Newsletter

How should the EU position itself in the AI technology race?

Publishing date
14 October 2024
Authors
Bertin Martens
feat image
title nl

Generative artificial intelligence (GenAI) models, such as ChatGPT, have become a general-purpose technology with applications in every economic activity. But artificial intelligence (AI) model training costs are growing exponentially and will reach billions of euros in the next years. Global AI computing infrastructure costs may reach a trillion euros. However, productivity gains from AI are growing at a much slower place because they take more time. Unless new technologies can slow down the cost explosion or accelerate productivity growth, this may put a brake on AI innovation.    

The European Commission’s ‘AI Factories’ initiative and Draghi’s AI proposals suggest that the EU aims to catch up with the US by upgrading existing EuroHPC supercomputers. This hardware focus, at the expense of a wider economic view, has characterised EU digital policies for decades. In a forthcoming Policy brief, we show how this is especially misguided in AI. EuroHPC computers are not designed for GenAI models. Upgrading to competitive standards is simply beyond the financial capacity of EU budgets. They lack access to large-scale business models that can generate the revenue required to amortise the huge cost of frontier AI models.  

The EU can prosper below the AI technology frontier. It can use existing open-source and commercial state-of-the-art AI models to produce derived, specialised models and AI application services at much lower costs. They can be rolled-out across sectors and embedded in smaller EU companies with sufficient revenue to bear the investment costs. This private sector approach would contribute more to accelerating EU productivity growth than betting taxpayer money on a few super-expensive supercomputers and AI models. It would give the EU time to address missing or poorly functioning complementary markets, including private equity for AI start-ups and put its regulatory house in order with a razor-sharp focus on competitiveness and innovation.  

Read the working paper by Bertin Martens on the exploding costs of AI model development and keep an eye out for the forthcoming Policy brief on how the EU should position itself in the AI technology race, coming next week.

The Why Axis is a weekly newsletter distributed by Bruegel, bringing you the latest research on European economic policy. 

About the authors

  • Bertin Martens

    Bertin Martens is a Senior fellow at Bruegel. He has been working on digital economy issues, including e-commerce, geo-blocking, digital copyright and media, online platforms and data markets and regulation, as senior economist at the Joint Research Centre (Seville) of the European Commission, for more than a decade until April 2022.  Prior to that, he was deputy chief economist for trade policy at the European Commission, and held various other assignments in the international economic policy domain.  He is currently a non-resident research fellow at the Tilburg Law & Economics Centre (TILEC) at Tilburg University (Netherlands).  

    His current research interests focus on economic and regulatory issues in digital data markets and online platforms, the impact of digital technology on institutions in society and, more broadly, the long-term evolution of knowledge accumulation and transmission systems in human societies.  Institutions are tools to organise information flows.  When digital technologies change information costs and distribution channels, institutional and organisational borderlines will shift.  

    He holds a PhD in economics from the Free University of Brussels.

    Disclosure of external interests  

    Declaration of interests 2023

Related content