Enhancing IoT Systems with Agentic AI
episode
The Fast Mode Podcasts: Breaking News, Analysis and Updates From Telecoms Industry
23 min
1 speaker
8 chapters
transcribed 1 month ago
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What is Agentic AI and how does it differ from traditional AI in industrial IoT?
Welcome to the Fast Mode Podcast series. I'm Tara Neal and with me today is Linair Zamir, AI engineer team lead at Telite Centerion. Tillit Centerion offers comprehensive IoT solutions that reduce time to market and costs through custom market ready connected devices. With over thirty years of IoT innovation experience, the company delivers award winning secure and integrated IoT solutions. Welcome, Linier. Great to have you on today's episode.
Thank you for having me.
Awesome. Well, great to have you with us today and I think we have uh quite a number of questions, uh, you know, things that we want to talk about in IoT on IoT, on AI and stuff. So looking forward um, you know, to an interesting session today. And to start off, okay, let's talk about um, you know, how agentique AI and industrial agents are enhancing what traditional IoT systems can do.
Uh first of all, thank you again for having me. Um and yeah, uh the AI world is moving at a rapid speed, um, as we can all all understand and see. Um so in the in the industrial settings, when we talk about AI and agentic AI. First of all we need to understand what the agentic is actually means. What's the word agentic AI actually means.
Yep.
Uh so unlike the traditional AI that that was what was before the whole innovation that we see nowadays Um the traditional AI was able to basically query data, look at the data and then understand it and basically give you the outcome or the the uh the understanding of the data based on a question that you ask it. Whereas nowadays the Agentic AI is a much more sophisticated and autonomous tool so that it can work independently. So unlike the traditional applications of AI within the in the the industrial settings. Now you have an agent that can be somewhat of a co pilot and can help the operator I can help management. and do everything autonomously by uh looking at the data. understanding the data and then autonomously give you the outcome, the results based on all the information and the context that it has.
Mm-hmm. Oh. Okay. So when you have um you know these agents running the show on our behalf, right?
How do Agentic AI agents act as co‑pilots to improve decision‑making and reduce human involvement?
So one thing is that um we do come in, uh humans do come in in the process at the beginning. And then once these um agents uh have learnt, you know, have learnt and mastered the process, so basically we can just let them do um you know what is routinely done by humans. So in this case In case, um, you know, w in relation to traditional IoT systems, um, what what's the exact change that we would see? Is it that now humans are less involved, or do we see better decisions, faster decisions? Yeah.
Uh a great question. Uh uh yeah, and this is uh I think this is a point that scares many people Um, when we we say all the capabilities that AI has, some people might say, Oh my god, it's going to replace me and it's gonna take over. Uh yeah, but this is uh uh this is not the case, uh in uh you know, in the industrial setting I would say. Uh uh Well the the AI tools that we have nowadays, we can think about it as more of a co pilot, as more of a an assistant. to the human to make better decisions. That's it. At the end of the day, the the uh uh the per we need the person to uh uh to confirm the decision, to monitor everything, make sure everything is done smoothly. It is true that as we evolve and as AI evolve, it has more and more capabilities.
But we would always have to have a person uh that monitors that uh uh that confirm everything that the AI decides to do. Um but now you can think about it as uh uh even the industrial revolution, right, going back uh in time. Uh when it first started people got scared that oh my god, you know, it's gonna take over all all the work and the engines and and uh you know, the speed of operations, it's going to be significantly faster now uh that it's gonna take over jobs. Uh and that's the same case that we see nowadays with the AI revolution. Uh and yeah, I call it the AI revolution. Uh it's pretty much the same where uh it's true that Uh some tasks can be replaced by a I
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Chapters
8 chapters
1
What is Agentic AI and how does it differ from traditional AI in industrial IoT?
0:11–2:38
2
How do Agentic AI agents act as co‑pilots to improve decision‑making and reduce human involvement?
2:38–5:22
3
What concrete benefits does Agentic AI bring to IoT systems compared to legacy solutions?
5:22–8:28
4
How is Telit Cinterion integrating AI into its DeviceWise orchestration platform?
8:28–11:26
5
Why is bringing AI to the edge important for industrial customers and how is it achieved?
11:26–14:01
6
What are the main challenges when deploying Agentic AI in IoT ecosystems (human acceptance, security, data ownership)?
14:01–17:11
7
How does Telit’s edge AI solution handle data privacy and on‑premises deployment requirements?
17:11–20:34
8
Can you share a real‑world case study of a robot inspection use‑case powered by Agentic AI?
20:34–23:00
Speakers
1 identifiedMore from The Fast Mode Podcasts: Breaking News, Analysis and Updates From Telecoms Industry
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