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 Industrial AI Podcast is a proud partner of the Women in AI & Robotics initiative. 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
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あらすじ・解説

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 Industrial AI Podcast is a proud partner of the Women in AI & Robotics initiative. 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 博物学 経済学
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エピソード
  • Redefine Safety and AI with xLSTM and SLAM

    Redefine Safety and AI with xLSTM and SLAM
    2024/11/20
    Spleenlab is a highly specialized AI software company founded with the Idea to redefine Safety and AI. Since April 2018, the company has been primarily engaged in the development and distribution of safe Machine Learning algorithms for the semi- and fully autonomous mobility, especially the flight of unmanned aerial vehicles (UAV), helicopters, Air Taxis, driving vehicles and beyond. The groundbreaking fusion of different sensors, such as camera, laser and radar by means of Machine Learning is the core business of the company. The generated SLAM (Simultaneous Localization and Mapping) enables completely new applications and products for any kind of autonomous mobility.
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    35 分
  • AI in MedTech: 20 % faster ramp up time

    AI in MedTech: 20 % faster ramp up time
    2024/11/13
    This episode unpacks how AI isn’t just about futuristic robotics but is already reshaping industries as unassuming as brooms and brushes. What makes a self-learning system adaptable in such high-stakes settings? Why does it matter that AI “never stops learning”? Join us as we uncover the unexpected depth behind automation and explore how cutting-edge AI is changing MedTech manufacturing from the ground up.
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    1 時間
  • Agentic Process Automation for Industrial Applications

    Agentic Process Automation for Industrial Applications
    2024/11/06
    In a fascinating conversation, Dr. Christian Gilcher guides us through the differences between RPA (Robotic Process Automation) and the more advanced APA approach, which uses AI agents to dynamically manage complex processes in a compliant and efficient manner. They discuss how APA not only solves cost and capacity issues in regulated industries but also provides an innovation boost within the industry. A highlight: APA’s potential goes far beyond optimization, paving the way for entirely new industrial processes in the future.
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    47 分

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