Techzine TV podcast
In the Techzine TV podcast we analyze B2B IT solutions, strategies, and trends. IT companies are happy to invite us to talk about what they are working on and what they are going to bring to market. We visit them all around the world, and in some cases, they visit us in our office.
We have a good understanding of how technologies work, or how they should work. We also hear a lot from the market about what companies need or where things go wrong. This gives us the ability to have really in-depth conversations on technology, strategies, and products, but we always try to keep it practical and easy to understand.
We explain innovations, interpret new IT concepts, and use practical examples to make complex technology understandable for everyone. Where necessary, we bring in experts to clarify matters further. The goal is to help IT professionals, decision makers, and other listeners better understand IT developments, but also to help them in their search for new solutions for their business and not get stuck on buzzwords and one-liners.
The Techzine TV podcast is an evolution of the previous Techzine Talks on Tour series. We still bring a lot of conversations and interviews from events to this series. We record so many video interviews nowadays, so we can select the best ones for this podcast series.
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Techzine TV podcast
Edge AI and private 5G are made for each other
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At NTT Upgrade 2026, Paul Bloudoff, senior director of Edge AI at NTT Data, discusses with us how edge computing, private 5G, and physical AI are transforming manufacturing operations. We talk about the symbiotic relationship between edge AI and private 5G connectivity, and focus on how manufacturers can achieve real-time insights and automation on the factory floor.
During our conversation, Bloudoff talks about real-world examples, including Cargill's deployment of private 5G across 50+ manufacturing facilities, and explains how NTT Data delivers full-stack solutions from sensors to cloud infrastructure. The conversation covers predictive maintenance, task verification through machine vision, and how foundation models can be trained with just 40 hours of video data instead of requiring months of preparation.
Key takeaways:
• Edge AI focuses on computing as close as possible to data sources in OT environments
• Private 5G enables low-latency, high-bandwidth connectivity for real-time manufacturing data
• Physical AI models can be deployed in weeks rather than years with modern foundation models
• Multiple use cases are typically needed to justify private 5G network deployments
• Safety and preventative maintenance are often the first use cases that enable adoption
• Full-stack solutions include sensors, connectivity, edge compute, algorithms, and managed services
• Partnerships with Nvidia, Qualcomm, and ISVs enable comprehensive edge AI solutions
Chapters:
1:35 - Defining the edge in enterprise environments
2:59 - Full stack edge AI solutions
4:54 - Private 5G and edge AI synergy
6:23 - Use cases for edge AI and physical AI
7:41 - Real-world private 5G deployments
13:36 - AI partnerships and ecosystem approach
13:59 - Measuring value and ROI
22:23 - Automation and the future of edge AI