Transcript 0:00 Talk to me. Information, news and entertainment on demand. WUSradio.com. 0:11 [upbeat music] Welcome to The Peggy Smedley Show, the voice of IoT in our connected world, with your host, Peggy Smedley. Hello, listeners, and welcome back to The Peggy Smedley Show. 0:26 My final guest today is a regular on the show. He conducts research in the field of human infrastructure interaction, and he just recently welcomed a new bundle of joy into his family. 0:38 Please welcome Joshua Peschel, Assistant Professor of Agriculture and Biosystems Engineering at Iowa State University. Josh, congratulations on the new addition to your family. Are you getting any sleep? 0:53 Well, first of all, let me say, thanks. It's good to be with you, and as a matter of fact, I'm very pleased to report that he did sleep four hours last night in a row. [laughs] And we're very excited about that. 1:04 Well, that's wonderful. Congratulations. How exciting. Well, I'm glad that you were able to make it on the show. We were, we were excited that you were able to do it, so thank you for that. 1:13 So let's talk about some exciting things that are happening in this space. You know, there are lots of exciting things happening in machine learning in the supply chain today and AI, and I know you know a lot about it. 1:23 What do you think? What's going on? What are some of the biggest drivers? So there's a lot of great drivers. 1:29 I think probably the important thing before we get into and drill down into, you know, what we're looking at there is to really, a lot of people say AI and machine learning kind of in the same sentence, but there is actually a pretty unique distinction between the two. 1:43 So when we're talking about AI, I think we're looking at more strategic things, and that's really, uh, our ability, um, 1:50 to have computers act like people or do things that people do at the present time, so that's like acquiring and applying knowledge. 1:58 But then on the other hand, you have machine learning, which I tend to think as more tactical. So that's really the acquisition of knowledge, skills, and abilities, things that are focused on tasks. 2:07 So when we look at, uh, really the crux of your question is what are the biggest drivers in that? So when we're, we're looking at AI, we're looking at improved decision-making. And in that we, we have automation. 2:18 But I think, you know, that gets talked about a lot. I think an exciting area that's being driven now is, is, uh, uh, augmentation. So how can we do things different and better? Okay? 2:29 And that might be, let's say, uh, your classic, uh, manufacturing example might be going into a warehouse and being able to see, uh, whatever is there through augmented reality or something like that. 2:42 When we talk about machine learning, I think that is a subset of artificial intelligence, really more making sense of the, of the data that we have, perhaps the things that we didn't know were there all along. 2:53 So on one hand, AI, strategic, machine learning, tactical, they go hand in hand. 2:59 Um, and, and there, there are many things driving them from profitability to efficiency to just making things different and better for the people, uh, who are parts of these processes and systems. 3:12 As we advance right now, it's we envision man, machine working together in this new supply chain. You know, people are even talking about the digital twin. We've talked about that on the show before. 3:23 Are we now seeing in the supply chain? You know, we're gonna see tasks being eliminated. We're gonna see... 3:29 We've talked about even in agriculture, how we can actually apply these things and really get the data to make things better. How quickly, and I, you know, I just asked our last guest this as well. 3:41 Are we gonna see this moving i-in a, in a way that we can actually leverage it? But we gotta have the information, we gotta have the data. Are we gonna be willing to share the data yet? 3:52 Are we still gonna be hindered by our own limitations? Well, I think that that-- I think the answer to that question is it depends. 4:00 If you're looking at the data as a commodity in itself, it depends on who owns it, what it's gonna be used for, uh, how it's gonna interact with existing and future systems. 4:10 If we kind of bring more of the human element into it, then it kind of gets into a, a different kind of question. 4:16 And so if we look at the implementation of, of these technologies in the supply chain, you know, when we start looking at people, a lot of people start talking about replacement, and it, and it's, it's not really that. 4:29 I think that it's really repurposing. It's repurposing the place of the person as a decision-maker to either kind of get into understanding a process or system more deeply. 4:41 And a lot of times, it's just managing more proficiently of, of what they're dealing with. And a really great example that I like to talk about with this is assistive technology and having that data be effectively... 4:53 You know, you talked about a digital twin or, or how, how can you leverage that data or that, uh, technology either as a, as an agent or the data as an agent in some way. And so let's say animal production systems. 5:05 You talked about agriculture. Caretakers have to manage thousands of animals on a daily basis, twenty-four hours a day. 5:12 And so how can you watch all of those animals to apply your knowledge, skills, and abilities to maybe see which ones are getting sick or which ones might need some help? 5:22 It's just really impractical, but with some assistive technology, you could do that. And I've got one better for you. A lot of the caretaker turnover rates in terms of employment are pretty high. 5:32 So how do you bring in a brand new person that can get into all this data, uh, and, and, and manage these systems so that you don't have a disruption in the supply chain? In this case, it's, it's, it's animals. 5:45 Uh, it-- That technology, that data effectively provides a, a management safety net for that person to make them more proficient as they learn to do their job different and better. 5:54 So it, it's really all this data, all this technology, it's really applicable to people who are very expert in what they do and also very novice in what they do. 6:04 So it's reallyIt, it's really repurposing the role of the operator with this data and technology, and I think, I think that's, that's the way I think we should look at how data and people are gonna interact with the supply chain as AI and ML ramps up in, in the coming months and years. 6:22 It's an interesting point that you just made because as people hear the word data scientists, we all think this has got to be a highly educated, highly sophisticated, and in some ways it has to be someone who can understand how to interpret data. 6:35 So really when we look at data, it's just got to be someone who needs to understand their job and what they're doing, and they don't have to be this highly educated like we think. 6:43 You just have to understand what the data means, right? I mean, that's what you're saying. So sometimes, you know, this idea- I think- This... Go ahead. I'm sorry. Yeah. I, I think so. 6:52 I, I think that, you know, when you look at the people who interact with it, it's, it's trying to lift them up. And so, you know, anyone who's working in whatever sector that they, they may be, uh, you really... 7:05 they really have to focus on managing their skill set portfolio. And that... 7:09 It doesn't really matter if it's the CEO of Walmart, doesn't matter if it's the manager of a baseball team or if it's person who's work-working a bulldozer to pull raw materials out of the ground. I think being able to, 7:22 to know your job well, but learning how to leverage effectively AI and machine learning to do your job different and better, that's part of sort of managing that skill set portfolio. 7:35 And what I usually tell people is that AI and machine learning, uh, like fire, should really be respected and not feared. 7:43 Uh, with fire, you, you know, there are many benefits that come from that, so you shouldn't really be afraid of it, but you should, I think, have a responsibility to know how to well manage it to be able to do what you're doing different and better. 7:55 And I think that's how all that fits together as it relates to, uh, you know, people using it. We've got about thirty seconds left, Josh. 8:06 Looking at all of this right now, what excites you most when you look at AI right now and you see it being applied in the things that you're doing and the research you've been doing? 8:16 So there's the classical examples of the supply chains, the Walmarts, the Twitters, the Facebooks and all that. 8:21 I think the really most exciting thing right now that's happening is the implementation of machine learning in video production, media and video production, and especially as it relates to what are called deep fakes. 8:34 So that's actually changing, augmenting, uh, repurposing video into something that either never was or that has changed to something else, and I think that's the most exciting place. 8:46 So either it's producing a new broadcast or, or being able to sniff out when somebody's doing something that they shouldn't be doing represented in a video format. 8:55 I think that's the most exciting thing coming as it relates to machine learning that, that I'm working on, that others are as well. 9:01 Well, Josh Peschel, Assistant Professor of Agriculture and Biosystems Engineering at Iowa State University, as always, thank you for being with us. 9:08 Where can our listeners go, as always, to learn more about what you guys are doing? Sure. 9:13 To learn more about what we're doing here in the department at Iowa State, it's abe.iastate.edu, and if you want to look at what we're doing here in my research group, it's just peschelgroup.org. 9:22 All right, Josh, get some rest. Thank you for joining us. Thank you. It's good to be with you today. All right, listeners, we're out of time. 9:29 Check out our website at connectedworld.com or any of the show archives at thepeggySmedleyShow.com or tweet at us at ConnectedWMag. [upbeat music] Thanks for listening. 9:39 Remember, we're broadcast every week, every Tuesday at twelve PM Central. As always, this is The Peggy Smedley Show, the podcasting voice of IoT and relevant technology. 9:48 Remember, with great technology comes great responsibility. Have an awesome week. 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