# AI Accelerators

The US dominates AI accelerator production through NVIDIA's near-monopoly on training GPUs. Export controls have severely limited China's access to cutting-edge chips, though domestic alternatives are emerging.

**Measure:** Effective FLOPS Production Capacity (Peak x MFU)

**US & Allies Score:** 9.0/10  
**China Score:** 3.0/10  
**Leader:** US & Allies

## Key Metrics

- **Effective compute produced:** Effective FLOPs ≈ (Units shipped) × (Peak FLOPs) × (Realized MFU)
- **System throughput:** Throughput is limited by min(Compute, Memory bandwidth, Interconnect, Power)

## What matters in this layer

Dominance comes from the full stack: architectures, compilers, supply contracts, and the ability to scale systems. Export controls and allocation policies can redirect global compute flows.

### Supply chain coupling

Accelerators are the intersection of leading fabs, advanced packaging, and HBM. A constraint in any upstream layer appears here as shipping delays.

### Software moat

Compilers, kernels, and libraries determine real MFU. Software ecosystems are sticky and convert hardware advantage into durable platform power.

> Below is a first‑principles embedded module that turns “Effective FLOPs produced” into a compact, scroll‑driven comparison.

## Recent Developments

### NVIDIA's H100 Dominates AI Training
*2 days ago | Hardware*

NVIDIA's H100 GPU continues to be the gold standard for large-scale AI model training, with US-based hyperscalers deploying hundreds of thousands of units in their data centers. The company controls over 80% of the AI training chip market.

### Export Controls Limit Chinese Access to Advanced GPUs
*5 days ago | Policy*

US export controls have effectively blocked Chinese entities from acquiring the most advanced AI accelerators, forcing domestic alternatives that lag 2-3 generations behind in performance and efficiency.

### Huawei's Ascend 910C Gains Traction
*1 week ago | Competition*

Despite sanctions, Huawei has developed the Ascend 910C AI accelerator using older process nodes. While performance remains below cutting-edge US chips, domestic adoption is growing among Chinese AI labs.

### NVIDIA Blackwell Architecture Ships
*2 weeks ago | Product Launch*

NVIDIA has begun shipping its next-generation Blackwell architecture GPUs, offering 4x the training performance of H100 for large language models. Demand far exceeds supply.

### Google TPU v5 Powers Gemini Models
*3 weeks ago | Technology*

Google has deployed its fifth-generation Tensor Processing Units (TPUs) across its data centers, optimized specifically for training and serving large language models like Gemini.