By Toby Sterling
AMSTERDAM (Reuters) – The European Commission is raising $20 billion to construct four “AI gigafactories” as part of Europe’s strategy to catch up with the U.S. and China on artificial intelligence, but some industry experts question whether it makes sense to build them.
The plan for the large public access data centres, unveiled by European Commission President Ursula von der Leyen last month, will face challenges ranging from obtaining chips to finding suitable sites and electricity.
“Even if we would build such a big computing factory in Europe, and even if we would train a model on that infrastructure, once it’s ready, what do we do with it?,” said Bertin Martens, of economic think tank Bruegel.
It’s a chicken and egg problem. The hope is that new local firms such as France’s Nvidia-backed Mistral start-up will grow and use them to create AI models that operate in line with EU AI safety and data protection rules, which are stricter than those in the U.S. or China.
But in the absence of large European cloud services businesses like Google and Amazon, or firms with millions of paying customers, like ChatGPT maker OpenAI, building hardware on this scale is a risky venture.
EUROPE’S ANSWER TO STARGATE
The gigafactory plan is part of Europe’s response to the Draghi report on competitiveness, which advised bold investments and a more active industrial policy. Von der Leyen released details for the first time at the February 11 AI summit in Paris as part of InvestAI, Europe’s 200 billion euro ($216.92 billion) answer to the $500 billion U.S. Stargate plan.
She described gigafactories as a “public-private partnership … (that) will enable all our scientists and companies – not just the biggest – to develop the most advanced very large models needed to make Europe an AI continent.”
They are to be financed via a new 20 billion-euro fund, with money being drawn from existing EU programmes, and from member states. The European Investment Bank will participate.
Von der Leyen said gigafactories will contain 100,000 “cutting-edge” chips each — making them more than four times larger than the biggest supercomputer currently under construction in the EU, the Jupiter project in Germany. U.S. chipmaker Nvidia sells the cutting-edge GPU chips needed to train AI for around $40,000 each — implying a price tag of several billion euros per gigafactory.
While that’s big, it still trails projects announced by U.S. firms. Facebook owner Meta is spending $10 billion to build a 1.3 million GPU facility in Louisiana powered by 1.5 gigawatts of electricity.
