according to the materials of the website - By Cryptopolitan_News
SAP CEO Christian Klein was upset by the idea that Europe needs to catch up with the rest of the world by building more data centers equipped with powerful chips.
Speaking to reporters at a press conference at SAP's headquarters in Walldorf, Germany, Klein highlighted comments made by Nvidia CEO Jensen Huang during his high-profile European tour.
"Do we really need to build five data centers and install great chips there? Is that what Europe needs? I doubt it," Klein said.
Huang, whose company is a leader in the artificial intelligence chip market, stated at an event in June that Europe is losing ground in artificial intelligence because it lacks sufficient computing power.
During his visit, Huang announced several partnerships that would help build this artificial intelligence infrastructure on the continent, all based on Nvidia technologies. He urged European leaders to take the same step that American tech giants have taken by investing huge sums into many sectors for greater processing power.
However, Klein argues that such an approach would be a mistake for Europe. For him, the power of the continent lies in its industrial base, automotive manufacturing, production, chemistry, engineering, etc., rather than in the ability to go head-to-head with American tech titans in the race for the bottom of raw computing.
Instead of trying to mimic the Silicon Valley hardware-focused strategy, Klein said that Europe should focus on creating smart AI applications that will serve its core industries.
SAP is moving away from the ambitions of gigafactories.
Klein's statements indicate a radical shift in SAP's strategy regarding AI. Just six months ago, he said he fully supported Europe building its own AI 'gigafactories' - massive facilities for training and scaling AI models. At the World Economic Forum in Davos in January, he called the U.S. efforts on the 'Stargate' project a 'great model to emulate' for Europe. At that time, he vowed to 'fully support' similar European efforts.
SAP has been negotiating behind the scenes with other German companies for joint investments in one of the series of EU-supported AI gigafactories. But ultimately, the discussions fell apart. According to SAP's head of customer service and supply Thomas Saueressig, it turned into 'nothing' due to differences in views and short-term prospects.
This week, SAP clarified that it is no longer interested in investing or operational participation in such megaprojects. Instead, it wants to support such initiatives as a technology and software provider, supplying tools, platforms, and customizable AI applications for those involved in infrastructure.
Earlier this year, the European Union committed to spending 20 billion euros ($23 billion) to create five AI gigafactories. While the ambitions are clear, SAP's withdrawal highlights the growing skepticism among European industrial leaders regarding attempts to copy the American model of AI supremacy.
Developers are embracing open-source AI for faster innovations.
Klein also questioned the long-term value of the race for training huge proprietary AI models. Instead, he sees a movement towards cheaper open-source alternatives. He cited the Chinese company DeepSeek, which recently made headlines for outpacing leading American AI companies using a model built on open-source code, trained at a fraction of the cost.
Klein stated that the success of open-source models demonstrates that it is not necessary to have unlimited computing power or billion-dollar budgets to develop effective AI solutions. He emphasized that intelligent, optimized models that fit the market and work well in real business environments are what matter.
He suggested that the days of monolithic AI infrastructure are coming to an end. Now that models have become mainstream, an important question will be how effectively companies apply these tools to solve real problems.
SAP's priority is integrating AI capabilities into enterprise software systems. Klein wrote about workflows using AI for logistics, predictive maintenance of factory equipment, intelligent bots for customer service, and real-time decision-making panels for supply chain managers.
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