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People learn about Baidu’s artificial intelligence chatbot service Ernie Bot during the 2nd Global Digital Trade Expo at Hangzhou International Expo Center on November 23, 2023 in Hangzhou, Zhejiang Province of China. 

China News Service | China News Service | Getty Images

Nvidia’s rocket-ship ride in the stock market underscores the extent to which chip quality and availability will dictate the winners in the generative AI era. But there’s another aspect to measuring early leads in the space. In China, which is angling to produce its own chips or get more from Nvidia, no dominant gen AI contender to OpenAI has emerged yet among dozens of Chinese tech titans and startups.    

Late to the game, China is seeking to catch the lead of OpenAI in a wider U.S. AI market shaped by tech titans Microsoft, Alphabet’s Google and Amazon, and well-financed startups including Anthropic, which this week received a $2.7 billion infusion of cash from Amazon.

In the fast-moving field, the gap between the U.S. and its tech rival China is seen as wide. “The leading Chinese companies are benchmarking against ChatGPT, which indicates how far behind they are,” said Paul Triolo, senior vice president for China and technology policy lead at Dentons Global Advisors in Washington, D.C.

“Not too many companies can support their own large language model. It takes a lot of capital. Silicon Valley is definitely well ahead of the game,” said Jenny Xiao, a partner at AI VC firm Leonis Capital in San Francisco.

The U.S. remains the biggest investment market. Last year, funding of gen AI upstarts accounted for nearly half of $42.5 billion invested globally in artificial intelligence companies, according to CB Insights. In the U.S., VCs and corporate investors drove AI investment to $31 billion across 1,151 deals, led by large outlays in OpenAI, Anthropic and Inflection. This compares with $2 billion in 68 deals in China, which marked a large drop from 2022’s $5.5 billion in 377 deals. The fall-off is partly attributable to restrictions on of U.S. venture investment into China.

“China is at a big disadvantage in building the foundation models for Gen AI,” said Rui Ma, an AI investor and co-founder of investment syndicate and podcast TechBuzz China.  

But where China lags in foundational models, which are dominated by OpenAI and Google’s Gemini, it’s closing the gap by using Meta’s open source, large language model Llama 1, and Triolo said the Chinese contenders, if behind, are improving on the U.S. model.

“Many of the China models are effectively forks of Llama, and the consensus is that these forks are one to two years behind the leading U.S companies OpenAI and its video-to-text model Sora,” Ma said.

China does have the tech talent to make a difference in the AI rivalry in the years ahead.

A new study by think tank Marco Polo, run by the Paulson Institute, shows that the U.S. is home to 60% of top AI institutions, and the U.S. remains by far the leading destination for elite AI talent at 57% of the total, compared with China at 12%. But the research finds that China leads the U.S. by a few other measures, including being ahead of the U.S. in producing top-tier AI researchers, based on undergraduate degrees, with China at 47% and the U.S. lagging with 18%. Additionally, among top-tier AI researchers working at U.S. institutions, 38% have China as their country of origin, compared with 37% from the U.S.

New Chinese gen AI market entries can also reach mass adoption quickly. Baidu’s ChatGPT competitor, Ernie Bot, released in August 2023, reached 100 million users by the end of the year. Samsung is planning to integrate Baidu’s Ernie AI into its new Galaxy S smartphones while in another high-profile development that speaks to U.S.-China relations, Apple is in talks with Baidu about supplying the iPhone 16 with the Chinese company’s gen AI technology. 

Within its current slate of AI contenders, Baidu’s Ernie Bot models are considered among the most advanced, according to Leong.

Apple reportedly in talks with Baidu on AI for devices

Several other Chinese companies are forging ahead, funded by major players in its own technology market. Large cloud companies such as such as Baidu and Alibaba, social media players ByteDance and Tencent, and tech companies SenseTime, iFlyTek, Megvii and Horizon Robotics, as well as research institutes, are all aiding the effort. 

Moonshot AI, funded by China’s e-commerce giant Alibaba and VC firm Hongshan (previously Sequoia China), is building large language models that can handle long content inputs. Meanwhile, former Google China president Kai-Fu Lee has developed an open source gen AI model, 01.AI, funded by Alibaba and his firm Sinovation Ventures.   

While China has accelerated development of its homegrown chip industry and advanced AI, its AI development has been limited in part by U.S. restrictions on exporting high-end AI chips, a market cornered by Nvidia, as part of a new battleground for tech supremacy between the U.S. and China

“Despite efforts to develop indigenous solutions, Chinese AI developers still largely rely on foreign hardware, particularly from U.S. companies, which is a vulnerability in the current geopolitical climate,” said Bernard Leong, founder and CEO of tech advisory Analyse Asia in Singapore.    

The ongoing tensions between the U.S. and China over technology innovation and national security issues is leading to a split in gen AI development, following the pattern of other impactful technologies caught up in superpower tech arms races. Given regulations and bans over sensitive, cutting-edge technologies, the likely outcome is two parallel ecosystems for gen AI, one in the U.S. and one in China. ChatGPT is blocked in China while Baidu’s Ernie Bot can only be accessed in the U.S. with a mainland Chinese cell phone number. “U.S. companies can’t go into China and Chinese companies can’t go into the U.S.,” Xiao said.  

U.S. Secretary of Commerce Gina Raimondo has stated that a goal of U.S. curbs on AI chip exports is to prevent China from acquiring or producing advanced chips. As mainland China focuses on homegrown capabilities, Chinese companies SMIC or Huawei could be an alternative to Nvidia. But the future for alternates is likely uncertain if export controls cut off these companies from the most advanced designs for manufacturing. Triolo noted that Huawei recently developed a series of AI chips as a rival to Nvidia.  

China is getting ahead in applying AI to certain categories, such as computer vision. “The chip shortage is very important for training foundational models where you need certain chips, but for applications, you don’t need that,” Ma said.

The “real killer app” for gen AI, according to Triolo, will be in companies that are willing to pay money to harness the technology as part of their business operations. Alibaba is focusing on integrating AI into its e-commerce ecosystem. Huawei, while competing more successfully against Apple’s iPhone in the consumer market in the past year, also has broader ambitions, developing AI for specific industries including mining, using its in-house hardware, Leong said.

Boston Consulting Group research suggests it may be a while before this wider gen AI market ramps outside of tech. Sixty percent of 1,400 executives surveyed are waiting to see how gen AI regulations develop, while only 6 percent of companies have trained their employees on gen AI tools.

AI and tech issues are front and center for China’s leadership, with the country’s release of guardrails on AI in 2023 after ChatGPT’s breakthrough, and then modifications of some measures.

The open source gen AI technology many Chinese developers use can encourage collaboration among globally and lead to shared insights as AI advances, but Leong said open source also leads to issues related to ensuring quality and security of the models, as well as managing bias and potential misuse of AI.

“China wants to make sure content is not spewing out. They also want their companies to lead and are willing to reign in draconian measures,” Triolo said.

Ethical and social concerns hinder gen AI advances in China as well as other regions, including the U.S., as see in the battle for control over OpenAI’s mission. Within China, there is another factor that could slow AI acceleration, according to Leong: maintaining control of gen AI applications, especially in areas sensitive to state interests.

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

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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.

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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.

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IBM pledges $150 billion to boost U.S. tech growth, computer manufacturing

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IBM pledges 0 billion to boost U.S. tech growth, computer manufacturing

Arvind Krishna, chief executive officer of International Business Machines Corp. (IBM), during a Bloomberg Television interview at the World Governments Summit in Dubai, United Arab Emirates, on Tuesday, Feb. 11, 2025.

Christopher Pike | Bloomberg | Getty Images

International Business Machines Corporation on Monday announced it will invest $150 billion in the U.S. over the next five years, including more than $30 billion to advance American manufacturing of its mainframe and quantum computers.

“We have been focused on American jobs and manufacturing since our founding 114 years ago, and with this investment and manufacturing commitment we are ensuring that IBM remains the epicenter of the world’s most advanced computing and AI capabilities,” IBM CEO Arvind Krishna said in a release.   

The company’s announcement comes weeks after President Donald Trump unveiled a far-reaching and aggressive “reciprocal” tariff policy to boost manufacturing in the U.S. As of late April, Trump has exempted chips, as well as smartphonescomputers, and other tech devices and components, from the tariffs.

IBM said its investment will help accelerate America’s role as a global leader in computing and fuel the economy. The company said it operates the “world’s largest fleet of quantum computer systems,” and will continue to build and assemble them in the U.S., according to the release.

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IBM competitor Nvidia, the chipmaker that has been the primary benefactor of the artificial intelligence boom, announced a similar push earlier this month to produce its NVIDIA AI supercomputers entirely in the U.S. 

Nvidia plans to produce up to $500 billion of AI infrastructure in the U.S. via its manufacturing partnerships over the next four years.

Last week, IBM reported better-than-expected first-quarter results. The company said it generated $14.54 billion in revenue for the period, above the $14.4 billion expected by analysts. IBM’s net income narrowed to $1.06 billion, or $1.12 per share, from $1.61 billion, or $1.72 per share, in the same quarter a year ago.

IBM’s infrastructure division, which includes mainframe computers, posted $2.89 billion in revenue for the quarter, beating expectations of $2.76 billion.

The company announced a new z17 AI mainframe earlier this month.

CNBC’s Jordan Novet contributed to this report.

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Meta’s AI spending comes into focus amid Trump’s tariff policies

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Meta’s AI spending comes into focus amid Trump’s tariff policies

Meta CEO Mark Zuckerberg looks on before the luncheon on the inauguration day of U.S. President Donald Trump’s second Presidential term in Washington, U.S., Jan. 20, 2025. 

Evelyn Hockstein | Reuters

Mark Zuckerberg’s plan is to make Meta the market leader in artificial intelligence. Investors will want to know how President Donald Trump’s tariffs-heavy trade policies will impact that strategy. 

Those answers could start to come as soon as this week as Meta’s AI strategy takes center stage when the company hosts its first Llama-branded conference for AI developers on Tuesday then reports its latest quarterly earnings the next day.

Already, tech companies are starting to talk about the potential impact they’re bracing for as a result of the Trump tariffs. 

Intel Chief Financial Officer David Zinsner said Thursday during the chip giant’s first-quarter earnings call that U.S. trade policies “have increased the chance of an economic slowdown, with the probability of a recession growing.” Meanwhile, Google CFO Anat Ashkenazi said that day during a first-quarter earnings call that the tech giant remains committed to its $75 billion investment in capital expenditures, or capex, this year, but also acknowledged that the “timing of deliveries and construction schedules” could cause some quarter-to-quarter spending fluctuation. 

For now, analysts expect Meta to follow Alphabet’s lead and remain firm in its plan to spend as much as $65 billion in capex for AI infrastructure this year when it reports earnings Wednesday. Some analysts believe Meta could even raise the figure because AI is a core priority for the company.

“We do not expect META to cut its CapX guidance of $60B-$65B in 2025, for its GenAI infrastructure,  because they see this as an important 10-year investment, we believe,” Needham analysts wrote in a research note published Wednesday. “However, tariffs add risks of upward cost revisions.”

Investors will also be monitoring Meta’s LlamaCon event at its Menlo Park, California, headquarters for any signs that its AI investments are having an immediate business impact. This will be the first time Meta hosts a developer conference specifically for its Llama family of AI models.

“Investors want to see ROI on all these AI investments, and while Meta has shown clear benefits from leveraging AI to improve its products and drive faster revenue growth, it’s been hard to quantify those benefits,” Truist Securities analyst Youssef Squali told CNBC.

Meta in April released a couple of its new Llama 4 models, which Meta Chief Product Officer Chris Cox previously said can help power so-called AI agents that can perform tasks for users via web browsers and other online interfaces.

It’s critical that Meta keep improving Llama to create a major business involving AI agents that companies can use to interact with their customers within apps like Facebook and WhatsApp, William Blair research analyst Ralph Schackart said.

Meta has an early mover advantage at scale in a multi-trillion dollar market,” Schackart said in an email. “We believe Meta is very well positioned to leverage its billions of global users across multiple platforms.”

Meta is unlikely to curb its Llama investment any time soon, but should eventually consider doing so if it fails to generates enough money to justify its costs, said Ken Gawrelski, a Wells Fargo managing director of equity research.

“We do believe that over time Meta needs to continue to evaluate whether Llama needs to be competitive with the leading-edge models,” Gawrelski said. “This is a very expensive proposition and thus far, unlike Google, Meta does not directly monetize its model in any material way.”

Chris Cox, Chief Product Officer at Meta Platforms, speaks during The Wall Street Journal’s WSJ Tech Live Conference in Laguna Beach, California on October 17, 2023. 

Patrick T. Fallon | AFP | Getty Images

Meta AI and the consumer

Analysts are also following the Meta AI digital assistant. That’s because the ChatGPT rival represents the second pillar of Zuckerberg‘s AI strategy. 

Zuckerberg in January said he believes 2025 “is going to be the year when a highly intelligent and personalized AI assistant reaches more than 1 billion people, and I expect Meta AI to be that leading AI assistant.”

In February, CNBC reported that Meta was planning to debut a standalone Meta AI app during the second quarter and test a paid subscription service, in which users could pay monthly fees to access more powerful versions like users can with ChatGPT. 

Although Meta’s enormous user base across its family of apps gives Meta AI an advantage over rivals like ChatGPT in terms of reach, they may not interact with Meta AI in the same way they do with rival chat apps, said Cantor Fitzgerald analyst Deepak Mathivanan.

Gawrelski said that people may not want to use Meta AI within Facebook and Instagram if all they want to do is passively watch the short videos that Meta algorithmically recommends to their feeds.

“This is why a separate Meta AI, where Meta could clearly articulate its use case and value proposition, could be helpful,” Gawrelski said.

A standalone Meta AI app could help the company better market the digital assistant and distinguish it from rivals, said Debra Aho Williamson, founder and chief analyst for Sonata Insights.

“ChatGPT has such wide brand awareness, that it’s become a moat that is soon going to be very hard to overcome,” Williamson said.

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