Is ChatGPT taking my job?

Artificial intelligence is revolutionizing the market and the world. Brad Watkins, a self-described "technology evangelist," joins Dave and Ryan to explain where we are with AI, where we're headed, and what it means for you.

Brad Watkins and any mentioned companies are not affiliated with The O.N. Equity Sales Company or O.N. Investment Management Company.

David Smyth and Ryan Petrunyak talk about family, finances and fun. Learn more about Family Financial Partners at familyfinancialpartners.com.

Securities offered through The O.N. Equity Sales Company, Member FINRA/SIPC, One Financial Way Cincinnati, Ohio 45242 (513) 794-6794. David Smyth is an Investment Advisor Representative offering Investment Advisory services through O.N. Investment Management Company. Estate planning services provided in conjunction with your licensed legal advisor.

Transcript

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Sideburns versus skinny jeans, Walkmans versus AirPods, millennial or Gen Xer. We're going to dive right in to family, finances and fun. Mom, is my laundry done? Really? Ryan? Welcome to end my day. Hi everyone. Welcome back to In My Day, I'm here with Dave Smith as always, and today we have Brad Watkins joining us. He is a self-described technology evangelist, and he will be helping us break down AI and how it's gonna change our world. How you doing today, Dave? Well, I'm getting ready to go to church Ryan. I can't wait for AI. Whenever you say the word evangelist, that just makes me want to rise up in the pew, get excited, wave my hands in the air, and get some praise music going. Let's go. But when it comes to AI, everyone's asked us to do a show on this. Everyone's like, I want to kind of understand a little bit more of what artificial intelligence is, where is it going and how can I benefit from it? Right? But there's also a lot of kind of misinformation out there. I think that, depending on your age, right, if you're a younger person, you've kind of like grown up into it. You don't even realize maybe how you're using AI. At the other end of the spectrum, we've got a lot of our boomer clients that are worried that these computers are getting smarter and smarter and smarter, and they're gonna take over everything. And, they're not only not gonna get Social security, but they're gonna have computers telling 'em what to do. Yeah, yeah. Have you seen anything like that? Yeah, I've talked to a friend the other day that was telling me that she was very upset about AI because they were calling her, so she thought all scam calls were AI. And there might be some AI involved in some scam calls, so not completely wrong, but I think there is a general Misunderstanding as to everything that AI could do in a positive way. Yeah. For our world. And I'm hoping Brad can shed some light on that. Yeah. For everybody today. But more importantly, let's just start with what is AI, Brad? Like if you were describing it to general population, what's a definition for us? So AI is a technology that allows computers to do work that would normally take human intelligence. Okay. So it's allowing computers to do things that we couldn't let them do before. Right. It's not tabulating a spreadsheet, it's helping make decisions, recommendations, and things that historically have taken a human brain. Okay. That's it in a nutshell. That's what artificial intelligence says. We're taking capabilities that have been uniquely human and we're building a technology stack that allows us to do that at a different scale and pace. Right. And that's what Artificial Intelligence is in a nutshell. So we no longer have these sci-fi movies where we're having to take all these humans and put 'em in like little cocoons and tap their brainwaves. That's right. We can actually do this with a computer instead of a human body now. Correct. Correct. Well, hallelujah. That's one of my biggest nightmares in life. Now we're not gonna be abducted., we're not gonna be plugging into the matrix. Right. That ain't happening. Oh my gosh. Okay, good. But you know, you mentioned there's a lot of misunderstanding, misconceptions about AI. Any new technology, people are fearful of change. And this is revolutionary. This is the AI and the adoption and the use of this technology. So it's not new. People feel like it's new because it's really become, with chat GPT especially, it's become very visible. This stuff's been under development for years. Okay. Many years. But it is hidden inflection point. The adoption of the technology, the real world uses are tremendous. Now, With any new technology... well, no new or otherwise with any capability technology, there is the potential for misuse. And could AI help the scam callers be better? Absolutely. And it will. And it is. But there's a whole lot of positive benefits that are gonna come from this, right? Much, much more. My true feeling, and I read a lot about this. I watched what's really happening in the world, right? So I've been doing high technology stuff for, let's just say 20 plus years, right? I didn't have these gray hairs when I started doing this, but this is one of the most compelling technology advancements in my lifetime. In our lifetime, okay? So there have been a lot of cool technologies invented, and everybody loves Uber and everybody thinks Teslas are cool and all that stuff. Yeah. But this is gonna touch every single aspect of our life in a meaningful way. Now getting back to your scam callers, is it gonna help the scam callers be more targeted? Absolutely. Yeah. But that's gonna be, if you look on balance, that's gonna be the potential negative uses exist. But I think that what we will see is that the beneficial uses are gonna vastly outweigh any kind of abuses really. Right. So, yeah. I'm interested to hear from you too... to expand on it a little bit some of the uses that we're gonna see. So one of the things that I've already seen, my wife loves her plants. Mm-hmm. My living room looks like a jungle. Got it. And she is very Okay at keeping them alive. I mean, she's gotten better. Very, okay. Okay. One of the reasons she's gotten better at it, Sounds like she may be listening to this. Yeah, yeah. But one of the reasons that she's gotten better at it is she had an app, and I don't remember the name of the app, but it used AI technology where basically she could scan the plant and it would use AI to figure out if it needs more water, it needs less water, it needs more sunlight. And tell her exactly what a person that knows a lot about plants would tell her. Yeah. So that's one of the things that I've seen just in a little way in our lives that already, you know, is starting to impact day-to-day life a little bit. Yeah. What are some things that you think, obviously our crystal balls are all broken, so we don't know exactly, but in five, 10 years from now, what is something that could be a part of everyone's life? Sure. Like iPhones are now, yeah. That they weren't 15 years ago. So couple things there. You said five to 10 years? Think three. Okay. Okay. Why is that? The adoption of this technology is happening at a pace like nothing I've ever seen in the technology space before. Okay. Though, because it is a way, it has impact across so many, there is potential use cases every as across every aspect of our lives. And it is such a competitive advantage for companies if they adopt it correctly, that it will, some companies will die because they don't, people, especially in established industries, if they don't have the vision to see where it can apply to them, they will be beaten by the people that adopt it. Now, that could be established businesses that adopt the technology or that could be new upstarts, right. You know, startups that just are native using this stuff. That's how impactful this will be. So if you're part of a business, if you're investing in a business and they are not adopting this technology in a meaningful way, they will be at a disadvantage and a significant one in the market. So that's making people run towards this. So, and I'll explain some of the indicators that tell me that. Some of these very large tech companies are buying so much of the equipment that enables this technology, the stuff that none of us will see. It's well stuff I see cuz I design these systems, but they're buying so much of it, the manufacturers can't make enough of it. Like you order the equipment that it takes to do the stuff that makes this happen, and you gotta wait a year to get it. Wow. Because it's in such high demand. Te Yeah. So the rate of adoption is like nothing I've ever seen. Cause the business benefits are dramatic. You could take three companies that are on an even footing and one of 'em gets ahead in this kind of technology race, and they're gonna beat 'em. Like, there's no doubt in my mind, like if they adopt it in a meaningful way and are thoughtful about it, it will give them a competitive advantage that will stomp the competition. So this is almost like an old USA/USSR arms race. Absolutely. It's occurring right now for these chips, for these yes programs. For all the stuff to the infrastructure. Yes. They need to run these capabilities. Right. So two things have happened recently that have accelerated this, well, three things. The first being these businesses realize, Hey man, this is a big deal. This can really give my business an advantage. So that realization at the C level, not that get out of the nerds, right? The nerds have to make it happen. But once marketing, the CFO, the CMO, and the CEO, right? So you got the guy that runs the business is responsible for his success. CEO, you got the marketing people CMO, and you got the CFO who's responsible for the money. When those three people, those three groups start seeing the benefit and adopt it, that's the arm they're winning. The arms race, the geeks have to work with guys like me to make it all happen. But that's when it takes off. So if, again, this is just Brad, if I'm investing in a company and I can't determine that they're doing something meaningful in this space, I'm gonna have some questions about that. And I'm probably gonna look at their competition and see if they are adopting this technology. So you talked about your wife and watering plants or taking care of plants, and what you said was the app tells her what somebody that's really good at this would do. Mm-hmm. You scan the plant and then body of knowledge. From somebody that spent their life taking care of plants and they've learned the tips and tricks. My dad goes to the farmer's market and talks to the lady that brings flowers to the farmer's market and she gives him tips on gardening. She's taken a lifetime of knowledge and distilling that and sharing that with my dad in the app. That app is taking somebody's body of knowledge, making sense of it, and giving your wife tips on how to better take care of plants. That is essentially in my mind what the really compelling part of AI is. Okay. So I'll give you an example. Think about healthcare. Comes to my mind cuz we're gonna see benefits in healthcare that we've not seen in generations. Right? So here's an example. We were talking earlier about a person that's got cancer. Yeah. Okay. Now, if you are diagnosed with cancer and you live in Phelps, Kentucky, does anybody know where Phelps is down in east far? No, I do not. As far eastern Kentucky Pikeville, right? Pike County, yep. Okay. Wonderful people in that area, but the medical care that is available to them locally is maybe not as rich as the medical care available to somebody in Chicago. Right. If you look at the best of the best in cancer treatment, UK Markey Cancer Center, that's in Lexington. So if you get a diagnosis whether it be cancer or some other rare disease, I'm not talking about the common cold or day-to-day stuff. I'm talking about something serious. Mm-hmm. Depending on where you are in our country or in the world, your access to medical care is a big deal. Right? A lot of people travel to the Mayo Clinic or to some specialty area, right. People come to UK's Markey Cancer Center from all over to access treatment that otherwise wouldn't be available. Okay. Now, so what are they accessing? They're accessing a person, a body of knowledge that is typically delivered by the people that have spent their careers becoming experts. Right? So what AI does is allow us to build, I won't get into the real nitty gritty, but build models that take that body of knowledge and now that is built into the model that makes the Artificial Intelligence smarter. Okay. So let's say you could pick a field, I'm talking about cancer, but this applies to any field. Let's say you got 10 people in the world that are best and the brightest and they've been doing it for decades. They're really, really good at what they do. I don't care if that's financial analysis, market analysis, if it's doctors, if it's construction people. Pick an industry, take the 10 best at that, and you build all 10 of those bodies of knowledge into the model that runs the AI. So now you've got a model that's smarter, that has the combined wisdom and experience of all 10 of them, and you've codified that It's built into the model now, okay, does that resonate? Like, yeah. So now you use those people to train the model. So these models are iterative and AI gets smarter every minute. Right. Every time they retrain that model based on inputs from the best and the brightest. Okay. It gets better, faster, stronger. Right. Constantly. And that's why it's so compelling, right? So what we're seeing right now is large businesses taking their internal domain expertise, whatever their business is, whatever they do and what they're doing is building, they're taking their best and brightest across their whole company. Right. And they're bringing that in to models that allow them to unlock the benefit of all of that. Okay. You ever called customer support for anything? Yes. Right. Sometimes it's a good experience. You're call Amazon, I'm gonna use Amazon. Cause I've had really good experiences with customer support at Amazon. Mm-hmm. But at the end of the day, you're dealing with a person if you call. One day and you get Fred and Fred's having a bad day, your experience is probably gonna be bad. If you call the same day, you call back an hour later and you get John, John's having a good day, your experience is gonna be better. Well, what if you could take that variation out? What if you could take the best of the stuff that Fred knows how to do and John knows how to do? And then you can take all your historical data on when customers had a good experience or they had a bad experience, and you build that into a model. And now when you call or you text, chatbot or text message, however you want to interact with that, if you're interacting with AI as a business, I can ensure my customers are having a good experience every time. Yeah. And I'm, wow. Yeah. Yeah. And I'm capturing, okay, we've got a product that's getting a lot of calls, so let's go do some digging on why that is. So it enables you to ensure a consistent experience for your customer in a customer support use case. And you can gather data on, Hey, I've got a problem with product A, B, or C, and now I can go root cause analysis on that, fix, whatever that is. And all that happens in real time. Like it's not like somebody looks at a report and says, well, last month we had however many calls on product A. And then somebody might be intelligent enough to go, you know what? Let's investigate product A. Maybe there's a problem with our product. So that type of stuff. What I'm getting at is in every aspect, so medicine and if I'm just rambling on, just tell me, but No, you're good. So right now I don't know, probably not you Ron, but Dave, I don't know, do you take a blood pressure pill? Yeah. Yep. Do you mind telling what that medicine is? With Lisinopril? Okay. I take Lisinopril. Yeah. We're two different people. Our health profiles are vastly different probably, right? I mean, how tall are you? Six two, right? I'm five eight. Right. We're different, but we both take lisinopril. So the manufacturer, the developer of Lisinopril had to find something that was effective for the vast majority of people, for the largest common denominator, and that's how medicine's built. Okay. if you go get a blood pressure medicine that's not built for you, that's built for the least common denominator. What benefit can the drug bring with no adverse side effects to the most number of people? Now, how do you get that? How does a drug company make that happen? They do a lot of R&D to develop something that is basically generic. Okay. It's not like a tailored suit. They didn't build it for Dave, they built it for everybody hoping it would help Dave and it would help Brad. Okay. So they trade efficacy for the least common denominator. Right? And that's what we've accepted. That's how this works, right? And they get it FDA approved and they start selling it. They've been selling lisinopril for, you know, 50 years. What we're gonna see in the very near term is drug manufacturers are a great example. They will be able to give something that may be based on lisinopril, but is tailored to Dave. So the lisinopril or the blood pressure medicine, let's just say that you take, is no longer built for the least common denominator. It's built for you, like you. And the one I would take is built for me, like the chemical compounds will be adjusted so that they do better in my body based on my makeup than yours. This is like, Sci-fi kind of, this is gonna happen in 50 years stuff people think about. No, it's gonna happen in the very near term. Wow. The things that'll slow it down are regulatory. Our government and our regulations that are in place to keep us safe, they will not be able to keep up with the pace of innovation. Covid vaccine, dramatic, never seen before disease. Right. The plague comes out. The drug companies were able to use AI and massive computing power, but AI, yeah. To develop a vaccine that was effective in a minuscule you know, how long it takes to develop a drug? 10 plus years, right? They did it in months and it was effective. Now there's a lot of debate on did we move too fast? Is it causing unintended consequences? And I don't know. I'm not a medical person, so I'm not gonna get into that debate. But what I'll tell you is that is an example of how they can shrink the development cycles. They can build things that are effective much more quickly. And what I'm saying is one of the things that we're gonna see is an insurance company doesn't want Brad to have blood pressure, because later in my life that's gonna cost that my health insurance company more money, they're gonna have to spend more money to treat all the ailments that are gonna come along with that. So if they can better manage my high blood pressure, well then maybe they're not my managing diabetes, maybe they're not managing other ancillary health issues. Right. So the insurance companies are very interested in helping the drug companies get better at what they do. Right. So it could get to the point of it may not just be one pill. It may be that due to AI in the future we could be taking a pill or a shot that may have a variety of different Meds in there. Yeah. That all are built for you. Help us Yes. To help Dave function better. Yep. Based on just me. Yes. Absolutely. And not saying that I need it, but I know that a lot of my friends will be very excited, in that 50 year age to have correct doses of Viagra. Yes. Right. Yes. I mean, right. You know, I mean, that's game changer for them. Yeah. That's why they're listening. They're like okay, Dave, I'm not getting into, I needed that. I didn't know we were going down that now on the other, but to take it a different direction, then take it, clean it up. Okay. So the other side, you going back to that body of work. Yep. Right. Where you said they're taking like the 10 smartest people. Yeah. And they're gonna take their knowledge, they're gonna put in that body of work and they're gonna use this body of work. I'm also thinking even from the low tech side mm-hmm. That changes the knowledge gap and the knowledge base, even in a trade. Absolutely. You're like an electrician. Yes. Or a plumber or a, or a welder, where suddenly the new guy can learn really, really fast based on having proper training that maybe previously wasn't done in that particular union. Yes. Or, or something. Right. So there's a thing that I like to call tribal knowledge, right? You've heard of this before. This is where the old sage and the young guy set and talk and the old sage shares info with the young guy. And the young guy's like got the energy that the old Sage doesn't anymore. And he takes that info and he mixes it with his own grit, determination, capabilities, capacities, and he goes and does something cool. Right? I've never heard of anything like that, Dave, have you? I never put my own spin on comments or instruction at all. So, so you, so you get this, you talk about an electrician, for instance. You get the young guy that's coming in to learn the trade. You got somebody that's been in the trade for 15, 20 plus years, whatever it might be. What if that guy, what if whoever the new guy is learning from new guy, girl, if they're getting bad information, they propagate it. They they take it as the gospel. Cause Dave's been doing this for 20 years. He knows you know, you see people, I don't know how many times you've hired a repair person. Let's say we're talking about electricians come to your house to look at something. What do they say? I've never seen anybody do something so stupid before me that was completely wrong. They all say, right? Yep. Yep. Years ago when I was doing like repairing and installing technology solutions, it was often that I would come in, in my twenties and be like, who did this? They must have been an idiot. Right? So you can remove that. So what I talked to clients of mine about is we can use this technology to remove undifferentiated heavy lifting. And here's what I mean by that. If you've got people in your business, whatever that business is that are doing things that are not making you more competitive in your market, more efficient in your delivery of whatever good or service they're doing something that's not making you money, it's not benefiting your customer, it's not benefiting your business. If we can remove that stuff through the application, the appropriate application of technology that makes you more competitive. I was working with a semiconductor manufacturer that we used AI to solve a pretty significant problem for them. So they make a lot of the stuff that goes into your electronics. They don't make the iPhone, but they might make a component that goes in it. So they're not making the end product that you buy, so you don't know who they are, you've never dealt with them on a consumer basis, but they're critical to the functionality of whatever you're buying. Okay? So their manufacturing process has a significant number of checkpoints trying to make sure they're producing a quality product. But at the end of the day, typically the real litmus test is usually happening after the thing's done, finished, ready to go in a box, to be sold up the supply chain to the next person in the chain. What we posed to them is what if we could see problems well before you got to a finished good, when you still had a chance to maybe correct it. So that finished good didn't have to be scrapped. It could be remedied early in the manufacturing process, right? So we used computer vision and Artificial Intelligence. To look at components as they were being manufactured when they move from one step to the next and many of these steps are performed by robots, okay, let's just some human intervention, but a lot of this stuff is robots right now. As it as it moves, we can use computer vision to see something that a human, if they could sit there and look at it and take their time, some expert that had been doing that could say, Hey, that pen is not in the right place, or something looks funny there. Well, we take that guy's knowledge, he's about to retire. He can just glance at it and be like, that's wrong. Well, we use him to train the model and now we've got his body of knowledge in a computer, in a machine that's watching this and can remediate and intervene much earlier in the manufacturing process. So they make better products, they have less waste. You see what I'm saying? Absolutely. Yeah. So that is a that, so you can identify those things earlier. You can also take this tons of data you have these measurement points they have along their manufacturing process and you can make better sense outta that. So think about a 20 step manufacturing process. Ryan knows step three through 12. He's the expert. Dave knows 12 through 20. Brad knows the first part. What if we could take all three of those levels of expertise, those bodies of knowledge, put 'em into a model so you can correlate step one through seven, seven through 12, 12 through 20 in a more meaningful way. It's not the three of us sitting around the water cooler going, you know what line number three has been putting out bad stuff. Wonder why? And you're like, it's not in step 12 through 20. And you're like, it's not in seven through 12. And I'm like one through seven. So where is it? Right? So you remove that. Okay. Again, I'm gonna go back to in my estimation, businesses that aren't looking at ways to thoughtfully deploy this technology are gonna suffer. They're gonna lose, if they have a competitive advantage, grit and determination ain't gonna be enough, right? Just working harder. Elbow grease, rolling up your sleeves. No, you need to roll up your sleeves and get some smart guys in a room and figure out how your business can benefit from it, right? You got an army of people out here doing what you all do for your clients and you all provide a great service. If you can make every one of them more effective, that helps your clients and move the bottom line. Everything helps. Helps you as a business. It helps you deliver a better service for your customer. You look at marketing, we were talking about spam calls. They're gonna get better. You know what else is gonna get better? You marketing your good or service to your consumer because you can do hyper targeted advertising right now. I was looking for when we went out to Utah. My little guy that was taking out, we went overlanding out west and I needed to get new gear for him cuz he's growing and the last time we did a camper trip, he was smaller, he's growing, he's at that age, he's 11 now. He's like, his clothes, his clothes last two months and then I gotta buy, nor, you know, so I had to go buy some stuff and then I start getting ads for that stuff. Yeah. Now I had already bought the stuff. So was that advertising dollar, whoever was advertising to me on these websites, that costs money, right? So REI is starting to advertise to me for this stuff, and they're wasting their money. I've already spent a thousand dollars with 'em, I'm done for three months. Right? Yeah. But there's still, that's cost them money to put that in front of me. What if they didn't have to do that? What if they knew they could close that loop and they're like, Hey, Brad bought that so we don't need to advertise. Okay. Maybe what you advertise to Brad is what? Me being an REI person, if I worked for REI I would know what the life cycle of my customer is. They're gonna buy this today. The next thing they might buy is this. Hmm. So instead of marketing something to them that they already bought, which is wasting my marketing dollars, I can be thoughtful and I can say, oh, Brad bought that. He's most likely to buy this next, so let me advertise to him what is appropriate, right. What would be next? If I see Brad buying a whole lot of chicken wings at Costco, I might wanna market a high blood pressure medicine to him next. Okay. You see what I'm saying? So, and you can market Brad's personal high blood pressure medicine Exactly like you said. Right. So, in other words, they're not gonna need to have the personal information of like, Brad bought a ticket to fly to Colorado, and based on that, we're gonna market REI. They could have previously, last year, Brad went to Colorado or bought REI gear. Yep. And now we know that wasn't Brad's size, that was his son's size. We now know this young whipper snapper's probably grown up. Yes. So we're gonna market the new size and the new style Absolutely. Seasonally. Yes. And wow. And it can be so targeted. That's the thing. Right Now, anybody listening that's in marketing, they understand they're just like that blood pressure medicine. They're trying to create a marketing campaign that applies to the broadest audience possible based on their mode of delivery. And it's gotten better. Right. The Facebooks of the world, Instagrams, they know enough about us that that helps those marketers target us more accurately. But it's gonna get hyper accurate. Okay. It's gonna get scare eerily accurate. So I am a early adopter of technology. I am ready, willing, and able to trade perceived privacy for better ads. I love it when I'm on Amazon, it says, you know what? You're buying this. You might also buy this to go with it. Yes. Half the time I knew I needed that other thing, but I was gonna have to go look for it. But it's already there. Amazon already said, Hey, most people that buy, I was buying something to work on my boat for the weekend. Mm-hmm. I bought a battery crimper for like a car battery, like it's a big crimper. Well, right there said, Hey, if you're buying this, you might also, once the ends that you crimp on, if you're buying a crimper, you're gonna crimp something onto something. So you might want that too. I was gonna go search for that next. It was right there. Click, click, boom. Okay, so you're, and, and if you think you have privacy in this world, if you're one of those people you don't. That's a whole nother podcast. Just give up. That's a whole nother podcast. But like, if you have any perception that people don't know absolutely everything about you, you're wrong. Okay? if you've got any kind of loyalty card for anything, if you've got, do you have a phone? Do you have a smartphone? Soon as you did that, let's just stop at the start. Smartphone, they know where you are, when you are, what you're doing. Don't kid yourself, you gotta go off the grid and stay off the grid. But yeah, so we could do a whole nother podcast on that. Yeah. What I'll tell you, one of the interesting things that I'm seeing about AI that is that it help might be a good way to help you understand the power is, we talked about taking these various bodies of knowledge, right? And it's obvious if I were gonna come into FFP and build this capability, I would want to take your best and brightest. And what they do is we build a model. The model already exists for financial services. And then what we would do is expand that or augment that with what's unique about FFP, what's your value proposition to your customers? So we start doing something that enhances that. And then we use your best and brightest to train the model. Okay. Input output. Oh, that output could be a little different. So we change the model so that when we get this input, the output's more accurate. And what happens in the middle is black magic. A hundred percent. There's some computer scientists that a few years ago, some of the best and brightest I've worked with we're like, we're not sure exactly what happens in there. Now that's a hyperbole that they know what happens. But you train the model. Okay, so Tesla, self-driving cars. Self-driving cars are gonna be a thing. And when we ever get there, like where everybody's got one, which that will take a long time cause people keep cars forever. But traffic will be a thing in the past. Cars driven by computers will be so much more efficient than humans. You won't need red lights, I mean, it'll all just happen, okay? And you won't have that backup on I 75 because nobody will zipper in. Nobody will let somebody in front of them. So the whole line of traffic stops when you get to a construction zone, right? All right, so Tesla has a machine learning model, has an AI model that lives on the car, cuz you have to make decisions in real time when you're driving a car. Acceleration, braking, turning that's happening milliseconds or too long. We're talking about microsecond decisions, okay? Now there's, golly, the number's escaping me right now, but there's a vast amount of data that a Tesla is collecting all the time. All the time. It's making decisions on it, but it's also storing it. Do you know why? Because when? When it has time. It's streaming that back to Tesla's data center and they're using that data from all these cars to make their models better. And then once they perfect that and they get the model incrementally better, they shoot it back down to the car. And your car just got smarter. It got better able to drive itself. Hmm. That is happening iteratively all day, every day. Their cars are getting smarter cause of all the user data. You remember a few years ago when Facebook was like, this is what you're gonna look like when you're, older and you're like, does this look right? Or your, I hope it's wrong. Okay. I'm just saying. So, and they would put pictures up. Is this you? Yeah. Hey Dave, is this you? We thought this might be you, a picture that you didn't post, somebody else posted, but you had posted pictures of yourself and they got access to all this. So they'd be like, Hey, is this you over here? You're like, oh yeah, that's me. I was out with Brad. We were having a good time. Brad must have posted that. I didn't even know. He didn't tag me. But you tagged yourself. What'd you just do? You trained their model. Hmm. You gave them a reinforcement. Is that good? Is that bad? Is that me? And when you said Yeah, that's me. Sure. Now people can see us hanging out together. But you know what else? Their model just got better. So you're saying I might have inconspicuously helped the Russians influenced the election. Yeah. All this data's out there. Wow. That's a mindful, it's Dave's fault. It's Dave's fault. I was always wondering who to blame right there. Yeah, yeah, yeah. So all the, all of those things sound awesome. Like we have a world where we're driving Teslas with no traffic and these businesses are running efficiently and healthcare's gonna move more efficiently. Yep. And all these things are great, right? Yep. Something that went through the back of my head, so I'm sure it went through some other people's head too, when you were talking about AI. Mm-hmm. And you were talking about our jobs out there specifically. Yep. And I was like, what if they can create a smarter Ryan that never has doctor's appointments, so he'll never miss a day at work. Why would Dave keep me around? I was actually excited by that idea. So my question for you, Dave, is for all the people your staff burden went Yeah, yeah. For all the people out there from me, to the guy that works at Amazon that you mentioned, that works at the call center to potentially even some doctors that you have to go to to get your blood pressure medication. Yep. But maybe that could be automated. Do you think that all of these jobs are in jeopardy or are they just gonna look different? And if so, how does that affect our economy and how everything works? So that's more a question for you, Dave, but just wondering your thoughts on that. My understanding, tell me if I'm wrong on this, Brad, but my understanding of how this is really gonna impact jobs is like the example of why we used to use travel agents to book a airplane and tickets and now travel agents pretty much don't exist unless they really have a specialty. Yeah. And they specialize in something that you may not even be able to find that data. Yep. On the internet. Yeah. Or in TripAdvisor or in Yeah. If they know of a unique hotel or a restaurant in a town that's not even online in Italy. Yeah. That is amazing that they can get you a seat at the table Yep. Or booked at and take care of it for you that otherwise you'd never find online. Yeah. I feel like it all comes down to where the critical thinking's occurring. Yes. You're absolutely right. So if your goal in life is to do a job that is repetitive and low value, that kind of job is going to be automated. Okay. When it was Eli Whitney invented the cotton gin. Okay. Everybody thought, all those people in the fields that were picking cotton, well what are they gonna do? They're gonna lose their jobs cuz the cotton gin can pick way more. Cotton gin can do this better than a human can. Same thing. Same idea. We got an automated way to do a job that a human was doing, but what really happened, it could pick more cotton so the farmers could grow more cotton. They had the capability. Now, they were limited by the number of people they could get into a field to pick and harvest the cotton. Well, when the cotton gin came out, they could harvest way more cotton, so they got more land and grew more cotton. And now people that were picking the cotton were now processing like they moved higher in the value chain. Okay? So that's the key thing. It these people are gonna move higher in the value chain, and that's gonna cause the iterative nature of all. This is what's exciting for me. All these models are getting smarter and better and constantly. And if you apply it to your business, that will happen, right? You're gonna find a way for that to benefit your business. It's gonna get better and faster, smarter, and then, Ryan can go do something that maybe in his career he would've done in two or three years as he worked through the mundane stuff. And now I don't have to do the mundane stuff. I get trained on it or knowledge of it, but then I start doing more high value things. So that's really what I see happening. Yeah. So what you almost described is like what we actually do here with our newbies. We bring a newbie in, like even through an internship, right? Mm-hmm. Into our operations side, and they have to work in operations and they have to figure out what we actually do in operations. And once they figure that out, they then move from operations to paraplanning. Gotcha. Right? And as they're doing that, they're getting their appropriate licensure and any kind of regulatory type things they're working on. Yep. But they will do some operations and eventually they move fully into paraplanning once they get that skillset Yep. We then move them paraplanning slash advisor. Yeah. Right. And during that time, they're sitting in meetings, they're taking notes, they're building plans, they're doing all this. They're cultivating their own business, but they're also working with the main advisor. Yep. Right. One of the primary advisors to assist them so that that advisor's not opening their mail. Absolutely. They're not answering their emails. They can, kiss babies and shake hands and promise the world to somebody, but the actual follow-up is all occurring through that paraplanner. Yeah. And then eventually, as that paraplanner learns the business, we turn 'em loose and they're full advisor and they're full, call 'em like Ninja Warrior, right? Yeah. They don't have to do anything administrative at all. Right. They just have to service their clients and, their number one job is to be face to face Yep. With their clients and helping 'em. Yeah, absolutely. So it's, you'll accelerate that, that, so we could, it will get faster. Right. So you will generate more ninja warriors. More quickly. Okay. I'm really excited about this. Yeah. I'm a little disappointed he didn't come five years earlier cause I was not very good at the operation. Right. It probably could have helped him along the way a little bit. So, so what's more valuable? What's more valuable to your clients? What's in Ryan's head and him knowing how to use these different mechanisms and patterns to better benefit them or him filling out the appropriate forms or doing a spreadsheet so they can show it that's not high value. The thought, the experience. That's high value. Right. Okay. So if you can remove, okay. Let's say that I'm coming in here I'm gonna build a AI system for FFP We set, we start dissecting. I'm not saying I can do that. I can get the right people to do that Dave, but what I'm saying is, so we set in a meeting. Multiple meetings and we start distilling down what's valuable to FFP and then I'm gonna have to go back and I'm gonna have to build a PowerPoint presentation. Well, if I'm dealing with you, I don't, but if I'm dealing with you Yeah. We gotta build a presentation, right. To show Dave why he's gonna spend X amount of dollars Yeah. To build this capability and into your business. Yeah. Now is me building that PowerPoint presentation high value? No. Okay. And that's the thing that people, that's one of the things, one of the compelling things from AI that we've been dealing with for some years now to generative AI. Okay. I don't know if the people listening and understand there's a difference, what's the difference? I'm gonna explain it. So AI is taking vast data sets and helping you make decisions and things based on those data sets, helping you do something generative. AI is the AI doing something? It's not helping you do something. It's doing something. And that's the acceleration that we're gonna see. Mm-hmm. You go to chat gt, everybody's heard of it, so let's talk about it. You say, okay, I had a friend and her daughter had gone to school for computer science, and it posted all her code at whatever her school said, this is where you post your code. We'll keep this repository for you. So when you go get a job in these fields, they wanna see what you can do. Like you look at Ryan's resume, what he's done before, what his education is in, in these computer science fields they look at that, but then they're like, Hey, as a part of your education, you had to write code that did things. We wanna see what you did. What was your problem you were trying to solve? How'd you solve it? What'd your code look like? Are you writing in the same language that we use? Okay. All these things matter to this stuff. Well, so this friend's daughter gone through school, done all this work. She's going to apply for jobs. And that platform that all that code was posted on and ran on had been deprecated, which means it's gone. Which means, the places that the businesses she was applying to, they had a whole different platform to run it on. So all this work she had spent years doing was stranded, locked, done, couldn't give it to her potential employer to show what she did and couldn't run it. That's horrible. Can you imagine You do all this work and now it's essentially gone. Her mother got on ChatGPT and says, how do I get my code from platform A to platform B? And it's spit out a step-by-step instruction. Wow. Here's exactly how you do it. So this girl, her daughter was absolutely distraught. Like, I mean, she's working at a bar. She's got a degree in computer science and she's done all this work, but she can't prove it. So her mom sends her the steps, Hey, I didn't know how to do this. The reason I'm aware this happened, Dave, is cause the lady called me and I'm like, I don't know how to get from this to this. I will have to do some research for you. And we were talking about ChatGPT and I was said, well ,try it. She tried it and it gave her wow, you know, 15 steps to move it from A to B. It's all right. That amazing. All right. So doing things like Jay, my little guy likes to get on there and have it make pictures, Hey, I wanna see Spider-Man with a Wolverine head. And there's something, right? I mean, so the generative AI is where it starts doing things for you. Make me a PowerPoint presentation on why FFP should adopt AI. I give it the inputs and it does that. Like, that kind of stuff is very impactful, right? So you remove the undifferentiated heavy lifting if you're doing something. And this is one of the ways I model my day and I've been doing it for years. If I'm doing a task that does not help me better deliver services to my clients, why am I doing it? Is there a way I can automate it? Is there a way I can remove that step? And if I can, I share that with my peers. Hey guys, here's a better, faster way to do this, but that's me doing that. What if there was some automation? What if there's some AI that helps that just happen? And if you've got a Salesforce of a thousand people or thousands of people, Brad finds a better way to do something. You build that in the model, everybody gets the benefit of it right away. Now, another piece of this that I can't go have this talk without mentioning is one of the things that has impressed me the most is it makes a lot of sense to people to say, we're gonna take our 10 best people and we're gonna distill that knowledge down into an AI model. Cool. That makes sense. These, those are my 10 best guys. But what if I could take my 10 best guys distill their knowledge down and then take a lot of seemingly disconnected data, stuff that doesn't readily, it's not readily apparent why it would matter. Okay. AI has the ability, cause of the immense processing power to take in data sets. Massive, big data was a big, was a term a few years back. Everybody was big data. Big data. Nobody knew what the heck that meant. This is where the promise of big data is paying off. I gotta be careful what I say, but let's say that well, being able to take data sets that are not readily apparently relevant. They're not, you can't, well, why would that matter? Mm-hmm. But they are, so I talked to a guy probably seven years ago, one of the smartest people you'll meet. He can't talk to people much, but boy, he's smart, right? Yeah. And he was talking to me about the concept of dark data. Okay, so we're collecting more data all day, every day. The building we're in, if I own this building, I'm getting data off the HVAC systems, the electrical systems. I'm collecting a ton of data about the building. So I guess data generation is exploding, right? We're talking about exabytes of data are being generated. It's crazy. More data has been generated in the last two years that had been generated historically, ever. Right? And that is accelerating. So vast amounts of data, seemingly disconnected data. How do I make use of that? And that's where he was explaining to me this dark data. Let's think about all this data that exists about us, about what you buy at Kroger's, or what you buy at Costco, or how you drive your car, right? All this stuff. We don't need to analyze how I drive my car all, let's go back to the Kroger. That Costco, yeah. Yeah. Okay. So you got all this data and we understand there's a percentage of that data that the business already knows how they can make use of. If Dave's buying steaks, I might wanna market charcoal or wood pellets for his grill, whatever, right? So they understand some of it. But it's just like an iceberg in the ocean. You see the tip, but what's underneath? And that underneath is all the data that we have that we don't even know why we would use it, but it exists and there's gonna be a market for it. Do you understand what I'm saying? This is a market opportunity. There are companies that are collecting data that they don't even know how they're going to use because, and it's, the promise is being delivered now because some folks were smart enough to go, you know what, I don't know what I'm gonna do with this, but it might be useful and I can keep it. So they're keeping it. Okay. And now they're starting to unlock. Okay. If you sold hamburgers, well, FiveGuys down here, it's being renovated. It's killing me. It's my favorite place and I can't have it right now. Yep. Okay. Because DoorDash and FiveGuys just doesn't work. It's not, it's not. You gotta be there. Okay. So if I'm a FiveGuys franchisee and I want to deliver the best customer experience I can, right? What if I could plan my staffing levels so that I've got the right folks to cook those burgers when Brad walks in? I understand that historically between four and six o'clock, I get a lot of people coming in on a Friday, but what about a Tuesday or a Thursday or a Wednesday and what happens if so? So I've got some historical knowledge and gut feel, but is that really accurate? No. But if I could take in data, like what's going on in the community? Are there concerts? Is a school having a graduation or some kind of performance? What's the barometric pressure? Is it raining? Last Friday when I got a big rush. So when I was in college, I delivered pizzas. We got really busy when it rained. Yep. Because people didn't want to get out and go get pizzas. But the guy that was making the schedule and said, Brad, we're gonna need you to deliver pizzas tonight, he didn't know it was gonna rain. He didn't care if it was gonna rain. He just said, you know what, typically on a Friday we need six delivery drivers. So every Friday, six or eight or 10, I can't remember how many of us there were. Mm-hmm. Yep. Yep. And then what they do, so you drive in, you're gonna deliver pizzas tonight, and then they're not busy so they send you home. It's not good for the employee, it's not good for the business. Cuz now you've paid hourly wages that you didn't need to and the employee was counting on making some money that then they didn't get. So nobody's happy. Sure. But if you can accurately predict what you need for delivery drivers. Right. So that model is a good example. So a pizza place, they wanna deliver quality pizza. Right. I've said this before and I don't wanna besmirch any particular company, but there's a pizza company. Yeah, that makes pizzas that are sitting there under heat lamp ready for you anytime of the day or night. Yeah. If they're open, they got pepperoni pizza sitting there. Cause least common denominator. Yeah. This is, we're gonna least common denominator. Most everybody likes a pepperoni pizza. They probably got some cheese for the kids, whatever cheese pizzas for the kids. But they're selling a substandard product and you are accepting a substandard product because it's ready. Yeah. You can roll right in. Grab a pizza. Your kids want cheese pizza. Here it is. Problem solved. So least common denominator. I can make a couple of pizzas leave'em sitting there in their heat lamp. People know it's not gonna be great, but it's ready. So I'm trading speed for deliciousness. Right. I know it ain't gonna be great, but it's gonna be ready. Okay. What if I'm a pizza company and I'm like, you know what? I wanna deliver on that fast and ready. But I also want to have a superior product. So I'm a competitor to this company that is doing the ready. It's hot and ready. It's sitting there. It's it. You can come in and get it. I wanna compete with them. They're a massive national chain. I'm Brad, I'm gonna start a pizza company. Well, I decide that I'm gonna use AI and I don't have any historical sales data cuz I'm brand new. I just started a pizza shop. Sure. I'm gonna be in the slot next door to this guy. But what I'm gonna do is take in data, historical data really helps. Really, really helps. Cuz part of our wisdom at my age is the wisdom I've gained over decades, right? Mm-hmm. So if I got historical data, that's great, but then I can also take in, is it raining? Is there an event? All these other data sets that a human can't make sense of all this data and tie it all together. A UK game of Yes. Bowl game. Correct. Monday night Football or whatever. Right? Yeah. So some of that stuff is obviously gonna drive an increase in business, but there's other stuff that's not. Right. Right. But if I can take in all these data sources, then I can know what pizzas to make before they're ordered. You follow what I'm saying? Yeah. I know that based on this, when all of these, and the more factors you can consume, the more data points you can consume makes your outputs more accurate. And I know that I'm gonna sell at 6:00 PM on Thursday. I'm gonna sell three Supreme pizzas, not at 6:03. Pizza's got a pretty short lifespan. Yep. Right. It takes so long to cook 'em. Everybody's using the same pizza cooking ovens. They've optimized that 12 minutes, I think is the number. Yep. Right. To cook. You, you make a pizza. The guys making it are all pretty good at it. I don't care if you work for the guy that's making it. It's just sitting there ready or somewhere else. Making a pizza takes x number of minutes. Cooking a pizza takes x number of minutes. Delivering the pizza is optimized. Right? So I've optimized making the pizza cuz I've got guys that have been doing it and they're good at slapping tomato sauce and cheese on a thing. I've optimized the ovens, the manufacturers of the ovens are like, we can only move that pizza through this oven on a belt so fast and make it cook. Right? Right. So that's optimized. They've squeezed all the goodness outta that. You've squeezed all the efficiency you can outta the guy making it. Well what's the next step? I put it in a box and I put it in a car and somebody drives it to your house. Well, guess what? All those drivers are using Waze or Google Maps or Apple Map. They're using some mapping application that is smart enough to know if there's traffic construction, a wreck. Like it knows all that. Can you imagine when I was your age, I had a paper map. Yeah. When I was going somewhere, I used to deliver pizzas. I did too. Yeah. Remember it. And I had a map in the car. Yep. I would go up and I'm like, oh, this delivery's going to E four on this map. You even know what that is Anyway, so you could see the street and you're right. Yeah. Right. So like, and then I'd have to have my knowledge of how to navigate that town, the little college town where I was in school. Alright., so all that's optimized now, it's built into your phone. Yep. So you are avoiding, all the stuff construction right now, but now you're gonna, you're gonna know on, on, on Friday night at 6:00 PM this family always orders two pizzas. And the pizzas have these toppings. Yes. And you're gonna have those pizzas literally rolling off the line when the phone rings. A synthetic order will hit your order system. So your people doing all this process. They just know they gotta make a supreme or a pizza with anchovies or whatever. And it can be that esoteric, right? It can be that specific and you have to be able to do that with a degree of accuracy so that the person that owns the business isn't throwing away pizzas. Yeah. Because if I make a bunch of something and nobody orders it, that's a problem too. Yeah. But a project I worked on with a guy, he had just gotten off of a project for a grocer in India. If you ever looked at the scope and scale of India, it's massive country. Mm-hmm. Tons and tons and tons of people. Well this grocer had a high degree of waste. They were selling a lot of produce. Produce was part of what they sell. Mm-hmm. Anything that's perishable. Right. Meat produce all the perishable things. That is a science for those stores to know how much to stock, cuz you don't wanna stock. Too little cuz people are frustrated. They want tomatoes, you don't have 'em or they want steak and you don't have it. Or okay, you stock too little, it's a bad customer experience. You stock too much and you're losing money cuz you're throwing heads of lettuce out, you're throwing, right? So that grocer in India applied AI to better and more accurately stock their stores and they reduced their waste by 40%. Wow. Wow. Now what do you think that did to their, now that is one cost component of their overall business. There's real estate costs, there's staffing costs, there's all this other stuff. But if I can reduce my waste significantly, that's a big help. If I can more accurately predict my staffing levels, that's a big help. So these are all ways that this technology can be used. We talked about the semiconductor manufacturer. They're putting out a higher quality product and have less waste. That's good for their bottom line and their customer experience. So, I've got a marketing company that can more accurately market to Dave, Ryan, Brad. They're wasting less money on marketing. They're being more targeted. So their return on every dollar spent, their cost of acquisition for a customer goes down. Okay? So that's more efficient, and you know, custom medicine, you're gonna have a better medical outcome because your treatments are tailored to you, right? You got you. You go in and give blood and there's all these little markers that they look at, but how many did they really look at? Five. I don't know. Last time I had my blood drawn, there was a two or three pages where the stuff they measured, right? And like five were highlighted, right? So that tells me the doctor's looking at five of those cuz he's a human and he knows that these five should look about like this. But what if an AI model could look at that and go, you know what? You don't usually look at, I don't know what all these things are, but some little random thing on this chart that I'm already measuring and I'm measuring it for thousands or hundreds of thousands of people. And now I can see that if that thing changes by this much, that's gonna lead to this something hereto for not realized. I've got the ability to measure and collect all this data, but the power of the data is not unlocked yet. So applying these models allows you to do things like that that may take years for people to realize that smoking's not good for you. Yeah, right. Took years, people getting cancer and dying and stuff. But the idea being that if, if it's like, take the blood example. Yep. If you have a physician who says, oh, well it's all within the normal perimeters, right? Yep. It could be that three of those hundreds of different blood tests that they're doing, if three of those move a certain way at the same time, even though they're in normal levels. Okay. There's actually AI studies that show that yes, you could be headed down this path and so let's try to catch this before you even get over the abnormal. Yes. Become abnormal. Absolute. Absolutely. Over the normal. So I'm working with folks right now that are taking the de-identified data. Mm-hmm. Cuz patient confidentiality. They're taking de-identified data sets for radiology and pathology and they're running models against it to make all of that happen. To see these unforeseen things to make them seen instead of unforeseen. Like, what are things that the human eye can't see in a radiology scan. Mm-hmm. Right. A good friend of ours is a radiologist. How much of his day does he spend separating cats from dogs? Yeah. Oh, I need to look at that more. That goes here. I don't need to look at that. So the first part of his day is going, cat, dog, cat, dog, cat, dog, cat, dog, cat, dog. No value. His 20 years of experience isn't being applied to anybody's outcome. Cat, dog, cat, dog, cat, dog. Let a machine do that. And then all the cats that he needs to look at he can look at. And then if he starts seeing something, you take his body of knowledge and another good radiologist, and another good radiologist, and you train a model and now the cat dog work moves higher up the value chain makes it faster. So now somebody reading the scans that they took of you to see if you had cancer or is it moving? You know, all these things, I don't know. I'm not a radiologist, so I don't know all it's, but the undifferentiated heavy lifting gets done by a machine. Again, look at what a machine can do for you that is not bringing value to your business. Move yourself as a young guy that's in the business and move up, move up the value chain quicker. Yeah. Just like a business is gonna use this technology to become more competitive in their space, people are gonna either find a way to move value in the value, higher in the value chain, or they're gonna find something else to do. Yeah. So I think that's a great point. And to kind of sum up, I think the best point you made among a lot of good points you made was the cotton gin. Because every, the main question I get from young people my age is, do I need to worry about this? Is this gonna take my job? Yeah. And that's why I asked that question because we get that question a lot. And I think the point is technology is always gonna continue to evolve. Technology is always gonna get better. And as long as you can find ways to make yourself move up the value chain, as you said Yep. And help businesses in an efficient way then you'll be just fine. Absolutely. Well, on the other side being just that innovation and efficiency, right? Yeah. Always beats inflation. Yes. And in today's time where we're experiencing very high significant inflation in this country. Yep. And there's a lot of people being squeezed. The idea that you have this technology that is coming in that can go through every single sector. Yes. Everything of our day-to-day lives. Yep. And bring change, part of that can be for some companies it's gonna be more profits because they can run more scans or more. More, yes. Whatever it is, whatever it is. But for other areas it's gonna drive cost down. And in competitive business, when they can both lower their costs, they're gonna try to drop prices to outgain the competition. And that's how we lower inflation in some ways. So it's a really good point. So, well Brad, I really appreciate you having you on and yeah, thanks. I know it took a lot of time outta your busy schedule to come on. So we really appreciate having you and appreciate all of our listeners. Tune in to In My Day and we'll see you again next month. Take care.