Jochen Witte

🔮✨ When AI Meets Quantum: A powerful feedback loop for discovery   Once a niche for physicists and tech nerds, today the focus of industry leaders and policymakers. With 1,800+ participants, the AIDAQ Summit in Berlin proved: quantum is moving center stage. The real game-changer? AI and quantum don’t just coexist, they amplify each other. 🤖 AI improves quantum by stabilizing fragile qubits.  ⚡ Quantum enhances AI by solving problems classical machines cannot.  Together, they create a powerful feedback loop of innovation.  ✨ The exciting part: AI + Quantum is not distant science fiction. And it holds enormous opportunities for Germany and Europe. Microsoft is committed to helping unlock this potential:  ↪️ In Germany, we support EIN Quantum NRW, strengthening a national ecosystem of universities, research institutes, and companies.  ↪️ In Denmark, our Quantum Lab with 350+ scientists pushes the boundaries of scalable systems together with the University of Copenhagen and the Niels Bohr Institute.  ↪️ At QuTech Delft, we partner with leading academics to bring quantum closer to scale. What excites me most? The potential impact on materials science and chemistry.   🔬 The interplay of AI and quantum could define the next century of discovery.   🌱Imagine self-healing materials, sustainable batteries, catalysts that break down microplastics, or eliminating forever chemicals.     🙏 Thanks to AIDAQ Summit for shining a light on one of the most exciting frontiers of innovation. And for bringing together the people who will shape it.  #AIDAQ #aidatasummit25 #quantumsummit25 

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Last week at the Axel Springer #aisummit25 in Berlin, one message was clear: AI MUST move from vision to value. Scaling AI is key – the fuel for the AI engine is data: reliable, context-rich, and trusted data, that is, with quality over quantity. Here, Europe can lead the way by providing sectoral data spaces and small data rooms, harmonizing and setting clear standards, helping companies, specifically SMBs to close gaps. The Data Act and Data Governance Act are strong foundations. We now need simplification, interoperability and quick ways for SMBs to join in. Thank you Axel Springer for bringing politics and business together to discuss #AIandData. A strong step toward shaping Europe’s digital future. Christina Raab Nicole Büttner Julia Reuss Dr. Christian Loefert Kevin Eversmann Ian Kahan Vanessa Cann Tobias Regenfuss Fernando Lucini Florian Schaudel Vlad Larichev Dr. Dirk Alexander Molitor Igor Aranovsky

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I’ve said it before, but it’s worth repeating: the best way to understand AI is to roll up your sleeves and build something with it.   That’s exactly what we did with our first EBS #GenAI Hackathon.   We gave our #WalmartEBS associates one week to solve one real problem. Whether the project was aimed at improving customer experience, associate experience, or operations efficiency, the mission was the same: turn something “hard and slow” into “easy and fast.”   The result? Hundreds of real, working prototypes you could put in the hands of associates or customers tomorrow. Many teams went all in on vibe coding, letting AI generate the code end to end. It wasn’t the only path, but it showed what’s possible when we lean into new ways of working. That’s the bar we’re aiming for.   Associates from every corner of EBS teamed up with business partners, dove deep into learning sessions with technical experts, and yes, competed for prizes. But the real win was watching people jump in, experiment, and cook.   The best ideas come from our associates, and this hackathon proved it. To everyone who took part, thank you. I’m proud of the creativity and grit you showed, and even more excited to watch these prototypes grow into tools that make a difference for associates and customers.   Fast. Hands-on. Messy in the best way.   This is what “all in on AI” looks like. Walmart Global Tech Elisebeth Collins (Cook) Greg Cathey

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Ever wondered how AI and quantum fit together to classify medical images? 🔥 Fire up your inner geek with this cutting-edge research by our SAP colleagues jointly with Ludwig-Maximilians-Universität München and Aqarios.    The researchers used parallel quantum annealing to train Boltzmann machines – a type of neural network that models complex probability distributions – for classifying medical images. By embedding multiple problem instances in parallel on a quantum computer, they reduced sampling time and achieved a 70% speed-up compared to previous approaches.   Why I think it matters?   ⚙️ Boltzmann machines could be used beyond healthcare – in manufacturing, predictive maintenance, demand forecasting, and data generation. ⚙️ Training quantum Boltzmann machines has been a major challenge – parallel quantum annealing could offer a promising way to scale. ⚙️ Quantum machine learning is evolving quickly. This research highlights one of many new directions that could make quantum AI more practical.   Curious about your thoughts and ideas! Florian Krellner Max Halbich Yaad Oren Dr. Carsten Polenz Dr. Marcus Krug Alexa Gorman Michael Schroedl-Baumann Peter Limacher Mathias Kohler

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