KI in der Industrie

Why imperfect twins may shape robotics' future. From CNC startups to the Coca-Cola of AI, we rethink automation. In this episode, we dive into the evolving world of industrial AI, exploring everything from CNC innovation in Tel Aviv to the surprising rise of digital cousins over traditional digital twins. We unpack how startups and established players alike are reimagining automation, robotics, and the very nature of intelligent agents on the factory floor. Along the way, we discuss the parallels between LLMs and the invention of refrigeration, ask who will become the 'Coca-Cola' of AI, and reflect on the real impact of democratizing advanced technology. Join us as we debate the future of humanoid robots, the shifting boundaries between tool and actor, and the practical challenges of bringing AI-driven agents into real-world industry. If you're curious about where industrial automation is headed—and what innovations might define the next era—this conversation is not to be missed.

How AI revolutionizes manufacturing, from press shop to global scale. Discover the inside story of Audi’s industrial transformation. In this episode, I sit down with Andre Sagodi, a manufacturing and innovation expert at Audi, to explore how artificial intelligence is transforming the car production process. We dive into Audi’s journey from piloting AI-based crack detection in sheet metal parts to scaling these solutions across multiple global sites. Andre shares practical insights on overcoming challenges like data consistency, model scalability, and workforce collaboration, all while aligning with Audi’s strategic vision. Together, we discuss what it really takes to turn promising AI pilots into production-ready systems that deliver real business value. If you’re curious about the future of industrial AI and want a behind-the-scenes look at innovation inside a world-class manufacturer, this episode is for you.

From AI-driven personal agents to revolutionizing drug discovery—exploring what’s shaking up industrial AI and chemistry. In this episode, we dive into the seismic shifts happening in industrial AI, from the so-called 'SaaS-mageddon' disrupting established software models to the rise of AI-powered agents that promise to redefine productivity. We share first-hand insights on how large language models and open-source projects are reshaping the landscape, and what this means for the future of industry solutions. We then turn to the frontier of pharmaceutical innovation with Stanisław Jastrzębski, CTO & Co-Founder from molecule.one, who reveals how deep learning, automation, and custom data are accelerating drug discovery. Join us as we connect the dots between industrial AI trends, the evolution of personal assistants, and the chemistry breakthroughs powering tomorrow’s medicines. Tune in for a global perspective and a dash of inspiration straight from the heart of Istanbul.

Meet Norbert Jung, CEO of Bosch Connected Industry. We tackle the challenges of scaling innovation, the future of lights-out factories, and why Europe's workforce transformation is both a necessity and an opportunity. In this episode, I sit down with Norbert Jung, CEO of Bosch Connected Industry, to explore the evolving landscape of manufacturing co-intelligence. We dive into how AI agents and data are reshaping factories, why human expertise remains irreplaceable, and what 'industrial grade' really means in this new era. Norbert shares practical examples from Bosch's own production lines, debunks common myths, and explains how semantic data and agentic AI are driving real-world results. We also tackle the challenges of scaling innovation, the future of lights-out factories, and why Europe's workforce transformation is both a necessity and an opportunity. If you want an inside look at the practical side of AI in industry—and what it means for the people behind the machines—this conversation delivers fresh perspective and actionable insights.

You'll hear my conversation with John Harrington of HighByte, who breaks down the role of MCP services and why they’re critical for bridging the gap between factory data and intelligent agents. In this episode, we journey from weather woes in Franconia straight into the heart of Amsterdam’s AI innovation, exploring what happens when robotics, world models, and agentic AI collide. We share our firsthand impressions from deep-dive research sessions at Lab42, where startups and researchers are joining forces to push industrial AI forward. You'll hear my conversation with John Harrington of HighByte, who breaks down the role of MCP services and why they’re critical for bridging the gap between factory data and intelligent agents. We don’t just talk tech—we talk about the people, the practical challenges, and the evolving landscape that’s making industrial data accessible to everyone, not just engineers. If you’re curious about how symbolic AI, digital cousins, and scalable architectures are transforming manufacturing, or you want to know what’s next for AI in the Alps, this episode is your front-row seat. Tune in for insights, laughs, and a clear-eyed look at the road ahead for industrial-grade AI. Siemens https://www.siemens.com/global/en.html HighByte https://www.highbyte.com/ MCP (Model Context Protocol) https://docs.anthropic.com/claude/docs/model-context-protocol-mcp OPC Foundation https://opcfoundation.org/ OPC UA (Open Platform Communications Unified Architecture) https://opcfoundation.org/about/opc-technologies/opc-ua/ MES (Manufacturing Execution System) https://en.wikipedia.org/wiki/Manufacturingexecutionsystem Anthropic https://www.anthropic.com/ Snowflake https://www.snowflake.com/ Amazon Web Services (AWS) https://aws.amazon.com/ Azure (Microsoft Azure) https://azure.microsoft.com/ Pi System (OSIsoft) https://www.osisoft.com/pi-system/ AspenTech https://www.aspentech.com/ Novotek https://www.novotek.com/ MQTT https://mqtt.org/ REST API https://en.wikipedia.org/wiki/Representationalstatetransfer Lab42 (Lab Forty Two) https://www.lab42.nl/ OPC UA Information Model https://opcfoundation.org/about/opc-technologies/opc-ua/opc-ua-information-model/ Purdue Model (ISA-95) https://en.wikipedia.org/wiki/ANSI/ISA-95

Discover how inline AI transforms manufacturing, boosts robustness, and redefines European efficiency. Precision meets innovation in real-world production. In this episode, I dive deep into the future of industrial AI with Andreas de Jonge, exploring how inline AI is reshaping real-world manufacturing. We discuss why tailored, ultra-efficient AI models can outperform bulky, generic solutions—especially in Europe’s highly specialized industries. Andreas shares how his company’s EdgeBrain device brings intelligence directly to the data stream, enabling plug-and-play integration and unprecedented robustness for even the oldest production lines. Together, we unpack the challenges of brownfield integration, the power of synthetic data, and the path to true European digital sovereignty. If you’re curious about the next wave of industrial automation and what it means for productivity, this conversation is not to be missed. Siemens https://www.siemens.com/global/en.html EdgeBrain [https://dejonge.ai/en) FPGA (Field Programmable Gate Array) https://en.wikipedia.org/wiki/Field-programmablegatearray TensorFlow https://www.tensorflow.org/ PyTorch https://pytorch.org/ ONNX (Open Neural Network Exchange) https://onnx.ai/ Teacher-Student Model (Knowledge Distillation) https://en.wikipedia.org/wiki/Knowledge_distillation Industrial Ethernet https://en.wikipedia.org/wiki/Industrial_Ethernet Brownfield Integration https://en.wikipedia.org/wiki/Brownfield(softwaredevelopment) Unmanned Aerial Vehicle (UAV) https://en.wikipedia.org/wiki/Unmannedaerialvehicle PLC (Programmable Logic Controller) https://en.wikipedia.org/wiki/Programmablelogiccontroller

A few months ago we interviewed Albert van Breemen and he presented his cucumber robot. Now they developed an industrial solution. In this episode, we dive into the evolution of AI robotics, exploring how lessons from cucumber-picking robots are now revolutionizing industrial inspection. We sit down with Wouter from VBTI to unpack the journey from complex greenhouse challenges to the development of Adam One—an inspection robot that doesn’t just automate, but truly understands the task at hand. We reflect on the unique technical hurdles, the fusion of multiple AI models, and the potential for scalable, domain-specific foundation models. As always, we bring our authentic curiosity and skepticism to the latest industry trends, from federated learning revivals to the shifting boundaries of edge and cloud AI. Join us for a conversation that connects practical innovation with the big questions shaping industrial AI. Siemens https://www.siemens.com/global/en.html Roland Busch https://new.siemens.com/global/en/company/about/management/roland-busch.html CES (Consumer Electronics Show) https://www.ces.tech/ Bosch https://www.bosch.com/ Yann Le Cun https://en.wikipedia.org/wiki/Yann_LeCun Federated Learning https://en.wikipedia.org/wiki/Federated_learning OPC Foundation https://opcfoundation.org/ OPC UA (Unified Architecture) https://opcfoundation.org/about/opc-technologies/opc-ua/ Resource Description Framework (RDF) https://www.w3.org/RDF/ Boston Dynamics Atlas https://www.bostondynamics.com/atlas/ Hyundai Motor Group https://www.hyundai.com/worldwide/en/company/newsroom/hyundai-motor-group-completes-acquisition-of-boston-dynamics-0000016337 Neura Robotics https://www.neura-robotics.com/ European Robotics Forum https://erf2024.eu/ World Economic Forum (Davos) https://www.weforum.org/events/world-economic-forum-annual-meeting-2024/ The Magic Mountain by Thomas Mann https://en.wikipedia.org/wiki/TheMagicMountain Path Robotics https://www.path-robotics.com/ ASML https://www.asml.com/ Blender https://www.blender.org/ Moondream (Vision Language Model) https://github.com/itsnamgyu/moondream VBTI https://www.vbti.nl/ Adam One (Inspection Robot) https://www.vbti.nl/adam-one/

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

Explore how synthetic sound data is reshaping robotics, manufacturing, and the future of industrial AI. Hear the next frontier. Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co. We thank our partner SIEMENS In this episode, we dive into why sound is the next big leap for AI in industry. I share insights from recent events, including the SPS exhibition and Europe's AI scene, and discuss why edge AI is outpacing the cloud on the shop floor. Then, I sit down with Dr. Finnur Pind from Treble Technologies to explore how synthetic sound data is powering smarter machines—from voice recognition in cars to giving robots a sense of hearing. You'll hear how simulating sound opens up new possibilities for robotics and spatial awareness, and why industries are racing to make AI models that can truly listen. We also touch on the unique AI startup scene in Reykjavik, the challenges of accurate sound modeling, and what the future holds for audio-driven innovation. Join us to discover why the future of industrial AI might just depend on what machines can hear. Siemens https://new.siemens.com/global/en.html SPS Exhibition https://sps.mesago.com/nuernberg/en.html Beckhoff Automation https://www.beckhoff.com/en-en/ Phoenix Contact https://www.phoenixcontact.com/online/portal/us KUKA https://www.kuka.com/en-de/ Bosch https://www.bosch.com/ OPC Foundation https://opcfoundation.org/ MQTT https://mqtt.org/ HiByte https://www.hibyte.com/ MathWorks https://www.mathworks.com/ Jürgen Schmidhuber https://people.idsia.ch/~juergen/ Richard Sutton http://incompleteideas.net/IncIdeas/BitterLesson.html LSTM (Long Short-Term Memory) https://en.wikipedia.org/wiki/Longshort-termmemory OpenAI https://openai.com/ Google DeepMind https://deepmind.google/ AlphaFold https://www.deepmind.com/research/highlighted-research/alphafold Boston Dynamics https://www.bostondynamics.com/ NeurIPS (Conference on Neural Information Processing Systems) https://nips.cc/ Treble Technologies https://www.treble.tech/ DTU (Technical University of Denmark) https://www.dtu.dk/english Slush https://slush.org/

Discover how engineering, simulation, and AI converge to shape tomorrow’s breakthroughs. Why combining math and machine learning changes everything. In this episode, I sit down once again with Professor Oliver Niggemann to unravel the world of numerical machine learning—where traditional engineering meets cutting-edge AI. We explore real-world projects from diagnosing the International Space Station to designing safer bridges, smarter batteries, and even optimizing biodiversity. Oliver breaks down how fusing symbolic knowledge and neural networks is revolutionizing simulation, design, and problem-solving across industries. If you’ve ever wondered how AI can speed up material discovery or what the future holds for interdisciplinary engineers, this conversation is for you. We dive into the power of surrogate models, the evolution of engineering education, and why tomorrow’s innovations demand both deep technical expertise and creative collaboration. Join us for a look at the next frontier in industrial AI. Siemens https://new.siemens.com/global/en/company/topic-areas/artificial-intelligence.html Oliver Niggemann https://www.hsu-hh.de/ims/team/niggemann/ Helmut Schmidt University (University of the Armed Forces Hamburg) https://www.hsu-hh.de/ KISS Project https://www.dlr.de/rd/en/desktopdefault.aspx/tabid-2441/3587_read-5637/ Airbus Defence and Space https://www.airbus.com/en/products-services/space International Space Station (ISS) Columbus Module https://www.esa.int/ScienceExploration/HumanandRoboticExploration/Columbus Fraunhofer IOSB https://www.iosb.fraunhofer.de/ Physics-Informed Neural Networks (PINNs) https://en.wikipedia.org/wiki/Physics-informedneuralnetworks Surrogate Models https://en.wikipedia.org/wiki/Surrogate_model Cusp.ai https://www.cusp.ai/ Jeffrey Hinton https://en.wikipedia.org/wiki/Geoffrey_Hinton Yann LeCun https://en.wikipedia.org/wiki/Yann_LeCun DeepMind Protein Folding (AlphaFold) https://www.deepmind.com/research/highlighted-research/alphafold

Exploring digital sovereignty, world models, and the new AI battleground. Dive into the race shaping tomorrow’s robotics. In this episode, we dig deep into the evolving landscape of industrial AI, from billion-dollar cloud partnerships in Europe to the fierce debate over digital sovereignty. We break down what sets 'sovereign by contract' apart from 'sovereign by origin,' and why this matters for companies navigating global AI strategies. We’re joined by Professor Stratis Gavves from the University of Amsterdam to unpack the world of robotics models and the critical role of physics-informed AI. Alongside the latest industry news—like SAP’s move into open-source models and the rise of edge AI—we explore what it takes to stay competitive in a rapidly shifting market. Join us as we question, challenge, and celebrate the innovations set to define the next era of industrial intelligence.

From neural networks in the ‘90s to the rise of AI copilots—how MathWorks is shaping the future of engineering innovation. In this episode, I sit down with Richard Rovner, Vice President of Marketing at MathWorks, to explore the fascinating evolution of AI in engineering. We trace the technology’s journey from its early days in the 1980s, through transformative milestones like deep learning and code generation, all the way to today's AI-driven design tools and copilots. Richard shares insider perspectives on how AI is changing the engineer’s workflow, what generative AI means for the future, and why the human touch remains essential in a world of accelerating automation. If you’re curious about where engineering and AI are headed—or how to stay ahead in this rapidly shifting landscape—this conversation is packed with insights you won’t want to miss. Siemens https://new.siemens.com/global/en/company/topic-areas/artificial-intelligence.html MathWorks https://www.mathworks.com/ MATLAB https://www.mathworks.com/products/matlab.html Simulink https://www.mathworks.com/products/simulink.html Neural Network Toolbox https://www.mathworks.com/products/neural-network.html Deep Learning Toolbox https://www.mathworks.com/products/deep-learning.html Statistics and Machine Learning Toolbox https://www.mathworks.com/products/statistics.html Text Analytics Toolbox https://www.mathworks.com/products/text-analytics.html MATLAB Copilot https://www.mathworks.com/products/matlab-copilot.html SAS https://www.sas.com/ FAW Ulm (Forschungsinstitut für anwendungsorientierte Wissensverarbeitung) https://www.faw-ulm.de/ Coca-Cola Freestyle https://www.coca-colafreestyle.com/ ARM Cortex-M https://www.arm.com/products/silicon-ip-cpu/cortex-m Max Planck Society https://www.mpg.de/en Reinforcement Learning https://en.wikipedia.org/wiki/Reinforcement_learning Model-Based Design https://www.mathworks.com/solutions/model-based-design.html

GenAI hype meets industrial reality. Discover why data teams still matter—and where AI is truly delivering impact. In this episode, we dive deep into the real-world state of AI adoption across industries, unpacking the findings of a major new survey with Gabriel Krummenacher. We explore which AI use cases actually move the needle—hint: operational efficiency tops the list—and why simply chasing the latest GenAI trends won't deliver results without a solid data science foundation. You'll hear our honest takes on what separates hype from impact, why ethical frameworks and governance drive innovation (not stifle it), and how US and European companies are taking very different paths with AI. If you're wondering where AI is truly transforming business—and what it really takes to succeed—this episode is for you. Quantum Systems https://www.quantum-systems.com/ Kaggle https://www.kaggle.com/ Antropic https://www.anthropic.com/ AlphaFold (DeepMind) https://www.deepmind.com/research/highlighted-research/alphafold Trumpf https://www.trumpf.com/ ASML https://www.asml.com/ Qualcomm https://www.qualcomm.com/ ETH Zurich https://ethz.ch/en.html Zühlke https://www.zuehlke.com/ OpenAI https://openai.com/ Toby Walsh https://www.cse.unsw.edu.au/~tw/

From cutting-edge grippers to Gemini’s world-building vision - insights from Schunk’s CTO and Google DeepMind’s Phillip Lippe In this episode, I sit down with Schunk CTO Timo Gessmann and Google DeepMind’s Phillip Lippe to explore how AI is transforming the world of robotics and industrial automation. We kick things off with Timo, who shares his vision for merging mechanical expertise with AI, the challenges of attracting top talent, and why Europe needs its own world-class robotics models. Then, I’m joined by Phillip Lippe from the Gemini team, who dives into the latest advances in generative AI, the power of foundation models, and what the future holds for scalable, domain-specific intelligence. Whether you’re fascinated by embodied AI, curious about industry trends, or want a peek into the minds shaping tomorrow’s robots, this episode is packed with insights you won’t want to miss. Siemens https://www.siemens.com/global/en.html Schunk https://schunk.com/ Google Gemini https://deepmind.google/technologies/gemini/ Google DeepMind https://deepmind.google/ NVIDIA https://www.nvidia.com/ ROS (Robot Operating System) https://www.ros.org/ Automatica Munich https://automatica-munich.com/en/ Bosch https://www.bosch.com/ EPi by AI (European Processor Initiative) https://www.european-processor-initiative.eu/ NVIDIA GTC https://www.nvidia.com/gtc/ NXAI https://www.nxai.io/ Samsung Nano model https://research.samsung.com/artificial-intelligence NeurIPS https://nips.cc/

Dive into the future of industrial AI with unique human stories and cutting-edge model breakthroughs. Discover why time series is the next frontier. We spent time at our event in the Black Forest, where innovation met inspiration at our latest industrial AI gathering. In this episode, we share stories—from empowering autistic talent in data annotation to the technical leaps in foundation models for time series. You’ll hear from leading minds like Jakub Tomczak, who flew in from San Francisco to challenge what’s possible in generative AI, and explore how the landscape is shifting from traditional machine learning to adaptive, context-rich automation. Join us as we question what makes AI truly intelligent, debate the role of human factors, and look ahead to the next wave of industrial transformation. If you’re curious about how AI is evolving in real factories, how new job profiles are emerging, or why continuous learning and time series matter more than ever, this conversation is for you.

How ultrasonic data and AI are transforming spot weld inspection. A look inside next-gen automotive manufacturing innovation. Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co. We thank our partner SIEMENS In this episode, I dive into the fascinating world of non-destructive material testing with Christian Wagner from Vogt Ultrasonics and Jan Kutnik from Evoptima. Together, we explore how AI is revolutionizing spot weld inspection in the automotive industry, making quality control smarter and more precise than ever before. We discuss the challenges of processing massive ultrasonic datasets, adapting AI models to real-world manufacturing, and the journey from legacy systems to cutting-edge solutions. If you’re curious about how collaborative robots, vision systems, and robust AI are reshaping factory floors—and what it takes for mid-sized companies to lead the charge—this is an episode you won’t want to miss. Siemens https://new.siemens.com/global/en/products/automation/topic-areas/industrial-ai.html VOGT Ultrasonics https://www.vogt-ultrasonics.de/en/ Evoptima https://evoptima.com/ Phased Array Ultrasonic Testing (PAUT) https://en.wikipedia.org/wiki/Phasedarrayultrasonic_testing LSTM (Long Short-Term Memory) Networks https://en.wikipedia.org/wiki/Longshort-termmemory Collaborative Robots (Cobots) https://en.wikipedia.org/wiki/Collaborative_robot REST API https://en.wikipedia.org/wiki/Representationalstatetransfer Czech Technical University in Prague https://www.cvut.cz/en IDS Imaging Development Systems https://en.ids-imaging.com/

From industrial skepticism to breakthrough robotics—why adaptability and real-world data change everything. Discover what’s next for manufacturing AI. In this episode, we dive into the realities behind industrial AI adoption—both the successes and the setbacks. We share candid conversations with engineers frustrated by unreliable AI and explore why real-world robustness remains the central challenge. Then, I sit down with Andy from Path Robotics, who reveals how their AI-driven welding robots are redefining adaptability and reliability on the shop floor. We unpack what makes their approach unique, from multi-modal sensors to reinforcement learning and massive real-world datasets. If you care about the future of manufacturing, data-driven automation, and the evolution of industrial roles, you won’t want to miss this discussion. Join us as we look ahead to what’s possible when AI finally delivers on its industrial promise. Siemens https://new.siemens.com/global/en.html Path Robotics https://www.path-robotics.com/ Obsidian (Path Robotics AI Model) https://www.path-robotics.com/technology/ Yaskawa https://www.yaskawa.com/ Universal Robots https://www.universal-robots.com/ ABB https://global.abb/group/en KUKA https://www.kuka.com/ FANUC https://www.fanuc.eu/ Reinforcement Learning https://en.wikipedia.org/wiki/Reinforcement_learning World Models (AI) https://worldmodels.github.io/ Industrial AI Podcast https://www.industrial-ai-podcast.com/ Machine Learning Week https://machinelearningweek.eu/ Frankfurter Allgemeine Zeitung (FAZ) https://www.faz.net/ Rich Sutton's 'The Bitter Lesson' http://www.incompleteideas.net/IncIdeas/BitterLesson.html XLSTM Scaling Laws Paper https://arxiv.org/abs/2404.07143 Embraceable AI https://embraceable.ai/ Deloitte Agentic Framework https://www2.deloitte.com/global/en/pages/about-deloitte/articles/agentic-ai.html Isaac Asimov's 'Sally' https://en.wikipedia.org/wiki/Sally(shortstory)