DeepSeek has rattled large AI players — but smaller chip firms see it as a force multiplier

Published

5 months ago

February 7, 2025

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Dado Ruvic | Reuters

DeepSeek has rattled the U.S.-led AI ecosystem with its latest model, shaving hundreds of billions in chip leader Nvidia’s market cap. While the sector leaders grapple with the fallout, smaller AI companies see an opportunity to scale with the Chinese startup.

Several AI-related firms told CNBC that DeepSeek’s emergence is a “massive” opportunity for them, rather than a threat.

“Developers are very keen to replace OpenAI’s expensive and closed models with open source models like DeepSeek R1…” said Andrew Feldman, CEO of artificial intelligence chip startup Cerebras Systems.

The company competes with Nvidia’s graphic processing units and offers cloud-based services through its own computing clusters. Feldman said the release of the R1 model generated one of Cerebras’ largest-ever spikes in demand for its services.

“R1 shows that [AI market] growth will not be dominated by a single company — hardware and software moats do not exist for open-source models,” Feldman added.

Open source refers to software in which the source code is made freely available on the web for possible modification and redistribution. DeepSeek’s models are open source, unlike those of competitors such as OpenAI.

DeepSeek also claims its R1 reasoning model rivals the best American tech, despite running at lower costs and being trained without cutting-edge graphic processing units, though industry watchers and competitors have questioned these assertions.

“Like in the PC and internet markets, falling prices help fuel global adoption. The AI market is on a similar secular growth path,” Feldman said.

Inference chips

DeepSeek could increase the adoption of new chip technologies by accelerating the AI cycle from the training to “inference” phase, chip start-ups and industry experts said.

Inference refers to the act of using and applying AI to make predictions or decisions based on new information, rather than the building or training of the model.

“To put it simply, AI training is about building a tool, or algorithm, while inference is about actually deploying this tool for use in real applications,” said Phelix Lee, an equity analyst at Morningstar, with a focus on semiconductors.

While Nvidia holds a dominant position in GPUs used for AI training, many competitors see room for expansion in the “inference” segment, where they promise higher efficiency for lower costs.

AI training is very compute-intensive, but inference can work with less powerful chips that are programmed to perform a narrower range of tasks, Lee added.

A number of AI chip startups told CNBC that they were seeing more demand for inference chips and computing as clients adopt and build on DeepSeek’s open source model.

“[DeepSeek] has demonstrated that smaller open models can be trained to be as capable or more capable than larger proprietary models and this can be done at a fraction of the cost,” said Sid Sheth, CEO of AI chip start-up d-Matrix.

“With the broad availability of small capable models, they have catalyzed the age of inference,” he told CNBC, adding that the company has recently seen a surge in interest from global customers looking to speed up their inference plans.

Robert Wachen, co-founder and COO of AI chipmaker Etched, said dozens of companies have reached out to the startup since DeepSeek released its reasoning models.

“Companies are [now] shifting their spend from training clusters to inference clusters,” he said.

“DeepSeek-R1 proved that inference-time compute is now the [state-of-the-art] approach for every major model vendor and thinking isn’t cheap – we’ll only need more and more compute capacity to scale these models for millions of users.”

Jevon’s Paradox

Analysts and industry experts agree that DeepSeek’s accomplishments are a boost for AI inference and the wider AI chip industry.

“DeepSeek’s performance appears to be based on a series of engineering innovations that significantly reduce inference costs while also improving training cost,” according to a report from Bain & Company.

“In a bullish scenario, ongoing efficiency improvements would lead to cheaper inference, spurring greater AI adoption,” it added.

This pattern explains Jevon’s Paradox, a theory in which cost reductions in a new technology drive increased demand.

Financial services and investment firm Wedbush said in a research note last week that it continues to expect the use of AI across enterprise and retail consumers globally to drive demand.

Speaking to CNBC’s “Fast Money” last week, Sunny Madra, COO at Groq, which develops chips for AI inference, suggested that as the overall demand for AI grows, smaller players will have more room to grow.

“As the world is going to need more tokens [a unit of data that an AI model processes] Nvidia can’t supply enough chips to everyone, so it gives opportunities for us to sell into the market even more aggressively,” Madra said.

Technology

AI voice startup ElevenLabs pushes global expansion as it gears up for an IPO

Published

3 hours ago

July 3, 2025

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AI voice startup ElevenLabs pushes global expansion as it gears up for an IPO

Founded in 2022, ElevenLabs is an AI voice generation startup based in London. It competes with the likes of Speechmatics and Hume AI.

Sopa Images | Lightrocket | Getty Images

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.

For example, Deliveroo, whose shares tanked nearly 30% when the company went public, was recently acquired by U.S. food delivery rival DoorDash for close to $4 billion.

Meanwhile, British money transfer firm Wise last 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.

Technology

U.S. lifts chip software curbs on China amid trade truce, Synopsys says

Published

6 hours ago

July 3, 2025

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U.S. lifts chip software curbs on China amid trade truce, Synopsys says

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.

Technology

Datadog stock jumps 10% on tech company’s inclusion in S&P 500 index

Published

9 hours ago

July 2, 2025

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Datadog stock jumps 10% on tech company’s inclusion in S&P 500 index

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.

Chris Jung | Nurphoto | Getty Images

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.

DoorDash was the latest tech company to join during the last rebalancing in March. Cloud software vendor Workday was added in December, and that was preceded earlier in 2024 with the additions of Palantir, Dell, CrowdStrike, GoDaddy and Super Micro Computer.

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.

— CNBC’s Ari Levy contributed to this report.

CNBC: Datadog CEO Olivier Pomel on the cloud computing outlook