Industrial AI Podcast

Discover how digital knowledge workers are transforming manufacturing floors. Explore the future of hybrid workforces with AI agents. In this episode, I sit down with James Zhang, co-founder and CPO of OpsMate AI, to explore the game-changing role of AI agents in factory operations. We discuss why traditional human-centric manufacturing models are hitting their limits and how a hybrid workforce—combining humans, robots, and digital agents—can address the skilled labor shortage and boost productivity. James shares firsthand insights into the unique challenges of deploying AI in diverse factory environments, the importance of knowledge graphs, and why empowering frontline teams is key to successful adoption. If you’re curious about the practical steps to bring AI agents onto your shop floor, or just want to understand what the future of industrial automation looks like, this conversation is for you. Siemens https://www.siemens.com/global/en.html Gartner https://www.opsmateai.com/reports/gartner-cool-vendor OpsMate AI https://www.opsmate.ai/ Microsoft https://www.microsoft.com/en-us/industry/manufacturing Generative AI https://en.wikipedia.org/wiki/Generativeartificialintelligence Agentic AI https://www.microsoft.com/en-us/research/blog/agentic-ai-a-new-paradigm-for-human-ai-collaboration/ Knowledge Graph https://en.wikipedia.org/wiki/Knowledge_graph MES (Manufacturing Execution System) https://en.wikipedia.org/wiki/Manufacturingexecutionsystem ERP (Enterprise Resource Planning) https://en.wikipedia.org/wiki/Enterpriseresourceplanning Azure Databricks https://azure.microsoft.com/en-us/products/databricks/ Microsoft Fabric https://www.microsoft.com/en-us/microsoft-fabric PTC https://www.ptc.com/ SAP https://www.sap.com/industries/manufacturing.html ChatGPT https://chat.openai.com/ Gemini (Google AI) https://gemini.google.com/

What does it take to build Europe's next AI powerhouse? Discover the race for a billion. In this episode, we dive into the ambitious European initiative offering up to one billion euros to fuel the next wave of AI innovation. I sit down with Johannes Otterbach, the so-called "billion euro man," to discuss how SPRIND is bridging the gap between research and industry, and what it really takes to launch a world-class AI lab in Europe. We explore the challenges of scaling, the importance of industrial-grade AI, and why Europe's unique landscape demands new strategies for success. Along the way, you'll hear our candid thoughts on talent, technology, and the future of frontier AI. If you're curious about the intersection of ambitious funding, cutting-edge research, and industrial application, this conversation is for you. Siemens https://new.siemens.com/global/en/company/topic-areas/artificial-intelligence.html Neura Robotics https://www.neura-robotics.com/ NVIDIA https://www.nvidia.com/en-us/ai-data-science/ Fraunhofer Society https://www.fraunhofer.de/en.html Agile Robots https://www.agilerobots.com/ OPC Foundation https://opcfoundation.org/ Softing https://industrial.softing.com/ Audi https://www.audi.com/en/innovation/ai.html Mistral AI https://mistral.ai/ Sprint (German Federal Agency for Disruptive Innovation) https://www.sprind.org/en/ OpenAI https://openai.com/ DeepMind https://www.deepmind.com/ XAI https://x.ai/ Next Frontier AI Challenge https://next-frontier.ai/

Discover how neurodivergent talent is transforming AI data quality. A new era of responsible annotation begins here. Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co. We thank our partner SIEMENS

Discover how smart cable management and AI are transforming downtime into uptime. Real-world insights from the heart of industrial automation. Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co. We thank our partner SIEMENS

Dr. Finnur Pind, Co-founder and CTO at Treble Technologies, dives into the revolutionary world of synthetic sound data. He explains how simulating sound enhances robotics, enabling smarter machines with spatial awareness. The conversation uncovers the hurdles of accurate sound modeling and how sound could redefine AI applications beyond traditional text processing. Finnur also highlights Reykjavik's vibrant AI scene and Treble's vision for expanding audio-driven innovations in various industries.

Oliver Niggemann, a Professor of Computer Science in Mechanical Engineering at Helmut Schmidt University, delves into the fascinating intersection of numerical machine learning and engineering. He reveals how this fusion is transforming everything from diagnosing issues in the International Space Station to optimizing bridge designs. The conversation highlights the revolutionary role of surrogate models in speeding up simulations, AI-driven automated design workflows, and the critical need for interdisciplinary collaboration in today's engineering education.

Join Professor Stratis Gavves from the University of Amsterdam, an expert in physics-informed robotics, as he delves into the critical role of physics and causality in robot learning. Discover why traditional robot manufacturers struggle with adopting advanced world models, and how integrating multimodal data can lead to more explainable and efficient robots. Stratis also predicts a future of specialized models versus a universal one, exploring the balance between edge and cloud architectures for optimal robotics performance.

Richard Rovner, Vice President of Marketing at MathWorks with a 25-year tenure, dives into how AI has transformed engineering. He traces the evolution from 90s neural networks to today's AI copilots and model-based design. Richard shares insights on the significance of generative AI and the crucial human role amid automation. He discusses real-world applications like Coca-Cola's machine learning innovations and the upcoming Simulink Copilot. As engineering roles evolve, he highlights the need for AI literacy and cross-discipline collaboration in this rapidly shifting landscape.

Gabriel Krummenacher, Director of data science at Zühlke, delves into the complexities of industrial AI adoption. He discusses a survey revealing that operational efficiency is the top impactful AI use case. Gabriel emphasizes the necessity of strong data science teams to leverage GenAI, noting that ethical frameworks significantly enhance success rates. He highlights differing regional approaches to AI and stresses the importance of measurable KPIs and leveraging internal data for impactful custom applications. Tune in for insights on how to navigate the AI landscape effectively!

Timo Gessmann, CTO of Schunk, discusses blending mechanical design with AI to enhance robotics and the challenges of recruiting top talent for industrial AI roles. He emphasizes the need for strong European robotic models and outlines Schunk's vision for automation. Phillip Lippe from Google DeepMind shares insights on generative AI and the importance of foundation models in creating domain-specific intelligence. They also explore the future of AI scaling, hybrid architectures, and the potential safety implications in applications across various industries.