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A.I. Computing Power Is Splitting the World Into Haves and Have-Nots

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A.I. Computing Power Is Splitting the World Into Haves and Have-Nots

Where A.I. Data Centers Are Located

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Only 32 nations, mostly in the Northern Hemisphere, have A.I.-specialized data centers.

Source: Oxford University

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Note: Count of data centers in China excludes facilities in Hong Kong and Taiwan.

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.

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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.”

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Nicolás Wolovick, a computer science professor at the National University of Cordoba in Argentina. “We are losing,” he said.

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Sarah Pabst for The New York Times

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.

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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.

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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.

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Mr. Wolovick runs one of Argentina’s most advanced A.I. computing hubs out of a converted classroom at his university.

Video by Sarah Pabst for The New York Times

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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.

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“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.

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The research does not include every data center worldwide, but the trends were unmistakable. U.S. companies operated 87 A.I. computing hubs, which can sometimes include multiple data centers, or almost two-thirds of the global total, compared with 39 operated by Chinese firms and six by Europeans, according to the research. Inside the data centers, most of the chips — the foundational components for making calculations — were from the U.S. chipmaker Nvidia.

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An Nvidia H100 graphics processing unit.

Marlena Sloss/Bloomberg

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“We have a computing divide at the heart of the A.I. revolution,” said Lacina Koné, the director general of Smart Africa, which coordinates digital policy across the continent. He added: “It’s not merely a hardware problem. It’s the sovereignty of our digital future.”

‘Sometimes I Want to Cry’

There has long been a tech gap between rich and developing countries. Over the past decade, cheap smartphones, expanding internet coverage and flourishing app-based businesses led some experts to conclude that the divide was diminishing. Last year, 68 percent of the world’s population used the internet, up from 33 percent in 2012, according to the International Telecommunication Union, a United Nations agency.

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With a computer and knowledge of coding, getting a company off the ground became cheaper and easier. That lifted tech industries across the world, be they mobile payments in Africa or ride hailing in Southeast Asia.

But in April, the U.N. warned that the digital gap would widen without action on A.I. Just 100 companies, mostly in the United States and China, were behind 40 percent of global investment in the technology, the U.N. said. The biggest tech companies, it added, were “gaining control over the technology’s future.”

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Few Companies Control A.I. Computing

Tiles show total availability zones for A.I. offered by each company, a metric used by researchers as a proxy for A.I. data centers.

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Source: Oxford University

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The gap stems partly from a component everyone wants: a microchip known as a graphics processing unit, or GPU. The chips require multibillion-dollar factories to produce. Packed into data centers by the thousands and mostly made by Nvidia, GPUs provide the computing power for creating and delivering cutting-edge A.I. models.

Obtaining these pieces of silicon is difficult. As demand has increased, prices for the chips have soared, and everyone wants to be at the front of the line for orders. Adding to the challenges, these chips then need to be corralled into giant data centers that guzzle up dizzying amounts of power and water.

Many wealthy nations have access to the chips in data centers, but other countries are being left behind, according to interviews with more than two dozen tech executives and experts across 20 countries. Renting computing power from faraway data centers is common but can lead to challenges, including high costs, slower connection speeds, compliance with different laws, and vulnerability to the whims of American and Chinese companies.

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Qhala, a start-up in Kenya, illustrates the issues. The company, founded by a former Google engineer, is building an A.I. system known as a large language model that is based on African languages. But Qhala has no nearby computing power and rents from data centers outside Africa. Employees cram their work into the morning, when most American programmers are sleeping, so there is less traffic and faster speeds to transfer data across the world.

“Proximity is essential,” said Shikoh Gitau, 44, Qhala’s founder.

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“If you don’t have the resources for compute to process the data and to build your A.I. models, then you can’t go anywhere,” said Kate Kallot, a former Nvidia executive and the founder of Amini, another A.I. start-up in Kenya.

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Kate Kallot, founder of Amini, an A.I. start-up, at the company’s office in Nairobi, Kenya.

Natalia Jidovanu for The New York Times

In the United States, by contrast, Amazon, Microsoft, Google, Meta and OpenAI have pledged to spend more than $300 billion this year, much of it on A.I. infrastructure. The expenditure approaches Canada’s national budget. Harvard’s Kempner Institute, which focuses on A.I., has more computing power than all African-owned facilities on that continent combined, according to one survey of the world’s largest supercomputers.

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Brad Smith, Microsoft’s president, said many countries wanted more computing infrastructure as a form of sovereignty. But closing the gap will be difficult, particularly in Africa, where many places do not have reliable electricity, he said. Microsoft, which is building a data center in Kenya with a company in the United Arab Emirates, G42, chooses data center locations based largely on market need, electricity and skilled labor.

“The A.I. era runs the risk of leaving Africa even further behind,” Mr. Smith said.

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Jay Puri, Nvidia’s executive vice president for global business, said the company was also working with various countries to build out their A.I. offerings.

“It is absolutely a challenge,” he said.

Chris Lehane, OpenAI’s vice president of global affairs, said the company had started a program to adapt its products for local needs and languages. A risk of the A.I. divide, he said, is that “the benefits don’t get broadly distributed, they don’t get democratized.”

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Tencent, Alibaba, Huawei, Google, Amazon, Hetzner and OVHcloud declined to comment.

The gap has led to brain drains. In Argentina, Dr. Wolovick, 51, the computer science professor, cannot offer much compute power. His top students regularly leave for the United States or Europe, where they can get access to GPUs, he said.

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“Sometimes I want to cry, but I don’t give up,” he said. “I keep talking to people and saying: ‘I need more GPUs. I need more GPUs.’”

Few Choices

The uneven distribution of A.I. computing power has split the world into two camps: nations that rely on China and those that depend on the United States.

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The two countries not only control the most data centers but are set to build more than others by far. And they have wielded their tech advantage to exert influence. The Biden and Trump administrations have used trade restrictions to control which countries can buy powerful A.I. chips, allowing the United States to pick winners. China has used state-backed loans to encourage sales of its companies’ networking equipment and data centers.

The effects are evident in Southeast Asia and the Middle East.

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In the 2010s, Chinese companies made inroads into the tech infrastructure of Saudi Arabia and the Emirates, which are key American partners, with official visits and generous financing. The United States sought to use its A.I. lead to push back. In one deal with the Biden administration, an Emirati company promised to keep out Chinese technology in exchange for access to A.I. technology from Nvidia and Microsoft.

In May, President Trump signed additional deals to give Saudi Arabia and the Emirates even more access to American chips.

A similar jostling is taking place in Southeast Asia. Chinese and U.S. companies like Amazon, Alibaba, Nvidia, Google and ByteDance, the owner of TikTok, are building data centers in Singapore and Malaysia to deliver services across Asia.

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Globally, the United States has the lead, with American companies building 63 A.I computing hubs outside the country’s borders, compared with 19 by China, according to the Oxford data. All but three of the data centers operated by Chinese firms outside their home country use chips from Nvidia, despite efforts by China to produce competing chips. Chinese firms were able to buy Nvidia chips before U.S. government restrictions.

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Where the World Gets Its A.I.

Companies and countries throughout the world rely mostly on major American and Chinese cloud operators for A.I. facilities.

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Source: Oxford University

Even U.S.-friendly countries have been left out of the A.I. race by trade limits. Last year, William Ruto, Kenya’s president, visited Washington for a state dinner hosted by President Joseph R. Biden Jr. Several months later, Kenya was omitted from a list of countries that had open access to needed semiconductors.

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That has given China an opening, even though experts consider the country’s A.I. chips to be less advanced. In Africa, policymakers are talking with Huawei, which is developing its own A.I. chips, about converting existing data centers to include Chinese-made chips, said Mr. Koné of Smart Africa.

“Africa will strike a deal with whoever can give access to GPUs,” he said.

If You Build It

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An aerial view of the construction underway on an A.I. infrastructure site that is a collaboration between OpenAI, SoftBank, and Oracle in Abilene, Texas.

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Daniel Cole/Reuters

Alarmed by the concentration of A.I. power, many countries and regions are trying to close the gap. They are providing access to land and cheaper energy, fast-tracking development permits and using public funds and other resources to acquire chips and construct data centers. The goal is to create “sovereign A.I.” available to local businesses and institutions.

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In India, the government is subsidizing compute power and the creation of an A.I. model proficient in the country’s languages. In Africa, governments are discussing collaborating on regional compute hubs. Brazil has pledged $4 billion on A.I. projects.

“Instead of waiting for A.I. to come from China, the U.S., South Korea, Japan, why not have our own?” Brazil’s president, Luiz Inácio Lula da Silva, said last year when he proposed the investment plan.

Even in Europe, there is growing concern that American companies control most of the data centers. In February, the European Union outlined plans to invest 200 billion euros for A.I. projects, including new data centers across the 27-nation bloc.

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Mathias Nobauer, the chief executive of Exoscale, a cloud computing provider in Switzerland, said many European businesses want to reduce their reliance on U.S. tech companies. Such a change will take time and “doesn’t happen overnight,” he said.

Still, closing the divide is likely to require help from the United States or China.

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Cassava, a tech company founded by a Zimbabwean billionaire, Strive Masiyiwa, is scheduled to open one of Africa’s most advanced data centers this summer. The plans, three years in the making, culminated in an October meeting in California between Cassava executives and Jensen Huang, Nvidia’s chief executive, to buy hundreds of his company’s chips. Google is also one of Cassava’s investors.

The data center is part of a $500 million effort to build five such facilities across Africa. Even so, Cassava expects it to address only 10 percent to 20 percent of the region’s demand for A.I. At least 3,000 start-ups have expressed interest in using the computing systems.

“I don’t think Africa can afford to outsource this A.I. sovereignty to others,” said Hardy Pemhiwa, Cassava’s chief executive. “We absolutely have to focus on and ensure that we don’t get left behind.”

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Indian truckers sue California’s DMV for revoking their licenses

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Indian truckers sue California’s DMV for revoking their licenses

Immigrant truck drivers have sued the California Department of Motor Vehicles for terminating the commercial driver’s licenses of thousands of drivers, alleging that the decision violated their rights and threatened their livelihood.

California’s DMV gave a 60-day cancellation notice to 17,000 drivers on Nov. 6 after a federal audit found the licenses issued to immigrant drivers were set to expire after the time they were legally allowed to remain in the U.S.

In the event of such clerical errors by the DMV, the suit alleges, California law requires the DMV to change the expiration of its own accord or to allow applicants to reapply for a corrected license.

“The state of California must help these 20,000 drivers because, at the end of the day, the clerical errors threatening their livelihoods are of the CA-DMV’s own making,” said Munmeeth Kaur, legal director of the Sikh Coalition, a group fighting for the civil rights of Sikhs.

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The Sikh Coalition and Asian Law Caucus filed the class-action lawsuit on behalf of five commercial driver’s license holders, challenging the DMV’s decision to revoke licenses.

Since November, the number of cancellation notifications has grown to more than 20,000.

“If the court does not issue a stay, we will see a devastating wave of unemployment that harms individual families, as well as the destabilization of supply chains on which we all rely,” said Kaur.

The Sikh Coalition also noted that the action was taken under pressure from the federal government. It said the California DMV has failed to provide recourse, and informed applicants that it’s not issuing or renewing non-resident commercial driver’s licenses.

Punjabi Sikh truckers have emerged as a pillar of the American trucking industry. For years, many have sought asylum in the U.S. and entered the transportation industry.

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There are around 750,000 Punjabi Sikhs in the United States. Of those, about 150,000 work in the trucking industry, with the majority based on the West Coast.

The issue of immigrant truckers became a political flash point earlier this year, when a Punjabi Sikh driver took an illegal U-turn at a turnpike that caused a crash in Florida that killed three people. The Trump administration swung into action and found seven states, including California, Washington and Texas, that had lax licensing rules.

The crackdown has caused a wave of racism and racial profiling of Sikh truckers, many of whom sport turbans and beards as symbols of their faith, which is neither Hindu nor Muslim.

Secretary of Transportation Sean Duffy singled out California for issuing commercial driver’s licenses to what his department says are unqualified immigrant truckers that put lives on the road in danger. Many truckers quit the industry after the introduction of enhanced English proficiency tests, where highway inspectors check for language proficiency and highway traffic sign competency.

Policy changes regarding noncitizen commercial licenses and English-language proficiency enforcement could remove more than 400,000 commercial drivers from the market over the next three years, according to J.B. Hunt, one of the largest trucking companies.

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Commentary: The latest government inflation and GDP figures are worthless, and will be for months to come

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Commentary: The latest government inflation and GDP figures are worthless, and will be for months to come

The federal government’s monthly releases of economic statistics — especially the inflation rate and growth as tracked by gross domestic product — have long occasioned partisan preening (or denunciation) and for a general public stock-taking of the health of the economy.

Not this month. This time, they’re the occasion for doubt and confusion.

On Dec. 18, the Bureau of Labor Statistics reported that inflation had fallen to an annual rate of 2.7% in November, down from 3% in September and well below the 3.1% consensus of economists. And on Tuesday, the Bureau of Economic Analysis reported that real gross domestic product had shot up by a surprising 4.3% annual rate in the third quarter of 2025 ended Sept. 30.

The numbers give you meaningful information about the system, but not about how people experience their actual lives.

— Zachary Karabell

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Unsurprisingly, the Trump administration and its Republican acolytes seized on the figures to boast about Trump’s economic policies. White House economic advisor Kevin Hassett proclaimed the inflation figure to be “an absolute blockbuster report.” He described the GDP figure as “a great Christmas present for the American people.”

“America is winning again,” crowed House Speaker Mike Johnson (R-La.) after the GDP report. He called it “the direct result of congressional Republicans and President Trump delivering policies that drive growth and expand opportunity for American families and workers.”

Um, not so fast.

The economists whose jobs involve scrutinizing those statistics to glean what they really mean don’t view them as unalloyed support for Trumponomics. Quite the contrary. Many see them as artifacts of the long government shutdown, which halted the collection of data that go into those reports, severely distorting the results. Furthermore, they expect the flaws in those reports to persist well into 2026, undermining their usefulness as true economic indicators.

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“You’ve got to take it with a grain of salt,” said Diane Swonk, chief economist at KPMG US, of the inflation report. “It’s confusing and it doesn’t quite square with prices that we’ve observed.”

A close examination of the GDP figures also underscores the narrow basis driving economic growth in recent months — it’s essentially the product of robust spending by wealthy consumers and massive corporate investments in AI technology. For middle- and lower-income Americans, the economic present and future don’t look anywhere as sunny as the numbers would suggest.

“The numbers give you meaningful information about the system, but not about how people experience their actual lives,” says financial analyst and economic commentator Zachary Karabell, whose 2014 book “The Leading Indicators” injected some perspective on how we interpret economic statistics and explained why our faith in them is often misplaced.

Indeed, consumer confidence has been sinking for months, according to the Conference Board. That points to an enduring question about the U.S. economy: Whose economy is it?

More than ever, it belongs to the rich, producing a “K-shaped” economy, which has been playing out in shopping patterns this holiday season, as my colleague Caroline Petrow-Cohen recently wrote.

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According to Bank of America analysts, since this spring, spending by the highest-earning third of Americans has been soaring, while that of middle- and lower-income households has stagnated. In part that’s because the stock market has remained vibrant.

Since the top 20% of households as measured by income own about 87% of directly-held equities, stock market gains “tend to disproportionately benefit the higher-income cohort,” the BofA analysts noted. By contrast, “almost 30% of lower-income households appear to be living ‘paycheck to paycheck.’”

The highest-earning 10% of households now account for nearly half of all consumer spending, according to Moody’s Analytics. That’s the highest level since the data began to be collected in the 1980s, when the rich accounted for only about one-third of spending.

Job growth may already have turned negative, even if the published employment figures don’t yet show it, Federal Reserve Chairman Jerome Powell acknowledged during a Dec. 10 news conference following the Fed’s decision to lower interest rates by 0.25 percentage points.

Non-farm payroll gains have averaged about 40,000 a month since April, Powell observed. “We think there’s an overstatement in these numbers by about 60,000,” he said. “So that would be negative 20,000 per month.”

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The divergence between the gross economic statistics and the lived experience of Americans is nothing new. It was remarked on by Robert F. Kennedy Sr. in a speech in March 1968, less than three months before his nascent presidential campaign was ended by an assassin’s bullet.

“Gross national product counts air pollution and cigarette advertising, and ambulances to clear our highways of carnage,” he observed. “It counts special locks for our doors and the jails for the people who break them. It counts the destruction of the redwood and the loss of our natural wonder in chaotic sprawl. It counts napalm and counts nuclear warheads and armored cars for the police to fight the riots in our cities. … Yet the gross national product does not allow for the health of our children, the quality of their education or the joy of their play. … It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion to our country, it measures everything in short, except that which makes life worthwhile.”

That brings us to the specific flaws in the latest statistics.

The government shutdown, which lasted 43 days from Oct. 1 to Nov. 12, was the most important cause of gaps in the collected data for the consumer price index calculation. As Swonk noted in a social media post, cutbacks at the BLS had already reduced the staff assigned to sampling prices by 25%. That prompted the agency to substitute “imputed” numbers for hard data.

“Those cases can show up as zeros in the percent change of the release,” Swonk wrote — obviously lowering the bottom-line figure. A sampling scheduled for mid-October had to be canceled, so figures dating from August were used instead — concealing any price increases in subsequent months.

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A major problem concerns housing costs, which account for about one-third of the data inputs for the CPI. Because the BLS was unable to collect rental data for October, it implied that the monthly change in rents was 0% in October — further skewing the reported CPI lower. Experts say it will take at least six months to use newly collected data to provide a reliable estimate of housing inflation.

The delay in sampling, Swonk adds, means that some seasonal price phenomena were missed. She points specifically to airfares — the originally scheduled sampling would have incorporated a pre-Thanksgiving run-up in fares, but by the time the data were collected fares had returned to a non-holiday level.

Inflation data also are incorporated into GDP estimates — the lower the inflation rate, Swonk notes, the better the GDP looks. An artificially reduced inflation rate will translate into higher reported GDP growth.

All this might have a limited economic impact — corporations, banks and academic economists generally have sources other than the government to reach their conclusions — if not for the partisan political exploitation of the numbers.

As Karabell reported in his 2014 book, Simon Kuznets, the government statistician who helped to codify the collection of government figures in the 1930s, was concerned about how politics would give the statistics a misleading social significance.

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“These numbers have turned into absolute markets of the human condition,” Karabell wrote, “when they are simply statistical descriptions of specific systems.”

Economists have warned that some economic factors haven’t yet fully played out. That includes Trump’s tariffs, which in their execution have been lower than they appeared on the surface, and higher healthcare premiums, which have been forecast or announced but won’t actually become effective until 2026.

If the job market continues to weaken, that will show up more vividly in 2026. The interplay between “a surging economy and a soft labor market,” argues Joseph Brusuelas, chief economist at the business consulting firm RSM, “is likely to be the major economic narrative next year.”

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California crypto company accused of illegally inflating Katy Perry NFTs and fraud

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California crypto company accused of illegally inflating Katy Perry NFTs and fraud

Four years ago, California startup Theta Labs’ cryptocurrency was soaring, and its future appeared bright when it landed a partnership with pop star Katy Perry.

The Bay Area company had built a marketplace for digital collectibles known as nonfungible tokens, or NFTs, and had teamed up with Perry to launch NFTs tied to her Las Vegas concert residency. Its THETA token jumped by more than 500% in early 2021, reaching a peak of more than $15, making it one of the world’s most valuable cryptocurrencies. Later in the year, the spotlight shone on the company when it announced the Perry partnership.

“I can’t wait to dive in with the Theta team on all the exciting and memorable creative pieces, so my fans can own a special moment of my residency,” Perry said in a June 2021 news release.

Today, like many cryptocurrencies, THETA is 95% off its 2021 peak. It took a hit this week after former executives accused it of manipulating markets to dupe consumers into buying its products. On Tuesday, it was trading at less than 30 cents.

Two former executives from Theta Labs sued the startup, alleging in separate lawsuits that the company and its chief executive, Mitch Liu, engaged in fraud and manipulated the cryptocurrency market for his benefit. Liu retaliated against them after the employees refused to engage in deceptive business practices and raised concerns, the lawsuits say.

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Some of the alleged misconduct involved placing fake bids on Perry’s NFTs, engaging in token “pump and dump” schemes and using celebrity endorsements and “misleading” partnerships with high-profile companies such as Google to deceive the public, according to the December lawsuits filed in Los Angeles Superior Court.

Perry is not accused of any wrongdoing in the suit, and Theta denies the charges.

The lawsuits against Theta Labs are the latest controversy to rattle an industry beset by scandals.

Cryptocurrency exchange FTX collapsed, and its founder, Samuel Bankman-Fried, was sentenced to 25 years in prison in 2024 after being found guilty of multiple fraud charges. Binance founder and former Chief Executive Changpeng Zhao also got prison time after he pleaded guilty to violating money laundering laws, but President Trump pardoned him this year.

The U.S. Securities and Exchange Commission previously charged celebrities such as Kim Kardashian, Lindsay Lohan, Jake Paul and Ne-Yo for promoting crypto without disclosing they were paid to do so.

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Theta Labs created a network that rewarded people with cryptocurrency for contributing spare bandwidth and computing power to enhance video streaming and lower content delivery costs. The company describes Theta Network as a “blockchain-powered decentralized cloud for AI, media and entertainment.” The network has two tokens: THETA, used to secure the network, and TFUEL, used to pay users for services and power operations.

The whistleblowers suing Theta Labs are Jerry Kowal, its former head of content, and Andrea Berry, previously the company’s head of business development.

“Liu used Theta Labs as his personal trading vehicle, perpetrating fraud, self-dealing, and market manipulation,” said Mark Mermelstein, Kowal’s attorney, in a statement. “His calculated ‘pump-and-dump’ schemes repeatedly wiped out employee and investor value. This suit is about demanding accountability and proving no one is above the law.”

Theta, Liu and its parent company, Sliver VR Technologies, deny the allegations and “intend to prove with evidence the fallacy of the stories being told in the lawsuits,” according to Kronenberger Rosenfeld, the law firm representing the defendants. The lawsuits are an attempt to paint the company in a negative light in hopes of securing a settlement, a lawyer for the firm said.

Kowal has sued his former employers before. In 2014, he accused Netflix of spreading false claims that he stole confidential information and Amazon of wrongful termination.

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The latest lawsuits allege that Liu profited from buying and selling THETA tokens using insider knowledge about partnerships with celebrities, studios and others in the entertainment industry.

“Liu’s true motive in pursuing such partnerships was not to develop a sustainable content business but to generate publicity that could be used to artificially inflate token prices for Liu’s personal gain,” Kowal’s lawsuit says.

Kowal worked for Theta from 2020 to 2025.

In 2020, Liu traded and sold tokens knowing that the company would close a content licensing deal with MGM Studios, according to the lawsuit. After the deal’s announcement, THETA token’s market capitalization increased by more than $50 million in just 24 hours, the lawsuit says.

When NFTs started to take off in 2021, Kowal closed deals with high-profile partners such as Perry, Fremantle Media and Resorts World Las Vegas for the startup’s NFT marketplace.

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As part of the deal with Perry, the singer received $8.5 million and additional warrants for the right to license her image and likeness for the NFTs.

To inflate the price and demand for these digital collectibles, Liu allegedly made bids on NFTs and directed employees to do the same. This led to people overpaying for the Perry NFTs.

Representatives for Perry didn’t immediately respond to a request for comment.

Multiple examples of alleged manipulation are outlined in the lawsuits. In one instance from 2022, the startup launched a new token called TDROP that employees also received as part of a bonus.

Liu gained control of 43% of the supply of the cryptocurrency, according to Kowal’s lawsuit. When the TDROP token reached a high, he then sold the token, and its price collapsed by more than 90% within months.

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Berry’s lawsuit also alleges that Theta Labs announced “misleading” or fake partnerships with high-profile companies such as Google and entities including NASA to pump up the value of the THETA token. Theta paid for Google Cloud products but claimed it was a partner when it was a Google customer, according to the lawsuit.

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