deliver ROI, and how to fix it You approved the AI budget. The servers were ordered. The infrastructure…
Liquid Cooling for GPU Infrastructure: How Air Cooling Limits AI Scaling
Liquid cooling is quickly becoming a structural requirement for modern AI infrastructure. As GPU power density climbs toward 500 kW per rack, traditional air-cooled…
GPU Infrastructure for Medical Imaging AI: A 2026 Guide for Radiology and Pathology
Medical imaging AI isn’t limited by models. It’s limited by infrastructure. This guide explains how hospitals and healthtech teams should design GPU clusters for…
Why AI Servers Are Getting More Expensive
AI server costs are rising at a pace that is breaking procurement plans, budget models, and deployment timelines across the industry. Every layer of…
Blackwell, Hopper, or Wait for Rubin? A Practical Guide to Buying AI Infrastructure in 2026
Buying GPUs in 2026 is no longer about picking the fastest chip on a roadmap. It’s about understanding what you can actually buy, at…
Why Data Sovereignty Matters for AI Workloads in Financial Services
If you’re accountable for AI infrastructure in a regulated financial environment, data sovereignty isn’t an abstract compliance concept—it’s an operational reality that shapes where…
The Hidden Costs of Hyperscaler GPUs in Financial Services
If you’re accountable for AI infrastructure costs and uptime in a regulated financial environment, you’ve likely experienced this pattern: hyperscaler GPU stacks that seemed…
From Overnight Risk to Intraday Decisions: How AI and GPUs Are Reshaping Financial Risk Management
Financial markets are moving faster than the risk infrastructure many institutions still rely on, making delayed risk insight increasingly costly. To keep pace, firms…
Scaling Fraud Detection in 2026: Why GPU Acceleration Is Non-Negotiable for Real-Time Anti-Money Laundering
Fraud detection has crossed a threshold. At global payment scale, financial institutions no longer have minutes to investigate risk. They have milliseconds. Networks like…
The $7 Trillion Reality Check: AI’s Battle Is Concrete, Not Code
AI’s biggest breakthrough won’t be determined by a larger context window or a smarter reasoning engine. It will be determined by who can keep…
The Hidden Crisis in AI Right Now: Server Memory Is In Short Supply – Here’s How to Stay Ahead of It
AI teams are running into a problem the market isn’t built to solve: server memory prices are up more than 300 percent this year thanks to…
Becoming AI Native in High Frequency Trading: Why GPUs Are Now Essential
Even two or three decades ago, high frequency trading was already one of the most technologically advanced and competitive frontiers in finance. Today, it…
Aivres NVIDIA HGX B200 & B300 GPU Servers: Air and Liquid-Cooled Performance at Scale
Today’s AI-driven enterprises and research institutions require more than raw performance. They need scalable, reliable infrastructure that can be deployed fast and operated efficiently.…
Liquid Cooling & Green AI Infrastructure: Designing Sustainable GPU Data Centers
Liquid cooling is becoming the baseline for AI-ready infrastructure. As AI, cloud, and HPC workloads scale, the limits of traditional air cooling are clear.…
The Difference Between NVIDIA HGX B200 vs B300 vs GB300 NVL72
AI infrastructure decisions are defined by scale, efficiency, and readiness for next-generation workloads. As enterprises deploy large language models (LLMs), retrieval-augmented generation (RAG), and…
InfiniBand vs. Ethernet: Choosing the Right Network Fabric for AI Clusters
When scaling an AI cluster for large language models (LLMs), high performance computing (HPC), or enterprise AI, your choice of backend network fabric can…
Cutting Costs and Latency in 4 Weeks: Inside a Trading Firm’s GPU Upgrade
When it comes to building trading infrastructure, the choice between cloud and on-premise GPUs is not just about technology. It’s about speed, cost, and competitive advantage. For real-time…
Should You Wait for NVIDIA B300 or Go with H200 or B200 Now?
UPDATE NVIDIA HGX B300 GPU Servers are now available to order. When it comes to scaling AI infrastructure, deciding whether to wait for the NVIDIA B300 or move ahead with the H200 or B200 isn’t…
5 GPU Infrastructure Challenges We Hear Every Week
Building modern GPU infrastructure isn’t just a technical hurdle. It’s a complex mix of procurement strategy, system design, and long-term planning. Whether leading an…