News Article July 08, 2024

AI-based Method to Detect Doping Cases

Thousands of athletes are currently competing for medals at the Olympic Games in Paris. And in some cases, questions will be asked about whether medals were won fairly or whether doping was involved.

AI-based Method to Detect Doping Cases

Thousands of athletes are currently competing for medals at the Olympic Games in Paris. And in some cases, questions will be asked about whether medals were won fairly or whether doping was involved. Software developed by a team led by Wolfgang Maaß, professor of business informatics at Saarland University, could help to answer these questions in future competitions. The software, which is currently being presented at the International Joint Conference on AI (3–9 August in South Korea), needs only a handful of data points to predict with unprecedented accuracy which athletes have definitely not doped – and can thus identify those cases where a closer look is required.

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ESCADE Closing Event: Three Years of Research on Energy-Efficient AI

On 30 July 2026, more than 50 guests from research, industry and public administration came to DFKI Saarbrücken for the closing event of the ESCADE project. After three years, the consortium coordinated by Prof. Wolfgang Maaß presented how the energy demand of AI can be reduced by up to 90 percent – and drew wide media attention in the days around the event.

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ESCADE in the Frankfurter Allgemeine Zeitung

The Frankfurter Allgemeine Zeitung reported on the results of the ESCADE project, placing the consortium's efficiency gains in the wider context of the global data center buildout.

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How AI Becomes Significantly More Energy Efficient – Press Coverage of the ESCADE Results

Ahead of the closing event of the ESCADE project, Saarland University issued a press release on the results of the research consortium led by Prof. Wolfgang Maaß: how the electricity demand of AI can be cut by up to 90 percent through smaller models, automated network design and neuromorphic hardware.

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