# AI Factory

AI factories are massive data centers purpose-built for training frontier AI models. US hyperscalers have deployed the largest clusters, though China is rapidly building capacity.

**Measure:** Installed AI Training Compute Clusters

**US & Allies Score:** 8.0/10  
**China Score:** 5.0/10  
**Leader:** US & Allies

## Key Metrics

- **Installed training capacity:** Capacity = (Accelerators installed) × (Average utilization) × (Time online)
- **Cluster power density:** Power Density (kW/rack) drives cooling architecture, floor design, and failure rates

## What matters in this layer

The limiting factors are often mundane: permitting, transformers, chilled water, and network lead times. Operators who can compress these timelines turn capital into compute faster.

### Build velocity

Time from site selection to first training run determines advantage. Standardized designs, supply contracts, and execution discipline compound over repeated builds.

### Operations and reliability

Achieving high utilization requires strong SRE practices, failure recovery, and workload scheduling. Reliability is a strategic capability, not a back‑office concern.

## Recent Developments

### xAI's Colossus Cluster Goes Live
*1 week ago | Infrastructure*

Elon Musk's xAI has brought online the Colossus cluster with 100,000+ H100 GPUs, making it one of the largest AI training installations in the world.

### Meta Plans 2GW Data Center Campus
*2 weeks ago | Expansion*

Meta has announced plans for a 2 gigawatt AI data center campus, representing one of the largest single-site compute deployments ever planned.

### China Builds National AI Compute Network
*3 weeks ago | Strategy*

China is constructing a national network of AI compute centers, pooling resources across state-backed entities to maximize utilization of domestic chips.