Jensen Huang, co-founder and chief executive officer of Nvidia Corp., during a news conference in Taipei, Taiwan, on Tuesday, June 4, 2024. Nvidia is still working on the certification process for Samsung Electronics Co.’s high-bandwidth memory chips, a final required step before the Korean company can begin supplying a component essential to training AI platforms.
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Nvidia called DeepSeek’s R1 model “an excellent AI advancement,” despite the Chinese startup’s emergence causing the chip maker’s stock price to plunge 17% on Monday.
“DeepSeek is an excellent AI advancement and a perfect example of Test Time Scaling,” an Nvidia spokesperson told CNBC on Monday. “DeepSeek’s work illustrates how new models can be created using that technique, leveraging widely-available models and compute that is fully export control compliant.”
The comments come after DeepSeek last week released R1, which is an open-source reasoning model that reportedly outperformed the best models from U.S. companies such as OpenAI. R1’s self-reported training cost was less than $6 million, which is a fraction of the billions that Silicon Valley companies are spending to build their artificial-intelligence models.
Nvidia’s statement indicates that it sees DeepSeek’s breakthrough as creating more work for the American chip maker’s graphics processing units, or GPUs.
Read more DeepSeek coverage
“Inference requires significant numbers of NVIDIA GPUs and high-performance networking,” the spokesperson added. “We now have three scaling laws: pre-training and post-training, which continue, and new test-time scaling.”
Nvidia also said that the GPUs that DeepSeek used were fully export compliant. That counters Scale AI CEO Alexandr Wang’s comments on CNBC last week that he believed DeepSeek used Nvidia GPUs models which are banned in mainland China. DeepSeek says it used special versions of Nvidia’s GPUs intended for the Chinese market.
Analysts are now asking if multi-billion dollar capital investments from companies like Microsoft, Google and Meta for Nvidia-based AI infrastructure are being wasted when the same results can be achieved more cheaply.
Earlier this month, Microsoft said it is spending $80 billion on AI infrastructure in 2025 alone while Meta CEO Mark Zuckerberg last week said the social media company planned to invest between $60 to $65 billion in capital expenditures in 2025 as part of its AI strategy.
“If model training costs prove to be significantly lower, we would expect a near-term cost benefit for advertising, travel, and other consumer app companies that use cloud AI services, while long-term hyperscaler AI-related revenues and costs would likely be lower,” wrote BofA Securities analyst Justin Post in a note on Monday.
Nvidia’s comment also reflects a new theme that Nvidia CEO Jensen Huang, OpenAI CEO Sam Altman and Microsoft CEO Satya Nadella have discussed in recent months.
Much of the AI boom and the demand for Nvidia GPUs was driven by the “scaling law,” a concept in AI development proposed by OpenAI researchers in 2020. That concept suggested that better AI systems could be developed by greatly expanding the amount of computation and data that went into building a new model, requiring more and more chips.
Since November, Huang and Altman have been focusing on a new wrinkle to the scaling law, which Huang calls “test-time scaling.”
This concept says that if a fully trained AI model spends more time using extra computer power when making predictions or generating text or images to allow it to “reason,” it will provided better answers than it would have if it ran for less time.
Forms of the test-time scaling law are used in some of OpenAI’s models such as o1 as well as DeepSeek’s breakthrough R1 model.
Founded in 2022, ElevenLabs is an AI voice generation startup based in London. It competes with the likes of Speechmatics and Hume AI.
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LONDON — ElevenLabs, a London-based startup that specializes in generating synthetic voices through artificial intelligence, has revealed plans to be IPO-ready within five years.
The company told CNBC it is targeting major global expansion as it prepares for an initial public offering.
“We expect to build more hubs in Europe, Asia and South America, and just keep scaling,” Mati Staniszewski, ElevenLabs’ CEO and co-founder, told CNBC in an interview at the firm’s London office.
He identified Paris, Singapore, Brazil and Mexico as potential new locations. London is currently ElevenLabs’ biggest office, followed by New York, Warsaw, San Francisco, Japan, India and Bangalore.
Staniszewski said the eventual aim is to get the company ready for an IPO in the next five years.
“From a commercial standpoint, we would like to be ready for an IPO in that time,” he said. “If the market is right, we would like to create a public company … that’s going to be here for the next generation.”
Undecided on location
Founded in 2022 by Staniszewski and Piotr Dąbkowski, ElevenLabs is an AI voice generation startup that competes with the likes of Speechmatics and Hume AI.
The company divides its business into three main camps: consumer-facing voice assistants, integrations with corporates such as Cisco, and tailor-made applications for specific industries like health care.
Staniszewski said the firm hasn’t yet decided where it could list, but that this decision will largely rest on where most of its users are located at the time.
“If the U.K. is able to start accelerating,” ElevenLabs will consider London as a listing destination, Staniszewski said.
The city has faced criticisms from entrepreneurs and venture capitalists that its stock market is unfavorable toward high-growth tech firms.
Meanwhile, British money transfer firm Wiselast month said it plans to move its primary listing location to the U.S.,
Fundraising plans
ElevenLabs was valued at $3.3 billion following a recent $180 million funding round. The company is backed by the likes of Andreessen Horowitz, Sequoia Capital and ICONIQ Growth, as well as corporate names like Salesforce and Deutsche Telekom.
Staniszewski said his startup was open to raising more money from VCs, but it would depend on whether it sees a valid business need, like scaling further in other markets. “The way we try to raise is very much like, if there’s a bet we want to take, to accelerate that bet [we will] take the money,” he said.
Synopsys logo is seen displayed on a smartphone with the flag of China in the background.
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The U.S. government has rescinded its export restrictions on chip design software to China, U.S.-based Synopsys announced Thursday.
“Synopsys is working to restore access to the recently restricted products in China,” it said in a statement.
The U.S. had reportedly told several chip design software companies, including Synopsys, in May that they were required to obtain licenses before exporting goods, such as software and chemicals for semiconductors, to China.
The U.S. Commerce Department did not immediately respond to a request for comment from CNBC.
The news comes after China signaled last week that they are making progress on a trade truce with the U.S. and confirmed conditional agreements to resume some exchanges of rare earths and advanced technology.
The Datadog stand is being displayed on day one of the AWS Summit Seoul 2024 at the COEX Convention and Exhibition Center in Seoul, South Korea, on May 16, 2024.
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Datadog shares were up 10% in extended trading on Wednesday after S&P Global said the monitoring software provider will replace Juniper Networks in the S&P 500 U.S. stock index.
S&P Global is making the change effective before the beginning of trading on July 9, according to a statement.
Computer server maker Hewlett Packard Enterprise, also a constituent of the index, said earlier on Wednesday that it had completed its acquisition of Juniper, which makes data center networking hardware. HPE disclosed in a filing that it paid $13.4 billion to Juniper shareholders.
Over the weekend, the two companies reached a settlement with the U.S. Justice Department, which had sued in opposition to the deal. As part of the settlement, HPE agreed to divest its global Instant On campus and branch business.
While tech already makes up an outsized portion of the S&P 500, the index has has been continuously lifting its exposure as the industry expands into more areas of society.
Stocks often rally when they’re added to a major index, as fund managers need to rebalance their portfolios to reflect the changes.
New York-based Datadog went public in 2019. The company generated $24.6 million in net income on $761.6 million in revenue in the first quarter of 2025, according to a statement. Competitors include Cisco, which bought Splunk last year, as well as Elastic and cloud infrastructure providers such as Amazon and Microsoft.
Datadog has underperformed the broader tech sector so far this year. The stock was down 5.5% as of Wednesday’s close, while the Nasdaq was up 5.6%. Still, with a market cap of $46.6 billion, Datadog’s valuation is significantly higher than the median for that index.