Intel’s CEO Lip-Bu Tan speaks at the company’s Annual Manufacturing Technology Conference in San Jose, California, U.S. April 29, 2025.
Laure Andrillon | Reuters
When Lip-Bu Tan was named CEO of Intel a little over two months ago, he brought with him plenty of name recognition. Tan spent 12 years running Cadence Design Systems and before that was a prominent venture capitalist. He’s also held board seats at SoftBank and Hewlett Packard Enterprise.
“Lip-Bu’s Rolodex is like nobody else’s in the semiconductor industry,” Intel CFO David Zinsner said at a financial conference this month. Zinsner said Tan recently met with 22 potential customers and partners in a single day.
At age 65, Tan is going to need more than a vast database of contacts and four decades of operating and investing experience to turn around the company that put the silicon in Silicon Valley but is struggling to stay relevant in a market that’s increasingly centered around artificial intelligence.
Once the world’s largest chipmaker, Intel has lost 70% of its value since early 2020. It’s roughly flat since Tan was named as CEO on March 12.
Tan’s jam-packed schedule in large part reflects a need to change the industry’s perception of Intel. No longer the dominant player in semiconductors, Intel is trying to pivot into chip manufacturing, especially as the U.S. focuses on investing in onshoring critical technologies. Tan has been listening to customers to find out specific technical requirements they would need from Intel as a foundry, he’s said in public remarks.
Under Tan’s predecessor, Pat Gelsinger, Intel spent $90 billion between 2021 and 2024 on building the company’s foundry operations and unlocking additional U.S. government funding. Capital expenditures in 2025 are expected to reach $18 billion.
Investors, and eventually the board, lost trust in Gelsinger’s ability to generate much of a return on that investment, leading to his ouster late last year. In an industry where roadmaps and capital plans are measured in five-year increments, Tan is under pressure to start building confidence immediately.
“The foundry business, it operates at a different time scale,” said Alvin Nguyen, an analyst at Forrester. “It operates with a level of investment that is tough to stomach, and very few publicly traded companies can deal with it.”
Intel faces a plethora of other challenges that all predate Tan’s tenure. The company’s central processors, or CPUs, that for decades were the most expensive and important part in computers, have been supplanted by AI chips, primarily graphics processing units, or GPUs, from Nvidia. Meanwhile, Advanced Micro Devices has picked up substantial market share in CPUs and server chips, and Qualcomm has emerged as a big challenger as well.
Tan is working on an AI strategy under Sachin Katti, who was named chief technology officer in April after joining the company in 2021.
Tan was born in Malaysia and raised in Singapore. He moved to the U.S. in the 1970s and studied nuclear engineering at the Massachusetts Institute of Technology. He’s since touched just about every aspect of the chip industry.
Before joining Intel, he was CEO of Cadence, which makes electronic design automation, or EDA, software, widely used by engineers at fabless chip companies to design new processors. As a venture capitalist at Walden International, Tan invested in Semiconductor Manufacturing International Corporation, China’s national foundry, in 2001, and was on the board for over a decade.
He’s now betting on Intel, not just with his time but also his wallet. When he became CEO, he bought $25 million of shares, which he’ll have to hold in order to earn his full compensation over the next five years.
Tan has been keeping a fairly low profile since starting the gig in March. He’s yet to sit for a press interview, and Intel declined to make Tan available for this story. But in his two public speeches as CEO at Intel events, he’s laid out elements of his strategy.
“We need to do a better job — make it easier for all of you to use our technology,” Tan said at a foundry event earlier this month. “We will rapidly embrace industrial standards, EDA tools and best design practices.”
One big customer
The fastest way to change the trajectory would be to announce a big foundry customer. Locking in substantial orders would serve as both a vote of approval to other potential customers and a signal to Wall Street that all those expenses will soon start turning into revenue.
“One Nvidia, one Qualcomm, one Apple, one something of volume that really shows this meaningful commitment for the fab to build significant volume would really change the whole narrative,” said Daniel Newman, CEO of industry research firm The Futurum Group.
Tan’s second public appearance as CEO came in April at Intel’s Foundry Direct Connect event in San Jose, California, a few miles from the company’s headquarters. There he hinted at one of his key objectives: rebuilding confidence.
“This is a truly a service business, and that is built on the foundational principle of trust,” Tan said. “You have to be patient to earn your trust.”
Intel wafers are displayed on stage at the company’s Annual Manufacturing Technology Conference in San Jose, California, U.S. April 29, 2025.
Laure Andrillon | Reuters
At the event, populated largely by people from the insular world of chip design and manufacturing, Tan directly addressed foundry customers, discussing the company’s specific technologies in power and packaging that put it in position to take on Taiwan Semiconductor Manufacturing Company, the largest foundry in the world.
Outside the convention center, banners still hung promoting the Nvidia GTC conference, which had taken place the prior month and packed the building’s ballroom.
Tan mostly acted like an emcee, calling up the CEOs of chip design partners such as Synopsys, Cadence and Siemens, who took the stage to discuss using Intel’s technology.
A key issue for Intel to address is the broadening of its foundry, which was originally designed for its own chip design teams, meaning some of the tools and infrastructure were company-specific. Intel has given the name 18A to its chip technology that it hopes to start producing in volume this year.
“One thing about 18A was, it was developed initially as just something for Intel, and we intercepted it relatively early,” Zinsner said earlier this month. That allowed the company to develop process design kits, or PDKs, “for the industry, but it still was not from the ground up developed as a foundry node,” he said.
Zinsner said the company’s next chip generation, 14A, will be built for external customers. Analysts say that 18A may be Intel’s first foundry process that could beat TSMC’s rival process to market.
Tan also recognizes that TSMC has created an industry standard, so using the same tools and technology would allow companies to more simply bring over work from other foundries. He said Intel is making its PDK easier to use.
“My top priority is to make it easier for the ecosystem to do business with Intel,” he said.
One of the speakers at the event was Anirudh Devgan, who succeeded Tan as CEO of Cadence. Tan asked Devgan what AI chip companies need to see if they’re to build on Intel. Devgan said the most important consideration is the need to focus on what the customer wants rather than what Intel prefers.
“Intel Foundry, as you all know, is like the service business, so the customer comes first,” Devgan said. “I know Lip-Bu has very good instincts to understand what the customer wants.”
It’s a stark change in approach for a company that for decades was focused on selling its own chips and not on creating an ecosystem. In a podcast earlier this year, TSMC founder Morris Chang said that Intel, during its glory years, acted “like they were the only guy with microprocessors.”
If there was a disappointment at the Intel event, it was the lack of an announcement about a major new customer.
Zinsner previously said, in response to a question about how many customers Intel had signed up for its foundry, that the company first needs to “eat its own dogfood,” indicating that the 18A process would be primarily used by Intel itself.
Leaner company
While Tan looks outward for business development, he’s turning inward to try to fix corporate culture, flattening the organization, which grew fiercely in recent years as it staffed up to build the foundry unit.
Intel said on its April earnings call that job cuts will come this quarter, though the company didn’t provide a specific number. An Intel representative declined to comment on the matter. Intel announced in August, while Gelsinger was still in charge, that it was laying off 15,000 employees and would explore cuts in its portfolio.
Wall Street welcomes more belt tightening but warns that the company can’t cut its way to a successful revival.
Deutsche Bank’s Ross Seymour, who recommends holding the stock, wrote in a May note that, even with the “welcome and necessary cost-cutting actions,” the company’s “path to meaningful earnings/free cash flow generation remains cloudy and highly dependent on a turnaround” in the foundry business.
Equally important to Tan is getting rid of what he views as too much bureaucracy.
“It has been eye-opening for me to see how much time and energy is spent on internal administrative work that does not move our business forward,” Tan wrote, in a memo to employees in April.
He said Intel would have to learn how to do more with fewer people and that employees must be back in the office for at least four days a week by September.
“I’ve been surprised to learn that, in recent years, the most important KPI for many managers at Intel has been the size of their teams,” Tan wrote, referring to key performance indicators. “Going forward, this will not be the case.”
Tan also promoted several engineering leaders, giving him greater visibility into the organization. Zinsner said Tan has between 15 and 17 direct reports, because he wants to be closer to the “lowest” levels of the organization.
“He’s hearing the good, the bad, the ugly of what’s going on, so that he can help address those,” Zinsner said.
Spotify shares dropped about 4% Tuesday after the music streaming platform fell short of Wall Street’s expectations and posted weak guidance for the current quarter.
Here’s how the company did versus LSEG estimates:
Loss: Loss of .42 euros vs earnings of 1.90 euros per share expected
Revenue: 4.19 billion euros vs. 4.26 billion expected
The Sweden-based music platform’s revenues rose 10% from about 3.81 billion euros in the year-ago period. The company posted a net loss of 86 million euros, or a loss of .42 euros per share, down from net income of 225 million euros, or 1.10 euros per share a year ago.
Third-quarter guidance came up short of Wall Street’s forecast.
The company expects revenues to reach 4.2 billion euros, compared to a 4.47 billion euro estimate from StreetAccount. Spotify said the forecast accounts for a 490-basis-point headwind due to foreign exchange rates.
Read more CNBC tech news
Monthly active users on the platform jumped 11% to 696 million, while paying subscribers rose 12% from a year ago to 276 million.
For the current quarter, Spotify said it expects to reach 710 million monthly active users, with 14 million net adds. The company expects 5 million net new premium subscribers in the third quarter to reach 281 million subscriptions.
During the period, Spotify said it rolled out a request feature for its artificial intelligence DJ. The company said engagement with the offering has roughly doubled over the last year.
In 2024, Spotify posted its first full year of profitability. Shares are up 57% this year.
The Rebel-Quad is the second-generation product from Rebellions and is made up of four Rebel AI chips. Rebellions, a South Korean firm, is looking to rival companies like Nvidia in AI chips.
Rebellions
South Korean artificial intelligence chip startup Rebellions has raised money from tech giant Samsung and is targeting a funding round of up to $200 million ahead of a public listing, the company’s management told CNBC on Tuesday.
Last year, Rebellions merged with another startup in South Korea called Sapeon, creating a firm that is being positioned as one of the country’s promising rivals to Nvidia.
Rebellions is currently raising money and is targeting funding of between $150 million and $200 million, Sungkyue Shin, chief financial officer of the startup, told CNBC on Tuesday.
Samsung’s investment in Rebellions last week was part of that, Shin said, though he declined to say how much the tech giant poured in.
Since its founding in 2020, Rebellions has raised $220 million, Shin added.
The current funding round is ongoing and Shin said Rebellions is talking to its current investors as well as investors in Korea and globally to participate in the capital raise. Rebellions has some big investors, including South Korean chip giant SK Hynix, telecommunication firms SK Telecom and Korea Telecom, and Saudi Arabian oil giant Aramco.
Rebellions was last valued at $1 billion. Shin said the current round of funding would push the valuation over $1 billion but declined to give specific figure.
Rebellions is aiming for an initial public offering once this funding round has closed.
“Our master plan is going public,” Shin said.
Rebellions designs chips that are focused on AI inferencing rather than training. Inferencing is when a pre-trained AI model interprets live data to come up with a result, much like the answers that are produced by popular chatbots.
With the backing of major South Korean firms and investors, Rebellions is hoping to make a global play where it will look to challenge Nvidia and AMD as well as a slew of other startups in the inferencing space.
Samsung collaboration
Rebellions has been working with Samsung to bring its second-generation chip, Rebel, to market. Samsung owns a chip manufacturing business, also known as foundry. Four Rebel chips are put together to make the Rebel-Quad, the product that Rebellions will eventually sell. A Rebellions spokesperson said the chip will be launched later this year.
The funding will partly go toward Rebellions’ product development. Rebellions is currently testing its chip which will eventually be produced on a larger scale by Samsung.
“Initial results have been very promising,” Sunghyun Park, CEO of Rebellions, told CNBC on Tuesday.
Park said Samsung invested in Rebellions partly because of the the good results that the chip has so far produced.
Samsung is manufacturing Rebellions’ semiconductor using its 4 nanometer process, which is among the leading-edge chipmaking nodes. For comparison, Nvidia’s current Blackwell chips use the 4 nanometer process from Taiwan Semiconductor Manufacturing Co. Rebellions will also use Samsung’s high bandwidth memory, known as HBM3e. This type of memory is stacked and is required to handle large data processing loads.
That could turn out to be a strategic win for Samsung, which is a very distant second to TSMC in terms of market share in the foundry business. Samsung has been looking to boost its chipmaking division. Samsung Electronics recently entered into a $16.5 billion contract for supplying semiconductors to Tesla.
If Rebellions manages to find a large customer base, this could give Samsung a major customer for its foundry business.
Data storage tapes are stored at the National Energy Research Scientific Computing Center (NERSC) facility at the Lawrence Berkeley National Laboratory, which will house the U.S. supercomputer to be powered by Nvidia’s forthcoming Vera Rubin chips, in Berkeley, California, U.S. May 29, 2025.
Manuel Orbegozo | Reuters
Europe is setting its sights on gigawatt factories in a bid to bolster its lagging artificial intelligence industry and meet the challenges of a rapidly-changing sector.
Buzz around the concept of factories that industrialize manufacturing AI has gained ground in recent months, particularly as Nvidia CEO Jensen Huang stressed the importance of the infrastructure at a June event. Huang hailed a new “industrial revolution” at the GTC conference in Paris, France, and said his firm was working to help countries build revenue-generating AI factories through partnerships in France, Italy and the U.K.
For its part, the European Union describes the factories as a “dynamic ecosystem” that brings together computing power, data and talent to create AI models and applications.
The bloc has long been a laggard behind the U.S. and China in the race to scale up artificial intelligence. With 27 members in the union, the region is slower to act when it comes to agreeing new legislation. Higher energy costs, permitting delays and a grid in dire need of modernization can also hamper developments.
Henna Virkkunen, the European Commission’s executive vice president for tech sovereignty, told CNBC that the bloc’s goal is to bring together high quality data sets, computing capacity and researchers, all in one place.
“We have, for example, 30% more researchers per capita than the U.S. has, focused on AI. Also we have around 7,000 startups [that] are developing AI, but the main obstacle for them is that they have very limited computing capacity. And that’s why we decided that, together with our member states, we are investing in this very crucial infrastructure,” she said.
These are very big investments because they are four times more powerful when it comes to computing capacities than the biggest AI factories.
Henna Virkkunen
European Commission’s executive vice president for tech sovereignty
“We have everything what is needed to be competitive in this sector, but at the same time we want to build up our technological sovereignty and our competitiveness.”
So far, the EU has put up 10 billion euros ($11.8 billion) in funding to set up 13 AI factories and 20 billion euros as a starting point for investment in the gigafactories, marking what it says is the “largest public investment in AI in the world.” The bloc has already received 76 expressions of interest in the gigafactories from 16 member states across 60 sites, Virkkunen said.
The call for interest in gigafactories was “overwhelming,” going far beyond the bloc’s expectations, Virkkunen noted. However, in order for the factories to make a noteworthy addition to Europe’s computing capacity, significantly more investment will be required from the private sector to fund the expensive infrastructure.
‘Intelligence revolution’
The EU describes the facilities as a “one-stop shop” for AI firms. They’re intended to mirror the process carried out in industrial factories, which transform raw materials into goods and services. With an AI factory, raw data goes into the input, and advanced AI products are the expected outcome.
It’s essentially a data center with additional infrastructure related to how the technology will be adopted, according to Andre Kukhnin, equity research analyst at UBS.
“The idea is to create GPU [graphics processing units] capacity, so to basically build data centers with GPUs that can train models and run inference… and then to create an infrastructure that allows you to make this accessible to SMEs and parties that would not be able to just go and build their own,” Kukhnin said.
How the facility will be used is key to its designation as an AI factory, adds Martin Wilkie, research analyst at Citi.
“You’re creating a platform by having these chips that have insane levels of compute capacity,” he said. “And if you’ve attached it to a grid that is able to get the power to actually use them to full capacity, then the world is at your feet. You have this enormous ability to do something, but what the success of it is, will be defined by what you use it for.”
Telecommunications firm Telenor is already exploring possible use cases for such facilities with the launch of its AI factory in Norway in November last year. The company currently has a small cluster of GPUs up and running, as it looks to test the market before scaling up.
Telenor’s Chief Innovation Officer and Head of the AI Factory Kaaren Hilsen and EVP Infrastructure Jannicke Hilland in front of a Nvidia rack at the firm’s AI factory
Telenor
“The journey started with a belief — Nvidia had a belief that every country needs to produce its own intelligence,” Telenor’s Chief Innovation Officer and Head of the AI Factory Kaaren Hilsen told CNBC.
Hilsen stressed that data sovereignty is key. “If you want to use AI to innovate and to make business more efficient, then you’re potentially putting business critical and business sensitive information into these AI models,” she said.
The company is working with BabelSpeak, which Hilsen described as a Norwegian version of ChatGPT. The technology translates sensitive dialogues, such as its pilot with the border police who can’t use public translation services because of security issues.
We’re experiencing an “intelligence revolution” whereby “sovereign AI factories can really help advance society,” Hilsen said.
Billion-euro investments
Virkkunen said the region’s first AI factory will be operational in coming weeks, with one of the biggest projects launching in Munich, Germany in the first days of September. It’s a different story for the gigafactories.
“These are very big investments because they are four times more powerful when it comes to computing capacities than the biggest AI factories, and it means billions in investments. Each of these need three to five billion [euros] in investment,” the commissioner said, adding that the bloc will look to set up a consortium of partners and then officially open a call for investment later this year.
Bertin Martens, senior research fellow at Bruegel, questioned why such investments needed to subsidized by government funds.
“We don’t know yet how much private investment has been proposed as a complement to the taxpayer subsidy, and what capacity and how big these factories are. This is still very much unclear at this stage, so it’s very hard to say how much this will add in terms of computing capacity,” he said.
Power consumption is also a key issue. Martens noted that building an AI gigafactory may take one to two years — but building a power generation of that size requires much more time.
“If you want to build a state-of-the-art gigafactory with hundreds of thousands of Nvidia chips, you have to count on the power consumption of at least one gigawatt for one of those factories. Whether there’s enough space in Europe’s electricity grid in all of these countries to create those factories remains to be seen… this will require major investment in power regeneration capacity,” he told CNBC.
UBS forecasts that thecurrent installed global data center capacity of 85 GW will double due to soaring demand. Based on the EU’s 20-billion-euro investment and the plan for each factory to run 100,000 advanced processors, UBS estimates each factory could be around 100-150 MW with a total capacity for all of the facilities of around 1.5-2 GW.
That could add around 15% to Europe’s total capacity — a sizeable boost, even when compared to the U.S., which currently owns around a third of global capacity, according to the data.
Following the announcement of the EU-U.S. trade framework, EU chief Ursula von der Leyen said Sunday that U.S. AI chips will help power the bloc’s AI gigafactories in a bid to help the States “maintain their technological edge.”
“One could argue that it’s relatively easy, provided you have the money. It’s relatively easy to buy the chips from Nvidia and to create these hardware factories, but to make it run and to make it economically viable is a completely different question,” Martens told CNBC.
He said that the EU will likely have to start at a smaller scale, as the region is unable to immediately build its own frontier models in AI because of their expense.
“I think in time, Europe can gradually build up its infrastructure and its business models around AI to reach that stage, but that will not happen immediately,” Martens said.