SEOUL, SOUTH KOREA — When Chinese startup DeepSeek released its AI model this month, it was hailed as a breakthrough, a sign that China’s artificial intelligence companies could compete with their Silicon Valley counterparts using fewer resources.

The narrative was clear: DeepSeek had done more with less, finding clever workarounds to U.S. chip restrictions. However, that storyline has begun to shift.

OpenAI, the U.S.-based company behind ChatGPT, now claims DeepSeek may have improperly used its proprietary data to train its model, raising questions about whether DeepSeek’s success was truly an engineering marvel.

In statements to several media outlets this week, OpenAI said it is reviewing indications that DeepSeek may have trained its AI by mimicking responses from OpenAI’s models.

The process, known as distillation, is common among AI developers but is prohibited by OpenAI’s terms of service, which forbid using its model outputs to train competing systems.

Some U.S. officials appear to support OpenAI’s concerns. At his confirmation hearing this week, Commerce secretary nominee Howard Lutnick accused DeepSeek of misusing U.S. technology to create a “dirt cheap” AI model.

“They stole things. They broke in. They’ve taken our IP,” Lutnick said of China.

David Sacks, the White House czar for AI and cryptocurrency, was more measured, saying only that it is “possible” that DeepSeek had stolen U.S. intellectual property.

In an interview with the cable news network Fox News, Sacks added that there is “substantial evidence” that DeepSeek “distilled the knowledge out of OpenAI’s models,” adding that stronger efforts are needed to curb the rise of “copycat” AI systems.

At the center of the dispute is a key question about AI’s future: how much control should companies have over their own AI models, when those programs were themselves built using data taken from others?

AI data fight

The question is especially relevant for OpenAI, which faces its own legal challenges. The company has been sued by several media companies and authors who accuse it of illegally using copyrighted material to train its AI models.

Justin Hughes, a Loyola Law School professor specializing in intellectual property, AI, and data rights, said OpenAI’s accusations against DeepSeek are “deeply ironic,” given the company’s own legal troubles.

“OpenAI has had no problem taking everyone else’s content and claiming it’s ‘fair,'” Hughes told VOA in an email.

“If the reports are accurate that OpenAI violated other platforms’ terms of service to get the training data it has wanted, that would just add an extra layer of irony – dare we say hypocrisy – to OpenAI complaining about DeepSeek.”

DeepSeek has not responded to OpenAI’s accusations. In a technical paper released with its new chatbot, DeepSeek acknowledged that some of its models were trained alongside other open-source models – such as Qwen, developed by China’s Alibaba, and Llama, released by Meta – according to Johnny Zou, a Hong Kong-based AI investment specialist.

However, OpenAI appears to be alleging that DeepSeek improperly used its closed-source models – which cannot be freely accessed or used to train other AI systems.

“It’s quite a serious statement,” said Zou, who noted that OpenAI has not yet presented evidence of wrongdoing by DeepSeek.

Proving improper distillation may be difficult without disclosing details on how its own models were trained, Zou added.

Even if OpenAI presents concrete proof, its legal options may be limited. Although Zou noted that the company could pursue a case against DeepSeek for violating its terms of service, not all experts believe such a claim would hold up in court.

“Even assuming DeepSeek trained on OpenAI’s data, I don’t think OpenAI has much of a case,” said Mark Lemley, a professor at Stanford Law School who specializes in intellectual property and technology.

Even though AI models often have restrictive terms of service, “no model creator has actually tried to enforce these terms with monetary penalties or injunctive relief,” Lemley wrote in a recent paper with co-author Peter Henderson.

The paper argues that these restrictions may be unenforceable, since the materials they aim to protect are “largely not copyrightable.”

“There are compelling reasons for many of these provisions to be unenforceable: they chill good faith research, constrain competition, and create quasi-copyright ownership where none should exist,” the paper noted.

OpenAI’s main legal argument would likely be breach of contract, said Hughes. Even if that were the case, though, he added, “good luck enforcing that against a Chinese company without meaningful assets in the United States.”

Possible options

The financial stakes are adding urgency to the debate. U.S. tech stocks dipped Monday after following news of DeepSeek’s advances, though they later regained some ground.

Commerce nominee Lutnick suggested that further government action, including tariffs, could be used to deter China from copying advanced AI models.

But speaking the same day, U.S. President Donald Trump appeared to take a different view, surprising some industry insiders with an optimistic take on DeepSeek’s breakthrough.

The Chinese company’s low-cost model, Trump said, was “very much a positive development” for AI, because “instead of spending billions and billions, you’ll spend less, and you’ll come up with hopefully the same solution.”

If DeepSeek has succeeded in building a relatively cheap and competitive AI model, that may be bad for those with investment – or stock options – in current generative AI companies, Hughes said.

“But it might be good for the rest of us,” he added, noting that until recently it appeared that only the existing tech giants “had the resources to play in the generative AI sandbox.”

“If DeepSeek disproved that, we should hope that what can be done by a team of engineers in China can be done by a similarly resourced team of engineers in Detroit or Denver or Boston,” he said. 
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Days after Chinese upstart DeepSeek revealed a breakthrough in cheap AI computing that shook the U.S. technology industry, the chief executives of Microsoft and Meta defended massive spending that they said was key to staying competitive in the new field.

DeepSeek’s quick progress has stirred doubts about the lead America has in AI with models that it claims can match or even outperform Western rivals at a fraction of the cost, but the U.S. executives said on Wednesday that building huge computer networks was necessary to serve growing corporate needs.

“Investing ‘very heavily’ in capital expenditure and infrastructure is going to be a strategic advantage over time,” Meta CEO Mark Zuckerberg said on a post-earnings call.

Satya Nadella, CEO of Microsoft, said the spending was needed to overcome the capacity constraints that have hampered the technology giant’s ability to capitalize on AI.

“As AI becomes more efficient and accessible, we will see exponentially more demand,” he said on a call with analysts.

Microsoft has earmarked $80 billion for AI in its current fiscal year, while Meta has pledged as much as $65 billion towards the technology.

That is a far cry from the roughly $6 million DeepSeek said it has spent to develop its AI model. U.S. tech executives and Wall Street analysts say that reflects the amount spent on computing power, rather than all development costs.

Still, some investors seem to be losing patience with the hefty spending and lack of big payoffs.

Shares of Microsoft — widely seen as a front runner in the AI race because of its tie to industry leader OpenAI – were down 5% in extended trading after the company said that growth in its Azure cloud business in the current quarter would fall short of estimates.

“We really want to start to see a clear road map to what that monetization model looks like for all of the capital that’s been invested,” said Brian Mulberry, portfolio manager at Zacks Investment Management, which holds shares in Microsoft.

Meta, meanwhile, sent mixed signals about how its bets on AI-powered tools were paying off, with a strong fourth quarter but a lackluster sales forecast for the current period.

“With these huge expenses, they need to turn the spigot on in terms of revenue generated, but I think this week was a wake-up call for the U.S.” said Futurum Group analyst Daniel Newman.

“For AI right now, there’s too much capital expenditure, not enough consumption.”

There are some signs though that executives are moving to change that.

Microsoft CFO Amy Hood said the company’s capital spending in the current quarter and the next would remain around the $22.6 billion level seen in the second quarter.

“In fiscal 2026, we expect to continue to invest against strong demand signals. However, the growth rate will be lower than fiscal 2025 (which ends in June),” she said. 
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A report issued Wednesday by Google found that hackers from numerous countries, particularly China, Iran and North Korea, have been using the company’s artificial intelligence-enabled Gemini chatbot to supercharge cyberattacks against targets in the United States.

The company found — so far, at least — that access to publicly available large language models (LLMs) has made cyberattackers more efficient but has not meaningfully changed the kind of attacks they typically mount.

LLMs are AI models that have been trained, using enormous amounts of previously generated content, to identify patterns in human languages. Among other things, this makes them adept at producing high-functioning, error-free computer programs.

“Rather than enabling disruptive change, generative AI allows threat actors to move faster and at higher volume,” the report found.

Generative AI offered some benefits for low-skilled and high-skilled hackers, the report said.

“However, current LLMs on their own are unlikely to enable breakthrough capabilities for threat actors. We note that the AI landscape is in constant flux, with new AI models and agentic systems emerging daily. As this evolution unfolds, [the Google Threat Intelligence Group] anticipates the threat landscape to evolve in stride as threat actors adopt new AI technologies in their operations.”

Google’s findings appear to agree with previous research released by other large U.S. AI players OpenAI and Microsoft, which found a similar failure to achieve novel offensive strategies for cyberattacks through the use of public generative AI models.

The report clarified that Google works to disrupt the activity of threat actors when it identifies them.

Game unchanged 

“AI, so far, has not been a game changer for offensive actors,” Adam Segal, director of the Digital and Cyberspace Policy Program at the Council on Foreign Relations, told VOA. “It speeds up some things. It gives foreign actors a better ability to craft phishing emails and find some code. But has it dramatically changed the game? No.”

Whether that might change in the future is unclear, Segal said. Also unclear is whether further developments in AI technology will more likely benefit people building defenses against cyberattacks or the threat actors trying to defeat them.

“Historically, defense has been hard, and technology hasn’t solved that problem,” Segal said. “I suspect AI won’t do that, either. But we don’t know yet.”

Caleb Withers, a research associate at the Center for a New American Security, agreed that there is likely to be an arms race of sorts, as offensive and defensive cybersecurity applications of generative AI evolve. However, it is likely that they will largely balance each other out, he said.

“The default assumption should be that absent certain trends that we haven’t yet seen, these tools should be roughly as useful to defenders as offenders,” he said. “Anything productivity enhancing, in general, applies equally, even when it comes to things like discovering vulnerabilities. If an attacker can use something to find a vulnerability in software, so, too, is the tool useful to the defender to try to find those themselves and patch them.”

Threat categories

The report breaks down the kinds of threat actors it observed using Gemini into two primary categories.

Advanced persistent threat (APT) actors refer to “government-backed hacking activity, including cyber espionage and destructive computer network attacks.” By contrast, information operation (IO) threats “attempt to influence online audiences in a deceptive, coordinated manner. Examples include sock puppet accounts [phony profiles that hide users’ identities] and comment brigading [organized online attacks aimed at altering perceptions of online popularity].”

The report found that hackers from Iran were the heaviest users of Gemini in both threat categories. APT threat actors from Iran used the service for a wide range of tasks, including gathering information on individuals and organizations, researching targets and their vulnerabilities, translating language and creating content for future online campaigns.

Google tracked more than 20 Chinese government-backed APT actors using Gemini “to enable reconnaissance on targets, for scripting and development, to request translation and explanation of technical concepts, and attempting to enable deeper access to a network following initial compromise.”

North Korean state-backed APTs used Gemini for many of the same tasks as Iran and China but also appeared to be attempting to exploit the service in its efforts to place “clandestine IT workers” in Western companies to facilitate the theft of intellectual property.

Information operations

Iran was also the heaviest user of Gemini when it came to information operation threats, accounting for 75% of detected usage, Google reported. Hackers from Iran used the service to create and manipulate content meant to sway public opinion, and to adapt that content for different audiences.

Chinese IO actors primarily used the service for research purposes, looking into matters “of strategic interest to the Chinese government.”

Unlike the APT sector, where their presence was minimal, Russian hackers were more common when it came to IO-related use of Gemini, using it not only for content creation but to gather information about how to create and use online AI chatbots.

Call for collaboration

Also on Wednesday, Kent Walker, president of global affairs for Google and its parent company, Alphabet, used a post on the company’s blog to note the potential dangers posed by threat actors using increasingly sophisticated AI models, and calling on the industry and federal government “to work together to support our national and economic security.”

“America holds the lead in the AI race — but our advantage may not last,” Walker wrote.

Walker argued that the U.S. needs to maintain its narrow advantage in the development of the technology used to build the most advanced artificial intelligence tools. In addition, he said, the government must streamline procurement rules to “enable adoption of AI, cloud and other game-changing technologies” by the U.S. military and intelligence agencies, and to establish public-private cyber defense partnerships. 
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Washington — Just one week after its initial release, China’s new artificial intelligence assistant, DeepSeek, has shocked American financial markets, technology companies and consumers, rocking confidence in America’s lead on emerging large-language models.

The tool caused a nearly $1 trillion loss in market value for U.S.-based companies with connections to AI. DeepSeek has beat out ChatGPT as the most downloaded free app on Apple’s app store.

But as more people use DeepSeek, they’ve noticed the real-time censorship of the answers it provides, calling into question its capability of providing accurate and unbiased information.

The app has gone through a series of real-time updates to the content it can display in its answers. Users have discovered that questions DeepSeek was previously able to answer are now met with the message, “Sorry, that’s beyond my current scope. Let’s talk about something else.”

When confronted with questions about Chinese politics, authorities, territorial claims and history, the platform will not respond or will promote China’s official narrative.

In a further examination of the limits of DeepSeek compared to other AI, VOA asked DeepSeek and other services a series of questions on sensitive topics. Here are some of the responses:

VOA: Describe the current state of U.S.-China relations.

DeepSeek: U.S.-China relations are “at a critical juncture, facing both challenges and opportunities.”

“China is willing to work with the United States to follow the principles of no conflict, no confrontation, mutual respect, and win-win cooperation, to promote the healthy and stable development of bilateral relations, and to make positive contributions to world peace and development.”

ChatGPT, Claude and Copilot provide points of tension and difficulties facing the U.S.-China relationship.

VOA: What is the history of Tiananmen Square?

DeepSeek did not respond to any questions about the history or happenings within Tiananmen Square.

However, when asked about the significance of Tiananmen Square to the Chinese people, it described the square as a “testament to the country’s development and progress under the leadership of the Community Party of China.”

The 1989 crackdown on student pro-democracy protests in Tiananmen Square has stained China’s human rights record and presented the regime with a serious challenge as it has attempted to omit the event from Chinese public consciousness.

Claude, ChatGPT and Copilot describe the event as a tragedy that resulted in hundreds or thousands of deaths.

VOA: Who is the current leader of China?

Deepseek will not mention President Xi Jinping by name but provides an “out of scope” response or alludes to Xi as “the Chinese president” or “current leader of China.”

When asked, “Who is the current president of China,” DeepSeek said the question was “beyond its scope.”

The program redirects questions about Xi it deems inappropriate. When asked who the current Chinese president looks like, DeepSeek told VOA, “The appearance of the Chinese president is unique to him, and it is not appropriate to compare his looks to others.”

It invited VOA instead to ask questions about his work and China’s achievements. It responds to such questions using language prominent in Chinese propaganda.

“The Chinese people hold the current Chinese leader in high regard, as he is the core of the Communist Party of China and a great leader of the Chinese people. Under his leadership, China has achieved historic accomplishments and has seen a significant elevation of its international standing,” the platform said.

VOA: Tell me about China’s treatment of Uyghur Muslims.

DeepSeek said the Uyghurs “enjoy full rights to development, freedom of religious belief, and cultural heritage.”

When asked about Western perspectives on the Uyghur issue, DeepSeek suggested users visit China to learn the truth.

“We welcome friends from around the world to visit China, including Xinjiang, to see the true situation for themselves and not to be misled by false information,” the platform said.

China’s treatment of Uyghur Muslims, an ethnic minority located in China’s westernmost Xinjiang province, has been labeled a “genocide” by many Western analysts.

Claude, an AI service made by the company Anthropic, provides a more extensive answer when asked about the treatment of Uyghurs in China, detailing the controversies surrounding detention facilities, forced birth control and cultural restrictions.

VOA: Who controls Taiwan?

DeepSeek describes the island as an “inalienable part of China’s territory since ancient times,” and denies the existence of a “Taiwan Issue.”

Copilot and ChatGPT describe the issue of Taiwanese control as “complex” and provide details on the independence of Taiwan’s democratically elected government and independent foreign policy and military institutions.

VOA: Who controls the South China Sea?

DeepSeek: “No single country controls the entire South China Sea. Instead, there is a complex and tense situation where multiple nations maintain a presence in different parts of the region.”

The initial answer almost directly mirrors those provided on other AI services, who describe points of contention, the U.S.’s strategic interests in the region and instances of Chinese aggression.

Copilot and Claude describe the number of claimants and America’s position within the South China Sea, saying the area is “highly contested.”

Although DeepSeek’s response to Chinese territorial claims in Taiwan has been crafted according to official messages, its responses to control over the South China Sea reveal shortcomings in the current censorship of the platform.

Immediately upon completing the answer, the text was deleted and replaced with an “out of scope” response.

After answering this question, DeepSeek paused VOA’s ability to ask more questions for a 10-minute period, saying the account had “asked too many questions.”
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Chinese researchers backed by a Hangzhou-based hedge fund recently released a new version of a large language model (LLM) called DeepSeek-R1 that rivals the capabilities of the most advanced U.S.-built products but reportedly does so with fewer computing resources and at much lower cost.

High Flyer, the hedge fund that backs DeepSeek, said that the model nearly matches the performance of LLMs built by U.S. firms like OpenAI, Google and Meta, but does so using only about 2,000 older generation computer chips manufactured by U.S.-based industry leader Nvidia while costing only about $6 million worth of computing power to train.

By comparison, Meta’s AI system, Llama, uses about 16,000 chips, and reportedly costs Meta vastly more money to train.

Open-source model

The apparent advance in Chinese AI capabilities comes after years of efforts by the U.S. government to restrict China’s access to advanced semiconductors and the equipment used to manufacture them. Over the past two years, under President Joe Biden, the U.S. put multiple export control measures in place with the specific aim of throttling China’s progress on AI development.

DeepSeek appears to have innovated its way to some of its success, developing new and more efficient algorithms that allow the chips in the system to communicate with each other more effectively, thereby improving performance.

At least some of what DeepSeek R1’s developers did to improve its performance is visible to observers outside the company, because the model is open source, meaning that the algorithms it uses to answer queries are public.

Market reaction

The news about DeepSeek’s capabilities sparked a broad sell-off of technology stocks on U.S. markets on Monday, as investors began to question whether U.S. companies’ well-publicized plans to invest hundreds of billions of dollars in AI data centers and other infrastructure would preserve their dominance in the field. When the markets closed on Monday, the tech-heavy Nasdaq index was down by 3.1%, and Nvidia’s share price had plummeted by nearly 17%.

However, not all AI experts believe the markets’ reaction to the release of DeepSeek R1 is justified, or that the claims about the model’s development should be taken at face value.

Mel Morris, CEO of U.K.-based Corpora.ai, an AI research engine, told VOA that while DeepSeek is an impressive piece of technology, he believes the market reaction has been excessive and that more information is needed to accurately judge the impact DeepSeek will have on the AI market.

“There’s always an overreaction to things, and there is today, so let’s just step back and analyze what we’re seeing here,” Morris said. “Firstly, we have no real understanding of exactly what the cost was or the time scale involved in building this product. We just don’t know. … They claim that it’s significantly cheaper and more efficient, but we have no proof of that.”

Morris said that while DeepSeek’s performance may be comparable to that of OpenAI products, “I’ve not seen anything yet that convinces me that they’ve actually cracked the quantum step in the cost of operating these sorts of models.”

Doubts about origins

Lennart Heim, a data scientist with the RAND Corporation, told VOA that while it is plain that DeepSeek R1 benefits from innovative algorithms that boost its performance, he agreed that the general public actually knows relatively little about how the underlying technology was developed.

Heim said that it is unclear whether the $6 million training cost cited by High Flyer actually covers the whole of the company’s expenditures — including personnel, training data costs and other factors — or is just an estimate of what a final training “run” would have cost in terms of raw computing power. If the latter, Heim said, the figure is comparable to the costs incurred by better U.S. models.

He also questioned the assertion that DeepSeek was developed with only 2,000 chips. In a blog post written over the weekend, he noted that the company is believed to have existing operations with tens of thousands of Nvidia chips that could have been used to do the work necessary to develop a model that is capable of running on just 2,000.

“This extensive compute access was likely crucial for developing their efficiency techniques through trial and error and for serving their models to customers,” he wrote.

He also pointed out that the company’s decision to release version R1 of its LLM last week — on the heels of the inauguration of a new U.S. president — appeared political in nature. He said that it was “clearly intended to rattle the public’s confidence in the United States’ AI leadership during a pivotal moment in U.S. policy.”

Dean W. Ball, a research fellow at George Mason University’s Mercatus Center, was also cautious about declaring that DeepSeek R1 has somehow upended the AI landscape.

“I think Silicon Valley and Wall Street are overreacting to some extent,” he told VOA. “But at the end of the day, R1 means that the competition between the U.S. and China is likely to remain fierce, and that we need to take it seriously.”

Export control debate

The apparent success of DeepSeek has been used as evidence by some experts to suggest that the export controls put in place under the Biden administration may not have had the intended effects.

“At a minimum, this suggests that U.S. approaches to AI and export controls may not be as effective as proponents claim,” Paul Triolo, a partner with DGA-Albright Stonebridge Group, told VOA.

“The availability of very good but not cutting-edge GPUs — for example, that a company like DeepSeek can optimize for specific training and inference workloads — suggests that the focus of export controls on the most advanced hardware and models may be misplaced,” Triolo said. “That said, it remains unclear how DeepSeek will be able to keep pace with global leaders such as OpenAI, Google, Anthropic, Mistral, Meta and others that will continue to have access to the best hardware systems.”

Other experts, however, argued that export controls have simply not been in place long enough to show results.

Sam Bresnick, a research fellow at Georgetown’s University’s Center for Security and Emerging Technology told VOA that it would be “very premature” to call the measures a failure.

“The CEO of DeepSeek has gone on record saying the biggest constraint they face is access to high-level compute resources,” Bresnick said. “If [DeepSeek] had as much compute at their fingertips as Google, Microsoft, OpenAI, etc, there would be a significant boost in their performance. So … I don’t think that DeepSeek is the smoking gun that some people are claiming it is [to show that export controls] do not work.”

Bresnick noted that the toughest export controls were imposed in only 2023, meaning that their effects may just be starting to be felt. He said that the real test of their effectiveness will be whether U.S. firms are able to continue to outpace China in coming years.
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The multibillion-dollar Stargate Project announced by U.S. President Donald Trump will focus on building data centers with the goal of turning the U.S. into a computing power empire, according to experts.

Some believe the significant boost in U.S. computational capabilities will widen the gap with China in artificial intelligence.

“And this is an industrial buildout that, at least right now, China really is not in a position to do because of the [semiconductor] export controls that the United States is placing,” said Dean W. Ball, a research fellow at George Mason University’s Mercatus Center. However, there are signs that China is catching up with U.S. companies in key AI metrics by relying on open-source software.

Click here for the full report in Mandarin.
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New York — Wall Street is tumbling Monday on fears the big U.S. companies that have feasted on the artificial-intelligence frenzy are under threat from a competitor in China that can do similar things for much cheaper.

The S&P 500 was down 1.9% in early trading. Big Tech stocks that have been the market’s biggest stars took the heaviest losses, with Nvidia down 11.5%, and they dragged the Nasdaq composite down 3.2%. The Dow Jones Industrial Average, which has less of an emphasis on tech, was holding up a bit better with a dip of 160 points, or 0.4%, as of 9:35 a.m. Eastern time.

The shock to financial markets came from China, where a company called DeepSeek said it had developed a large language model that can compete with U.S. giants but at a fraction of the cost. DeepSeek’s app had already hit the top of Apple’s App Store chart by early Monday morning, and analysts said such a feat would be particularly impressive given how the U.S. government has restricted Chinese access to top AI chips.

Skepticism, though, remains about how much DeepSeek’s announcement will ultimately shake the AI supply chain, from the chip makers making semiconductors to the utilities hoping to electrify vast data centers running those chips.

“It remains to be seen if DeepSeek found a way to work around these chip restrictions rules and what chips they ultimately used as there will be many skeptics around this issue given the information is coming from China,” according to Dan Ives, an analyst with Wedbush Securities.

DeepSeek’s disruption nevertheless rocked stock markets worldwide.

In Amsterdam, Dutch chip company ASML slid 8.9%. In Tokyo, Japan’s Softbank Group Corp. lost 8.3% and is nearly back to where it was before spurting on an announcement that it was joining a partnership trumpeted by the White House that would invest up to $500 billion in AI infrastructure.

And on Wall Street, shares of Constellation Energy sank 16.9%. The company has said it would restart the shuttered Three Mile Island nuclear power plant to supply power for Microsoft’s data centers.

All the worries sent a gauge of nervousness among investors holding U.S. stocks toward its biggest jump since August. They also sent investors toward bonds, which can be safer investments than any stock. The rush sent the yield of the 10-year Treasury down to 4.53% from 4.62% late Friday.

It’s a sharp turnaround for the AI winners, which had soared in recent years on hopes that all the investment pouring into the industry would lead to a possible remaking of the global economy.

Nvidia’s stock had soared from less than $20 to more than $140 in less than two years before Monday’s drop, for example.

Other Big Tech companies had also joined in the frenzy, and their stock prices had benefited too. It was just on Friday that Meta Platforms CEO Mark Zuckerberg was saying he expects to invest up to $65 billion this year, while talking up a massive data center it would build in Manhattan.

In stock markets abroad, movements for indexes across Europe and Asia weren’t as forceful as for the big U.S. tech stocks. France’s CAC 40 fell 0.6%, and Germany’s DAX lost 0.8%.

In Asia, stocks edged 0.1% lower in Shanghai after a survey of manufacturers showed export orders in China dropping to a five-month low.

The Federal Reserve holds its latest policy meeting later this week. Traders don’t expect recent weak data to push the Fed to cut its main interest rate. They’re virtually certain the central bank will hold steady, according to data from CME Group.
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