A.I. Computing Power Is Splitting the World Into Haves and Have-Nots
Where A.I. Data Centers Are Located
Only 32 nations, mostly in the Northern Hemisphere, have A.I.-specialized data centers.
Last month, Sam Altman, the chief executive of the artificial intelligence company OpenAI, donned a helmet, work boots and a luminescent high-visibility vest to visit the construction site of the company’s new data center project in Texas.
Bigger than New York’s Central Park, the estimated $60 billion project, which has its own natural gas plant, will be one of the most powerful computing hubs ever created when completed as soon as next year.
Around the same time as Mr. Altman’s visit to Texas, Nicolás Wolovick, a computer science professor at the National University of Córdoba in Argentina, was running what counts as one of his country’s most advanced A.I. computing hubs. It was in a converted room at the university, where wires snaked between aging A.I. chips and server computers.
“Everything is becoming more split,” Dr. Wolovick said. “We are losing.”
Artificial intelligence has created a new digital divide, fracturing the world between nations with the computing power for building cutting-edge A.I. systems and those without. The split is influencing geopolitics and global economics, creating new dependencies and prompting a desperate rush to not be excluded from a technology race that could reorder economies, drive scientific discovery and change the way that people live and work.
The biggest beneficiaries by far are the United States, China and the European Union. Those regions host more than half of the world’s most powerful data centers, which are used for developing the most complex A.I. systems, according to data compiled by Oxford University researchers. Only 32 countries, or about 16 percent of nations, have these large facilities filled with microchips and computers, giving them what is known in industry parlance as “compute power.”
The United States and China, which dominate the tech world, have particular influence. American and Chinese companies operate more than 90 percent of the data centers that other companies and institutions use for A.I. work, according to the Oxford data and other research.
In contrast, Africa and South America have almost no A.I. computing hubs, while India has at least five and Japan at least four, according to the Oxford data. More than 150 countries have nothing.
Today’s A.I. data centers dwarf their predecessors, which powered simpler tasks like email and video streaming. Vast, power-hungry and packed with powerful chips, these hubs cost billions to build and require infrastructure that not every country can provide. With ownership concentrated among a few tech giants, the effects of the gap between those with such computing power and those without it are already playing out.
The world’s most used A.I. systems, which power chatbots like OpenAI’s ChatGPT, are more proficient and accurate in English and Chinese, languages spoken in the countries where the compute power is concentrated. Tech giants with access to the top equipment are using A.I. to process data, automate tasks and develop new services. Scientific breakthroughs, including drug discovery and gene editing, rely on powerful computers. A.I.-powered weapons are making their way onto battlefields.
Nations with little or no A.I. compute power are running into limits in scientific work, in the growth of young companies and in talent retention. Some officials have become alarmed by how the need for computing resources has made them beholden to foreign corporations and governments.
“Oil-producing countries have had an oversized influence on international affairs; in an A.I.-powered near future, compute producers could have something similar since they control access to a critical resource,” said Vili Lehdonvirta, an Oxford professor who conducted the research on A.I. data centers with his colleagues Zoe Jay Hawkins and Boxi Wu.
A.I. computing power is so precious that the components in data centers, such as microchips, have become a crucial part of foreign and trade policies for China and the United States, which are jockeying for influence in the Persian Gulf, in Southeast Asia and elsewhere. At the same time, some countries are beginning to pour public funds into A.I. infrastructure, aiming for more control over their technological futures.
The Oxford researchers mapped the world’s A.I. data centers, information that companies and governments often keep secret. To create a representative sample, they went through the customer websites of nine of the world’s biggest cloud-service providers to see what compute power was available and where their hubs were at the end of last year. The companies were the U.S. firms Amazon, Google and Microsoft; China’s Tencent, Alibaba and Huawei; and Europe’s Exoscale, Hetzner and OVHcloud.
computing power is highlighted by the dominance of U.S. chipmaker Nvidia in supplying most of the chips used in data centers for making calculations. The rise of computing power has divided the world into two factions: those reliant on China and those dependent on the United States. These two nations not only dominate the data center market but are also leading the way in building new facilities. They have leveraged their technological prowess to exert influence on a global scale.
The Biden and Trump administrations have used trade restrictions to control the flow of powerful A.I. chips, effectively picking winners in the industry. On the other hand, China has used state-backed loans to promote the sales of its networking equipment and data centers. The effects of this power struggle are evident in regions like Southeast Asia and the Middle East.
In Southeast Asia, companies from both China and the U.S. are establishing data centers to provide services across the region. Despite China’s efforts to produce competing chips, most of the data centers operated by Chinese firms outside their home country use chips from Nvidia, a U.S. company. The U.S. currently leads in this race, with American companies building more A.I. computing hubs globally compared to China.
Even U.S.-friendly countries like Kenya have been left out of the A.I. race due to trade restrictions. This has provided China with an opportunity to expand its influence, despite experts considering its A.I. chips to be less advanced. In Africa, countries are exploring partnerships with companies like Huawei to incorporate Chinese-made chips in their data centers.
To close the gap, many countries are taking steps to develop their own sovereign A.I. capabilities. India is subsidizing compute power and language-specific A.I. models, while Africa is discussing collaborations on regional compute hubs. Brazil has pledged a significant investment in A.I. projects to reduce reliance on foreign technology.
European countries are also concerned about their dependence on American companies for data centers. The European Union has outlined plans to invest in A.I. projects, including new data centers across the bloc. European businesses are looking to reduce their reliance on U.S. tech companies, although this transition will take time.
Ultimately, bridging the gap in A.I. capabilities will require collaboration between countries like the United States and China. Companies like Cassava in Africa are taking steps to build advanced data centers and address the region’s demand for A.I. technology. It is crucial for regions like Africa to focus on developing their own A.I. sovereignty to avoid being left behind in this global competition. following sentence:
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