by Nvidia, worth $3.01 trillion (€2.76 trillion) as of Thursday, overtook Apple as the world’s second most valuable company.
The firm’s share price rose more than 60 points, or five percent, on Wednesday to more than $1,224 (€1,125) per share. Nvidia is only the third company in the world, after Microsoft and Apple, to be valued at the trillion-dollar mark.
Nvidia has been designing semiconductors, or microchips, since 1993; first for video game consoles and now for the generation of artificial intelligence (GenAI) companies.
The big question now is can any European companies compete with Nvidia’s meteoric rise?
Who’s who in the booming AI microchip industry
Microchips are the engines that power the world’s largest technology companies and their AI divisions.
There are five distinct types of companies in the semiconductor market, according to Cem Dilmegani, principal analyst with consulting company AIMultiple.
At the bottom of the industry are those who create the engines needed to mass-produce microchips, including the Dutch company Advanced Semiconductor Materials Lithography (ASML), which is worth €361.67 billion.
Then, foundry companies like Taiwan Semiconductor Manufacturing Company (TSMC) use these machines to manufacture the chips that other design companies, like Nvidia, will refine for AI models. The largest global players at this level of the semiconductor industry are located in China, South Korea, and Taiwan.
Next up are design companies like Nvidia who, according to the company’s website, “engineer the most advanced chips, systems and software for the AI factories of the future.”
The big tech companies then buy those engineered chips—from France’s Mistral AI to Big Tech giants Amazon, Google, Meta, and Microsoft—to program the big language models (LLMs) that power AI.
Nvidia specializes in particular in graphics processing unit (GPU) chips that produce higher quality images than the central processing units (CPUs) that their American competitors Intel and Advanced Micro Devices (AMD) are known for.
These GPUs are able to perform calculations in a way that CPU chips cannot, which means they can better handle the kind of work that AI companies need.
For companies that can get their hands on Nvidia chips, it also means they’ll need fewer staff to train their languages, according to Dilmegani.
“It’s going to need a lot more work and you’re going to have to put more engineers on it,” he said. “You may need more computer time or the [language] the model may be running slowly”.
‘We create a whole ecosystem’
Serge Palaric, VP EMEA for Nvidia, joined the company in 2004 when they were still designing GPU chips for video consoles like the Xbox.
Then, by 2006, Nvidia launched Compute Unified Device Architecture (CUDA), their own programming language for their GPU chips. It’s now a deep learning program that companies can buy software alongside the engineering chips.
Palaric attributes his company’s rise in the semiconductor market to the hardware he has designed and the software that simplifies the work of these large technology companies.
“We’re not selling chips, we’re selling software,” Palaric said. “We create a whole ecosystem so that we can address and support those enterprises that want to move here [generative] AI”.
In 2012, Nvidia and the University of Toronto discovered that GPUs make deep learning—the kind of learning that powers today’s AI—more accurate. From there, the race was on within Nvidia to make way for the eventual AI boom.
So, when ChatGPT OpenAI started in 2022, Palaric said Nvidia was not surprised and was ready to meet the moment.
“ChatGPT was developed over 10,000 GPUs so we knew what was coming,” said Palaric. “We’re always looking at what’s the next step, how do we do it, [and] how we help our partners do it”.
On June 2, both AMD and Intel Announced new AI processors to recapture some of the market share from Nvidia, which controls about 80 percent of the market for chip design.
‘Nvidia is in a class of its own’
Based on market share alone, ASML is Europe’s largest player in the AI semiconductor industry, according to Dilmegani.
But, because Nvidia engineers provide the GPU and ASML chips of the machines to those who manufacture them, it is not accurate to equate the dominance of ASML and Nvidia in their respective parts of the industry, according to Michelle Brophy, Director of Research at AlphaSense, an AI-powered market platform .
“None of the Europeans are close [Nvidia’s market cap] at all,” Brophy told Euronews Next. “They will find their niche areas but Nvidia is in a class of its own”.
In theory, Dilmegani said ASML could scale vertically to begin designing its own microchip technology. However, it would be “strange” and “very complicated” because it will then compete with other chip manufacturing companies that make up its client base.
Where ASML is competitive, according to Brophy, is in helping TSMC improve its chip manufacturing. The Taiwanese manufacturer has said publicly that it wants to start making 2-nanometer chips by 2025, offering chips with processing times 10 to 15 percent faster than the advanced 3-nanometer chips currently on the market.
Brophy said the only way [TSMC] can be found there” is to work with ASML.
Elsewhere, two European companies are already designing semiconductor chips: Germany’s Infineon and France-Italy’s STMicroelectronics, Brophy said.
Both companies work on CPU microchips specifically for the automotive industry and have not publicly indicated that they will be taking on Nvidia.
Brophy said it would not be wise for them to do so.
“They would have a lot of work ahead of them,” Brophy said. “If they were to take the next step towards AI, it would probably be in the processing side”.
Euronews Next contacted both Infineon and STMicroelectronics but did not receive a response from either company at the time of publication.
‘We are not taking many risks’
If European companies or start-ups want to be competitive in the industry, they need to develop a niche in another part of the semiconductor market such as ASML, according to Dilmegani and Brophy.
Alternatively, they should develop the necessary relationships so that leading chip design companies like Nvidia or AMD consider moving their operations to the continent.
Brophy cited a recent deal with Intel in Germany as an example of areas where Europe could invest more.
In 2023, Intel and Germany signed a €30 billion deal to create a microchip factory in Magdeburg, but the deal is still pending approval from the European Union, according to Politics.
An EU spokesperson told Euronews Next that the Union is unable to comment on the progress of this agreement.
The goal of companies like Intel investing in European chip manufacturing plants is to move away from dependence on TSMC, the largest chip manufacturer, because of political tensions between the West and China, Brophy said.
Nvidia’s Palaric said the company will continue to rely on TSMC for its chips.
What Nvidia is doing in Europe is investing in AI startups like France’s Mistral AI, the UK’s Synthesis, and Northern Germany’s Data Group AI Accelerator.
Their goal, according to Palaric, is to provide companies with the technology they need to develop their own languages.
Any startups trying to design chips like Nvidia will probably need at least a decade, according to Dilmegani, to grow their presence enough to be competitive.
“Startups need to think about where technology is going and take bold bets and make machines that are different than other processors,” said Dilmegani.
“But you need an ecosystem for these companies to thrive… and in the EU, we’re not accepting [many] risks in that aspect”.
