Nvidia earnings scare away AMD, Intel investors as legacy chipmakers lose ground in AI

Published

2 years ago

August 24, 2023

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Justin Sullivan | Getty Images

Developers in the world of artificial intelligence can’t get enough of Nvidia’s processors. Demand is so strong that the company said late Wednesday that revenue in the current quarter will jump 170% to roughly $16 billion.

Nvidia shares rose more than 2% on Thursday before slumping towards the end of the day to finish flat and miss a record close, while the broader market had a rough day.

There’s a flipside to the story. AMD, Nvidia’s main rival in the market for graphics processing units (GPUs), is falling further behind, while chip giant Intel continues to miss out on the hottest trend in technology.

Shares of AMD and Intel fell 7% and 4%, respectively, following Nvidia’s fiscal second-quarter earnings announcement.

Nvidia’s blowout report and comments from executives suggesting that demand will remain high through next year is giving investors a reason to ask if the company has any serious competition when it comes to making the kind of GPUs needed to build and run large AI models.

Nvidia’s success also signals a shift in the market for data center chips. The most important — and generally most expensive — part of a data center buildout is no longer tied to central processors, or CPUs, made by Intel or AMD. Rather, it’s the AI-accelerating GPUs that big cloud companies are buying.

Alphabet, Amazon, Meta and Microsoft are snapping up Nvidia’s next-generation processors, which are so profitable that the company’s adjusted gross margin increased 25.3 percentage points to 71.2% in the period.

“NVDA Data Center revenues are now expected to be more than double INTC+AMD Data Center revenues combined, underscoring the growing importance of accelerators for today’s Data Center customers,” Deutsche Bank analyst Ross Seymore wrote in a note on Thursday.

Nvidia is now expected to post $12 billion in data center sales in the current quarter, according to FactSet data. Intel’s data center group is expected to post $4 billion in revenue, while analysts project AMD’s division will generate sales of $1.64 billion.

AMD and Intel are trying to stay relevant in the AI market, but it’s a struggle.

Intel CEO Pat Gelsinger said on the chipmaker’s earnings call in July that the company still sees “persistent weakness” in all segments of its business through year-end and that cloud companies were focusing more on securing graphics processors for AI instead of Intel’s central processors. Intel’s next high-end data center GPU, called Falcon Shores, is expected to be released in 2025. Its 2023 chip was cancelled.

AMD said on Thursday it acquired a French AI software firm called Mipsology. The company is also working on its own software suite for AI developers called ROCm to compete with Nvidia’s CUDA offering.

Like Intel, AMD faces a timing challenge. Earlier this year, it announced a new flagship AI chip, the MI300. But it’s currently only being shipped in small quantities, a process called “sampling.” The chip will hit the market next year.

“There is no meaningful competition for Nvidia’s high-performance GPUs until AMD starts shipping its new AI accelerators in high volumes in early 2024,” said Raj Joshi, senior vice president at Moody’s Investors Services, in an email.

The window is closing. While AMD and Intel are developing AI technology, they may find that all their big prospective customers have filled up on Nvidia chips before they can start shipping in large quantities.

“AI spending will be a material driver for several companies in our coverage,” Morgan Stanley analyst Joseph Moore wrote in a report. Moore cited AMD, Marvel and Intel as “having strong AI prospects.”

“But for those companies,” he wrote, “AI strength is going be offset by a crowding out of the budget.”

WATCH: Dethroning Nvidia?

Dethroning Nvidia? Competition in the hardware and software space

Technology

Spotify stock falls on revenue miss, lackluster guidance

Published

4 hours ago

July 29, 2025

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Spotify stock falls on revenue miss, lackluster guidance

Thomas Fuller | Lightrocket | Getty Images

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.

Samsung backs South Korean AI chip startup Rebellions ahead of IPO

Published

7 hours ago

July 29, 2025

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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.

AI chip startup Rebellions looks to raise up to $200 million ahead of IPO

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.

South Korean AI startup Rebellions says tariffs could delay IPO by 'a little bit'

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.

Technology

Europe sets its sights on multi-billion-euro gigawatt factories as it plays catch-up on AI

Published

10 hours ago

July 29, 2025

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Europe sets its sights on multi-billion-euro gigawatt factories as it plays catch-up on AI

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 the current 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.