# Artificial Intelligence, Cloud Computing, Critical Infrastructure, Data and Information Security, Ia

Published articles for Artificial Intelligence, Cloud Computing, Critical Infrastructure, Data and Information Security, Ia.

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## The complicated AI infrastructure market

DevFeed: [The complicated AI infrastructure market](<https://devfeed.tech/articles/the-complicated-ai-infrastructure-market-47833.md>)

Original publisher: [Read original article](<https://www.infoworld.com/article/4221930/the-complicated-ai-infrastructure-market.html>)

Author: David Linthicum

Published: 2026-09-15T09:00:00Z

Content type: article

Language: en

Sources: [InfoWorld](<https://devfeed.tech/sources/infoworld.md>)

Topics: [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [data centers](<https://devfeed.tech/topics/data-centers.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Orchestration](<https://devfeed.tech/topics/orchestration.md>), [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>), [Computing](<https://devfeed.tech/topics/computing.md>)

Tags: [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [artificial-intelligence-cloud-computing-critical-infrastructure-data-and-information-security-ia](<https://devfeed.tech/tags/artificial-intelligence-cloud-computing-critical-infrastructure-data-and-information-security-ia.md>), [cloud-computing](<https://devfeed.tech/tags/cloud-computing.md>), [compute](<https://devfeed.tech/tags/compute.md>), [critical-infrastructure](<https://devfeed.tech/tags/critical-infrastructure.md>), [data-and-information-security](<https://devfeed.tech/tags/data-and-information-security.md>), [data-centers](<https://devfeed.tech/tags/data-centers.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [iaas](<https://devfeed.tech/tags/iaas.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [orchestration](<https://devfeed.tech/tags/orchestration.md>), [security](<https://devfeed.tech/tags/security.md>), [technology](<https://devfeed.tech/tags/technology.md>)

### AI overview

The article examines the emerging neocloud market, describing providers built specifically for AI workloads and distinguishing them from general-purpose hyperscalers. It focuses on the infrastructure required for AI, including GPU clusters, power, cooling, networking, orchestration, and inference services.

### Source excerpt

There is a quiet war happening underneath the AI boom, and most people are not paying attention to the right front. While headlines focus on which model is winning, which startup is raising money, or which chatbot is gaining users, a parallel race is playing out in data centers and corporate boardrooms across the world. The race is for AI infrastructure: the GPU clusters, power contracts, cooling systems, networking fabric, orchestration tools, and inference services that make modern AI actually work. The companies fighting in that race are called neoclouds. Understanding the importance of neoclouds matters for the same reason understanding cloud computing mattered in 2008. The companies that first saw the shift to cloud and positioned themselves around it correctly ended up controlling a massive layer of the technology industry. The same dynamics are playing out in AI infrastructure right now. But the neocloud market is more complicated than it looks. Not all of these companies do the same thing. Grouping them together as if they are all just GPU rental businesses misses the point entirely. The more useful way to understand the space is to recognize that neoclouds are evolving into four distinct categories, each with a different focus, a different customer, and a different role in the AI stack. What a neocloud actually is Before getting into categories, it helps to establish what the term means. A neocloud is a cloud infrastructure provider designed specifically for AI workloads. That sounds simple, but it covers a lot of ground. General-purpose hyperscalers like AWS, Azure, and Google Cloud were engineered to support a wide variety of workloads across many industries. They built architecture around flexibility, breadth of services, and broad enterprise appeal. Neoclouds took a different approach. They built around one mandate: make AI compute as fast, dense, and scalable as possible. That means designing facilities around high power density, integrating fast inter