Why Jensen Huang and NVIDIA's Full-Stack AI Factory Cannot Help European Artificial Intelligence

"To become part of the AI economy, you cannot just be a consumer of AI; you have to be a producer of AI." At the recent GTC Berlin conference, Nvidia founder Jensen Huang issued this call to Germany and Europe. Huang's European tour took him to several countries, including France, the UK, and Germany. Huang hopes Europe will embrace his AI factories. He positions them as an integrated platform for building and operating AI infrastructure, calling them "the foundation for how we help Europe integrate into the AI ecosystem and participate in the AI economy." Huang's full-stack AI factories do indeed have the potential to become the technological base for European enterprises. But in Nvidia's partnerships with numerous European companies such as Siemens, Porsche, and L'Oréal, the latter are recipients of AI technology rather than co-creators of new technology. Huang and Nvidia can offer only very limited help for the technological flourishing of homegrown European AI. The core reason is not that Nvidia's technology is insufficiently advanced, but precisely that Nvidia is too powerful. The full-stack AI factories Nvidia delivers to Europe are integrated platforms rather than single high-performance chips. This system covers GPU hardware, CUDA-X libraries, and models. European companies are unable to participate in building these high-performance chips, CUDA-X, or the model layer. Even if European companies adopt it, all they can do is have companies like Germany's Siemens or France's L'Oréal build their own application layers on top of it. Nor can Nvidia stimulate European companies to develop similar competing products. Nvidia's capabilities are so outstanding that almost no European company competes with it head-on. This is very different from the situation in the US and China. The US has AMD and Intel developing accelerator cards, and internet giants Amazon and Google also develop their own dedicated chips; China, subject to high-end chip import restrictions, is growing a domestic computing ecosystem made up of companies such as Huawei, Cambricon, and MetaX. Market competition stimulates technological progress and economic development. Nvidia's hefty profits are obvious and should attract more European companies to compete on the same stage. But European companies seem to have given up their ambitions and are unwilling to step up and fight. The same is true of chips, and similarly of large models. As far as I know, some large German companies operating in China connect at the underlying level either to models from America's Anthropic and OpenAI or to Chinese Alibaba models. Europe's representative model company is France's Mistral AI, but it currently shows no sign of gaining global recognition. Europe's workplace environment is also not conducive to technological iteration. A Chinese researcher who visited Mistral AI told me that while researchers in China and the US burn the midnight oil pushing large models to the frontier, Mistral AI's employee vacation policy seems overly lavish. Europe's AI talent pipeline is not as abundant as that of the US and China. Nokia was once at its zenith in mobile phones, and Siemens also once had a mobile phone business, but both missed the mobile internet wave, and the corresponding software and hardware talent lost the soil to grow in Europe. New technologies and innovative companies do not arise out of thin air; creators often come from the previous generation of technology and industry. The Transformer architecture that laid the foundation for AI was born from the hands of Google employees, and Google was the king of the mobile internet era. The career résumé of Anthropic founder Dario Amodei even includes Baidu, Google, and OpenAI. Financing for European startups is also less convenient than in China and the US. Huang said he will recently add another $2 billion in investment in Europe, having already invested $8 billion there. This may make Nvidia the largest investor in European AI and ease local startups' financing difficulties. This money is spread across multiple countries including France, Germany, and the UK, involving more than a dozen or even dozens of companies, so the average amount each company receives will not be large. The companies Nvidia invests in are mostly in application scenarios for Nvidia products such as healthcare, business software, and robotics. The key to AI lies in chips, models, and data. US companies in these fields routinely raise billions or tens of billions of dollars—for example, OpenAI is now seeking $30 billion in financing; Chinese company MetaX raised over 10 billion RMB before its listing, and DeepSeek is rumored to be raising 100 billion RMB. Even if AI seedlings are born in Europe, they will not easily find sufficient funding locally in Europe comparable to that in the US and China. In 2014, when DeepMind was acquired by Google, Europe's AI financing predicament was already evident. The company was founded in the UK, and founder Demis Hassabis tried to keep it independent, but it was difficult to obtain venture capital support in the UK, Europe's financial center, and only afterward was it taken in by Google. Demis Hassabis also joined Google and in 2024 won the Nobel Prize in Chemistry for "protein structure prediction." The US and China are the two major centers of this wave of AI, while Europe is in a relatively marginal position, caused by multiple factors including historical industrial ruptures, insufficient talent accumulation, and a lack of funding. Huang hopes Nvidia's AI factories will be embraced by European companies, and he has also brought a large sum of money. But these have limited effect on generating a homegrown AI ecosystem in Europe. It seems a difficult task for European AI to catch up with the US or China. The best approach for European companies remains to embrace US and Chinese technology and attempt breakthroughs at the application layer. Some European companies have already been actively setting up robotics research centers in China, conducting R&D together with Chinese companies to connect the links of this emerging industry. Europe should no longer over-regulate artificial intelligence, especially when the US and China prioritize technological progress rather than regulation. Necessary regulation is for safety, but excessive regulation may be needless worry and shut innovation out. As Huang said, if an industry has not even developed, then there is nothing to regulate.