Prune Truong

Could neutral atoms be a means to scalable quantum computing? Physicist Wenchao Xu and her team at PSI Paul Scherrer Institut and ETH Zürich are exploring exactly that—using ultra-cold atoms trapped by tightly focused laser beams to form programmable arrays of qubits. By using architectures based on two different types of atoms, her team is working to improve quantum error correction—one of the major hurdles on the road to universal quantum computing. Wenchao Xu leads the Quantum Engineering research group at Paul Scherrer Institute PSI and is a tenure-track assistant professor at ETH Zurich. 🔗 Read the full interview with Wenchao to learn more about how this innovative approach is taking shape at PSI, the challenges the team face and where it could lead: 👉 https://brnw.ch/21wSLdc #QuantumComputing #NeutralAtoms #ColdAtoms #FutureTechnologies #QuantumErrorCorrection #ResearchAtPSI #ETHZurich #QuantumResearch #ScienceFeature CC. Quantum Center, ETH Zurich, Department of Physics (D-PHYS), ETH Zurich

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📢 𝗦𝘄𝗶𝘁𝘇𝗲𝗿𝗹𝗮𝗻𝗱 𝗶𝘀 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗼𝗽𝗲𝗻 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹 𝗕𝗶𝗴 𝗧𝗲𝗰𝗵 𝘄𝗼𝗻’𝘁. ETH Zürich, EPFL, and the Swiss National Supercomputing Centre (CSCS) will release a fully open Large Language Model (LLM) – trained on 𝗔𝗹𝗽𝘀, one of Europe’s fastest AI supercomputers. 𝗪𝗵𝗮𝘁 𝘀𝗲𝘁𝘀 𝗶𝘁 𝗮𝗽𝗮𝗿𝘁? ✅ 𝗠𝘂𝗹𝘁𝗶𝗹𝗶𝗻𝗴𝘂𝗮𝗹 𝗯𝘆 𝗱𝗲𝘀𝗶𝗴𝗻 Trained on 1,500+ languages – with strong capabilities in underrepresented communities. ✅ 𝗙𝘂𝗹𝗹𝘆 𝗼𝗽𝗲𝗻 (unlike commercial models) Weights, code, and training data will be public. Licensed under Apache 2.0 for unrestricted reuse – commercial, scientific, or regulatory. ✅ 𝗚𝗹𝗼𝗯𝗮𝗹𝗹𝘆 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 Available in 8B and 70B parameter sizes – trained on 15 trillion high-quality tokens. ✅ 𝗧𝗿𝘂𝘀𝘁𝗲𝗱 𝗯𝘆 𝗱𝗲𝘀𝗶𝗴𝗻 Developed entirely on Swiss public infrastructure – aligned with Swiss law and the EU AI Act. ✅ 𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗯𝘆 𝗔𝗹𝗽𝘀 – 𝗴𝗿𝗲𝗲𝗻, 𝘀𝗼𝘃𝗲𝗿𝗲𝗶𝗴𝗻, 𝗮𝗻𝗱 𝗯𝘂𝗶𝗹𝘁 𝘁𝗼 𝘀𝗰𝗮𝗹𝗲 Trained on Alps, using 100% carbon-neutral electricity and 10,000+ NVIDIA Grace Hopper Superchips – enabled by a 15+ year collaboration between NVIDIA, Hewlett Packard Enterprise, and CSCS. ✅ 𝗪𝗶𝘁𝗵 𝘀𝘁𝗿𝗼𝗻𝗴 𝗿𝗼𝗼𝘁𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗚𝗿𝗲𝗮𝘁𝗲𝗿 𝗭𝘂𝗿𝗶𝗰𝗵 𝗔𝗿𝗲𝗮 😎 Where world-class universities, sovereign infrastructure, public funding, and a dense AI talent pool create one of Europe’s most trusted ecosystems for building technology at scale.🚀 👏 𝗟𝗲𝗱 𝗯𝘆 𝘄𝗼𝗿𝗹𝗱-𝗰𝗹𝗮𝘀𝘀 𝗔𝗜 𝗺𝗶𝗻𝗱𝘀: ETH AI Center’s Imanol Schlag, EPFL AI Center’s Antoine Bosselut and Martin Jaggi. Supported by the Swiss AI Initiative and ELLIS - European Laboratory for Learning and Intelligent Systems 🔗 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿 𝗵𝗼𝘄 𝗚𝗿𝗲𝗮𝘁𝗲𝗿 𝗭𝘂𝗿𝗶𝗰𝗵 𝘀𝘂𝗽𝗽𝗼𝗿𝘁𝘀 𝗴𝗹𝗼𝗯𝗮𝗹 𝗔𝗜 𝗯𝘂𝗶𝗹𝗱𝗲𝗿𝘀: https://okt.to/NCI68o More about the Swiss LLM: https://okt.to/BR2HIV

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🎉 Seven years of open-source #fiction! 🎉 At the Chair for Design Automation at the Technische Universität München, we're dedicated to #opensource. Today marks seven years since our framework fiction, the foundation of the Munich Nanotech Toolkit (#MNT), became public on GitHub. What a journey! 🚀 Over the past year, we've advanced from v0.6.6 to v0.6.12, and each release brought us closer to our vision of empowering the #nanotech and #FCN design communities with smarter, faster, and more flexible tools. 💡 Some highlights from this past year: 🔹 #ClusterComplete: a breakthrough physical simulation engine for SiDBs, enabling exact and fast 3-state simulations of over 80 quantum dots! You can try it out in #SiQAD via our simulator plugins: https://lnkd.in/eA3KaZyA 🔹 #ABC integration directly in the fiction #CLI, allowing state-of-the-art logic optimization before FCN layout mapping. 🔹 #QuickTrace, a new simulation algorithm to evaluate #SiDB defect robustness. 🔹 More flexible SiDB operational domain and temperature analyses. 🔹 And just today, a brand-new maximum-effort mode in the #gold physical design engine for exploring even more corners of the solution space. ✨ 🐍 With continuous improvements to our Python bindings, Docker builds, and documentation, you can easily get started with: pip install mnt.pyfiction 🙏 None of this would be possible without the incredible contributions, ideas, and dedication of our growing community — especially Jan Drewniok, Simon Hofmann, Benjamin Hien, Willem Lambooy, Robert Wille, and Samuel Ng. Thank you all for making fiction what it is today. Here's to another year of collaboration, discovery, and pushing the boundaries of what's possible in #nanotechnology and #designautomation. 🔗 Check out what's new in detail: https://lnkd.in/ek9Ex346 And while you're there, leave a star ⭐ 📦 Latest release: v0.6.12 — dropped today, right on the anniversary!

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ETH researchers at ETH Zurich, Department of Information Technology and Electrical Engineering created sensors to #Boost #SkiJumpers' training. Young athletes tested the devices for Swiss-Ski in Kandersteg.

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What Kind of Water Did the Dinosaurs Drink? 💧 At RWTH Science Night on November 14, Professor Heribert Nacken dives into the World of Water. We spoke with him in advance about his field of research – water – and his second passion: virtual reality. ❓ What can visitors expect from your lecture? 🗨️ A journey around the globe – all about water. We’ll explore flooding and drought, water purification, and the basics of water management. Each topic will be introduced at interactive stations before children answer questions about them. The event is based on the popular children’s TV show “Runaround” – meaning that the kids use colored cards to show which answer they think is correct. ❓ What kind of tasks will there be? 🗨️ A wide range! We’ll start with estimation questions, for example, how much water you use when brushing your teeth, cooking, or flushing the toilet – and then move on to the question of whether the dinosaurs drank the same water we do today. ❓ And did they? 🗨️ Yes. Unlike money, for instance, water is constant – it can’t be increased or reduced, only transformed between liquid, gas, and solid states. Incidentally, the cards don’t go up quite as quickly for that question as they do for the first! ❓ Has awareness of the topic changed over the years? 🗨️ Water can no longer be viewed in isolation from energy and nutrition – they’re all interconnected, and sustainability plays a key role. About 70 percent of global water consumption – and that’s also one of the questions – comes from agriculture. Yet water is only one of nine factors within the so-called planetary boundaries. Everything is connected: it’s not enough to reduce CO₂ emissions alone. Water use, microplastics, ocean acidification, sustainable agriculture – all of these are part of the same complex system. ❓ What do these planetary boundaries mean in practice? Can everyone make a difference? 🗨️ Absolutely. Take a simple example: as a meat eater, you produce about 1,800 kilograms of CO₂ per year, as a vegetarian around 1,400, and as a vegan about 1,050. I’m not telling anyone to become vegan, but as an engineer I say: 1,050 instead of 1,800 – that’s a significant difference. ❓ At Science Night, you’re also present in another role … 🗨️ … yes, with our virtual reality booth, as the Rector’s Delegate for Digital Transformation in Teaching & Learning. Our team will be there to assist students – and, of course, curious parents – as “buddies” when they experience virtual reality for the first time. ❓ Is there a particular message you’d like to convey that evening? 🗨️ Oh, I don’t have a specific mission. The RWTH Science Night is simply a fantastic event where the University not only showcases its research, but also how approachable it is to everyone. That’s what it’s all about – and that’s what I think is great. RWTH Science Night: ➡️ https://lnkd.in/ek9XCTzE 📸: Niels Knippertz

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📲 Does TikTok & Co. make learning more difficult? Studies by #TUBraunschweig on short videos and knowledge acquisition show significant impact 🔍 Instagram Reels, YouTube Shorts and TikToks are all fast, entertaining and visually appealing. But do they promote knowledge acquisition? The key findings of two recent studies by the Institute of Educational Psychology of TU Braunschweig: It seems that short videos promote the superficial processing of information, suppress rational thinking and are less suitable for knowledge transfer than text-based learning materials. 💡 “Short videos in the classroom are not problematic per se – but they are no substitute for in-depth learning processes,” says scientist Thorsten Otto. “If we make targeted use of their strengths in terms of capturing attention while at the same time reflecting on their limitations, they could certainly be used profitably in education." Read more in our magazine: 👉 https://lnkd.in/e4uv5pvw 📸 Westend61/zerocreatives

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🖼️ 𝗜𝗺𝗮𝗴𝗶𝗻𝗴 𝗣𝗹𝗮𝘇𝗮 𝗶𝘀 𝘁𝗮𝗸𝗶𝗻𝗴 𝘀𝗵𝗮𝗽𝗲 – 𝙖𝙣𝙙 𝙬𝙚’𝙙 𝙡𝙤𝙫𝙚 𝙮𝙤𝙪𝙧 𝙞𝙣𝙥𝙪𝙩. Together with colleagues at @EPFL Center for Imaging and the Swiss Data Science Center (SDSC), we’ve been working on a platform with the support of the EPFL Open Science Grant, the ETH ORD Explore Grant, and the PHRT Grant: 𝗜𝗺𝗮𝗴𝗶𝗻𝗴 𝗣𝗹𝗮𝘇𝗮 helps researchers and developers 𝗳𝗶𝗻𝗱 𝗮𝗻𝗱 𝘀𝗵𝗮𝗿𝗲 𝗶𝗺𝗮𝗴𝗶𝗻𝗴 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 across disciplines, in a way that supports the 𝗙𝗔𝗜𝗥 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 (Findable, Accessible, Interoperable, Reusable). It’s not a repository - it’s more like a 𝗰𝘂𝗿𝗮𝘁𝗲𝗱 𝗰𝗮𝘁𝗮𝗹𝗼𝗴𝘂𝗲: ✅ A place to discover imaging tools that others have found useful ✅ With direct links to where the software lives ✅ A simple FAIRness score (1–5) to help make reuse easier ✅ And categories designed collaboratively with the community 🌌 𝗙𝗿𝗼𝗺 𝗰𝗲𝗹𝗹𝘀 𝘁𝗼 𝗴𝗮𝗹𝗮𝘅𝗶𝗲𝘀: Whether you're working in bioimaging, climate science, astrophysics – or developing algorithms – we hope this can be a helpful resource. We're currently in a soft launch phase, and your feedback is very welcome. Imaging Plaza is evolving, and we’d love to hear how it could better support your work. Read full News Release: https://lnkd.in/d_Y9RTxJ   👉 𝗧𝗮𝗸𝗲 𝗮 𝗹𝗼𝗼𝗸 𝗵𝗲𝗿𝗲: imaging-plaza.epfl.ch 💬 Let us know what’s useful, what’s missing, or what you'd like to see next. We are deeply grateful to the 🇹​🇪​🇦​🇲 for making this success possible: Carlos Vivar Rios, Edward Andò, Robin F., Mallory Wittwer, Florian Aymanns, Hannah Casey, Quentin Chappuis, Laurène Donati, Oksana Riba Grognuz, Michael Unser, Olivier Verscheure, Gavin K. Lee, Olivia Mariani    #ImagingScience #InterdisciplinaryResearch #FAIRprinciples

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𝐓𝐮𝐫𝐧𝐢𝐧𝐠 𝐈𝐝𝐞𝐚𝐬 𝐢𝐧𝐭𝐨 𝐈𝐦𝐩𝐚𝐜𝐭 — 𝐓𝐞𝐭𝐡𝐲𝐬 𝐑𝐨𝐛𝐨𝐭𝐢𝐜𝐬’ 𝐔𝐧𝐝𝐞𝐫𝐰𝐚𝐭𝐞𝐫 𝐌𝐢𝐬𝐬𝐢𝐨𝐧 🌊🤖 At Wyss Zurich Translational Center, we love seeing bold ideas transform into technologies that solve real-world challenges. Today, we celebrate a major milestone for one of our own: Tethys Robotics. The ETH Zurich spin-off has raised €3.5 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 𝐢𝐧 𝐩𝐫𝐞-𝐬𝐞𝐞𝐝 𝐟𝐮𝐧𝐝𝐢𝐧𝐠 to scale their autonomous underwater robot, the 𝐓𝐞𝐭𝐡𝐲𝐬 𝐎𝐍𝐄, for safety-critical missions worldwide. Operating at depths of 𝐮𝐩 𝐭𝐨 300 𝐦𝐞𝐭𝐞𝐫𝐬, it supports offshore wind and energy inspections, ordnance disposal, and search-and-rescue operations — all 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬𝐥𝐲 𝐚𝐧𝐝 𝐬𝐚𝐟𝐞𝐥𝐲, with high-resolution 3D data collection. With over 30 𝐩𝐢𝐥𝐨𝐭 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬 underway and collaborations with the𝐒𝐰𝐢𝐬𝐬 𝐀𝐫𝐦𝐲 and 𝐒𝐃𝐑𝐂, Tethys Robotics is proving that innovation can meet both commercial and societal needs. We’re proud to have supported this journey — from lab concept to real-world impact beneath the waves. Congratulations to Jonas Wüst, and the team! More here 👉 https://lnkd.in/ggFAKsNq #WyssZurich #TethysRobotics #ETHZurich #Innovation #Robotics #UnderwaterTechnology #Safety #Entrepreneurship

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Empowering the next generation of AI builders together with the University of Zurich. 🎓 We’re excited to partner with the UZH Next Generation Computing team as one of the first adopters of our Academia Hub, a program that brings cutting-edge machine learning tools and infrastructure to classrooms and research labs. This collaboration gives UZH students and educators easy access to Hugging Face models and resources, from fine-tuning and training to hands-on experimentation, without worrying about compute limits or deployment complexity. We can’t wait to see what the next generation of researchers and engineers will build! 🤗 #UZH.ai

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As several media articles recently pointed out, large AI models and the data centres that power them consume a lot of energy. How serious are these concerns, and what can we do about them? We asked Ana Klimovic, Assistant Professor at ETH Zürich and specialist in sustainable machine learning frameworks, for her view. She explains why #AI workloads often underutilize precious #GPU resources and how we can improve their efficiency. Discover more: https://lnkd.in/d7uherYt

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