Visualizing the World’s AI Computing Hubs
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Key Takeaways
- Only 33 nations worldwide host data centers capable of training or inferencing AI, with just 24 having “training-relevant” AI compute needed for advanced models.
- In a cloud region with AI accelerators, interconnected data centers house specialized AI chips such as Nvidia GPUs.
- The U.S. and China/Hong Kong lead globally in AI compute by a significant margin.
Today, global AI computing resources are clearly concentrated in the U.S. and China.
Together, the two countries host 50 of the world’s 132 AI accelerator-enabled cloud regions. Given rising demand for AI systems, several countries are ramping up investment in local AI infrastructure, much of this in partnership with Nvidia.
This graphic shows AI computing hubs by country, based on data from the University of Oxford.
Ranked: AI Computing Clusters by Country
Below, we show the number of AI accelerator-enabled cloud regions by country:
Country | Number of AI Accelerator-enabled Cloud Regions |
---|---|
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26 |
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24 |
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7 |
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6 |
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5 |
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5 |
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5 |
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5 |
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4 |
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4 |
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4 |
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4 |
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4 |
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3 |
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3 |
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2 |
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2 |
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2 |
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2 |
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2 |
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2 |
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1 |
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1 |
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1 |
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1 |
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1 |
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1 |
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1 |
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1 |
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1 |
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1 |
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1 |
Today, the U.S. and China are the only countries globally with AI accelerators—specialized chips like Nvidia GPUs—from domestic suppliers.
In fact, over 95% of the world’s AI accelerators are powered by U.S. chipmakers.
As a result “compute sovereignty” is highly uneven globally, with the vast majority of nations having no AI infrastructure at all. More recently, the European Commission slotted $23 billion for creating five AI gigafactories. Meanwhile, the UAE is investing $1.4 trillion in AI infrastructure to drive economic transformation.
Overall, Nvidia says that 20 countries so far are expressing interest in AI sovereignty initiatives, including France, Germany, and Indonesia.
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To learn more about this topic from a revenue perspective, check out this graphic on how Nvidia makes its billions.
