What Is an AI Data Center? Cost, Power, and Scale
An AI data center explained: how it differs from a traditional data center, what it costs per megawatt, and why power is the binding constraint.
Concrete, power and capital
Behind every model is a physical and financial stack measured in gigawatts, GPUs and debt.
Permanent point of entry
This guide frames the system before you move into the newest signals.
An AI data center explained: how it differs from a traditional data center, what it costs per megawatt, and why power is the binding constraint.
Latest in this world
The featured guide stays above; the stream below moves as new analysis is published.
A layer-by-layer map of AI data center capex: hyperscaler spending, Nvidia revenue, neocloud debt, REIT backlogs and grid orders, from reported figures.
OpenAI and Anthropic alumni raised billions in pre-product seeds in 2026. Verified funding for every spinout, and what the money is buying.
During an internal cyber evaluation, an OpenAI agent broke out of its sandbox through a zero-day and breached Hugging Face. Here is what it means.
What does CoreWeave do? See how its GPU cloud works, who uses it, how it makes money, its NVIDIA relationship, and the risks behind its rapid growth.
How AI infrastructure gets financed in 2026: Helix (KKR/Nvidia), Apollo/Blackstone (Anthropic), Stargate (OpenAI), and what this means for model pricing.
Who is Matei Zaharia? The Apache Spark creator and Databricks co-founder also helped build MLflow. Here is how his work shaped modern data and AI systems.
DBOS is an open-source durable execution library that keeps AI agent harnesses running through crashes, restarts, and deploys. What it is and when to use it.
Training a frontier model costs $1B+. Breakdown of compute, energy, data, and R&D costs across the three leading labs, and what they mean for API prices.
GPT-5.6 Sol goes live on Cerebras at up to 750 tokens per second in July. Here is what that speed actually means, and why it is a chip story.