Industrial AI Podcast

In this episode, we dive deep into the world of autonomous AI for data science with Doudou BA, CEO and founder of Octopus. I explore how Octopus is transforming raw data into actionable business decisions using advanced time series foundation models and agentic AI. We discuss the unique reasoning capabilities of Octopus, its intuitive approach for non-technical users, and how it stands apart from traditional AutoML solutions. Along the way, I share insights from VivaTech in Paris, including thought-provoking moments with industry leaders like Yann LeCun and Jeff Bezos. Join us as we reimagine the data science workflow and uncover what’s next for AI-powered business intelligence.

More about NXAI (here)

The Soofi X Discussion (here)

Try OctOpus (here)

In this episode, I sit down with Scott Duncan, a chemical engineer who built an agentic manufacturing troubleshooting assistant – without any coding background. We dive into the real-world challenges of process manufacturing and how AI is transforming the way plant issues are solved. Scott shares his journey from hands-on troubleshooting to leveraging large language models, knowledge graphs, and real-time data for smarter, faster problem-solving. We also debate the future of domain expertise in an AI-driven world and what it means for education and workforce development. Join me as we explore the potential – and the limitations – of AI in reshaping the future of industrial operations.

www.nx-ai.com

https://www.anthropic.com/news/claude-3-opus-sonnet-haiku

https://www.mathworks.com/products/matlab.html

https://opcfoundation.org/

https://opcfoundation.org/about/opc-technologies/opc-ua/

https://www.aveva.com/en/products/pi-system/

https://en.wikipedia.org/wiki/Retrieval-augmented_generation

https://en.wikipedia.org/wiki/Knowledge_graph

https://docs.anthropic.com/claude/docs/mcp-server

We just returned from three inspiring days at AI in the Alps, and in this episode, we dive into the most exciting breakthroughs and honest challenges facing industrial AI today. I share my firsthand impressions of revolutionary tools like TiRex-2, and we unpack what agentic AI really means for engineering, from breaking down data silos to transforming anomaly detection. Alongside Stefan Suwelack from Renumics, we discuss why skepticism has given way to optimism, how data infrastructure is finally catching up, and what the future holds for AI-driven organizations. The conversation is loaded with real-world examples, candid reflections, and a look at the evolving balance between sovereignty, open source, and big tech. Whether you’re an engineer, decision-maker, or just curious about the future of AI in industry, this episode offers practical insights and a glimpse into what’s next.

In this episode, I sit down with Levente Zolyomi, a leading PhD researcher at NXAI, to unpack the next evolution in time series AI: TiRex-2. We explore how TiRex-2 builds on its predecessor by handling complex multivariate data and streaming scenarios, opening new frontiers for industrial forecasting. Levente shares the story behind TiRex-2’s architecture, its breakthrough capabilities, and what sets it apart from transformer-based models like Kronos. I ask the questions you’re thinking—about zero-shot forecasting, synthetic data, and real-world benchmarks—so you can understand what matters most for your business. If you’re navigating industrial AI or just curious about the future of time series models, this conversation is packed with the insights you need.

In this episode, we dive deep into how AI is revolutionizing the entire industrial customer journey. We explore how large language models and digital twins are reshaping everything from initial customer inquiries to spare parts management and predictive maintenance. I’m joined by Jan Seyler and Werner Reichelt from Festo, who share firsthand insights on integrating AI with engineering tools, orchestrating multi-agent systems, and bridging the gap between digital sales and real-world manufacturing. Together, we discuss the challenges of interoperability, the evolving role of sales engineers, and the opportunities presented by data-driven automation. If you’re curious about the practical impact of AI on industry, this conversation is packed with real examples and forward-looking ideas.

Thanks to our PARTNER NXAI

https://www.festo.com/

https://mistral.ai/

https://deepseek.com/

https://www.nvidia.com/en-us/

https://www.automateshow.com/

https://www.anthropic.com/claude

https://www.prometheus.com/

https://www.jku.at/en/

https://single-market-economy.ec.europa.eu/sectors/ecodesign/digital-product-passport_en

https://en.wikipedia.org/wiki/Knowledge_Graph

https://www.pinecone.io/learn/retrieval-augmented-generation/

https://en.wikipedia.org/wiki/Digital_twin

https://en.wikipedia.org/wiki/Predictive_maintenance

Our guest is Boris Scharinger from Siemens. He wrote an interesting book "Industrial AI: From Pilot to Profit" and in this episode, we sit down with him. He is a leading voice in industrial AI and we uncover what it really takes to move from flashy AI pilots to solutions that deliver real value on the shop floor and in product engineering. We dig into the challenges of bridging proof-of-concept and production, the unique demands of industrial environments, and why so many initiatives stall before reaching profitability. Our conversation cuts through the hype, sharing candid examples from Siemens Energy and Tesla to illustrate where AI is truly changing the game and where it’s still hitting walls.

We also tackle pressing topics like the impact of generative AI on management expectations, the evolving role of process mining, and the tough realities of deploying AI in brownfield versus greenfield environments. If you’re a startup, engineer, or decision-maker looking to understand the real mechanics—and pitfalls—of industrial AI, this episode is your inside track. Join us as we set the record straight on what it takes to turn AI ambition into sustainable success.

Order the book here

https://www.siemens-energy.com/global/en.html

https://www.tesla.com/blog/gigapress

https://en.wikipedia.org/wiki/Process_mining

https://www.vdaalst.com/

https://papers.nips.cc/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html

In this episode, I sit down at the Agile Robots headquarters in Munich with Laurenz von Czettritz to dive deep into the evolving world of robotics and AI. We explore why NVIDIA’s frameworks dominate the industry, what it really takes to build new physical AI solutions, and how foundation models are reshaping automation. Laurenz shares how his team is developing next-generation AI for robotics, from building their own models to tackling unique industrial data challenges. We discuss the obstacles, breakthroughs, and the strategic mindset required to stay ahead in this rapidly changing field. If you’re curious about the real-world journey to smarter, more adaptable robots, this conversation offers a candid look inside the industry’s most ambitious projects.

In this episode, I sit down with Georg Katzlinger to explore the surprising complexity of the flat glass industry and the unique challenges it faces. We dive into how AI solutions are revolutionizing the way custom glass orders are processed, from deciphering handwritten requests to integrating with legacy ERP systems. Georg shares his journey from engineering to AI entrepreneurship, revealing why deterministic, human-in-the-loop automation is essential for manufacturers. I ask the tough questions on accuracy, implementation, and industry-specific hurdles, giving you an insider’s perspective on what it takes to bring AI into traditional sectors. If you’re curious about the intersection of deep tech and real-world manufacturing, you won’t want to miss this conversation.

#### NXAI

https://lumeso.com/

https://en.wikipedia.org/wiki/Flat_glass

https://en.wikipedia.org/wiki/Enterpriseresourceplanning

https://en.wikipedia.org/wiki/Opticalcharacterrecognition

https://en.wikipedia.org/wiki/Largelanguagemodel

https://www.sap.com/

https://www.salesforce.com/

In this episode, we dive deep into the promise and pitfalls of industrial AI with hands-on experts from a unique Volkswagen-Siemens joint venture. We challenge the hype around humanoid robots, discuss the practical impact of AI on factory design and operations, and uncover what truly drives value on the shop floor. Our guests share candid insights on scaling AI solutions, the role of synthetic data, and why safety and trust remain at the core of industrial automation. Join us as we separate fact from fiction and chart the path forward for intelligent manufacturing. If you're curious about the real impact of AI beyond the buzzwords, this conversation is for you.

https://nx-ai.com/

NVIDIA Safety

https://www.figure.ai/

https://www.bmwgroup.com/

https://www.nvidia.com/en-us/industries/industrial/

https://www.sick.com/

https://openai.com/

https://www.anthropic.com/

https://gemini.google.com/

https://www.coursera.org/

https://www.andrewng.org/

https://new.siemens.com/global/en.html

https://www.volkswagenag.com/

https://www.inpro.de/en/

https://catena-x.net/en/

https://www.nvidia.com/en-us/omniverse/

In this episode, I sit down with Steven Yates, CTO and co-founder of Federant, to dive deep into the urgent need for runtime governance in edge AI. Drawing on decades of experience in embedded systems and PLC design, Steven reveals why the shift to the edge demands more than just powerful inference—it requires robust, local authority to keep operations safe when connectivity falters. We unpack real-world incidents where lack of governance led to costly mishaps, and explore how new open-source solutions are bridging the gap between cloud convenience and industrial reliability. If you think cloud SLAs are enough for industrial AI, this conversation will make you rethink the fundamentals. Join me as we explore the future of safe, autonomous operations—and why the old rules of industrial control are more relevant than ever.

https://federant.com/

https://artificialintelligenceact.eu/

https://www.geautomation.com/

https://www.intel.com/

https://en.wikipedia.org/wiki/Programmablelogiccontroller#History

https://www.starlink.com/

https://www2.deloitte.com/global/en/insights/industry/technology/physical-ai.html

https://www.edgeaicouncil.org/

https://www.wevolver.com/

https://www.linkedin.com/company/adi-engineering/

https://www.ieee.org/