『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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このコンテンツについて

 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
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  • MathWorks Safe AI, the Pope and Reinforcement Learning

    MathWorks Safe AI, the Pope and Reinforcement Learning
    2025/05/14
    In this episode, we talk to Lucas from MathWorks about their Safe AI Approach and how it can be used to make money, think about the Pope, and introduce our new US correspondent.
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    52 分
  • Multi-Agent Generative Systems (MAGS) for transforming industrial processes

    Multi-Agent Generative Systems (MAGS) for transforming industrial processes
    2025/05/07
    MAGS harness the creative potential of generative models while enabling intelligent agents to collaborate, adapt, and solve complex problems in real time. This new synergy elevates AI systems beyond traditional automation, pushing them into the realm of autonomous problem-solving, creative thinking, and adaptive decision-making. The development of MAGS marks a significant shift in the way organizations approach challenges in rapidly evolving environments. By integrating Large Language Models (LLMs) and other advanced generative models with agents capable of learning and interacting independently, MAGS enable organizations to address problems that are not only multifaceted but also constantly changing. This guide explores the foundational elements of MAGS, their architecture, and why they matter for industries that need to navigate complexity, unpredictability, and scale.
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    49 分
  • Do we need a "LexLeCun" or how to deal with US talents?

    Do we need a "LexLeCun" or how to deal with US talents?
    2025/04/30
    We need to talk about talents – AI talents. We lack them in companies (really?), but also in universities, and, "Now that Trump is in power in America, it is easy to poach them and bring them to Europe," according to some politicians. The idea is not far-fetched, but Trump bashing alone will not attract anyone to Europe. Europe first has to do its homework.
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    42 分

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