AI is in the news every single day and in conversations at every water cooler. And as it continues to evolve, it offers unprecedented opportunities for supply chain innovation, creating a more agile and resilient industry poised for the future. From enhanced efficiency, accuracy, and adaptability to the optimization of demand planning, inventory management, and logistics, AI continues to be front of mind for supply chain leaders around the globe.
Enter Noodle.ai, a trailblazing organization at the forefront of AI innovation in the global supply chain industry. In today’s episode, hosts Scott Luton and Greg White welcome Diego Klabjan, Professor at Northwestern University, Director, Master of Science in Machine Learning and Data Science, and Director, Center for Deep Learning along with Steve Pratt, the Founder & CEO of Noodle.ai, for an enlightening episode about the captivating realm of artificial intelligence (AI) and its profound impact on supply chain operations.
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Join us in this enlightening journey as we uncover the power of AI in shaping the future of supply chain management.
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Scott Luton (00:00:33):
Hey, good morning and good afternoon. Good evening, wherever you are, Scott Luton and Greg White with you here on Supply Chain. Now welcome to today’s show, Gregory. How we doing today?
Greg White (00:00:43):
I’m doing well. This is coming off
Scott Luton (00:00:45):
Greg White (00:00:45):
As glass, don’t
Scott Luton (00:00:46):
You think? <laugh>? That’s right. As smooth as Greg White and that’s world class smoothness folks. Lemme tell you. All right. So Greg, man, we are tickled to be kicking off a new limited run feature series here today on supply chain. Now we’re partnering with Noodle ai, a dynamic organization driving powerful innovation in global supply chain. And today, Greg, as you know, we kick off episode one of this new series that’s entitled, making Better Supply Chain Betts with the Power of Probabilities. And today we’re gonna be focused on building a strong
Greg White (00:01:20):
Scott Luton (00:01:20):
Really deme, I can never say demystifying, demystifying. I gotta go real slow, real slow. Two miles an hour. We’re gonna be focused on demystifying artificial intelligence and talking about real opportunities and outcomes for AI in supply chain. Greg, are you, uh, excited as I am here today?
Greg White (00:01:39):
What can I say, Scott? I’m, uh, excited, enthused, intimidated. Rarely do we get to talk to people
Scott Luton (00:01:45):
This much smarter
Greg White (00:01:47):
Than we are. Usually they’re this
Scott Luton (00:01:48):
Much smarter than we are <laugh>, so,
Greg White (00:01:50):
Scott Luton (00:01:51):
Greg White (00:01:52):
I’m excited. I think, you
Scott Luton (00:01:53):
Know, Noodle’s not a new kid
Greg White (00:01:55):
On the block. They’ve been doing this AI thing since
Scott Luton (00:01:57):
Greg White (00:01:58):
AI was cool.
Scott Luton (00:01:59):
Mm-hmm. So, yes. So with that said, let’s introduce our featured guests here today. I wanna welcome in Steve Pratt, founder and c e o with Noodle ai. Steve, how you doing?
Steve Pratt (00:02:10):
I’m doing great. Thanks Scott.
Scott Luton (00:02:12):
You bet. Really have enjoyed our pre-game already. And you’ve brought with you Professor Diego Kian with Northwestern University Diego, how you doing?
Diego Klabjan (00:02:22):
I’m good, thanks for asking. Great. Thanks for having me.
Scott Luton (00:02:25):
Well, great to have you. And, and Greg, we’ve gotta point out, we’ve got lots of sports allegiances, but Diego is a fellow Atlanta Braves fan, in addition to being a Cubs fan like Steve. Is that right, Greg? That’s what we learned in the pre ship.
Greg White (00:02:39):
Yeah, I heard him say Braves, so I’m gonna take that as fandom. <laugh>. Yes, <laugh>.
Scott Luton (00:02:44):
Alright, good, good, good. So Steve and Diego, great to have you here. Looking forward to a great baseball postseason and a great discussion here today. So I wanna start with this. So Steve, you’ve got an incredible background, man. We’d be here for days if we walked through it all. We really, really enjoyed our, our pre-show conversations I mentioned, but I wanna start with our team’s. Done a little intel, a little digging on your background. We understand you’re a parttime, grape And olive farmer, So you gotta tell
Steve Pratt (00:03:11):
Us more. It’s guilty as charge. Yes. I, so I have a ranch up in Napa County in St. Helena and got about 500 olive trees, several acres of grapes. And, and so I Actually Taught myself grape farming from YouTube, Videos, books, and, uh, a Yoda that lived down the street. In fact, we had our first harvest last Friday and it was four times what last year’s harvest was. Wow. And so we’re, which is like good news, bad news, <laugh>. ’cause it’s so much, it’s so much wine. Like we hadn’t planned for that. And so, but yeah, I, I think it’s connects me with nature, get to see the cycles of the seasons. I think. Well up there it’s sort of my, not quite my fortress of solitude, but something like that. <laugh>.
Scott Luton (00:04:06):
Well, Greg, if Steve is looking for, uh, regional fortress of sobriety, either <laugh>, yes. Right, right. Steve, if you’re looking for distribution representation in Southeast, hey, give us a call. We can help you get rid of any excess wide. Alright, so let’s switch gears here. And by the way, you’re paint a pi, pretty picture, 500 olive Trees there in California, I bet. No wonder it is a, a way to unplug and, and, and step away from all the cool things you’re do in the industry. Alright, so Diego, now this is a pretty unique piece of intel we gathered on you, Greg, our team says that Diego’s one of his biggest hobbies that you, that he wish he had more time to spend on mm-hmm. <affirmative> is coding. So in particular, Diego, we hear you love to explore and learn new computer programming languages. So I gotta ask you, when did this passion begin and what’s One of Your newest languages that you’ve tackled?
Diego Klabjan (00:05:00):
Yeah, so I, I liked computers and codings from my very early days from high school. That goes way back, what, 1980 roughly. So I started coding at that time, literally just for fun and I still love it. So I, as I said, I wish I, I have more time doing the actual coding. So my lady, sort of a computer language that I started exploring about a year ago, and I spent a few days working on it during the summer is rust, r u s t. Not sure if you’ve heard about it. So it’s a modern language that’s supposed to be called safe. Safe from the security perspective. So you kind of cannot do, you cannot create memory errors. Right. Okay. So that’s, that’s my passion. But now’s okay. On the less sort of professional side, I actually do enjoy a lot running marathons and I’m gonna run now on Sunday in the Chicago marathon. Oh, wow.
Steve Pratt (00:05:54):
Scott Luton (00:05:55):
So do you have a target?
Diego Klabjan (00:05:57):
I’m Getting old and older by the year, so my times are declining every year, so I do have it. So I do have it. I’m not proud of it anymore.
Scott Luton (00:06:07):
You’re better, you’re better off Diego than probably 98% of the rest of us. So keep running
Diego Klabjan (00:06:13):
If you want a number. Three 30. So three and a half, three hours. Okay.
Scott Luton (00:06:17):
Three and a half hours. Wow. That’s pretty solved. I’m writing that down <laugh>. So lemme go back though for a second. And Diego, you’ll have to let us know how you finish. We’re gonna, we’re writing that down and we’ll do a check on you. Greg, you, you were nodding your head when he said rust. Are you familiar with that, that computer language, Greg?
Greg White (00:06:33):
Nope, Not at all. But I have people who are familiar with it also. I’ve heard Them say it a lot lately. <laugh>. Yeah, I, I can name a lot of Languages. I haven’t Been allowed to write in any languages, including English since 2011. So.
Scott Luton (00:06:50):
<laugh> well, along those lines, I’ll share a little bit of that with you. When I started college, I started in computer science, Diego and Steve, as Greg knows, and I, I had one, one semester of c plus plus, and that was all I could take. So that was not my passion. Like it is perhaps both of yours, but nevertheless, we gotta move on. We got a lot to, a lot to get into today that I think is gonna really inform, educate and in enlighten and de uh, demystifies. We talked about a lot of our audience because of course, you can’t have a single conversation these days without saying AI or gen ai or both, or you name it. So the key focus here today is demystifying ai and of course, in particular talking about how to apply generative AI to global supply chain. And we’re not talking about chat G p t, Greg, not talking about chat, G P T. We’ll talk, uh, more on that in a second. So let’s build a foundation. So let’s start with you Steve, if you would please, you know, clarify what gen AI entails and how it sets itself apart from all the conventional machine learning, artificial intelligence techniques. Tell us more, Steve.
Steve Pratt (00:07:59):
Right, so the, the breakthrough in generative AI is that it produces new content that never existed before. So It’s predecessor or the other main category of ai, which is predictive AI would take the things in his memory and would label them, or he would say like, find a picture of a dog and it would label this as a dog. Whereas generative AI would draw a picture of a dog. The very important construct that most people don’t understand at this point is that there are really three general categories of generative ai. There’s large language models, which is getting all the press, which is text and documents. Then there’s large image models which generate unique images from some prompt. And then there’s large graph models which are used Basically modeling data as a graph. And the connections among the nodes in that graph. So it’s large image model or large language models, large image models and large graph models. It’s very important to have that construct when you’re talking about generative ai.
Scott Luton (00:09:09):
Very helpful. L l m. Mm-hmm. <affirmative>. L I M L G M. We love our acronyms around here. Don’t look Greg <laugh>.
Greg White (00:09:16):
Um, yeah, that’s a really, that’s really good description, Steven. And under 30 seconds. So Albert Einstein approves <laugh>.
Scott Luton (00:09:23):
Yes. Love that. All right. Diego, what would you, how would you expound, uh, on that one? Talk about the foundational, what gen AI entails.
Diego Klabjan (00:09:34):
Right, so I would say, so generative ai, it’s really how do you create creative output that’s actually similar to your historical data. So in with technical terms or historical data, it’s also called training data, right? So I’m gonna be using the term training data quite often, right? So here’s a, a use a possible use case really to images, right? Because, uh, Steve mentioned three areas. One is images. So we suppose you have historical images of damaged products, and now you want to, so generative AI essentially creates a new, an image of a damaged product. And that image is not exactly the same as the images you currently have, but it resembles them, it’s a new image, right? And how would you benefit? So what’s the business value, right? So you could actually identify that such a pro, such a defect actually can happen of your product. And then you can go out there and examine sort of, uh, how to prevail such potential damages. So the entire area of generative ai, it’s roughly five years old. So it started with something that’s called GaN, so generative adversarial network. And then two, three years ago, a new technique called, uh, diffusion models came Out.
Diego Klabjan (00:10:48):
And now these two techniques are now combined together and they form sort of the basis together with something that’s called transformers, right? So they, so these three concepts now form the basis of, of generative ai. So why generative AI today? So first of all, generative AI morals, they require a lot of data. And with today’s advances in it and data collection and data storage, sort of, we have access to a lot of data. And the big push actually behind generative AI or the differentiating or stepping stone, okay? The, the big, the big step actually is the fact that we can now handle larger morals. And what does it mean larger morals. So it’s literally, you have to think from the brain perspective. So we have a lot of neuros in our brains. And so larger morals literally means morals that have more neurons, right? So the generative AI morals, they, they try to mimic, uh, human brains.
Diego Klabjan (00:11:52):
And so that sort of having, being capable of handling more neurons, sort of, that’s the, that was a big advancement behind generative AI in the last two to three, two to three years. Another term that you commonly hear that that’s related to generative AI is a term of foundational morals. And a financial model essentially is a model that, that is supposed to perform, or it does actually perform just one particular task, but it’s capable with some minor adjustments to do similar tasks in other domains, right? So an example here would be, so you have, you can have a model that generates marketing material, for example, it generates text together with images, right? So it’s a nice kind of marketing brochure or ette, something like that.
Greg White (00:12:41):
Diego Klabjan (00:12:41):
And originally sort of, you use historical data, let’s say in the C P G space, right? So the moral is definitely going to be able to create good marketing material for C C P G type products. But now with this adv recent advancement with a little bit of your own tailored data, for example, on cars, you can teach the moral how to create marketing material based on cars, right? Mm-hmm. So cars being quite different from c P G products, but yet you’re talking about marketing material, right? So the basic marketing material model train on or, or yeah. So trained on C P G data, that’s the foundational model, right? So, and that’s, so that’s generative AI behind, behind that, right? So that’s sort of, that’s my explanation of what is generative ai.
Scott Luton (00:13:33):
Thank you, Diego. I really appreciate that. I love the examples you Use as well. We’re gonna, we’re gonna, uh, dive in a little deeper On, on some of Those examplesAnd aspects here in a minute. But Greg, bringing you in, we heard Steve’s framework and Then Diego Expounded a, A bit More your thoughts, Greg,
Greg White (00:13:50):
you had me at Transformers <laugh>. No, I think one of the things that we have to recognize is that what we are being shown sort of educated on as far as generative AI is just a small example. We’re gonna talk about that, of what it can do, what it means that it can do this generative thing means that it can learn continuously, learn a, a generative adversarial network, essentially argues with itself to determine what is right. It says, Hey, does this look right? And it’s other self says, no, that’s not right. And in a much more complex way, I can’t believe I just said that in front of you two guys <laugh>. But, but it is substantially, that’s what it does until it eliminates all the possibilities of being wrong and goes, this must be right. And that learning capability is a huge advancement. And the fact that it, it can take, these transformers can take the data that it knows and generate data that is speculatively, this is what it could look like or should look like. Mm-hmm. <affirmative>, that’s hugely transformative. Mm-hmm. Yeah. So There is a ton of opportunity In using that, those kind of techniques out there.
Scott Luton (00:14:59):
Yep. Well said Greg And I wanna go back to something Diego said. Hopefully it’s mimicking y’all’s brain, Steve and Diego, and not some of the other <laugh>, not some of the other Yeah. Not our brains out there. Alright.
Steve Pratt (00:15:10):
That was a pretty good explanation.
Scott Luton (00:15:12):
I agree with you. I completely agree.
Greg White (00:15:14):
I feel like I may be doing something on the side a little bit. <laugh>,
Steve Pratt (00:15:16):
that’s Strange. Exactly.
Scott Luton (00:15:18):
I feel like in the last seven minutes I’ve earned a certification. It feels like Steve, Diego, and Greg. Okay, so let’s do this With every big powerful trend, tool, innovation, breakthrough, you name it, you get lots of common myths and misconceptions that, uh, you know, generate from a wide variety of folks that may not quite grasp it the way that y’all do. So Diego and Steve, if you wanna jump in as well, but Diego, any common, and when you think of misconceptions out there about gene AI or AI in general, what’s one or two thoughts that come to your mind? You?
Diego Klabjan (00:15:51):
So one misconception that I wanna point out is more kind of from the human aspect perspective or say economics perspective, right? So a lot of people fear that generative AI is going to replace workforce. I don’t think so. It’s going to augment, uh, workforce, uh, is going to improve our productivity, right? So I like to explain this in terms of, so far we have human in the loop or humans in the loop, right? So interacting sort of frequently with information systems, generative AI actually, uh, takes that one level up, uh, to the human on the loop, right? Which essentially means we still have to monitor a system, but at a higher level with fewer potential interaction. But you still, we humans still have to be there. I also view this from the perspective of that generative ai, it should makes us better, not just from the productivity perspective, but also because it essentially, I view generative AI as a new competitor, right?
Diego Klabjan (00:16:54):
So some something that I have to compete with, something that I have to be better, right? So generative AI from that perspective, at least sort, that’s my personal goal or view, is that I want to be better than generative ai, right? So it, it brings me sort of, uh, additional motivation, right? Mm-hmm. So one and, and one thing another I think misconception about generative AI is people actually have too high of an opinion of generative ai. So when I started using generative AI about a year ago, yeah, I was impressed, right? So I was talking or not talking, alright? So I tried, for example, summarizing some extra long emails, uh, and those kind of things, and I was very impressed by that. But as I progressed, as I started using Genive AI more and more, I figured out that, so for more and more meaning, for more and more complex tasks, I figured out that there’s, there are definitely limitations, right?
Diego Klabjan (00:17:54):
Mm-hmm. So if I go back to my hobby of coding, right? So yeah, Genive AI is gonna produce very good basic code, but as soon as you try to come up with a more sophisticated data science machine learning code, it’s not gonna be able to. And in the last few months, I’m actually finding out that rather than using generative AI to give me a code template, that I have to then spend a lot of time fixing it and understanding and fixing sort of tons of bugs. I’m finding out that it, that it actually takes me less time if I just don’t use generative AI and start from a blank sheet of paper. Mm-hmm. Right? So in short, right? So people are afraid that generative AI is going to replace, uh, workforce, uh, I don’t think that’s gonna happen in any sort of foreseeable future, right? And
Diego Klabjan (00:18:45):
Second, I think people have too high of an opinion about or opinion, so they overvalue capabilities of generative ai. So it is powerful, so don’t get me wrong, it is powerful, but nevertheless, sort of when you’re talking about more complex, detailed stuff, uh, it’s still not quite there. And I kind of doubt it that okay? It’ll be There anytime soon.
Scott Luton (00:19:10):
All right. I appreciate that take. But you also said it’s a competitor, so maybe it’s gonna be motivating you to hit that three and a half hour <laugh> mark in the run coming up soon. Lemme switch gears for a second and then I’m gonna, I’m circle back to Greg and Diego. I wanna switch gears, Steve, and bring you back in when it comes to global supply chain management, right? Mm-hmm. <affirmative>, we love the focus on real results as a, and in this case, transformative use cases that you may be seeing as to how gen AI can make an impact. How would you, what are you seeing that regard and how would you characterize its potential impact? Steve?
Steve Pratt (00:19:44):
I think the combination of predictive AI and generative AI is going to completely change how supply chain professionals run supply chains, right? I think that, I think that generative ai, from a large language model perspective, that first category will have a MI minor, if any impact on supply chains. I th I think the people who are saying, I need to slap a text interface to my a p s is like that, that makes no sense to me. But the third category, right? Of large graph models is a perfect application for supply chains, right? In fact, we can talk about what we’ve done, but if you think of a supply chain is basically a graph, right? You have manufacturing nodes, distribution nodes, you have lanes that connect them, you have constraints, you have historical data that if you model a supply chain as a graph and, and run a large graph model on it, that you get astonishing results, right? So
Steve Pratt (00:20:47):
We’ve been, in fact, I can talk about this later, but we just received a, a patent for our generative probabilistic planning for supply chain optimization. So that was a really big deal for us. The reason that this is gonna transform supply chains is several fold. One is it’ll just give you better numbers. It’ll give you better recommendations on what your demand signal will be. Your supply signal will be your imbalances. The the constraints, the, the your fill rates, your inventory holding costs. And very, very importantly, that fundamental to, to generative ai and even predictive AI is they think probabilistically. It’s all about probability theory. And I think one of the fundamental flaws of existing advanced planning systems is there are what’s called deterministic. They give you one number, right? They give you the, your, your demand is going to be X and you can run different scenarios, but the output is always one number without any sense of it is how confident are you, it’s going to be close to that number, or do you have actually no idea what the answer is gonna be, but you had to give me a number.
Steve Pratt (00:21:59):
So I, I think moving to an AI perspective is moving from this next generation, moving from what we had sequential planning, then concurrent planning. I think that probabilistic planning is the next evolution, right? And that giving supply chain planners and understanding of the risks, you can tailor the risks. Where do you wanna take the risks? Do you wanna take more risk on fill rate? Do you wanna take more risk on inventory obsolescence? So I think those are really, really exciting things where we won’t be spending SS n o P meetings arguing about numbers. We’ll be making strategic decisions about mm-hmm. Would I rather risk a shortage in this customer? Or do I wanna risk my profits, my profitability number, right? Because of inventory outages and, and do that by skew or by product or by region or by time, right? So anyway, so I’m super excited about, we’ve in production with, with predictive AI now for four years at some major C B G brand hundred hundreds of C B G brands. Um, and yeah, we’re, so, I, I can talk more about the stuff we’re doing internally.
Scott Luton (00:23:10):
Well, it’s exciting. And we’re, and, and what’s one, that’s one next places that we’re gonna go is some of those ongoing projects that your team’s involved in. Congrats on the patent. Hey, before I go back to Diego, Greg, I wanna bring you in here. Probab, I know planning is next, is near and dear to your heart, probabilistic planning and how, as Steven put it, not just bigger strategic decisions, but better decisions. Greg, what’d you hear there? And what’s important do you think, for our listeners to take away?
Greg White (00:23:37):
Well, you know, one of the things I heard is this notion of trade-offs, right? Which is essentially what supply chain is all about. It’s you’re trading One risk for another. You’re trading, trading speed for reliability, for ethics, for cost, and various and sundry other things. But those are substantially the pillars that you’re basing it on. And there are, I mean, there have been plenty of deterministic models that assume, I’m gonna use some more statistics, stochastic scenarios, which basically means randomness that we can’t predict Or Manage. We have to consider that it could happen and provision for it as if it will happen. But if we can identify the likelihood of those events or the causes, even better, the causes of those events of disruption, let’s say, of your supply chain that put the speed or the reliability at risk, if we can do that from learning about past disruptions and imparting that to the model, then that changes the amount of inventory that needs to be held in supply chain, which goes directly to the economic Steve was talking about. Yeah. And
Greg White (00:24:42):
There are so many of those trade-offs, and, you know, a lot of what Steve is talking about is new to CPGs or manufacturers. It’s not new to retailers because they’ve had to carry the weight of the supply chain for virtually the entirety of the existence of the supply chain, because CPGs and brands and manufacturers have foisted the risk of supply chain off onto the retailers who carry it in warehouses or distributor distributors, right? Who carry extra inventory and warehouses who carry safety stock, presentation, stock, all these additional stocks. Yeah. And if we can somehow shave that down into a, a level throughout the supply chain, um, like retailers have done for decades, then I think, I think there is a ton of risk and also a ton of costs to be taken out at exactly the same time. Mm. The other thing that this allows us to uncover is these other risks, right? Let’s call ’em existential risks. Am I using a slave trader as a vendor? Mm-hmm. I mean, there are all kinds of things you can learn about your supply chain that are more than just the planning aspect of it. It’s the entirety of the ecosystem.
Steve Pratt (00:25:54):
Hmm. Yeah. I mean, one way we think about this is the, is that this is, you know, it’s basically supply chain professionals are, you can think of them as professional gamblers, right? They make betts, they’re constantly making betts, right? Mm-hmm. Every, every day it’s thousands of betts. And a lot of times the the there are systems do not even give them the probability. They don’t give them the odds, right? So they, they don’t, right? It should say like, Hey, if you’ve got, uh, two kings, you don’t hit Right? Right. Blackjack, right? Like, but it’s like the game is constantly changing and it doesn’t give you probabilities. And I feel like it’s like we all get together as a noodle team is like, it’s like sometimes we feel like it’s like gamblers anonymous. The first thing we have to like admit that we have a, that it’s that our, we have to help our customers understand the odds and where are the risks, AnThen they can play the game. Mm-hmm.
Steve Pratt (00:26:49):
Right? But we Have to inform them on how to Make better Betts.
Scott Luton (00:26:54):
And I love the gambling analogy, and I think one of the things that Comes to my mind As you’re using it is it’s almost like we’re moving it from roulette, which is complete chance to at least blackjack where there’s some sort of a system, right? As you were talking about. Alright, so Diego, I mean, it’s more than that, Scott.
Greg White (00:27:10):
It’s counting Cards at blackjack. There we go. Is what we’re doing? Yeah. <laugh>, I mean, that’s really where we’re going. I wasn’t gonna say that in case legally counting cards, right?
Steve Pratt (00:27:19):
Diego Klabjan (00:27:21):
No, exactly. One, one difference. So Greg mentioned to has, uh, I think you use the term optimization, right? So one big difference between what was in use five, 10 years ago, which was actually to has optimization, was that the subject matter expert in supply chain sort of, and risk management, they created a few scenarios, right? So let’s say three, four scenarios, and then they build the entire analysis around that scenario. So what Moodle is doing today, it’s actually not just two, three scenarios, it’s, we’re talking about millions of different scenarios and then reason on top of those region scenarios and create istic estimates taking into account of all possible interactions in the supply chain.
Scott Luton (00:28:03):
Mm-hmm. <affirmative>, Diego, thank you for adding that. And I wanna give you a chance before I ask Steve about chat, G P t I can’t wait to get, uh, his response and, and all of y’all to, uh, to weigh into. But Diego, anything else you wanna add? You were kind of touching on use cases and, and the impact of gen AI and current impact, potential impact earlier, but anything else you wanna add before I move forward, Diego, in terms of the impact that this is gonna make?
Diego Klabjan (00:28:28):
So in terms of supply chain sort of, and, and this is sort of what Steve already alluded to, generative AI is definitely able to capture all possible, or not all possible, so many, many possible interactions, right? So, and Steve mentioned sort of graphs and networks, right? So that capture interaction, right? So they’re capable of, of more, much more complex interactions and in greater detail than what we were able to do five, 10 years ago, right? So clearly you have to have the knowledge of the underlying generative ai, so scientific knowledge of the underlying generative AI to, to trend or to use that in, in a supply in supply chain networks, right? So, and, and Steve did, Steven did a fantastic job of assembling an excellent group of data scientists and, and together with management to develop these capabilities of using generative AI for supply chain method.
Scott Luton (00:29:19):
Wonderful. Uh, I appreciate you adding that. Alright, so before I move on to any of the casinos that may be listening, the Greg, we’re just using analogies just for Illustrate purposes, right? Greg? They’ve
Greg White (00:29:31):
Already got my picture of <laugh>. Yeah,<laugh> the eye in the sky Is looking for me.
Scott Luton (00:29:36):
Greg White (00:29:36):
Fortunately I don’t play blackjack, so.
Scott Luton (00:29:38):
<laugh>, right? Yeah. All right. Steve, Diego, Greg, let’s move. Steve, I wanna pick your brain on something and everybody try not to roll their eyes, but I think there’s a lot of listeners that are experimenting with chat G P T, it is, uh, easy to use, uh, you know, kind of a, I think of democratization when I see platforms like that, regardless of everyone’s opinion on the accuracy and all those concerns they have. But Steve, question for you. Is chat G p t good or bad for AI’s perception ministry?
Steve Pratt (00:30:10):
Um, of course the answer is yes, <laugh>, yes. Uh, so it’s the, i I think the, the good part about about chat G B T and large language models in general, whether it’s Bard or Llama or there other, there are other large language models, is that it’s, it’s made it easily accessible to individuals. You know, you can sit at home or sit on your phone and you can play around with it, and you see the power of it, of a neural network generating new text in an astonishing way. I’m still astonished by it. I just wrote, you know, I just told it to like, write a limerick about the use of graph neural nets and reinforcement learning, right? And it wrote this amazing Limerick, which was completely digestible, or you can say a love letter to somebody in the st in the style of Mark Twain, right? And it does it. So I think that’s a hugely positive thing. I I think the negative part of it is, first of all, it’s blotted out the sun. Hmm. Right?
Steve Pratt (00:31:10):
And any other, and so, and, and everything sort of gets sucked into that vortex where really cool other things like mid journey, which is for generating images, which is a large image model, right? Everyone’s saying, well, that’s chat G B T. It’s like, no, it’s completely, it’s completely different chat. G b is it, right now it’s just text. But mid journey, which generates new images is really cool. In fact, for some of the, the screen actors Guild strike that’s going right, right now is about the use of AI in images, large image models, because they were able to like de-age Harrison Ford and Raiders of the Lost Arc through generative large image models, right? And that was, they’re really worried that large image models are gonna like, overcome this. And the large graph models, I mean, like the cool stuff we’re doing, or the, uh, alpha fold, which is an example from Google, they’re using for protein folding, right? Right.
Steve Pratt (00:32:07):
Like, understanding how proteins fold is like one of the fundamental block like blockages of understanding discovery of new drugs and like alpha folds could revolutionize medicine. And it’s, so I, I think, I don’t like the fact that it’s blotting out the chat GPS blotting out the sun. And it especially kills me when they say like, it, large language models are the key to supply chain, right? Because it’s, it they’re not. Right. Right. It, I mean, it, it might help in some edge cases for accessing text data, but I think the other one misconception about chat G P T that people need to understand is that training a large language model is extraordinarily difficult, Which
Steve Pratt (00:32:53):
Congrats to all the people who’ve been able to do that, but you have to have a cutoff date for the information. So the cutoff date mm-hmm. For chat G P T is September, 2021. So if you ask it anything that’s happened in the planet since September, 2021, it has no idea. Right. Because the data that went into it was a cutoff there. So it, it, it kills me when it’s
Scott Luton (00:33:14):
A bit of a problem.
Steve Pratt (00:33:15):
It’s a little no. If you wanna opine about the Revolutionary War, it doesn’t matter. Right?
Scott Luton (00:33:21):
Steve Pratt (00:33:21):
But if you’re saying like, what’s the recent trend in whatever? Right?
Scott Luton (00:33:26):
Steve Pratt (00:33:26):
Absolute one idea. And, you know, ask it, ask it who the president is of the United States <laugh>.
Scott Luton (00:33:32):
All right. So Right. For the sake of time, I’ve gotta move forward. We’ve got a lot. Yeah. We got a lot more to, we wanna get into with Steve and Diego and of course Greg. Uh, and you know, Steve, you’ve been referencing kind of in passing some of the things that you and the Noodle AI team have been up to. So tell us a couple things here. First off, how your organization approaches specifically Gen ai and then, you know, talk about some of those ongoing projects that Noodle is leading that leverages that.
Steve Pratt (00:33:57):
Yeah, so right now all of our products are based on predictive ai, right? So we’re using predictive AI for, like I said, we’ve been in production at hundreds of very largest brands that you would all recognize for multiple years. We use predictive AI to find unknown hidden patterns within data, incredibly useful for predicting demand that much, much better than any other approach and supply and imbalances, and converting that to a probabilistic understanding of risk. So generative AI is something that we have finished the data science. So the data science is completely done, it’s now patent patent pending. We’ve run it on multiple customers’ data and it’s getting jaw dropping results, right? So we’re putting in more and more make sure all the real world constraints are in there. Make sure transportation lane capacity, shipment, shipment frequency, every possible constraint you possibly can put in. And so the data science has done, one of the things we’ve learned is noodle ai, is that creating an enterprise software application in ai is that the software engineering around that is as difficult, if not more difficult than the data science itself.
Steve Pratt (00:35:20):
So on generative supply chain planning, we’re done, we’re done with the data science, we know it works. It’s like we revolutionary, but getting it so it’s scalable, reliable, right? It’s, it, the data pipelines won’t go down that it can stay in tune all of that stuff, which is several, several generations ahead of sort of standard software development like DevOps, right? You go to DevOps and the ML ops and then, but having a learning algorithm in the middle of an en of an enterprise application is like really hard to do. I mean, we’ve been, there’s so many edge cases we’ve been working on this for, for three, four years of how do you make it so that it’s fault tolerant and it won’t go down in this mission critical part. So we’re super excited about gen ai. It’s scheduled the, uh, the, or the initial releases not, we’re already at Alpha, we wanna be like ga like a few customers we’ll do in Q one, right?
Steve Pratt (00:36:21):
And then, and then we’re already running in the background at one of our customers and we’ll be two very soon, but we’re super, super excited about it. I think it’s gonna be, it’s, I I I hope that the processes change accordingly, right? Mm-hmm. Like the way we run S N O P and SS n o E in most companies is a lot of it’s to get consensus. So that, okay, we all agreed to these numbers so nobody can complain, right? And, and so I, I think that let’s get away from arguing about the numbers and let’s get, let’s argue about strategic stuff, right? About what do we do? What, what is our intention? Where do we wanna, where do we wanna place our betts? Where do we wanna, where do we want to go strategically, right? In the company?
Scott Luton (00:37:09):
Love that, Steve. And I bet when I hear statements like that really, really truly modernize conversations and where there’s Powerful alignment Around data, we can get stuff done. It usually takes us weeks, if not months, and get it done in a matter of hours, right? Imagine what that will open up. Greg, I’m come to you after we get Diego to comment. Diego, any, anything you wanna add or comment on in terms of, as Steve laid out Noodles approach to Gene ai?
Diego Klabjan (00:37:39):
Sure. So we thought, so industry thinks that we pretty much have nailed down ML ops, uh, right? So, but now this generative AI actually sort of creates a new, uh, challenge when it comes to ops, right? So in other words, when it comes to deploying and maintaining and the actual pipeline in production of generative AI type type models, right? So what Steve just said sort of is, is actually known in, in, in the business community, right? So that no one in the sense that it’s, it’s a new challenge of how do you integrate now large language models or not, like, I’m sorry, say generative AI models in a production setting. And in this sort of, there reports there from consultants, et cetera, stating that there are actually very few companies that today use generative AI in, in deployments, right? So in live, live deployments. So we essentially went from something that, that we think we nearly down so lops now to step up, which is how do we put this generative AI in production? Hmm.
Scott Luton (00:38:46):
Uh, all right. So Greg, when you hear the approach, you hear a Patent pending, You hear it’s Being AppliedTo one client soon To be, uh, two Customers, or one, one customer, soon to be two customers. And it sounds like in a matter of days, If not weeks, another aspects of their Approach. Uh, Greg, what comes to your mind?
Greg White (00:39:02):
Well, a thing that astounds me, not just from what Steve and Diego have said, but just what I’ve seen as the investor is the rapidity with which generative ai, generative AI is generally what we’re talking about, has accelerated how much the technology itself has evolved over the last 20 minutes or so. I’ve had a few thoughts here, but, but I think the thing that’s really very impressive and that we have seen and heard Scott firsthand from a prominent retailer in the US is they took a process that did take 400 people and four months and condensed it to 11 people and a weekend. HmmSo
Greg White (00:39:48):
I, I believe that it will replace people and it will replace them in what we currently consider very, very high value jobs, consulting jobs. The writers had to write the writers that, from their writer’s strike, had to write a, an element into their contract that they can’t be replaced by AI if they weren’t worried about re being replaced by ai. And I think we’ve seen Mark Twain can be replaced by ai. I’m sure some of these TV writers can be replaced by ai. So I think there is so much that it can do that. And we talked about this on a show earlier, Scott, you know, I think we have to recognize that there is so much that it can do, and because it’s constantly learning, it will continue to accelerate its effectiveness. Hmm. And
Greg White (00:40:37):
I don’t think we need to be worried about that though, because it’s going to take jobs that are not what humans are best fit for anyway. Humans will still have to intervene if it writes a, a Mark Twain love letter and make sure that it’s saying the right things and it has the right tone and that sort of thing. But it will get you off the ground. And there are people that do that today. Hmm. Right. So People will move up the chain, just like people move from driving, from driving spikes on, on the railroad, John Henry, right? The old John Henry story. Yeah. People
Greg White (00:41:10):
Moved. We didn’t, we don’t have fewer people working in railroads after that. We have many, many more working in railroads after that. And you know, the jobs will move around because of that. But I think the key thing to understand here is that we can’t even conceive, and those, even those of us, like Steve and Diego and I, not me to the level these guys do, but who are thinking about what AI can and should do and trying to apply it to problems every day. I’m astounded at what AI can do And Every day. I mean, I’ve been asking, and I know Steve, you probably have too, as a founder, I’ve been asking the, well, could it do this question? Mm-hmm. <affirmative> and every day the answer is, let’s see, and a few weeks later, the answer is quote the great Stephen Pratt. Well, of course the answer is yes. <laugh>
Diego Klabjan (00:42:04):
<laugh>. So let me, can I ask the following, Carol, it’s not rhetorical philosophical question, right? So philosophical, it goes along the lines of replacing workforce, right? So suppose you go on Amazon and you try to buy a book And You see a note there next to the book that you are interested in, and the note says completely a hundred percent written by generative ai. Would you change the perception of that book? Would you buy it?
Scott Luton (00:42:31):
Interesting question, Greg.
Greg White (00:42:33):
Yeah, absolutely. I would. Okay. But that doesn’t change the fact that it will still replace
Diego Klabjan (00:42:39):
Well, ’cause see, so my answer is actually I would probably not buy it.
Scott Luton (00:42:43):
Greg White (00:42:44):
Oh, sorry. I’m sorry. Yes. Sorry. Your question was, would I buy it? I would think about it before I bought it. Absolutely. I thought your question was, would I think about it before I bought it? I would absolutely think about it before I would buy it, but we don’t have to debate it, Diego. I mean, chances are good. Yeah. But neither one of us are right.
Diego Klabjan (00:43:01):
<laugh>, my, my point is that at least sort of, I would not buy it. Right? So, and that kind of, yeah, I’m just one person, right? Yeah. So, but this does imply that at least sort of as far as I’m, I mean based on my taste or philosophy, whatever you wanna call it, generative ai, it’s not going to replace rider
Greg White (00:43:19):
It. Okay. Maybe not writers. So, right. <laugh>
Scott Luton (00:43:23):
It is fascinating. We would need a couple more hours, I believe, and really have a full conversation around some of the viewpoints here. But this is what I want.
Greg White (00:43:30):
This could turn into a sports show real quick, <laugh>. That’s
Scott Luton (00:43:33):
Right. With hot takes and all that good stuff. I don’t,
Greg White (00:43:35):
I think Patrick Mahomes is overrated.
Scott Luton (00:43:38):
<laugh>, but you know, it’s interesting when, I’m not sure if it was Steve or Diego, it could have been Greg, about the continuous learning aspect of ai. It is interesting to think about. Yeah. It’s, we humans try to get our, I don’t know about y’all my five hours of sleep at night, six or seven or whatever it is. It’s just working and learning and working and learning. And it’s just, it’s a fascinating thing to think about, right? Certainly one of the, and it never
Greg White (00:44:01):
Scott Luton (00:44:02):
Correct. And once
Greg White (00:44:02):
It learns something, it always uses it consistently.
Scott Luton (00:44:06):
Greg White (00:44:06):
Never is misdirected by emotion. Mm-hmm.
Scott Luton (00:44:09):
Greg White (00:44:09):
Or fatigue or,
Scott Luton (00:44:11):
or your favorite Sports team winning or losing, you know, all that good stuff. All right. So as we start to come down to home stretch, great conversation here, Steve and Diego, I wanna ask y’all a question, and I’m gonna try to, it, it, it’s along, it’s in the vein of what we’ve been asking, but I really wanna challenge y’all to think of something that maybe you haven’t shared here today. So, you know, I don’t know about y’all, but we hear it a lot. We get a lot of feedback from when we do these shows that Greg was referencing the course. Today’s, I still don’t get it. Why Gen ai, right? What’s the big deal, right? And think of those folks that we have plenty of folks doing big things out in the industry that aren’t necessarily technologists. But to that end, if you had to really boil it down to just a couple of thoughts that you hadn’t shared yet, what couple are the key primary advantages of adopting gen AI techniques? And let’s start with you, Diego.
Diego Klabjan (00:45:04):
Well, so <laugh>, I know answer is if I can make money, I would use generative ai, right? So if it can improve my business, clearly there’s a cost side as well, right? So we all know that fine tuning generative AI models is not cheap, right? But just from the business perspective, value. So if I can gain, if I can run my business more efficiently, if I can create a better product, et cetera, I’m all for it. I mean, use, use generative ai. And from that perspective, actually, you’re right. So alignment, safety, those kind of things, okay? We’re not here, we’re talking about strictly business perspective, right? So there’s potentially no issue for alignment, safety, those kind of things, right? So, but as long as I can increase my revenue or, or run away, I’m all for it.
Scott Luton (00:45:51):
Well said Diego. And I think that a lot of folks could agree with that. Steve, I’ll come to you next, but before I do, we’ll see if we can apply Gen AI to maybe some better baseball. Um, empowering. Do you think that’s in the cards, Steve? But anyway, getting aside, Steve, what would be your response to those to say?
Steve Pratt (00:46:07):
How about just actual
Scott Luton (00:46:08):
Intelligence to umpiring <laugh>, right? Yes,
Diego Klabjan (00:46:10):
Yes, yes. We’re gonna The brave, the Braves Don Yes. The Braves don’t need better Empires. Yeah. Bad.
Steve Pratt (00:46:20):
Her, her Hernandez ai. Yeah.
Scott Luton (00:46:23):
Oh, there you go, man. We’re gonna upset the 0.1% of our listening audience that are maybe active umpires. I don’t know, Steve, who cares. But you think about, again, why gen ai? What’s a couple key thoughts that come to your mind beyond what we’ve already talked about?
Steve Pratt (00:46:37):
Yeah. Well, I, I, I’ll just relate it to supply chain professionals. I think that there is a need to give much better information to supply chain professionals. I, I think there’s a lot of frustration and what is really an almost unachievable job, right? We had one customer before we came in, they were getting 580,000 inventory alerts on Monday. The team of hundreds of people would sort through those alerts. They’d try to figure out what’s real, what’s not real. By Wednesday, Thursday, Friday, they need to make thousands and thousands of critical decisions that are gonna infect billions of dollars of inventory. And it just, it’s a thankless job. It’s a frustrating job because there’s so little information. Ultimately it comes down to telephones and texting and Excel spreadsheets and just sort of this heroics at the end. And I think that, I think it can make that job a lot better, right? And more you can get better results. It’ll be more using what human, the human brain is amazing at judgment and thinking. It’s really bad at calculating and estimating probabilities. And, and so let the computer do what the computer does best. Let the human brain do what the human brain does best. And I, so I think that that to me, that’s a really, really exciting use of, you know, both predictive and generative AI is to, is to help the supply chain professional.
Scott Luton (00:48:09):
Steve. Well said. And if you heard Greg there, he said preach it, because there’s a lot of kindred spirits there. And I, I would add one more thing before I come to Greg. You’re talking about Better info. I would also argue they Need more time. They Need more time, they need More successful Practical tools that Can give them, Give more Time and some, and some peace of mind, frankly. Greg, your thoughts when you hear Steve and Diego talk about why gen the ai?
Greg White (00:48:31):
Yeah, well, lemme just start real quickly with what it won’t replace. It won’t replace the ability to make life and death decisions or high, high stakes decisions with very little no or inaccurate data. It will not replace that, it won’t replace any kind of knowledge that is required of the last two years or whatever. I’m sure they’ll shrink that timeline. Right? It also is gonna find it very difficult to, at least for now, to contemplate new concepts, right? For someone to visioner something that’s never happened before that is not based on a foundational premise or foundational data or a foundational information or something that just doesn’t exist today. So that is humans doing human things to Steve and Diego’s points both. What I think it will do is it will free us to do those things rather than those mundane, all those high stakes, but easily manageable with a base of knowledge, with enough data to support a base of knowledge that, that today take an entire week, like what Steve just described, that can be done literally overnight and say, Hey, we did this for you while you were out for the weekend.
Greg White (00:49:47):
Or at least we did these things for you. Here are some things that you need to continue to review. We didn’t have enough data. That sort of thing. The, that is what technology has always done and we’ve just reached such a level, high level of efficiency in terms of so many interactions with technology that this is just another condensing of timeframe around those kinds of challenges.
Scott Luton (00:50:11):
Greg White (00:50:12):
So I think that’s what it will do, is it will continue to allow humans to do less of those things that, I mean, you know, this whole back and forth, God, I was living it while you were saying it, Steve, this whole, Well why did that happen? How did you hurt the company yesterday? We gotta dig into this and figure out why that happened. And then by Thursday we’re back to work. Mm-hmm. <affirmative>, now we can come in and go to work on Monday and know that there are very few things that can’t be handled and we don’t require all this back and forth because all the data that supports the argument that we should do this differently or we should do this the same or this will never happen again. It’s all, it all exists in the models and is presented.
Scott Luton (00:50:56):
Yeah. Love that. Uh, you know, as you’re describing that and each of y’all are talking maybe a good or maybe a poor example, I don’t know, it’ll let humans focus on making, crafting that culinary delight, whatever big fancy recipe and focus on the creation. And maybe AI will take care of setting the table and washing the dishes. Wouldn’t that be something, maybe we’ll be there one day. Alright, so as we start to wrap, one last question before we make sure folks know how to connect with everybody. And if we can, what’s your, in a nutshell, simple straight to the point response here. And that question is one of my favorite questions to ask. Uh, we’ll start with you Steve. How would you suggest our listeners get started with Gen ai?
Steve Pratt (00:51:41):
I actually think playing around with Jet G P T in large language models is a good place to start because it’s accessible, it’s something you can use immediately. I think playing with mid journey for generating new images, you can say, I don’t know why you’d wanna do this, but like draw a picture of a dog juggling on the moon, right? It’ll, it’ll do it, right? So whatever you want, draw a new logo for my company or whatever, right? And large graph models are less accessible to a consumer, like an individual consumer. It’s, I’m not sure that there are ways of playing around with that, but I think, you know, obviously I would encourage people to call Noodle ai. I mean, you could, we could show you what we’re doing, we could show you what’s in production and predictive ai and that’s absolutely rock solid, that generative AI stuff, which we can show you the things that are working in Noodle Labs and that on customer data on a, in a production basis. And so, yeah, I, I would say, you know, just humans are sometimes afraid of things that are new and they, and that are, is kind of scary. And so I think just let’s increase your exposure to it, understand what it is, and you can understand how it can be used for good and the potential misuses of it. And I think that’s what I would say.
Scott Luton (00:52:59):
Excellent. And to your point, school, a generation of technologists were largely created with approachable video games in the eighties and nineties. Kind kind of little bit to your point. Alright, so Diego, same question in a nutshell. How can folks get started? How would you suggest they get started?
Diego Klabjan (00:53:16):
Oh, so if one is interested on the technical side, then, so what Steve said, so G p t,It’s a good start or it’s an excellent Starting point and if somebody wants to Go deeper, so something like link chain and hugging face and those kind of aspects, uh, not aspects, sorry, tools and another way. So there, there’s, there are now also cazillion of websites that offer generative ai. Uh, uh, they, let me just say they showcase generative ai for example, creating presentations, summarizing documents, uh, responding to emails, et cetera, et cetera. But if one is also for managers, I would actually say that the good starting point would be just Google search about potential use cases, hurdles to actually use generative ai. So I mentioned before like pipelines and those kind of things and cost of training so that there’s a lot of information available on the web, but I, I find attending conferences are also extremely valuable, right? So if one from the management perspective is interested in generative ai, so should it be used in my company then conferences and talking to others and hearing about use cases, that’s also, it’s my recommendation.
Scott Luton (00:54:28):
Diego Klabjan (00:54:28):
And where to find me at a marathon on Sunday?
Greg White (00:54:31):
Diego Klabjan (00:54:32):
And a half hours.
Scott Luton (00:54:33):
We’re writing it down. We’re Gonna check in. Alright, so Greg, before we Make sure Folks can connect with Steve, uh, and Diego, anything you wanna add in terms of how folks get started?
Greg White (00:54:44):
Yeah, I agree with Steve Chat. G P t I mean, it’s a party trick, but it, that’s the way we get people to learn these things is make it simple and consumable and, and I think you’ll find what you can do. You’ll find the limitation and you don’t, it doesn’t know anything past September, 2021. I found that really quick. It’s frustrating, but it is what it is. That’ll probably give all of us a lot of solace to Diego’s point about whether this could replace us. We know it’s not gonna replace us in the next two years. Right. And, and yeah, I mean if you are in business, and particularly if you’ve got, uh, the planning challenge, I can assure you I had a planning company. I’ve seen the competitors out there. There is no one using AI the right way that I have, I’ve spoken to, seen on the marketplace except noodle. Hmm.
Greg White (00:55:33):
Everyone is using it. The way that I see people using it is to select old fashioned forecasting models out of a best fit forecast model. And that’s about as good as it gets if you are doing something not just predictive, but also probabilistic and using gen AI to do it. Or if you need to be doing that, I would give Steve a call. First of all, just talking to him, you’re gonna learn something and I I I know also get some also that there’s no one else out there doing it. One more thing. Yeah. Is can I just, well should I save, I should probably save this for the close.
Scott Luton (00:56:08):
Yeah, let’s save. It. We’ll save it.
Greg White (00:56:10):
Let’s save it for the close.
Scott Luton (00:56:11):
We’ll. Keep an inventory For just a second. Yeah, we’ll fulfill The order and Just say, yeah,
Greg White (00:56:14):
Don’t fill it all now. Got it. <laugh>. Okay. Alright, lemme gimme note, save this later.
Scott Luton (00:56:20):
Steve and Diego. Steve, that is high praise. Trust me. I’ve been doing this for quite some time with Greg and when you get a compliment like that is high praise and genuine praise. So let’s do this. So Diego, first off, how can folks, other than the Chicago Marathon, if folks want reach out and compare notes. You talk about the Cubs and the Braves or all this cool stuff you’re doing and helping others do, and the now generation do it at Northwestern, how can folks connect with you
Diego Klabjan (00:56:47):
The usual, traditional way, sort of email X, what else? Discord. Yeah, that’s, so email is, is the best one. And as I said, X is Okay Twitter, right? So I’m talking about Twitter.
Scott Luton (00:57:00):
Yeah, yeah. You know, when are we gonna be able to drop that and just say X and stop saying formerly Twitter, right? All the, we’re still stuck in that cycle, but we’ll find Jill X and of course we’ll include those things in the show notes, Diego, to make it really easy for folks to connect with you. So, uh, Diego, really appreciate you being here today.
Diego Klabjan (00:57:19):
Scott Luton (00:57:21):
Alright, Steve, really have enjoyed your perspective here today. You and Diego are quite the one-two punch. Big thanks to you and the Noodle AI team that’s on the move as, as Greg was sharing, really appreciate y’all partnering with us on this. I think it’s gonna be a very informative, demystifying, we’re breaking the mold of some assumptions that I think a lot of folks have made based on what they’re reading or talking about. So really appreciate that. And folks, to our listeners, stay tuned. In the next episode, we’re gonna go deeper with more practical use cases for ministry to really help you connect the technology with the outcomes. So stay tuned. So Steve, how can folks connect with you and the Noodle AI team?
Steve Pratt (00:58:03):
So you can find us on firstname.lastname@example.org, so not too complicated. You can reach email@example.com and LinkedIn, although LinkedIn’s a little overwhelming, right? So it’s <laugh>, right? So my, I think I have tens of thousands of unread messages on LinkedIn, so I, and they make it really hard to delete messages, so it’s, so anyway, I would do, email is probably the, the best way. Or if you’d like to see a demo, you can go on Our website. It’s really cool stuff, so.
Scott Luton (00:58:40):
Excellent. And we’ll put that demo link in the show notes. And by the way, I’m being reminded the email address, Steve, that you’re bold to put out there, Steve, not Steven, firstname.lastname@example.org is what I’m being told Steve. Yes. Does that work?
Steve Pratt (00:58:54):
S st. S t v E at Noodle ai.
Scott Luton (00:58:57):
Wonderful. All right, good, good, good. Well really have enjoyed it. Uh, big thanks to both of our guests. Greg, I’m getting your key takeaway. We’re got order ready to go, but wanna thank Steve Pratt, founder and c e o with Noodle ai. Steve, thanks for being here today.
Steve Pratt (00:59:11):
Yeah, so absolute pleasure,
Scott Luton (00:59:15):
Abso, I, I feel smarter really after speaking with the three of y’all, but especially I agree, Steve Diego, thank you for
Greg White (00:59:21):
Bringing all this knowledge to us guys. I appreciate it.
Scott Luton (00:59:24):
Absolutely. And Professor Diego Klain with Northwestern University Diego, great, great to have you here today.
Greg White (00:59:31):
Scott Luton (00:59:32):
You very much. Appreciate it. Thanks
Greg White (00:59:34):
Scott Luton (00:59:35):
So Greg, a lot more coming. Big thanks to our cloud partners over at Noodle ai. We look forward to continuing the episodes of this limited run featured series making Better Supply Chain Betts With the Power ofProbabilities. So, Greg, For our wrap, What is, if You had To distill it all down Right, distill it All down into a bottle of Steve’s finest from the Vineyard,
Greg White (00:59:58):
never did determine whether he makes wine yet or if he’s just growing grapes.
Scott Luton (01:00:03):
Yes. What, What is, you Had to pick <laugh>, you had To pick one thing, Greg, that folks gotta pay attention to from this conversation with Steve and Diego. What would that be?
Greg White (01:00:12):
Yeah, well, it’s coming. Um, I mean, AI is gonna do a lot of things. I don’t know if anyone, uh, remembers an old Disney movie where people are sitting in big old cushy chairs and robots bring them everything that they want. Don’t be lazy because the more replaceable you are, the more likely you are to be replaced. Mm.
Greg White (01:00:38):
I mean, and it’s gonna start from the commodity jobs on up. So find a niche. I can tell you, I can tell you two people that are not gonna get replaced by AI and that’s Steve and Diego <laugh>. If you ha no, seriously if you have that kind of knowledge or if you, if you master something like this, right? If you really and truly are a, a master of some kind of skill, then you won’t be replaced. If you are an automaton, um, or a, or a production Worker,
Greg White (01:01:10):
It, it’s very likely, uh, just my opinion, Diego and I are gonna have a fist fight after this. But no, I mean, it’s very likely that you will be replaced. So be great if you haven’t read Good to great. Read it the Hedgehog concept, be good, great at something and make your living doing it. So, um, you know, it is all about economics. Both Diego and Steve both said that if you have an economic need that’s not being met, I would say by a technology that exists today, especially as regards planning, then take a look at this thing because there are massive limitations. Me and AI are writing a book together.
Scott Luton (01:01:52):
Greg White (01:01:53):
Um, I’m just kidding, Diego <laugh>. But I mean, you know, I am, I do have this whole list of supply chain rules and one of them is that the technology that exists today is not sufficient to, is not sufficient to tackle this. I think Noodle is onto something here and I think that they can do things that other technologies can’t. So take a look at it.
Scott Luton (01:02:14):
Mm-hmm. Wonderful. Greg, I appre really appreciate that, Greg. I’m gonna take a look at it. Also, by the way, <laugh>, great place to finish and to our listeners, hey, adding to that keep learning, keep learning. Yeah. Be bold, lean into new places that are new to you. Yeah, it may be scary and all, but that’s part of the secret sauce of this journey We’re all in. So to all our listeners, hopefully we’ve enjoyed this episode as as much as we have. Again, I feel smarter after the last hour or so. Be sure to connect with our speakers and their organizations. Be sure to find supply chain now, wherever you get your podcast. Subscribe to ’em, miss anything. And on behalf of all the team here at Supply Chain now, hey, remember, it’s Steve’s not words. Take something that Steve Diego, or Greg said here today. Put it into action. That’s, uh, the big must need, footsteps gotta be taken. So hey Scott Luden challenging you to do good, to give forward and to be the change. And we’ll see you next time, right back here on Supply Chain now. Thanks everybody.
Thanks for being a part of our supply chain now, community. Check out all of our email@example.com and make sure you subscribe to Supply Chain now, anywhere you listen to podcasts. And follow us on Facebook, LinkedIn, Twitter, and Instagram. See you next time on Supply Chain. Now.
Steve Pratt is Founder & CEO of Noodle.ai. Noodle.ai products are pioneering software applications powered by predictive and generative AI to identify and eliminate waste in complex supply chains. They are trailblazers in bringing the power of probability theory to master uncertainty and complexity. Noodle.ai products are used by hundreds of leading consumer products brands to get the right products in the right place at the right time with minimal waste and maximum profit. Prior to Noodle.ai, Steve was responsible for all implementations of Watson worldwide for IBM Global Business Services. He was also founder and CEO of Infosys Consulting, growing the business from startup to over 30,000 people. His career began doing classified projects in the intelligence community focused on electronic warfare, satellite communications, and applying neural networks to detect illegal activity. Steve has a Master’s degree in Digital Signal Processing from The George Washington University and a Bachelor’s degree in Electrical Engineering from Northwestern University. Connect with Steve on LinkedIn.
Diego Klabjan is a professor at Northwestern University, Department of Industrial Engineering and Management Sciences. He is also Founding Director, Master of Science in Machine Learning and Data Science and Director, Center for Deep Learning. After obtaining his doctorate from the School of Industrial and Systems Engineering of the Georgia Institute of Technology in 1999 in Algorithms, Combinatorics, and Optimization, in the same year he joined the University of Illinois at Urbana-Champaign. In 2007 he became an associate professor at Northwestern and in 2012 he was promoted to a full professor. His research is focused on machine learning and deep learning with concentration in finance, manufacturing, operations, insurance, sports, and bioinformatics. Professor Klabjan has led projects with large companies such as Intel, Baxter, Allstate, FedEx Express, and many others, and he is also assisting numerous start-ups with their machine learning needs. He was on the advisory board of Alpine Data Labs (now part of Tibco) and a member of the technical advisory board of AT Kearney, and has served as the subject matter expert for IRI Big Data. He was also a co-founder of Opex Analytics LLC, a Coupa company. Connect with Diego on LinkedIn.
Host, Supply Chain Now en Espanol
Demo Perez started his career in 1997 in the industry by chance when a relative asked him for help for two just weeks putting together an operation for FedEx Express at the Colon Free Zone, an area where he was never been but accepted the challenge. Worked in all roles possible from a truck driver to currier to a sales representative, helped the brand introduction, market share growth and recognition in the Colon Free Zone, at the end of 1999 had the chance to meet and have a chat with Fred Smith ( FedEx CEO), joined another company in 2018 who took over the FedEx operations as Operations and sales manager, in 2004 accepted the challenge from his company to leave the FedEx operations and business to take over the operation and business of DHL Express, his major competitor and rival so couldn’t say no, by changing completely its operation model in the Free Zone. In 2005 started his first entrepreneurial journey by quitting his job and joining two friends to start a Freight Forwarding company. After 8 months was recruited back by his company LSP with the General Manager role with the challenge of growing the company and make it fully capable warehousing 3PL. By 2009 joined CSCMP and WERC and started his journey of learning and growing his international network and high-level learning. In 2012 for the first time joined a local association ( the Panama Maritime Chamber) and worked in the country’s first Logistics Strategy plan, joined and lead other associations ending as president of the Panama Logistics Council in 2017. By finishing his professional mission at LSP with a company that was 8 times the size it was when accepted the role as GM with so many jobs generated and several young professionals coached, having great financial results, took the decision to move forward and start his own business from scratch by the end of 2019. with a friend and colleague co-founded IPL Group a company that started as a boutique 3PL and now is gearing up for the post-Covid era by moving to the big leagues.
Sales Support Intern
Alex is pursuing a Marketing degree and a Certificate in Legal Studies at the University of Georgia. As a dual citizen of both the US and UK; Alex has studied abroad at University College London and is passionate about travel and international business. Through her coursework at the Terry College of Business, Alex has gained valuable skills in digital marketing, analytics, and professional selling. She joined Supply Chain Now as a Sales Support Intern where she assists the team by prospecting and qualifying new business partners.
Joshua is a student from Institute of Technology and Higher Education of Monterrey Campus Guadalajara in Communication and Digital Media. His experience ranges from Plug and Play México, DearDoc, and Nissan México creating unique social media marketing campaigns and graphics design. Joshua helps to amplify the voice of supply chain here at Supply Chain Now by assisting in graphic design, content creation, asset logistics, and more. In his free time he likes to read and write short stories as well as watch movies and television series.
Director of Communications and Executive Producer
Donna Krache is a former CNN executive producer who has won several awards in journalism and communication, including three Peabodys. She has 30 years’ experience in broadcast and digital journalism. She led the first production team at CNN to convert its show to a digital platform. She has authored many articles for CNN and other media outlets. She taught digital journalism at Georgia State University and Arizona State University. Krache holds a bachelor’s degree in government from the College of William and Mary and a master’s degree in curriculum and instruction from the University of New Orleans. She is a serious sports fan who loves the Braves. She is president of the Dave Krache Foundation. Named in honor of her late husband, this non-profit pays fees for kids who want to play sports but whose parents are facing economic challenges.
Vicki has a long history of rising to challenges and keeping things up and running. First, she supported her family’s multi-million dollar business as controller for 12 years, beginning at the age of 17. Then, she worked as an office manager and controller for a wholesale food broker. But her biggest feat? Serving as the chief executive officer of her household, while her entrepreneur husband travelled the world extensively. She fed, nurtured, chaperoned, and chauffeured three daughters all while running a newsletter publishing business and remaining active in her community as a Stephen’s Minister, Sunday school teacher, school volunteer, licensed realtor and POA Board president (a title she holds to this day). A force to be reckoned with in the office, you might think twice before you meet Vicki on the tennis court! When she’s not keeping the books balanced at Supply Chain Now or playing tennis matches, you can find Vicki spending time with her husband Greg, her 4 fur babies, gardening, cleaning (yes, she loves to clean!) and learning new things.
Ben Harris is the Director of Supply Chain Ecosystem Expansion for the Metro Atlanta Chamber. Ben comes to the Metro Atlanta Chamber after serving as Senior Manager, Market Development for Manhattan Associates. There, Ben was responsible for developing Manhattan’s sales pipeline and overall Americas supply chain marketing strategy. Ben oversaw market positioning, messaging and campaign execution to build awareness and drive new pipeline growth. Prior to joining Manhattan, Ben spent four years with the Georgia Department of Economic Development’s Center of Innovation for Logistics where he played a key role in establishing the Center as a go-to industry resource for information, support, partnership building, and investment development. Additionally, he became a key SME for all logistics and supply chain-focused projects. Ben began his career at Page International, Inc. where he drove continuous improvement in complex global supply chain operations for a wide variety of businesses and Fortune 500 companies. An APICS Certified Supply Chain Professional (CSCP), Ben holds an Executive Master’s degree in Business Administration (EMBA) and bachelor’s degree in International Business (BBA) from the Terry College at the University of Georgia.
Host, The Freight Insider
Prior to joining TeamOne Logistics, Page Siplon served as the Executive Director of the Georgia Center of Innovation for Logistics, the State’s leading consulting resource for fueling logistics industry growth and global competitiveness. For over a decade, he directly assisted hundreds of companies to overcome challenges and capitalize on opportunities related to the movement of freight. During this time, Siplon was also appointed to concurrently serve the State of Georgia as Director of the larger Centers of Innovation Program, in which he provided executive leadership and vision for all six strategic industry-focused Centers. As a frequently requested keynote speaker, Siplon is called upon to address a range of audiences on unique aspects of technology, workforce, and logistics. This often includes topics of global and domestic logistics trends, supply chain visibility, collaboration, and strategic planning. He has also been quoted as an industry expert in publications such as Forbes, Journal of Commerce, Fortune, NPR, Wall Street Journal, Reuters, American Express, DC Velocity, Area Development Magazine, Site Selection Magazine, Inbound Logistics, Modern Material Handling, and is frequently a live special guest on SiriusXM’s Road Dog Radio Show. Siplon is an active industry participant, recognized by DC Velocity Magazine as a “2012 Logistics Rainmaker” which annually identifies the top-ten logistics professionals in the Nation; and named a “Pro to Know” by Supply & Demand Executive Magazine in 2014. Siplon was also selected by Georgia Trend Magazine as one of the “Top 100 Most Influential Georgians” for 2013, 2014, and 2015. He also serves various industry leadership roles at both the State and Federal level. Governor Nathan Deal nominated Siplon to represent Georgia on a National Supply Chain Competitiveness Advisory Committee, where he was appointed to a two-year term by the U.S. Secretary of Commerce and was then appointed to serve as its vice-chairman. At the State level, he was selected by then-Governor Sonny Perdue to serve as lead consultant on the Commission for New Georgia’s Freight and Logistics Task Force. In this effort, Siplon led a Private Sector Advisory Committee with invited executives from a range of private sector stakeholders including UPS, Coca-Cola, The Home Depot, Delta Airlines, Georgia Pacific, CSX, and Norfolk Southern. Siplon honorably served a combined 12 years in the United States Marine Corps and the United States Air Force. During this time, he led the integration of encryption techniques and deployed cryptographic devices for tactically secure voice and data platforms in critical ground-to-air communication systems. This service included support for all branches of the Department of Defense, multiple federal security agencies, and aiding NASA with multiple Space Shuttle launches. Originally from New York, Siplon received both a bachelor’s and master’s degree in electrical and computer engineering with a focus on digital signal processing from the Georgia Institute of Technology. He earned an associate’s degree in advanced electronic systems from the Air Force College and completed multiple military leadership academies in both the Marines and Air Force. Siplon currently lives in Cumming, Georgia (north of Atlanta), with his wife Jan, and two children Thomas (19) and Lily (15).
Host, Logistics with Purpose
Kristi Porter is VP of Sales and Marketing at Vector Global Logistics, a company that is changing the world through supply chain. In her role, she oversees all marketing efforts and supports the sales team in doing what they do best. In addition to this role, she is the Chief Do-Gooder at Signify, which assists nonprofits and social impact companies through copywriting and marketing strategy consulting. She has almost 20 years of professional experience, and loves every opportunity to help people do more good.
Host, Supply Chain Now en Espanol
Sofia Rivas Herrera is a Mexican Industrial Engineer from Tecnologico de Monterrey class 2019. Upon graduation, she earned a scholarship to study MIT’s Graduate Certificate in Logistics and Supply Chain Management and graduated as one of the Top 3 performers of her class in 2020. She also has a multicultural background due to her international academic experiences at Singapore Management University and Kühne Logistics University in Hamburg. Sofia self-identifies as a Supply Chain enthusiast & ambassador sharing her passion for the field in her daily life.
Sales and Marketing Coordinator
Katherine is a marketing professional and MBA candidate who strives to unite her love of people with a passion for positive experiences. Having a diverse background, which includes nonprofit work with digital marketing and start-ups, she serves as a leader who helps people live their most creative lives by cultivating community, order, collaboration, and respect. With equal parts creativity and analytics, she brings a unique skill set which fosters refining, problem solving, and connecting organizations with their true vision. In her free time, you can usually find her looking for her cup of coffee, playing with her puppy Charlie, and dreaming of her next road trip.
Host, Supply Chain Now
The founder of Logistics Executive Group, Kim Winter delivers 40 years of executive leadership experience spanning Executive Search & Recruitment, Leadership Development, Executive Coaching, Corporate Advisory, Motivational Speaking, Trade Facilitation and across the Supply Chain, Logistics, 3PL, E-commerce, Life Science, Cold Chain, FMCG, Retail, Maritime, Defence, Aviation, Resources, and Industrial sectors. Operating from the company’s global offices, he is a regular contributor of thought leadership to industry and media, is a professional Master of Ceremonies, and is frequently invited to chair international events.
He is a Board member of over a dozen companies throughout APAC, India, and the Middle East, a New Zealand citizen, he holds formal resident status in Australia and the UAE, and is the Australia & New Zealand representative for the UAE Government-owned Jebel Ali Free Zone (JAFZA), the Middle East’s largest Economic Free Zone.
A triathlete and ex-professional rugby player, Kim is a qualified (IECL Sydney) executive coach and the Founder / Chairman of the successful not for profit humanitarian organization, Oasis Africa (www. oasisafrica.org.au), which has provided freedom from poverty through education to over 8000 mainly orphaned children in East Africa’s slums. Kim holds an MBA and BA from Massey & Victoria Universities (NZ).
Host, Logistics with Purpose
Adrian Purtill serves as Business Development Manager at Vector Global Logistics, where he consults with importers and exporters in various industries to match their specific shipping requirements with the most effective supply chain solutions. Vector Global Logistics is an asset-free, multi-modal logistics company that provides exceptional sea freight, air freight, truck, rail, general logistic services and consulting for our clients. Our highly trained and professional team is committed to providing creative and effective solutions, always exceeding our customer’s expectations and fostering long-term relationships. With more than 20+ years of experience in both strategy consulting and logistics, Vector Global Logistics is your best choice to proactively minimize costs while having an exceptional service level.
Host, Logistics with Purpose
Kevin Brown is the Director of Business Development for Vector Global Logistics. He has a dedicated interest in Major Account Management, Enterprise Sales, and Corporate Leadership. He offers 25 years of exceptional experience and superior performance in the sales of Logistics, Supply Chain, and Transportation Management. Kevin is a dynamic, high-impact, sales executive and corporate leader who has consistently exceeded corporate goals. He effectively coordinates multiple resources to solution sell large complex opportunities while focusing on corporate level contacts across the enterprise. His specialties include targeting and securing key accounts by analyzing customer’s current business processes and developing solutions to meet their corporate goals. Connect with Kevin on LinkedIn.
Host, Logistics with Purpose
Jose Manuel Irarrazaval es parte del equipo de Vector Global Logistics Chile. José Manuel es un gerente experimentado con experiencia en finanzas corporativas, fusiones y adquisiciones, financiamiento y reestructuración, inversión directa y financiera, tanto en Chile como en el exterior. José Manuel tiene su MBA de la Universidad de Pennsylvania- The Wharton School. Conéctese con Jose Manuel en LinkedIn.
Host, Logistics with Purpose
Nick Roemer has had a very diverse and extensive career within design and sales over the last 15 years stretching from China, Dubai, Germany, Holland, UK, and the USA. In the last 5 years, Nick has developed a hawk's eye for sustainable tech and the human-centric marketing and sales procedures that come with it. With his far-reaching and strong network within the logistics industry, Nick has been able to open new avenues and routes to market within major industries in the USA and the UAE. Nick lives by the ethos, “Give more than you take." His professional mission is to make the logistics industry leaner, cleaner and greener.
Host, Logistics with Purpose
Allison Krache Giddens has been with Win-Tech, a veteran-owned small business and aerospace precision machine shop, for 15 years, recently buying the company from her mentor and Win-Tech’s Founder, Dennis Winslow. She and her business partner, John Hudson now serve as Co-Presidents, leading the 33-year old company through the pandemic.
She holds undergraduate degrees in psychology and criminal justice from the University of Georgia, a Masters in Conflict Management from Kennesaw State University, a Masters in Manufacturing from Georgia Institute of Technology, and a Certificate of Finance from the University of Georgia. She also holds certificates in Google Analytics, event planning, and Cybersecurity Risk Management from Harvard online. Allison founded the Georgia Chapter of Women in Manufacturing and currently serves as Treasurer. She serves on the Chattahoochee Technical College Foundation Board as its Secretary, the liveSAFE Resources Board of Directors as Resource Development Co-Chair, and on the Leadership Cobb Alumni Association Board as Membership Chair and is also a member of Cobb Executive Women. She is on the Board for the Cobb Chamber of Commerce’s Northwest Area Councils. Allison runs The Dave Krache Foundation, a non-profit that helps pay sports fees for local kids in need.
Host of Dial P for Procurement
Billy Taylor is a Proven Business Excellence Practitioner and Leadership Guru with over 25 years leading operations for a Fortune 500 company, Goodyear. He is also the CEO of LinkedXL (Excellence), a Business Operating Systems Architecting Firm dedicated to implementing sustainable operating systems that drive sustainable results. Taylor’s achievements in the industry have made him a Next Generational Lean pacesetter with significant contributions.
An American business executive, Taylor has made a name for himself as an innovative and energetic industry professional with an indispensable passion for his craft of operational excellence. His journey started many years ago and has worked with renowned corporations such as The Goodyear Tire & Rubber Co. (GT) leading multi-site operations. With over 3 decades of service leading North America operations, he is experienced in a deeply rooted process driven approach in customer service, process integrity for sustainability.
A disciple of continuous improvement, Taylor’s love for people inspires commitment to helping others achieve their full potential. He is a dynamic speaker and hosts "The Winning Link," a popular podcast centered on business and leadership excellence with the #1 rated Supply Chain Now Network. As a leadership guru, Taylor has earned several invitations to universities, international conferences, global publications, and the U.S. Army to demonstrate how to achieve and sustain effective results through cultural acceptance and employee ownership. Leveraging the wisdom of his business acumen, strong influence as a speaker and podcaster Taylor is set to release "The Winning Link" book under McGraw Hill publishing in 2022. The book is a how-to manual to help readers understand the management of business interactions while teaching them how to Deine, Align, and Execute Winning in Business.
A servant leader, Taylor, was named by The National Diversity Council as one of the Top 100 Diversity Officers in the country in 2021. He features among Oklahoma's Most Admired CEOs and maintains key leadership roles with the Executive Advisory Board for The Shingo Institute "The Nobel Prize of Operations" and The Association of Manufacturing Excellence (AME); two world-leading organizations for operational excellence, business development, and cultural learning. He is also an Independent Director for the M-D Building Products Board, a proud American manufacturer of quality products since 1920.
Lori is currently completing a degree in marketing with an emphasis in digital marketing at the University of Georgia. When she’s not supporting the marketing efforts at Supply Chain Now, you can find her at music festivals – or working toward her dream goal of a fashion career. Lori is involved in many extracurricular activities and appreciates all the learning experiences UGA has brought her.
Social Media Manager
My name is Chantel King and I am the Social Media Specialist at Supply Chain Now. My job is to make sure our audience is engaged and educated on the abundant amount of information the supply chain industry has to offer.
Social Media and Communications has been my niche ever since I graduated from college at The Academy of Art University in San Francisco. No, I am not a West Coast girl. I was born and raised in New Jersey, but my travel experience goes way beyond the garden state. My true passion is in creating editorial and graphic content that influences others to be great in whatever industry they are in. I’ve done this by working with lifestyle, financial, and editorial companies by providing resources to enhance their businesses.
Another passion of mine is trying new things. Whether it’s food, an activity, or a sport. I would like to say that I am an adventurous Taurus that never shies away from a new quest or challenge.
Trisha is new to the supply chain industry – but not to podcasting. She’s an experienced podcast manager and virtual assistant who also happens to have 20 years of experience as an elementary school teacher. It’s safe to say, she’s passionate about helping people, and she lives out that passion every day with the Supply Chain Now team, contributing to scheduling and podcast production.
Business Development Manager
Clay is passionate about two things: supply chain and the marketing that goes into it. Recently graduated with a degree in marketing at the University of Georgia, Clay got his start as a journalism major and inaugural member of the Owl’s football team at Kennesaw State University – but quickly saw tremendous opportunity in the Terry College of Business. He’s already putting his education to great use at Supply Chain Now, assisting with everything from sales and brand strategy to media production. Clay has contributed to initiatives such as our leap into video production, the guest blog series, and boosting social media presence, and after nearly two years in Supply Chain Now’s Marketing Department, Clay now heads up partnership and sales initiatives with the help of the rest of the Supply Chain Now sales team.
Vice President, Production
Amanda is a production and marketing veteran and entrepreneur with over 20 years of experience across a variety of industries and organizations including Von Maur, Anthropologie, AmericasMart Atlanta, and Children’s Healthcare of Atlanta. Amanda currently manages, produces, and develops modern digital content for Supply Chain Now and their clients. Amanda has previously served as the VP of Information Systems and Webmaster on the Board of Directors for APICS Savannah, and founded and managed her own successful digital marketing firm, Magnolia Marketing Group. When she’s not leading the Supply Chain Now production team, you can find Amanda in the kitchen, reading, listening to podcasts, or enjoying time with family.
Constantine Limberakis is a thought leader in the area of procurement and supply management. He has over 20 years of international experience, playing strategic roles in a wide spectrum of organizations related to analyst advisory, consulting, product marketing, product development, and market research. Throughout his career, he's been passionate about engaging global business leaders and the broader analyst and technology community with strategic content, speaking engagements, podcasts, research, webinars, and industry articles.Constantine holds a BA in History from the University of Illinois at Urbana-Champaign, and an MBA in Finance & Marketing / Masters in Public & International Affairs from the University of Pittsburgh.
Host, Veteran Voices
Mary Kate Soliva is a veteran of the US Army and cofounder of the Guam Human Rights Initiative. She is currently in the Doctor of Criminal Justice program at Saint Leo University. She is passionate about combating human trafficking and has spent the last decade conducting training for military personnel and the local community.
Host of Dial P for Procurement
Kelly is the Owner and Managing Director of Buyers Meeting Point and MyPurchasingCenter. She has been in procurement since 2003, starting as a practitioner and then as the Associate Director of Consulting at Emptoris. She has covered procurement news, events, publications, solutions, trends, and relevant economics at Buyers Meeting Point since 2009. Kelly is also the General Manager at Art of Procurement and Business Survey Chair for the ISM-New York Report on Business. Kelly has her MBA from Babson College as well as an MS in Library and Information Science from Simmons College and she has co-authored three books: ‘Supply Market Intelligence for Procurement Professionals’, ‘Procurement at a Crossroads’, and ‘Finance Unleashed’.
Host of Logistics with Purpose and Supply Chain Now en Español
Enrique serves as Managing Director at Vector Global Logistics and believes we all have a personal responsibility to change the world. He is hard working, relationship minded and pro-active. Enrique trusts that the key to logistics is having a good and responsible team that truly partners with the clients and does whatever is necessary to see them succeed. He is a proud sponsor of Vector’s unique results-based work environment and before venturing into logistics he worked for the Boston Consulting Group (BCG). During his time at BCG, he worked in different industries such as Telecommunications, Energy, Industrial Goods, Building Materials, and Private Banking. His main focus was always on the operations, sales, and supply chain processes, with case focus on, logistics, growth strategy, and cost reduction. Prior to joining BCG, Enrique worked for Grupo Vitro, a Mexican glass manufacturer, for five years holding different positions from sales and logistics manager to supply chain project leader in charge of five warehouses in Colombia.
He has an MBA from The Wharton School of Business and a BS, in Mechanical Engineer from the Technologico de Monterrey in Mexico. Enrique’s passions are soccer and the ocean, and he also enjoys traveling, getting to know new people, and spending time with his wife and two kids, Emma and Enrique.
Host of Digital Transformers
Kevin L. Jackson is a globally recognized Thought Leader, Industry Influencer and Founder/Author of the award winning “Cloud Musings” blog. He has also been recognized as a “Top 5G Influencer” (Onalytica 2019, Radar 2020), a “Top 50 Global Digital Transformation Thought Leader” (Thinkers 360 2019) and provides strategic consulting and integrated social media services to AT&T, Intel, Broadcom, Ericsson and other leading companies. Mr. Jackson’s commercial experience includes Vice President J.P. Morgan Chase, Worldwide Sales Executive for IBM and SAIC (Engility) Director Cloud Solutions. He has served on teams that have supported digital transformation projects for the North Atlantic Treaty Organization (NATO) and the US Intelligence Community. Kevin’s formal education includes a MS Computer Engineering from Naval Postgraduate School; MA National Security & Strategic Studies from Naval War College; and a BS Aerospace Engineering from the United States Naval Academy. Internationally recognizable firms that have sponsored articles authored by him include Cisco, Microsoft, Citrix and IBM. Books include “Click to Transform” (Leaders Press, 2020), “Architecting Cloud Computing Solutions” (Packt, 2018), and “Practical Cloud Security: A Cross Industry View” (Taylor & Francis, 2016). He also delivers online training through Tulane University, O’Reilly Media, LinkedIn Learning, and Pluralsight. Mr. Jackson retired from the U.S. Navy in 1994, earning specialties in Space Systems Engineering, Carrier Onboard Delivery Logistics and carrier-based Airborne Early Warning and Control. While active, he also served with the National Reconnaissance Office, Operational Support Office, providing tactical support to Navy and Marine Corps forces worldwide.
Director of Sales
Tyler Ward serves as Supply Chain Now's Director of Sales. Born and raised in Mid-Atlantic, Tyler is a proud graduate of Shippensburg University where he earned his degree in Communications. After college, he made his way to the beautiful state of Oregon, where he now lives with his wife and daughter.
With over a decade of experience in sales, Tyler has a proven track record of exceeding targets and leading high-performing teams. He credits his success to his ability to communicate effectively with customers and team members alike, as well as his strategic thinking and problem-solving skills.
When he's not closing deals, you can find Tyler on the links or cheering on his favorite football and basketball teams. He also enjoys spending time with his family, playing pick-up basketball, and traveling back to Ocean City, Maryland, his favorite place!
Principal, Supply Chain Now
Host of Supply Chain is Boring
Talk about world-class: Chris is one of the few professionals in the world to hold CPIM-F, CLTD-F and CSCP-F designations from ASCM/APICS. He’s also the APICS coach – and our resident Supply Chain Doctor. When he’s not hosting programs with Supply Chain Now, he’s sharing supply chain knowledge on the APICS Coach Youtube channel or serving as a professional education instructor for the Georgia Tech Supply Chain & Logistic Institute’s Supply Chain Management (SCM) program and University of Tennessee-Chattanooga Center for Professional Education courses.
Chris earned a BS in Industrial Engineering from Bradley University, an MBA with emphasis in Industrial Psychology from the University of West Florida, and is a Doctoral in Supply Chain Management candidate.
Principal & CMO, Supply Chain Now
Host of Supply Chain Now and TECHquila Sunrise
When rapid-growth technology companies, venture capital and private equity firms are looking for advisory, they call Greg – a founder, board director, advisor and catalyst of disruptive B2B technology and supply chain. An insightful visionary, Greg guides founders, investors and leadership teams in creating breakthroughs to gain market exposure and momentum – increasing overall company esteem and valuation.
Greg is a founder himself, creating Blue Ridge Solutions, a Gartner Magic Quadrant Leader in cloud-native supply chain applications, and bringing to market Curo, a field service management solution. He has also held leadership roles with Servigistics (PTC) and E3 Corporation (JDA/Blue Yonder). As a principal and host at Supply Chain Now, Greg helps guide the company’s strategic direction, hosts industry leader discussions, community livestreams, and all in addition to executive producing and hosting his original YouTube channel and podcast, TEChquila Sunrise.
Founder, CEO, & Host
As the founder and CEO of Supply Chain Now, you might say Scott is the voice of supply chain – but he’s too much of a team player to ever claim such a title. One thing’s for sure: he’s a tried and true supply chain expert. With over 15 years of experience in the end-to-end supply chain, Scott’s insights have appeared in major publications including The Wall Street Journal, USA Today, and CNN. He has also been named a top industry influencer by Thinkers360, ISCEA and more.
From 2009-2011, Scott was president of APICS Atlanta, and he continues to lead initiatives that support both the local business community and global industry. A United States Air Force Veteran, Scott has also regularly led efforts to give back to his fellow veteran community since his departure from active duty in 2002.