Andreas Nigg

European robotics is no longer concentrated. It’s fragmenting. But that’s a good thing. A few years ago, most “EU robotics” conversations pointed at one or two hubs. Now it’s regional, with clusters getting deeper: 🔹 Zurich and the Swiss cluster ANYbotics ABB ETH Zürich 🔹 Southern Germany cluster KUKA STÄUBLI Bosch Rexroth Festo Baumer Group 🔹 Stuttgart region cluster NEURA Robotics Bosch TRUMPF 🔹 Munich and Bavaria cluster Agile Robots SE Franka Robotics 🔹 Odense (Denmark) cluster Odense Robotics Universal Robots Mobile Industrial Robots 🔹 Lille / Paris (France) cluster Exotec Wandercraft Naïo Technologies Fragmentation matters because it changes the economics of shipping robots. When customers are closer, you iterate faster. When field support is local, uptime becomes normal. When integrators and suppliers sit in the same region, deployments stop resetting every time you cross a border. The next winners won’t be the loudest, they’ll be the densest. Clusters win because support and integration are local. It’s impossible to tag everyone in one post, so feel free to add the companies I missed that are building serious robots in Europe. #Robotics #Automation #IndustrialAutomation #DeepTech #EuropeanTech #AdvancedManufacturing Stuart Cooper

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🧠 ❤️ What do cognition, emotion, and personality have to do with #personalization? Everything. #Recsperts Episode No. 31 on #Psychology-Aware #recommendersystems with Elisabeth Lex from Technische Universität Graz is now live. 🎉 Elisabeth is a Full Professor of Human-Computer Interfaces and Inclusive Technologies at Graz University of Technology, head of the AI for Society Lab and a leading researcher at the intersection of recommender systems, psychology, and human–computer interaction. Together, we explore how recommender systems can become truly #human-centric by integrating cognitive, emotional, and personality-aware models into their design. We revisit the origins of psychology-informed recommendation, including the Grundy system -the first recommender system, built nearly 50 years ago - which framed book recommendation through stereotype #modeling. From there, we discuss how the community’s focus shifted toward solving recommendation mainly as an algorithmic #optimization problem, often sidelining richer models of human decision-making. We map out the three major branches of psychology-informed RecSys - #cognition-inspired, #affect-aware, and #personality-aware - and dive into practical examples. Elisabeth walks us through her work on modeling #music re-listening behavior using cognitive architectures such as ACT-R (Adaptive Control of Thought–Rational). Listen to this new episode of #Recsperts - Recommender Systems Experts! ✅ Subscribe on your favorite podcast player ⭐ Leave a rating, review or comment ✍ Share your thoughts on Psychology-Aware RecSys 🎧 Website: https://lnkd.in/dXGRggX2 🎧 Spotify: https://lnkd.in/d3Hwai2p 🎧 Apple: https://lnkd.in/dAAPSFS6

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von Mises stress - we see it in every analysis tool we open. But what is it…exactly, and why is it so useful? We just published our latest deep-dive tutorial on EngineeringSkills.com. This is one for coders AND non-coders and is available to all… Understanding Tresca and von Mises Elastic Failure Theories - linked below 👇 If you’re one of the many engineers with only a vague understanding of what the terms Tresca and von Mises refer to or what a failure theory actually is, this tutorial was written for you! In it, we’ll go from the fundamentals of elastic failure theory to implementing section analysis in Python using sectionproperties - the fantastic open-source section analysis library. Guest contributor, Julian Haudek, does an excellent job of presenting the core concepts of Tresca and von Mises failure theories before demonstrating their application with some manual calculations. Then, Julian supercharges proceedings by introducing the sectionproperties Python library to speed up the analysis process dramatically. The full tutorial, complete with downloadable code, is now available in the EngineeringSkills tutorial feed. #structuralengineering #civilengineering #engineeringskills #python #sectionproperties #stressanalysis #vonmises #fea

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🚨🚨 WE ARE PIVOTING 🚨🚨 Denzell and I are moving on from search. Unlike when we started in 2023, there are now many different open source solutions for quickly building highly relevant retrieval which I wouldn't mind recommending. Trieve is a great one, we have hundreds of paying customers, serve millions of requests every day, and make hundreds of thousands of dollars. But it's done. We have completed the project. Listed on AWS marketplace, built a drop-in component, shipped a Shopify app. There's no product left to build. Sure, we could grind more SEO and directory listings until we hit millions in revenue. But we'd burn out long before that happens, and frankly, that's not where we win. Our edge isn't in outmarketing Elastic or out-enterprise-selling OpenSearch. It's in being deeply technical and shipping fast. Different game entirely. If you use Trieve and like it, don't worry, it's not going anywhere. We'll still be resopnding to bug reports and feature requests. Same SLA, same support quality. It keeps us profitable! Just don't expect any big new features or flashy launches. Our new thing is called Threshold Security (onthreshold . com). Open source alternative to Coinbase Custody. Consider this, BITB is a $4B BTC ETF that stores everything at Coinbase. Forget crypto, I wouldn't put $4B of fiat USD into a single bank. I get why Bitwise does it though. Setting up your own custody solution is a nightmare rought now. Libraries exist (shouts out zcash and Luke Parker), but nobody has made a good server implementation. Coming from the search world, it's like having Lucene with no ElasticSearch. Soooo, we're fixing that! Going to build the thing which should already exist.

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#𝐀𝐢𝐢𝐧𝐚𝐈𝐧𝐀𝐜𝐭𝐢𝐨𝐧 – 𝐖𝐞𝐞𝐤 𝟏𝟗: 𝐍𝐨𝐭 𝐄𝐯𝐞𝐫𝐲 𝐂𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 𝐑𝐨𝐛𝐨𝐭 𝐍𝐞𝐞𝐝𝐬 𝐚 𝐅𝐚𝐜𝐞 Last week, my co-founders Claus Carste and Julian Hoffmann presented Aiina Robotics at the TUM Entrepreneurial Masterclass Graduation — a great opportunity to showcase our progress, but also to debate the future of automation in construction, 𝐚𝐬𝐤𝐢𝐧𝐠 𝐨𝐮𝐫𝐬𝐞𝐥𝐯𝐞𝐬 𝐰𝐡𝐞𝐭𝐡𝐞𝐫 𝐭𝐡𝐞 𝐜𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 𝐬𝐢𝐭𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐫𝐮𝐧 𝐛𝐲 𝐡𝐮𝐦𝐚𝐧𝐨𝐢𝐝 𝐫𝐨𝐛𝐨𝐭𝐬 - 𝐨𝐫 𝐛𝐲 𝐩𝐫𝐚𝐠𝐦𝐚𝐭𝐢𝐜, 𝐭𝐚𝐬𝐤-𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐦𝐚𝐜𝐡𝐢𝐧𝐞𝐬. At Aiina Robotics, we lean strongly toward the second. Here is why: 💭 𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐩𝐫𝐚𝐠𝐦𝐚𝐭𝐢𝐬𝐦 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐦𝐞𝐚𝐧? Pragmatism is a philosophy rooted in action and outcomes. Coined in the late 19th century by thinkers like Charles Peirce, it argues that the truth or value of an idea lies in its practical consequences. It’s not about how elegant or human-like a solution is—it’s about whether it works in the real world. 🔧 𝐒𝐨 𝐰𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐩𝐫𝐚𝐠𝐦𝐚𝐭𝐢𝐜 𝐫𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐦𝐞𝐚𝐧? Applying this philosophy to robotics, we do not focus on building human-like robots that could do everything, but on building machines that actually solve specific, real-world problems—reliably, affordably, and at scale. Thus, our pragmatic-robot-philosophy is built around three pillars: 𝟏. 𝐓𝐚𝐬𝐤-𝐅𝐢𝐫𝐬𝐭 𝐃𝐞𝐬𝐢𝐠𝐧: Pragmatic robots are created with one specific job in mind, not to imitate humans. In our case: removing damaged concrete, and doing it faster and safer than manual methods. 𝟐. 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐎𝐯𝐞𝐫 𝐅𝐨𝐫𝐦: Instead of chasing humanoid features, we design based on the environment and the task. This leads to more stable, robust, and adaptable machines for rough job site conditions like construction sites. 𝟑. 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭-𝐑𝐞𝐚𝐝𝐲 𝐒𝐢𝐦𝐩𝐥𝐢𝐜𝐢𝐭𝐲: Pragmatic robots aren’t just lab prototypes. They’re built to be used by real crews, in real conditions, tomorrow—not “someday.” Think plug-and-play, not years of training and integration. This concept is often overlooked in a world fascinated by humanoids. Yes, humanoid robots are visually impressive and technologically ambitious. But do we really need a bipedal robot to climb scaffolding and swing a hammer—when a mounted, modular machine could do the same task safer, cheaper, and more efficiently today?

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🛠️ AI meets maintenance - smarter, not more complicated 🤖 Today, I'll be speaking at Instandhaltungsforum 2025, hosted by Fraunhofer-Gesellschaft IMS in Dortmund. My topic: "Artificial intelligence as a maintenance assistant" (= “KI als Instandhaltungshelfer”).   We're facing a number of challenges in the industry: 🔸Increasingly complex systems 🔸Increasing demands on documentation 🔸Fewer skilled professionals to maintain them 🔸I am sure you will find lot of additional challenges I believe AI can make a real difference - not by replacing human expertise, but by supporting it. In my talk, I'll focus on how we can combine AI with photorealistic twins, with plans, reasoning and domain knowledge to provide practical help in areas such as 🔹Fault diagnosis 🔹Decision support 🔹Knowledge management 🔹Condition monitoring 🔹Graphical orientation and support The aim: to reduce complexity, preserve valuable expertise and make maintenance more resilient and efficient.   I am looking forward to great conversations and sharing ideas with those who see maintenance not just as a task, but as a key to future-proofing operations.   Will you be there? Let's connect. If you are interested in the programme: 🔗 https://lnkd.in/e4e8qN_R   #ArtificialIntelligence #Maintenance #FraunhoferIMS #Instandhaltungsform205 #Digitalisation #WorkforceChallenges #AIinIndustry #ExplainableAI

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