Connect with us

Published

on

China is focusing on large language models (LLMs) in the artificial intelligence space. 

Blackdovfx | Istock | Getty Images

China’s attempts to dominate the world of artificial intelligence could be paying off, with industry insiders and technology analysts telling CNBC that Chinese AI models are already hugely popular and are keeping pace with — and even surpassing — those from the U.S. in terms of performance.

AI has become the latest battleground between the U.S. and China, with both sides considering it a strategic technology. Washington continues to restrict China’s access to leading-edge chips designed to help power artificial intelligence amid fears that the technology could threaten U.S. national security.

It’s led China to pursue its own approach to boosting the appeal and performance of its AI models, including relying on open-sourcing technology and developing its own super-fast software and chips.

China is creating popular LLMs

On Hugging Face, a repository of LLMs, Chinese LLMs are the most downloaded, according to Tiezhen Wang, a machine learning engineer at the company. Qwen, a family of AI models created by Chinese e-commerce giant Alibaba, is the most popular on Hugging Face, he said.

“Qwen is rapidly gaining popularity due to its outstanding performance on competitive benchmarks,” Wang told CNBC by email.

He added that Qwen has a “highly favorable licensing model” which means it can be used by companies without the need for “extensive legal reviews.”

Qwen comes in various sizes, or parameters, as they’re known in the world of LLMs. Large parameter models are more powerful but have higher computational costs, while smaller ones are cheaper to run.

“Regardless of the size you choose, Qwen is likely to be one of the best-performing models available right now,” Wang added.

DeepSeek, a start-up, also made waves recently with a model called DeepSeek-R1. DeepSeek said last month that its R1 model competes with OpenAI’s o1 — a model designed for reasoning or solving more complex tasks.

These companies claim that their models can compete with other open-source offerings like Meta‘s Llama, as well as closed LLMs such as those from OpenAI, across various functions.

“In the last year, we’ve seen the rise of open source Chinese contributions to AI with really strong performance, low cost to serve and high throughput,” Grace Isford, a partner at Lux Capital, told CNBC by email.

China pushes open source to go global

Open sourcing a technology serves a number of purposes, including driving innovation as more developers have access to it, as well as building a community around a product.

It is not only Chinese firms that have launched open-source LLMs. Facebook parent Meta, as well as European start-up Mistral, also have open-source versions of AI models.

But with the technology industry caught in the crosshairs of the geopolitical battle between Washington and Beijing, open-source LLMs give Chinese firms another advantage: enabling their models to be used globally.

“Chinese companies would like to see their models used outside of China, so this is definitively a way for companies to become global players in the AI space,” Paul Triolo, a partner at global advisory firm DGA Group, told CNBC by email.

While the focus is on AI models right now, there is also debate over what applications will be built on top of them — and who will dominate this global internet landscape going forward.

“If you assume these frontier base AI models are table stakes, it’s about what these models are used for, like accelerating frontier science and engineering technology,” Lux Capital’s Isford said.

Today’s AI models have been compared to operating systems, such as Microsoft’s Windows, Google‘s Android and Apple‘s iOS, with the potential to dominate a market, like these companies do on mobile and PCs.

If true, this makes the stakes for building a dominant LLM higher.

“They [Chinese companies] perceive LLMs as the center of future tech ecosystems,” Xin Sun, senior lecturer in Chinese and East Asian business at King’s College London, told CNBC by email.

“Their future business models will rely on developers joining their ecosystems, developing new applications based on the LLMs, and attracting users and data from which profits can be generated subsequently through various means, including but far beyond directing users to use their cloud services,” Sun added.

Chip restrictions cast doubt over China’s AI future

AI models are trained on vast amounts of data, requiring huge amounts of computing power. Currently, Nvidia is the leading designer of the chips required for this, known as graphics processing units (GPUs).

Most of the leading AI companies are training their systems on Nvidia’s most high-performance chips — but not in China.

Over the past year or so, the U.S. has ramped up export restrictions on advanced semiconductor and chipmaking equipment to China. It means Nvidia‘s leading-edge chips cannot be exported to the country and the company has had to create sanction-compliant semiconductors to export.

Despite, these curbs, however, Chinese firms have still managed to launch advanced AI models.

“Major Chinese technology platforms currently have sufficient access to computing power to continue to improve models. This is because they have stockpiled large numbers of Nvidia GPUs and are also leveraging domestic GPUs from Huawei and other firms,” DGA Group’s Triolo said.

Indeed, Chinese companies have been boosting efforts to create viable alternatives to Nvidia. Huawei has been one of the leading players in pursuit of this goal in China, while firms like Baidu and Alibaba have also been investing in semiconductor design.

“However, the gap in terms of advanced hardware compute will become greater over time, particularly next year as Nvidia rolls out its Blackwell-based systems that are restricted for export to China,” Triolo said.

Lux Capital’s Isford flagged that China has been “systematically investing and growing their whole domestic AI infrastructure stack outside of Nvidia with high-performance AI chips from companies like Baidu.”

“Whether or not Nvidia chips are banned in China will not prevent China from investing and building their own infrastructure to build and train AI models,” she added.

Continue Reading

Technology

Spotify paid over $100 million to podcasts in the first quarter, including Joe Rogan, Alex Cooper and Theo Von

Published

on

By

Spotify paid over 0 million to podcasts in the first quarter, including Joe Rogan, Alex Cooper and Theo Von

Pavlo Gonchar | Lightrocket | Getty Images

Spotify said Monday it paid more than $100 million to podcast publishers and podcasters worldwide in the first quarter of 2025.

The figure includes all creators on the platform across all formats and agreements, including the platform’s biggest fish, Joe Rogan, Alex Cooper and Theo Von, the company said.

Rogan, host of “The Joe Rogan Experience,” Cooper of “Call Her Daddy” and “This Past Weekend w/ Theo Von” were among the top podcasts on Spotify globally in 2024.

Rogan and Cooper’s exclusivity deals with Spotify have ended, and while Rogan signed a new Spotify deal last year worth up to $250 million, including revenue sharing and the ability to post on YouTube, Cooper inked a SiriusXM deal in August.

Read more CNBC tech news

Even when shows are no longer exclusive to Spotify, they are still uploaded to the platform and qualify for the Spotify Partner Program, which launched in January in the U.S., U.K., Canada and Australia.

The program allows creators to earn revenue every time an ad monetized by Spotify plays in the episode, as well as revenue when Premium subscribers watch dynamic ads on videos.

Competing platform Patreon said it paid out over $472 million to podcasters from over 6.7 million paid memberships in 2024.

YouTube’s payouts are massive by comparison but include more than just podcasts. The company said it paid $70 billion to creators between 2021 and 2024 with payouts rising each year, according to YouTube CEO Neal Mohan.

Spotify reports first-quarter earnings on Tuesday.

Continue Reading

Technology

Palo Alto Networks acquiring Protect AI to boost artificial intelligence tools

Published

on

By

Palo Alto Networks acquiring Protect AI to boost artificial intelligence tools

Palo Alto Networks signage displays on the screen at the Nasdaq Market in New York City, U.S., March 25, 2025.

Jeenah Moon | Reuters

Palo Alto Networks announced on Monday its intent to acquire Protect AI, a startup specializing in securing artificial intelligence and machine learning applications, for an undisclosed sum.

The deal is set to close by the first quarter of fiscal year 2026.

“By extending our AI security capabilities to include Protect AI’s innovative solutions for Securing for AI, businesses will be able to build AI applications with comprehensive security,” said Anand Oswal, senior vice president and general manager of network security at Palo Alto Networks, in a release.

Palo Alto has been steadily bolstering its artificial intelligence systems to confront increasingly sophisticated cyber threats. The use of rapidly built ecosystems of AI models by large enterprises and government organizations has created new vulnerabilities. The company said those risks require purpose-built defenses beyond conventional cybersecurity.

Read more CNBC tech news

The acquisition would fold Protect AI’s solutions and team into Palo Alto’s newly announced Prisma AIRS platform. Palo Alto said Protect AI has established itself as a key player in what it called a “critical new area of security.”

Protect AI’s CEO Ian Swanson said joining Palo Alto would allow the company to “scale our mission of making the AI landscape more secure for users and organizations of all sizes.”

The company’s stock price is up 23% in the past year lifting its market cap close to $120 billion. Palo Alto reports third-quarter earnings on May 21.

Stock Chart IconStock chart icon

hide content

Year-to-date stock chart for Palo Alto Networks

Continue Reading

Technology

Cloud software vendors Atlassian, Snowflake and Workday are betting on security startup Veza

Published

on

By

Cloud software vendors Atlassian, Snowflake and Workday are betting on security startup Veza

From left, Veza founders Rob Whitcher, Tarun Thakur and Maohua Lu.

Veza

Tech giants like Google, Amazon, Microsoft and Nvidia have captured headlines in recent years for their massive investments in artificial intelligence startups like OpenAI and Anthropic.

But when it comes to corporate investing by tech companies, cloud software vendors are getting aggressive as well. And in some cases they’re banding together.

Veza, whose software helps companies manage the various internal technologies that employees can access, has just raised $108 million in a financing round that included participation from software vendors Atlassian, Snowflake and Workday.

New Enterprise Associates led the round, which values Veza at just over $800 million, including the fresh capital.

For two years, Snowflake’s managers have used Veza to check who has read and write access, Harsha Kapre, director of the data analytics software company’s venture group told CNBC. It sits alongside a host of other cloud solutions the company uses.

“We have Workday, we have Salesforce — we have all these things,” Kapre said. “What Veza really unlocks for us is understanding who has access and determining who should have access.”

Kapre said that “over-provisioning,” or allowing too many people access to too much stuff, “raises the odds of an attack, because there’s just a lot of stuff that no one is even paying attention to.”

With Veza, administrators can check which employees and automated accounts have authorization to see corporate data, while managing policies for new hires and departures. Managers can approve or reject existing permissions in the software.

Veza says it has built hooks into more than 250 technologies, including Snowflake.

The IPO market is likely to pick up near Labor Day, says FirstMark's Rick Heitzmann

The funding lands at a challenging time for traditional venture firms. Since inflation started soaring in late 2021 and was followed by rising interest rates, startup exits have cooled dramatically, meaning venture firms are struggling to generate returns.

Wall Street was banking on a revival in the initial public offering market with President Donald Trump’s return to the White House, but the president’s sweeping tariff proposals led several companies to delay their offerings.

That all means startup investors have to preserve their cash as well.

In the first quarter, venture firms made 7,551 deals, down from more than 11,000 in the same quarter a year ago, according to a report from researcher PitchBook.

Corporate venture operates differently as the capital comes from the parent company and many investments are strategic, not just about generating financial returns.

Atlassian’s standard agreement asks that portfolio companies disclose each quarter the percentage of a startup’s customers that integrate with Atlassian. Snowflake looks at how much extra product consumption of its own technology occurs as a result of its startup investments, Kapre said, adding that the company has increased its pace of deal-making in the past year.

‘Sleeping industry’

Within the tech startup world, Veza is also in a relatively advantageous spot, because the proliferation of cyberattacks has lifted the importance of next-generation security software.

On the public markets, the First Trust Nasdaq Cybersecurity ETF, which includes CrowdStrike and Palo Alto Networks, is up 3% so far this year, compared with a 10% drop in the Nasdaq.

Veza’s technology runs across a variety of security areas tied to identity and access. In access management, Microsoft is the leader, and Okta is the challenger. Veza isn’t directly competing there, and is instead focused on visibility, an area where other players in and around the space lack technology, said Brian Guthrie, an analyst at Gartner.

Tarun Thakur, Veza’s co-founder and CEO, said his company’s software has become a key part of the ecosystem as other security vendors have started seeing permissions and entitlements as a place to gain broad access to corporate networks.

“We have woken up a sleeping industry,” Thakur, who helped start the company in 2020, said in an interview.

Thakur’s home in Los Gatos, California, doubles as headquarters for the startup, which employs 200 people. It isn’t disclosing revenue figures but says sales more than doubled in the fiscal year that ended in January. Customers include AMD, CrowdStrike and Intuit.

Guthrie said enterprises started recognizing that they needed stronger visibility about two years ago.

“I think it’s because of the number of identities,” he said. Companies realized they had an audit problem or “an account that got compromised,” Guthrie said.

AI agents create a new challenge. Last week Microsoft published a report that advised organizations to figure out the proper ratio of agents to humans.

Veza is building enhancements to enable richer support for agent identities, Thakur said. The new funding will also help Veza expand in the U.S. government and internationally and build more integrations, he said.

Peter Lenke, head of Atlassian’s venture arm, said his company isn’t yet a paying Veza client.

“There’s always potential down the road,” he said. Lenke said he heard about Veza from another investor well before the new round and decided to pursue a stake when the opportunity arose.

Lenke said that startups benefit from Atlassian investments because the company “has a large footprint” inside of enterprises.

“I think there’s a great symbiotic match there,” he said.

Don’t miss these insights from CNBC PRO

Making deals with Menlo Ventures' Matt Murphy

Continue Reading

Trending