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.
http://www.aipod.de
Gesamtlänge aller Episoden: 6 days 20 hours 35 minutes
episode 205: Realtalk: Industrial AI, LLMs and demand forecasting for retailers and intralogistics
Helmut Prieschenk, CEO from WITRON, and Franziskos Kyriakopoulos, founder of 7LYTIX from Linz, discuss ChatGPT, machine learning in logistics and demand forecasting for food retail.
episode 204: Why everyone in the industrial sector should use/try code interpreter maybe for predictive quality.
We take a brief look back at our "AI in the Alps" event. Afterwards, Prof. Dr. Marco Huber from Fraunhofer IPA explains to us why he worked with the Code Interpreter all weekend and what the approach could mean for AutoML.
episode 203: Object-Centric Process Mining
Wil van der Aalst, professor at RWTH Aachen University and the "godfather of Process Mining" gives an introduction into Process Mining and next explains what Object-Centric Process Mining is.
episode 202: Women in AI & Robotics: Can truly reliable DL models exist on given hardware systems at all?
We are very proud to present the first edition of Women in AI & Robotics. Sheila Beladinejad's first guest is Prof. Dr. Gitta Kutyniok from LMU Munich. Gitta asks the question: can truly reliable DL models even exist on given hardware systems?
episode 201: AI in China: Socialist content for LLMs
Robert Weber met MERICS expert Rebecca Arcesati at Siemens' AI with purpose summit and discussed LLMs made in China, socialist content, how de-coupling should work and what the Chinese AI strategy looks like with the China analyst.
episode 200: Anniversary episode and how CLAAS designers use AI for CAD - 200 episodes Industrial AI Podcast
The agricultural machinery manufacturer CLAAS wants to cleverly reuse components from different product series in order to save manufacturing, development and storage costs. The enormous product complexity and diversity of variants makes it difficult.
episode 199: Supply Chain and Industrial AI - from prediction to prescriptive
Sascha Bütterling has over 20 billion data points per month. He and his team at Supplyframe have built a model from this and can make predictions about availability, delivery times or prices for electrical components.
episode 198: Is Google the new Xerox? And Industrial AI trends from IoT Analytics
In the news section we have a lot of interesting announcements from Google/Alphabet. In the main part Robert talks to Knud Lasse Lueth from IoT Analytics about trends in Industrial AI and clarifies the question why companies are advertising fewer AI jobs.
episode 197: Timeseries data and ChatGPT? Limits of LLMs in industrial applications
Peter Seeberg talked to Hanna Behnke from Merantix Momentum about LLMs, industrial use cases, prompting and finetuning of the models.
episode 196: China, patents and Industrial AI
In this episode, we talk to Michael Kühne Schlinkert of Katulu about patents in federated learning, how Chinese companies are strategizing in the patent space, and how he's trying to fight back.