Peter Sarlin, CEO of Silo AI, discusses the company's LLM-approach, use cases, and the unique features of their Poro model. They explore AI integration in software-defined businesses, value of large language models in innovation, and the global presence and talent acquisition strategies of Silo AI.

Dr. Julian Feinauer discusses the AINode by Timecho and ApacheIoTDB. Topics include multi-modal models in AI, industrial control systems using GPT-4, university collaboration on OPC UA models, Apache IoTDB efficiency, and deploying AI models in timeseries databases.

Dr. Mehmet Mercangöz, ABB Reader at Imperial College London, discusses autonomy in the process industry, human involvement in plant operations, and the future potential of autonomous systems. The conversation delves into balancing complexity and autonomy in AI systems, research initiatives, and the critical role of autonomous systems in producing essential goods.

Siemens and Schaeffler collaborate on industrial co-pilot training, AI integration, and factory automation. Topics include enhancing prompts for efficiency, data hierarchy in industrial applications, and problem-solving with shop floor copilot. Learn about their innovative approach to engineering processes and workforce communication.

The podcast discusses RAG in industrial AI, prioritizing data quality over specific AI models. It explores the benefits of RAC technology, industrial foundation models, evolution of RAC tooling, building Rackbase assistance, Sora and AI in engineering, and transformers in high-frequency time series data in industrial contexts.

A CISO from Mann+Hummel discusses their rules for GenAI and LLMs. They talk about Landing AI as a new partner and ponder if models are a commodity. In other chapters, they explore industrial AI in Europe, code translation, Microsoft and Mistral cooperation, and setting guidelines for AI usage in organizations.

Exploring AI-driven advancements in simulation for industry, predicting the future adoption of AI-based tools. Discussing challenges in scaling simulation models and integrating Larian and Lagrangian data. Guest speaker, Johannes Brandstetter, shares insights on building a foundation model for industry simulations.

Siemens Energy AI expert discusses reducing simulation computing time with machine learning. Topics include turbine optimization, evolution of turbines in energy generation, speeding up engineering simulations, evolution of machine learning models, simulating material deformation, and efficiency with NVIDIA A100 GPUs.

Richard Ahlfeld, CEO of Monolith AI, discusses the rising importance of battery testing for automotive applications and the application of AI and machine learning in this field. He shares insights on optimizing test plans, the technical aspects of battery testing with AI, and the challenges of deploying a cloud-based toolbox for battery testing.

Sepp Hochreiter, a researcher in LLM alternative architecture, discusses the advancement of XLSTM, the significance of context length in language models, the exploration of XLSTM potential and IP rights in Europe, and the evaluation of methods and abstract reasoning. The potential applications of large language models for companies are also explored.