『Industrial AI Podcast』のカバーアート

Industrial AI Podcast

Industrial AI Podcast

著者： Robert Weber / Peter Seeberg
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The Industrial AI Podcast reports weekly on the latest developments in AI and machine learning for the engineering, robotics, automotive, process and automation industries. The podcast features industrial users, scientists, vendors and startups in the field of Industrial AI and machine learning. The podcast is hosted by Peter Seeberg, Industrial AI consultant and Robert Weber, tech journalist.Their mission: Demystify Industrial AI and machine learning, inspire industrial users. The hosts: Peter Seeberg is an Industrial AI and machine learning expert for the manufacturing industry. He worked over 25 years in IT (Intel) and 10 years in Automation. He co-initiated the Industrial Data Intelligence Startup (Softing) where he was responsible for managing machine learning projects in industrial environments. Today he advises companies when it comes to Industrial AI and machine learning. Together with Robert Weber, journalist for industrial topics, he discusses AI and ML applications, standards, and education topics, make or buy decisions as well as regulation for AI in manufacturing.Robert Weber / Peter Seeberg マネジメント マネジメント・リーダーシップ 博物学 科学 経済学 自然・生態学
エピソード
  • Flat Earth: Are Engineering Tools About to Disappear?

    Flat Earth: Are Engineering Tools About to Disappear?
    2026/10/28
    We’re seeing an explosion of AI in engineering: models turning drawings into 3D designs, agents helping create plant layouts, and new tools challenging the way engineers work. So where will the value come from next—engineering software, AI platforms, or the context data behind them? I also explore whether agents could leap across the traditional automation pyramid and connect directly with industrial systems. Then I talk with Bosch’s Thorsten Brach about connecting AI agents to industrial robots using MCP, MHS, and SRCI. We get practical about robot integration, deterministic PLC functions, and why wheeled robots may arrive in factories before legged humanoids. The big question: how do we make these systems easier to use without losing the expertise needed to keep them safe and reliable?
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    1 時間 17 分
  • The Navier–Stokes Problem and the Agents

    The Navier–Stokes Problem and the Agents
    2026/10/21
    Did OpenAI really solve the Navier–Stokes problem? In this episode, we ask mathematician Gonzalo Caolabora. and AI professor Günter Klambauer what the proof means, why it has been difficult to verify, and whether large language models are discovering mathematics or combining ideas from existing research. We also discuss why AI can excel at problems with verifiable answers, where today’s systems still struggle, and how AI could reshape mathematical research and careers. The big question: as proofs become more automated, what will mathematicians focus on next?
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    27 分
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