Episode Transcript
[00:00:06] Speaker A: It's always exciting to be working on really cool emerging technology products. But what's really fascinating to be working on technology for the aging population or really for those of us who are in a sandwich generation one in three millennials and half of Gen Xers. Right. I squarely sit in a Gen X side is that, you know, it is one of those areas where technology use can be really exciting and really helpful. It's one of those areas where if we can incrementally do more and put our customers at the center of what we do, we could really change lives.
[00:00:57] Speaker B: You're listening to HR in America, a parent projects podcast production. Now here's your host, Tony Sears.
Look, I'm excited to have this conversation with you today. Shilin Simmons is joining us from logimark. They develop these super smart products. They think about things in a human centric way. She's going to help break a lot of that down for us. So start thinking in the back of what does that mean for you? How does that reflect in the products you're doing? Maybe you're thinking that what's that have to do with mom and Dad? I start thinking about what that means for us because as we start aging as well, we this is one trajectory we can actually make an impact again. So without any further ado, Charlene, I'm going to introduce you and bring you in. Thanks for joining us on this week's podcast. I'm sorry for murdering the whole first cold opening for you.
[00:01:45] Speaker A: Thank you for having me here, Tony. It's a pleasure to be on this podcast with you.
[00:01:50] Speaker B: Well, it is the authentic nature of this is an important part of getting into some of these conversations. And things don't always go perfect. You can plan a lot of the stuff and have it. But that is, I think one of the reasons you and I do what we do in using technology to kind of start bumping, to make things a little better, maybe to recover when things aren't going so well, your ability to go back and redo. But that said, it's got to understand how we function as human beings in the first place. That is something that you are uniquely really great at in a leadership standpoint for the companies.
I'm going to start with maybe a personal question at you.
This is a messy time of life. To develop products and make products for this is complex. It's difficulty. You have finicky consumers who are in the throes of chaos. What is it that gets you focused and fired up about helping people and products at this stage? Of life. What, what personal drive does that?
[00:02:54] Speaker A: Yeah, no, thanks for asking that question. It's definitely a personal one. You know, I think I spent most of my career in emerging or leading edge technology and so oftentimes working on things that probably wouldn't have your real mass adoption for potentially five, six, seven years. I mean, and I say this because I worked at Audible and I think I was doing a mobile based product in 2005 for Audible at a time when only 35% Americans had a smartphone. And so it's always exciting to be working on really cool emerging technology products. But what's really fascinating to be working on technology for the aging population or really for those of us who are in a sandwich generation, one in three millennials and half of Gen Xers. Right. I squarely sit in a Gen X side is that, you know, it is one of those areas where technology use can be really exciting and really helpful. You know, it's one of those areas where if we can incrementally do more and put our customers at the center of what we do, we could really change lives. And I think a lot of us went into tech because we want to help people versus just doing something cool. Although again, you know, that's the benefit, is that we get to do that too. Of course.
[00:04:13] Speaker B: Yeah. Well, and when you start looking at the age tech or longevity services marketplaces or those type of areas, there are full of people from mobile dog groomers to attorneys to technology companies that I find, I mean 98% of the people in it had some personal sad story that they want to see somebody else not repeat. Right. Or make some meaning out of that. So, so maybe some of the stuff and the technology challenges we've seen in these darker days of the last couple of years, right. We've like, maybe it shows American can learn. Like we could, we can learn. There's some lessons learned here. We can do better. And this is one place, boy, if we don't do better, we can probably make a lot of people to get victimized pretty quickly.
[00:05:00] Speaker A: Absolutely. And I think it's also interesting, right, because a lot of people go into businesses because it's personal to us and it's impactful. So we all have a story. In my, my case it was my mother in law. You know, my father in law had passed and she was visiting us and she was living in a two acre home by herself until she was able to get into community. And she was very kind. She wore one of these products. We did a lot of research and you know, As a tech person, it was very frustrating to feel like, boy, it all looks like a little garage opener. And so my very fashionable mother in law, who was a 40 year art teacher, she wears beautiful clothes, she's just graceful.
And so she had to wear this big honking thing because we wanted her to be safe. And she was very gracious to allow us to slap one of these items on her. Right. We were in the restaurant. She sits down too quickly. Their fall detection is horrible. And so she sits down too quickly and immediately the vice screams out, Mrs. Becker, are you okay? And like some kind of movie, everybody turns and like right, and this beautiful, graceful woman's like, yeah, I'm fine. You know, like. And she's trying to desperately to turn to off. And I remember filing in it back my mind like, boy, somebody's got to do something about this. And then we, you know, had our ramen and I sort of filed it away in the back of my mind. And so when the opportunity came, certainly, you know, that really colored about whether or not I feel like I could be that person to help transform how we look at this particular business. But ultimately there's a lot of us, you know, who listen to your podcast and you know, are a part of this community that say also, you know, is that enough just having that personal drive? And I think it's you couple that sort of personal relationship with the product to, you know what I think are larger, you know, economic reasons for wanting to do businesses like this. I mean, you know, by, by the time 20, 30 rolls around, you know, one in four Americans will be, you know, 65 and over.
[00:06:56] Speaker B: Right.
[00:06:56] Speaker A: I'm when basically, you know, there was actually less and less of us actually able to take care of them. And you know, even before COVID right. There was actually a crisis, I think in terms of like personal health care aids, that number.
And so who's going to be able to help take care of parents when there's a time where it's really asymmetrical in terms of people available to people who need help. And 90% of them, 50 plus and over all want to age at home. And so to me, that really kind of created a momentum for me to say, I think that there are some real opportunities for us to do better and to look ahead and see the macroeconomic trends favor the development of technology. But coupled with my personal experience as well, that those two things sort of, you know, marry, marry together makes a perfect time for me to sort of take over at this company.
[00:07:48] Speaker B: Yeah, the timing definitely is Great. I mean, we, we were early in the market in 2019 and trying to apply AI and everybody's like, I mean, it just wasn't, you know, it's not quite where we're going today. Now we're building with like reasoning engines and we're, I mean, you just, it is incredible what, what the learning curve has been. I still don't think we're what we. There's so much whitewash, you know, there's so much fake of what AI really is or really, I think, what's being used there. I think we have some solid, solid solutions in play for aggregating a lot of data very quickly, whether you're doing a homework assignment or, you know, you're trying to search the Internet a little better with a perplexity or something like, these are, these are cool tools and I really like that. But I, you know, one of the things that you said, that comment, I mean, the, the demographics. Yeah. We're, we're, we went from 48 million to 90 million people over 65. It's creating a insolvency position on the entitlements programs that we set out there for them. Like those social, they're not even social safety nets. Their standard way of practice, Medicare. Right. I mean, it's like the way of the land. And those things have a difficult time. So, you know, you have to come up with some solution.
I wonder. You and I had a brief talk on this when I was at the wedding last week. Last. Yeah, last weekend or so.
I wonder what your thoughts would be on the fact that the baby boomers in general that are getting older, they used to spend like 70% of the money, like out in the marketplace. Right. And we were very focused on baby boomers. I remember seeing those presentations and working that well. Now they've gone into asset preservation mode. They're not spending cash the same way they spent cash before. And the people spending cash are millennials and Gen Y and Gen Z and whatever the next gen is going to be that comes after that. Right. So, I mean, is that one reason that you see this, this hyper focus now that there's so much technology that's coming because it can iterate so quickly? Are we seeing this flood of devices that are really focused there? Is that creating a, a quiet zone, like a dangerous kind of quiet zone in age tech for, for seniors up there, because there's such, this flood down here of the people who spend money? Or do you think that this demographic might be big enough that we can attract others to Join us and, and build this technology up above as well. That's more human centric as you say.
[00:10:15] Speaker A: Yeah, I think that certainly like everything in the world, you know, we as a society tend to be very focused on the young. And so the spending for Gen Z, the, the millennials are there, but ironically we are a very large part of this demographic and I really in many ways see our customers not necessarily as the boomers that are aging, but really like folks like myself that are Gen Xers. And we're definitely still actively out there spending as well as the one in three millennials out there who are actually taking care of their elderly loved ones. And so, you know, I think that really the problem that we're solving for that, like we're really trying to solve their problem because we're in a marketplace and I see us as company. That is what I constantly tell people. I'm trying to put safety nets under people who want to fly and so, and they want to fly independently and I want them to do so, but with a little safety net behind them in case they need it. And that's really how we perceive our business for our end customers are the caretakers. Because there's very rarely does one believe as a boomer or those in an aging population that they have need of a device that because they feel weak. Right. So our target audience is generally a very large swath of people just like yours, which is caretaking.
[00:11:35] Speaker B: Yeah, yeah, those, you know, the what the blessing of that too is that that 45 to 65 year old working mom, right. Balancing homeschool work, kids, and now they've got a parent that needs help. That's generally the first that tends to step up. So when you want to learn, you know, we've, we've oriented there. We catch everybody else. Obviously I'm working a parent project, my brother in law is number one in that, that role.
But they are using AI more and more. They're using technology more and more. They're seeing, and maybe it's, it's not even just technology. I mean you have physical devices, right? You guys with the, with the guardian device and the other things that you guys work through. These are, these are a touch between kinetic and technology like digital. You've got to marry these things up, that is art and science.
Because then you have to introduce that, that customer's got to introduce to an end user of how to do that. I think maybe that. Yeah, talk about that like especially too when you're making a design, you essentially have to turn the buyer but they're not the ones that put it into play. You have to get them to be able to like field train almost your product like right out of the, right out of the box. Right.
[00:12:47] Speaker A: And then we tend to think too that our product is because we have a product portfolio that you know, we actually follow you along from a user journey perspective. Right. And so very rarely were an active 65 year old think that they're in need of a medical alerts products. And so we actually originally divide created our Astra product which looks like a tiny airtag. It literally looks almost like an airtag. Right. And we started, we started looking at the development of this product as a senior based product because the active seniors are like, hey, look, you know, I don't know what you're talking about in the medical, like medical, it's like I already have an iPhone, like I'm totally good. Right, right. And so we were like, well look, you know, when you're hiking and you're running, you know, these things are huge. Like you're not running around, you know, with this in your hand in case you fell. And so it's typically in your pocket. And so what you really want is something small that you could clip to your jacket or you know, clip to, you know, a lanyard or something like that. And so when you're running then you know, something happens. You could clip just basically really quickly, lo and behold, like this is, you know, a product that's really popular with 18 year olds going off to college for the first time. And so that's what I was saying. It's like we're kind or like giving safety nets to people on both sides of the market because there's need. But the most important thing was that we kept the customer in mind and said, look, you know, people go out for runs, people don't feel like they're quite at the level of a device yet. And so this is just part of their journey. And so when this is part of your journey, one device isn't going to make everything work for you. And so you're really trying to develop to their journey with you. And so we start with something like this and it fits with their needs. And then as they graduate into sort of being a little bit older and saying, you know, look, like man, my hand grips are not so good as I get older and this is so clunky and so I just want to be able to have a phone and why does it have to have this doodads and like pay and all this kind of Stuff. So why don't I just wear something small? Because wearing this around your neck is very, very heavy.
[00:14:46] Speaker B: Right.
[00:14:47] Speaker A: And so now suddenly you graduate to a freedom alert max and it's medical at 4. So the single most important thing is as you're aging is that you don't want to fall and you don't want to be the person who lies there for a day or God forbid, worse, and not be able to get help. And you want it to automatically understand you fell even if you're unconscious. Yeah, these things are important. And so, but you're in a different part of the life journey.
[00:15:11] Speaker B: Well, you're, you're, you're giving yourself to that opportunity of, of implementation of these technologies at like smaller level, ecosystem levels to also see how they all start coming together in suites of product. When I watch, sorry, I might have cut you off off of that. You got my brain firing on when, when I watched how many people lined up to pay like five or six thousand bucks for an Apple Vision Pro, I really started understanding. Well, this, I think the wearables thing is going to be something for us. We develop, we have a platform and it's a web based type platform. Today the runoff of that is to get into iOS and Android for those. But it's not for my team. It is, how does it, how do I integrate that into a wearable? Like I, I, you've got to start thinking where that technology as you said, you know that three to five years out from now. And I think you have to kind of, you have to bite this up. Nobody thinks that they're, they need to follow. I have not met even the ones that need it. I, I've not found somebody who told me, oh yeah, I needed something for a fall indicator. They were, because somebody who cared about them said, hey, this is going to help me respond to you quicker and help you.
[00:16:24] Speaker A: Yes. And nobody thinks they want a wearable. And so we, you know, to your point, you know, we try to think about, you know, you know, Wayne Gretzky always talks about this. I'm not, you know, I love hockey. So this idea of like, look, you know, you're skating, you're not skating to where the puck is, you're skating to where the puck is going to be that concept. And so for us a wearable is sort of where the history of these devices have been. But we still think about also, you know, what, what about passive and ambient, sort of like monitoring where you're going to be in a shower. 50% of falls happen in the Shower. So what do we need to do to help you get the help that you need? And so that may actually amount to a non wearable now we actually have devices where, you know, I've sunk that thing into like 5ft of water and like so. Because it's got to withstand falling into a toilet, in a shower, all of those in a bath. Yeah, but you know, we don't recommend that. But it will withstand that. But, but honestly what you want is to not wear something. And so we think about that as well because that's really where the future may trend towards as well.
[00:17:26] Speaker B: Yeah, well, and you're, you're figuring out the core tasks, what the technology and the packaging is. That, that's a. But that's probably the next conversation I want to get into. But. And how you start developing that. But yeah, those are splitting that out.
Let's talk about that. Let's talk about kind of the packaging of what this technology goes into. You've done a great job in identifying those things. You use the term age centric. Tell us about age centric. What does that mean to you?
[00:17:53] Speaker A: I'm sorry, I missed what you said.
[00:17:55] Speaker B: I'm sorry. Human centric. You talk, you use a term human centric in the development of. I use the term like form factor is what I'd use before. But I really like where this is going and I like where your brain goes. Here, will you unpack that for you? What, what does that mean? As you understand the technology function and what it's doing and where it goes or how that, that the art around the science there. What is that?
[00:18:18] Speaker A: So you know, I, I grew up from the, you know, the technology industry and so we're, you know, much like other people who are complete geeks about like engineering and tech and ip, you know, we want to develop the coolest single possible thing to think of. And then like then you need to figure out whether or not there's a business around it. And that's kind of the almost entirety of silic, right. Which is you develop cool tech and then you look for quote product market fit. And so what I realized fairly early on is because I'm not the engineer typically, I'm the, you know, I like to code, but they hate me.
So you know, I really am much more of a product.
And so my biggest feedback has always been, well, you know, look this, why are we doing it backwards? Really what we should be understanding as a larger like macroeconomic level of what people are in need of. And then we should develop product that's going to meet their needs now and where their needs are going to be three, five years from now. And so, you know, it's when you go in with that, like, sort of feeling into like, venture capital and any of the things in the technology industry, they look at you like, well, you're not a real engineer or anyone who's a tech person.
[00:19:29] Speaker B: Amen.
[00:19:30] Speaker A: Yeah. And I'm like, well, well, sure, fair enough. But like, I am a business person and we like to make money and basically serve people's needs. And so, you know, so that means that when we look at product development, we think about what do people need and what do people, like, have requirements for and then how do we make that technology fit them so that they're not trying to twist themselves around to utilizing that technology. Right. And so case in point of like, you know, for things like Freedom Alert Max, right? Like, we really thought about this and like, one of the things that people come up is like, you know, but I have to carry it. You know, I have to wear a medical device and I have to have a phone. I'm just like, well, why don't we just make those two things together? Well, easier said than done because when you put everything on a phone, it's huge. And then they're like, well, but you have to wear it on your body in order to make fall detection really work. And so that means, you know, we're looking at, well, how do we make things smaller, you know, fit people's need. But then you make things too small and people are like, wow, like, I can't see it very well. And so, like, my fingers, and I'm 52 and like, I don't think my finger fat, finger pushing things. And so you have to design things by saying, like, what is, you know, at this stage of my customer, you know, what is the optimal sort of scenario and what will carry them three to five years from now. And so we design things with that in mind and saying, you know, there might be features here that they don't need now, but we can actually surface up when those needs occur. And so one of those things, for example, we could talk about that we're going to be launching this year is medicine reminder. And we feel like we need that because ultimately when you get people to talk about, like, what is their biggest fear about people aging at home, you worry about them falling and then you worry, like, my mom and dad take meds, but like that med pill box, like, I don't know if they take it or not. And they always get confused about what they take and did they take it? I don't even know. And so, you know, I have to call them all the time and say, did you take your meds? And so we are looking at ways to sort of step into that. And we do that because, you know, we know that that's gonna, that's like the next, the second thing that they're trying to solve as a caretaker. Right. That first you gotta make sure they don't, you know, if they fall, you're gonna find them in time within the hour and then two is that, well, okay, you know, what are the other things to keep them healthy that I need to do? And so that's like the second thing or third thing that pops up. And so we're trying to think ahead and then put that customer, the caretaker in the center of what we do and the people that they're caring for so that, hey caretaker, like I'm.
This thing got triggered. So you know, is my mom. Okay. And so we put in a camera so you could only. But this camera is really interesting because if it only happens if there's an emergency. So if there's an emergency you could peep in.
[00:22:16] Speaker B: Yeah.
[00:22:17] Speaker A: Oh my gosh. The camera looks like it's on the floor and I'm not seeing anything but like the chair legs. So definitely there's a fall. Let me go. But the caretaker, the person being cared for, they're like, you know, the last thing I need is my 50 year old daughter like peeping in on like I'm doing something like that's so invasive. I'm not a kid. And so we could reassure them that they can only. This only works if there's an emergency trigger when you need it the most. So we're trying to put everybody at the center of the things and consider what everybody's needs are.
[00:22:47] Speaker B: Yeah. You know, to the. That is a place I see great opportunities in technology. Right. Image recognition to recognize, I mean maybe even to sensor to work through. Let's say the fall happens in a bathroom. Right. And that ability for it to pick up and recognize I'm in a bathroom. This is this type of a location. It's more sensitive than something else like change of angle or all those types. I mean that stuff didn't exist nine months ago. You know, for, for data models to be able to query that and to teach and to train against all of that. But that said, to know what to do with that requires this thought process like you're talking about. It requires designing products around the Real challenges that they're doing. We, we fight this in one of the common things, I'm just like you, the technology side. I get in there, I'll write code. If I really want to annoy them, I'll tell them I'm going to put an Easter egg in something and then they just freak out on me like, it's not an Easter egg, it's not an Easter egg. Right. Like I can't write one of those. But the, in, in good jest, the, the technology team, it's really easy for them to be like, well, this is, look, we're accountable. This is the timeline we're already pressed because you want it six days earlier than we ever felt we could do. Whatever that thing is going to be, if we want to add this into it, it's going to slide this and we give up this. And there's that pushback and that balance back and forth in a team. When you're developing technology, what you allude to is I think just spot on delivery today of a software product, particularly because of that cycle of innovation almost being six months. I think it's got to be around six months now of a new innovation, innovative technology releasing.
I need to just, simply as we were talking before, I just need to get this thing that is an abstract idea. I need to get it to where they can touch it, taste it, feel it, see it and put it in their hands. And then I need a development team that can join my obsession with the feedback, right. Of what they really did with that and where it went. We have preconceived notions because we research the heck out of this stuff. We've been doing this for a decade. We've been spending time breaking down the problem. So we generally have an idea where we probably know why they're doing what they are doing. But that said, it is something to go at it with the curiosity of a child, right? Why did you touch that? What did you want to have? What did you think was going to happen? What did happen?
And to continue to keep that in the culture of your company, especially on the technology and engineering side when we're stepping on them. And as you know, as a leader, I find I got to make sure to insulate for that. I have to provide time for them to process those things and do it, because it's not something they're trained to do. And the people they look up to in Silicon Valley, that's not the way they were trained to build products. They build the product and then go find pmf, right? Or that product market fit. They're not dangle out the MVP and build off of that in a six month timeline and you know, and work from something to there because that, that's a really, it's a different animal. Does that resonate with you? I mean, is that what you're seeing too?
[00:25:48] Speaker A: Yeah, absolutely. I mean I, I think I, I've had the very good fortune of having worked at a number of different types of companies and so at places like Google, you know we used to say we eat our own dog food. So you know, we develop a product and it's, you know, I think Gmail was under beta for the time that there was billions of people were, was on, you know, Gmail because if there's something, something to the extent of like failure within Gmail, it's annoying. But most of the time it's not sort of life critical. And so what's interesting is that I've sort of balanced that experience of like launching products quickly to also having been at portions of the company like this one or you know, even when I was at Harman we were a Venrock backed company. Aha. That got acquired by Harman. We were in a connect a car space. And so anything you have in a car is life critical. Right. So the regression to death, like if life is life is very challenging when you work with Porsche engineers because they're a very exacting group of engineers and they're German to boot. And so you know that balance of sort of the criticality of trying to get something to market quickly. But know that you know, you're in a business of actually trying to help people at a very you know, critical time of their life. You know, that's, that's the kind of like go to market and sort of product development we look at consistently. You know recently I believe human AI was sold to hp. And so one of the things that came up was, you know, I think the product caught on fire when they were charging it. And so you know, I had a discussion with my team, I said, you know, just remember like this isn't a startup where random 23 year olds wearing like some AI enabled like wearable device and if it catches is on fire, like, I mean God forbid a catch is on fire when you're on your body. But we're talking about an elderly person typically. So like you know, we don't want to go to speed in that market. We don't want to have like development cycles and analysis where that can ever happen. And so our customer is a Radically different one. And so we need to be much more focused on what it means to develop that and what our development cycles look like. So I think there's a very healthy balance, you're a leader at a company to say like, you know, what is, you know, how fast do I want to be in a market and how innovative do I want to be to the balance of like, you know, my end customer may not be as willing. And for us, for example, you know, we have a platform so Freedom Alert Max has features and you know, like fall detection geofencing for memory care patients, for example. So when Medicine Reminder comes around, we'll have Q data to death, focus group data to death, but we'll also roll it out in a three month trial probably. And so you could try before you buy. I'm like a big fan of that. Like, you know, I'm a believer that like if you do a good job, you know, with your product, then people will want to keep it because they see that there's a critical impact in how they're, you know, living because the product is, you know, serving some good for them.
[00:28:52] Speaker B: It gives you that opportunity too to find the non, you know, emergency type failures to lean into those things that aren't going to be life threatening and to engage and actually build with those with a level of curiosity and to sample stuff out.
[00:29:07] Speaker A: Yeah, and I think you and I talked about AI because you guys have a tremendous amount of data and you're gathering that data. And so for us, for example, most people look at us as a reactive technology company. And so what am I doing to use AI to get better and optimize the AI consistently via a, you know, to recognize a file better. And that to me is what we should be very good at, which is critically like fall detection as a reactive technology. What we're interested in ultimately is like how does data and knowing like whether or not you, you know, were MED compliant or not MED compliant, whether or not you walk 10,000 steps a day or not walk 10,000 steps a day, whether or not the shifts and patterns of where you sort of geo located to you because you were always going to the Yoga Studio at 10:00 on Tuesdays and suddenly you're not like those shifts in pattern help us think about, you know, how does that impact your potential health and your potential issues related to falls because those data pieces are relevant. It's not. And sometimes in some cases, like you know, a blood pressure monitor cuff. Right. Everybody has an app. Chick Fil A has an app, right? Which is super crazy to me. And so like everybody has their little pods of data sitting everywhere. And so it's really only when you get to the doctor or your care provider that you put those pieces together.
[00:30:28] Speaker B: Hopefully.
[00:30:32] Speaker A: You'Re able to gather all those pieces together. And in our case we're like, we want to know if you're meta here and you're walking 10 steps, 10,000 steps a day because those things and pattern shifts can indicate to us health related issues and things that may result in a fall. We like, we built a digital twin and then we try to compare it. That's when we get really excited about the future of technology and AI, when we can say, boy, wouldn't it be great for everybody for you know, caretakers, for those who are being cared for, for the insurance companies even, you know, they shouldn't be a piece of that, but they are a piece of that, right? To know that like you're being protected, you're hopefully being given notification that there's a pattern change that may result in a fall and then you can try to do something ahead of it. That's the thing that excites us from a technology point of view. And I think everybody talks about AI now like that's the kind of stuff I think about versus like ChatGPT.
[00:31:31] Speaker B: Agree, I agree. Well, and the GPT is probably going to play an increased role in you and I being able to pull, to pull out those situations, right? That in the military we've referred to this as pattern of life, right? That pattern of life information, the things that make TikTok dangerous, that pattern of life being sure that you know where that data is and how it is. I think another big piece of this when we develop is where the data sits. So I mean you allude to one of the ideas. Everybody's got these pockets of data and the idea is that it should be usable. And the person that should be able to use that is probably at first your primary care physician. That's probably the person you want to be empowered to advise you kinetically based on a digital footprint of pattern of life. The reality is that is a constraint of like what, six, six and a half minutes, like per, per person, Right. So how do you extend that? Where do you work in that? Can you draw ahead? Can you draw a tail to that meeting? Can we extend that meeting by a day on either side digitally and preparing them for that six minute conversation with a series of either educated things that are based on their particular situation or likelihood of situation based on this associated data? Or aggregated data. Out of this aggregated data. I'm interested to see we work on a concept for us. I call it data hot spring. That is a new way of thinking around the data lakes out there and how we can safely aggregate that and keep the ownership information. What we learned is we keep that at the family because they're the ones that have that best opportunity to see where they're going to put it into play. When we, in this model we've, we've walked our way into. It's like scattered like you said, it's scattered everywhere. Even things that are important like your healthcare directives might sit in an attorney's office. Right. Or you're like those things literally. And that plays a significant role in maybe your mentality of how you approach something or which person is going to make the decision and how they're going to make it based on their own pattern of life. So yeah I'm, I love where your head goes there and I think those are things that are, they blow the brains of most people that I talk through about that and I've been talking about it since 2019. Really on it when I saw the knot for a form factor and I was managing a wedding and this will be fun. You should have me back now.
[00:35:01] Speaker A: Yes.
[00:35:02] Speaker B: There we go. Thank you.
That's probably God telling me I'm monologue.
[00:35:09] Speaker A: No, I was like, oh, I'm like getting into like. I'm like wait a minute, what's happening?
[00:35:16] Speaker B: What happens when you're in studio for a day? You burn through these things. Here you go guys. I'll let you charge those.
Yeah. So, so anyhow that the, the pull down. I think the conversation I want to cut back off of what you said. There is this aggregated data. I love the thinking on the digital twin. I love the thinking on pulling those things together.
That is what we saw. Now if you can, if you can enable and keep that data as close to the point of origin of what you're measuring.
Man, I think it, I honestly think then that we just create smarter and healthier ways to be able to access that at the right time. In fact we're working on push systems. So our, the, the, the insurance agents came out and said hey could you this while it's helping a family manage mom and dad, we can throw the long term care policy. Well you're collecting the data in ADL's so teach the family what activities of daily living are because when they cross two of them, well they don't have to pay the bill. Anymore, we pay the bills. And as much as you would have thought, you kind of grin a bit. When we talk about insurance companies, the original thought was, well, our insurance companies, what are they going to think? And they stink and love it because the insurance companies recognize, wow, we're going to push down and enable people to help at a lower sophistication level. Acuity levels will be lower. We don't have to just throw everybody in a senior living community and pay 35,000 bucks a month or, you know, 18,000 bucks a month and taking care of them, they can age in place, which is where everybody wants to be. Right. It's where the demand is. Exactly. So it's interesting though how all those things relate. It's to push the data. It's. Is it available at the right time? Do you know, does one family to use your product? Does it really matter to them that when it sends the report off, they want to, you know, take a p. They want to redact one particular thing. It's a very private thing for them that they don't want going over. And can we create that?
[00:37:18] Speaker A: Yeah. And I think that, you know, how do you. For us, you know, the question is always the reason why there's like, you know, everybody has pods of their own data, which is, you know, especially in the healthcare side, it's HIPAA compliance. So you don't really want to share that data. So what we're really looking at is, you know, we actually, in the three and a half years that we've been here, we found more than 20 plus like patents in all types of areas, including things like tokenization and like privacy and you know, I mean, game theory, like enable sort of technology and no knowledge proofs.
[00:37:53] Speaker B: Yeah, yeah.
[00:37:54] Speaker A: Really the reason why you need to build all of these things is because how do you share data in a way that's critical and then how do you push that data to the people at the right time that they need it? And how do you respect people? You know, my interest is not to be in a blood pressure monitor business. And so in many ways I don't need to know that your blood pressure is 165. What I do know is your norm is 122 and then you've been 165 for like, you know, three weeks and you haven't been meta parent because those combination of things, you know, is relevant. Right. And so, you know, you talked about keeping it close. And so in our case, because we're in a business of both hardware and software, so how do you keep that data tied to the people who are they're most relevant to which is the patient and their loved ones and keep it in a sort of notes of origin. And then so that in a sort of collective sort of platform experience. I don't, you know, I don't sort of leak data out that's not relevant. I deliver data to an emt. Because when you're down, like I'll be candid, like I don't remember, you know, when my mother in law was sick, like what meds she was on. I think she was on Coumadin. Like that's really important thing to know. That's one of the first things they ask you. But so when is the right time to share that level of data? And then I can bet you that my husband wouldn't have remembered that either. And so how do you feed that data to the caretaker? Because that you're the first person they're going to ask too. And so how do you make that a relevant sort of situation? And so we tie all of our patents around all of these things because we know that not only is it critical for companies and people to have that data and have that sort of held closely to them, but you need to be able to help them figure out how to get that data to the right hand so that it can actually be enacted upon for success.
[00:39:44] Speaker B: Right. At the right time too. At the right time. Which is a whole nother aspect of that. I mean it makes a difference if you empower them and push that data to them as they're walking into the hospital honestly under a geofence than it does if you give it to them when they're leaving the house. Like that is those we so we did this when we were developing technologies when I was with, with rural Metro amr, American Medical Response and we wanted to increase the throughput of that information and speed up getting information from the time an EMT worked on you on the street and push you to the hospital. But because the data packets the original problem when you go to start tackling that the data sat with between individuals and organizations from that that are fighting it out and EPIC and I have no interest in being involved in that fight of life. Right. But between that they're in their hipaa and the SOC2 compliance and all those things, I remember somebody saying well if man, I mean you need them to have it so that they can just give it to you. Like that's not, that's not the problem. And that whole problem goes away. They just need to know, hey, you have this information on you, it's readily accessible to you. Now is the time to share it at this point in time. And then we figured all that tech out. I mean we've got near field, we've got all kinds of stuff that could put, we can do it with a business card and a tap. So we know we've got some level of stuff that would allow us to an exchange. And even, you know, if you've used any of that technology, you get to, you got to edit it, right. You get to go through and say, oh no, I'm going to send them this. But I don't want them to have this information that's you're moving in the direction. I mean these are the directions. I've been trying to nudge everybody for, for a decade now as far as how they're working it. And I love, I think secret to that really is going to be that data packet sitting there. To the degree that people try to work on pattern of life information in their own data lakes, I think you're going to run into a lot of challenges. Yeah, I know, I think, I think the, I look at the New York Times lawsuits that are going through right now as far as what AI can and can't grab and where that sits, there'll be an impact of some of that stuff that's more intellectual property. But I think that that has cascades of stuff even in like real estate in the way that people were passing off the whole real estate industry that does the accreditation mls, it does the accreditation for agents got spanked by the Supreme Court and how, who was representing who, who was sharing whose information and what wasn't being shared and what was those transparency? These are the, these are the connective tissue that I see that is leading to a heck of a reckoning with those data models.
[00:42:23] Speaker A: Yeah. And I think that this is sort of where, you know, I've been asked in the past like, what makes you think critically because everybody can say that they're AI company. What makes you think that a company is AI versus not an AI? And so because I invest in companies as an angel investor myself and one of the things I always tell people is that, you know, look, I, you know, this copyright argument is I think a super relevant one because we are talking about the violation of people's, you know, data and all of that. And I think what's really interesting here is that for a person's whole health, right. You know, that ownership of that data from, you know, even from a conceptual copyright Perspective is that you own that data. So your blood pressure data is yours, you know, your blood glucose data is yours, your steps and all of those things are yours, even though, you know, the companies think that they own it. And so for me, like one of the things that really kind of came stuck to, to us is that, you know, AI companies, like if you're really looking at AI companies, you're looking at how much pods of data can they have and how consistent is the volume of data they're generating. That's net new. Because part of the problem with any AI company is that you're going to be in a situation where you run out of data because there's a fixed amount of data that's actually being able to pull from.
[00:43:38] Speaker B: Sure.
[00:43:38] Speaker A: So that means that if you're an AI company, you're hoping for, and in our case like we're getting constant supplies because you're constantly moving, you're constantly living your life. And so your life is basically, basically our data pod. Right, it's your data pod.
We have a non stop sort of like capability to help you manage your data pod with us. And so that AI is constantly learning and so they should be learning with you. And so good AI companies is that they're learning with you because that data is fresh all the time and you're sort of learning, but also you're managing the control of when you run out of data and whether or not the AI company starts to hallucinate. So make recommendations.
[00:44:18] Speaker B: Exactly. Or over train. Yeah.
[00:44:20] Speaker A: Like it's possible because AI has the capability to think outside of the box, but now it's thinking my grandmother is like hidden dragons, like you know, crouching tigers. Hidden dragons, Right. Like, no way. So we like think about things like this because like, for example, we have like a personal physics engine because we need to teach our AI. Like, hey, you know, we need you to model that. What's the probabilities of a fall here and a potential sort of scenario. But that scenario you painted is impossible because there's a physics engine that says like you live in a one bedroom apartment and she's 65, gone to yoga, but for the love of God, like that is, that's, that's gonna roll, tumble down.
[00:45:01] Speaker B: Yeah.
[00:45:03] Speaker A: You know, because she's in a one story building. Right. Like all of these things have to be grounded. And so when I think about all the excitements of AI, like those are the things I think really critically about, which is it's important to have that data. It's important to know that you own that data. And then it's important to know that you can ensure that the AI doesn't, that the hallucination is kept at as much of a minimal as possible.
I think any of us who are in the aging technology population or any sort of apply AI or personalized care scenario can get grounded because otherwise the AI can. You know, I think the fear of people is that it's going to create scenarios like a picture with like a person with six fingers, like.
[00:45:46] Speaker B: Yeah, yeah, right, right. And it's going to do that in your health care when it's making a recommendation on what medication you're going to take. Like I don't need the six things.
[00:45:55] Speaker A: Exactly.
[00:45:56] Speaker B: Right. That is. Well, you know, one of the things that, that when I look at the teams that are starting to build and get in and not diligently think about this, you think of how you buy data or how you acquire data when you were training something. So those big technology companies that come on, what is one of the first things they do? After you acquire a bunch of data, you have to go clean it. You have to work through that and you have to clean it and you have to condense and work from that. Who better to clean that data than the person who the pattern of life data is working on off of, like their ability? That's another reason to push that as far down as you can. It's like, it's like problem solving at the lowest efficient level, the most effective, lowest effective level. It's good in leadership, it's, it's good in data collection. I think from this standpoint and in addition to that, you start relieving yourself. Now you look at it, managing a business man, that is a great avenue, I think, for good cost containment strategy. When you're looking at something from that standpoint of the cost of holding data and working from all of that, do I want to do that and then pay someone to scrub and work from that or do I want to clean that as close to source as possible before it's coming in? You get back and make the use of the clusters for solar with them. We started building solar power plants and we want to push into the grid. And that was how we were going to get through one of our issues. One of the challenges that we had was you have to bar load, you have to meet this like a grid that I. And you know, I didn't know before I came in because I wasn't an engineer that way. Every time a light goes on, every time it comes out someplace, somewhere More energy is flowing in, there's this constant movement and the data that it takes that really looks at, that doesn't look at point data, it looks at associative data. Like I have this point and I have all of these characteristics around that piece of data. Right. Instead of the old models we learned in college. I'm really dating myself in classes right. Where you defrag and you'd move everything back down and condense.
Now doing that role, taking that out of the company and trying to push that as close as possible. Is it laborious in the front end? Yeah, it might be. It might be a problem with the market accepting like a barrier of use. Right. Too difficult to use. But man those company, if you can figure out that way that they are for us, what we think it is is hey, this is the information you collected. This should go to this person. If you send this right now to this insurance, to your insurance broker, this is a likelihood, a percentage based off of what we know that it is going to activate your long term care policy insurance, which means money's going to start flowing off of all this. Can you delete it? Yep, I redact that. That's gone from 96% down to about 83% potential approval. This gives people a way to start training them and what they're doing, they actually have ownership and accountability and responsibility for their information. I don't know that I see a lot of that out there today and we're reckless with it. We, you know, sure, I want cheap car insurance. What you want a permission to build a dossier from anywhere on all of my data? Okay, sure, just give me that product.
[00:49:09] Speaker A: Yeah. You know, of a click through. Right, right.
You know, generationally speaking, for example, the Gen Z I have a 16 year old and so they are comfortable living and checking off boxes and. But they're also candidly a lot more careful now or at least some of them are about how out loud they're living and you know, their real accounts versus the, you know, shared accounts versus the public accounts. And so in many ways they're adapting to sort of where the new sort of set of, you know, life is. And so I always kind of laugh a little bit to your point where people talk about in the frontier of AI and I always tell them like look, you know, AI is, you know, and people will say this all day long in the industry, but the everyday consumer don't think about this, which is AI is only as good as the data that you're actually giving it. Right. This is why some People are better at Google searches than others because some of us were taught how to do Boolean searches, right? So we're all like, plus, this is this, like, within quotes. And like, all because we're old school learning kind of, like, stuff. And in many ways, like, this is kind of the AI world that we're living in. So data is only as good as how you're able to identify that stuff. Because even when the AI, like, for example, we people fall and we, you know, want to be able to identify this as a fall. So we may take a look at a photo and say, this is definitely a fall, but somebody's got to validate that data. Computer might say, like, this is a fall. And we're like, no, that's literally a person sitting in a, like a little, you know, chair poof. Right?
[00:50:41] Speaker B: Yeah, yeah.
[00:50:42] Speaker A: Doesn't mean that's a fall, right? So it requires some level of human intervention. And in some cases, some technologies are much, much better with more human intervention than not, especially when you're looking at things that are much more subjective, you know, in terms of what you need to deliver. And so this is what makes sort of the future of AI sort of interesting, because in many ways, like our, again, human centric sort of side of this is that I will really blossom if we're able to inject into it as much as we think we can help it be, help it grow into the type of product that we want. Versus, you can have an AI, but it's somewhat junk because all of the tagging is randomly done. And then by the time you have a deep AI come in, it's like, been tagged by six different computers. And so not one single human person has touched that thing. And now it's decided that, you know, what is it? Somebody said, like, you can keep your cheese on your pizza if you put glue on it. While technically speaking, glue puts things together. So technically, ChatGPT wasn't wrong.
Just like, you know, glue, right?
But it's somehow taking multiple sets of data, but without some level of validation. And so that to me, again, we go, I go back to our physics, personal physics engine, which is like, you got to do some level of truing up. And in your case, you talked about, like, you need to basically have people sort and catalog that data. In our case, we do the same, right? We have some level of that sort of work. And so that is like the caretakers, that is the care, the patients themselves, and any number of those things as well.
[00:52:22] Speaker B: Well, I think I really like the idea of Those teams that are doing that and working in house, it's a good connection point between them and the end user and maybe a really appropriate one for technology for them to sync out in some way, shape or form there for them to just. My kids use the term touch grass. Right. To get out there and to touch grass and ground them. I think on the other side it can teach the next generation of why they're doing what they're doing. Like what's happening. What one of our. I remember my dad struggling with certain technology, my grandfather just getting it and with computers, because my grandfather had worked in the original punch systems like he, he built whole rooms. Right. And so he essentially stood inside my computer and that was, that was his life. And boom. In the slats. He understood what was going on and that purpose. And I, and I hear you talking about that, I hear that oozing out of what you're saying in that purpose. And if I can something I think I definitely want to keep pursuing for our own teams too. How do I pull those together?
How do I get my team that does have to work from that and touch that. It's a great integration point. Find the appropriate way to do it.
[00:53:31] Speaker A: Or most importantly, how do we create a technology platform or technology that allows the end users themselves to touch that data, make relevancy to that data. Because we talked about at the beginning of our discussion here, you know, we are very keen on sort of our place within sort of the aging or longevity business about hyper personalized care. It's only personalized and hyper personalized if you touch it, that you not somebody at my company.
And so the more you touch your data, the more you understand your data and those of your loved ones, the more you're able to sort of shape that technology and that care to really be focused on your parents or your elderly aunt or whoever that you're caring for. And so how do we democratize that sort of experience and so that it's easy for our customers who may not have tech experience like your grandfather. Right. To basically make that connection together and make it easier for them.
[00:54:31] Speaker B: Yeah, I couldn't pay you to say that. That would have been. I mean, that's exactly. That's. Look, that's. That's the call, one of the calls of what parent projects is doing there. And families are realizing it. They're not doing it for the purpose of, for them. I'm meeting them where they're at. They're doing it from the chaos needs to get to a level of calm. They have Got to get some organization from that. But one of the reasons they get along and go along is they can become a, a better version of themselves. There's a, there's a pull for that. You have to meet that on the other side. They can genuinely help themselves and help other people have less sad stories, which circles right back to around to where we had started. Right. A lot of us get into that and that is compelling not only for those of us developing technology, but for our clients and our families and our patrons that are down there using it. They have sad stories too, and they don't want them and they want to make meaning of that thing. That's tough. When they understand how something and why they're doing when they understand why they're doing something. Something they can deal with a heck of a lot of how I think is one of the best sayings in that. Right. So. Well, boy, Sheldon, that was fantastic conversation. I could sit down and do an absolute another hour. An hour flew by. Absolutely flew by for us.
Anything you want to throw up or anything to kind of get through as we start kind of wrapping up at least this session, I, I imagine you and I are going to do multiples of these. I could see us sitting down and really breaking some of this stuff, stuff down into the audiences, both the business and the families.
[00:56:01] Speaker A: Yeah, no, I mean, you know, it's such a great opportunity to chat with you, Tony, so thank you. You know, much like you guys, you know, we're in the business of actually hope, hopeful, being hopeful that we don't hear another sad story. Because when you're in our line of business, we hear a lot of sad stories. And so, you know, our job has always been, and as is yours, to basically hopefully have a good outcome story versus the sad story. And so, you know, I would sort of urge everybody that even if you don't think your parents ready for, you know, are ready for medical alert device or personal safety product for 18 year old going off to college, like, please do that research ahead of time. It's better safe to be. Better to be safe than sorry. It doesn't hurt anybody to carry something. But what'll hurt is we don't have something and you need it the most. When we plan for aging parents, it's not like when you were pregnant, you had eight months, you know, nine months to plan for somebody coming. Right. When things happen with your aging parents, it happens fairly quickly and there's not enough time to plan. So that's why, you know, you do what you do and work in what our business is which is, you know hope. We hope that we are the technology and products. Right. That actually help people prepare for the.
The the sort of, you know life.
[00:57:21] Speaker B: When life throws at them. Yeah.
[00:57:24] Speaker A: Times Right. So that you can't plan for so.
[00:57:27] Speaker B: And you are doing just the way you guys are developing. Like congratulations. Like it can't always be easy. Seriously, to you and your entire team it is. It is meaningful. I hear it from families and the demand of understanding where these companies why they're doing what they're doing particularly for wearables or the connectedness the IoT the Internet of things that kind of come around with helping to make the project work through And I see you guys are doing the right things for all the right reasons. I just got continues to bless you guys and what you guys are doing in your works and thank you so much for blessing us and our audience today with sitting down, having a call.
[00:58:05] Speaker A: Well, thank you so much for inviting us, Tony, and it's been such a pleasure to chat with you.
[00:58:09] Speaker B: So Tim here. Take care and we'll talk to you soon.
[00:58:12] Speaker A: Take care.
[00:58:18] Speaker B: Well, that's it for the team this week and thanks for joining us. If you've enjoyed the content, remember to subscribe and share this episode on the app that you're using right now. Your reviews and your comments, they really help us expand our reach as well as our perspectives. So if you have time, also drop us a note, let us know how we're doing. For tips and tools to clarify your parent project, simplify communication with your stakeholders and verify the professionals that you choose, you can find us on YouTube, follow us on Instagram and Facebook. Thanks again for trusting us. Until our next episode, Behold and be held.
Thank you for listening to this Parent Projects podcast production.
To access our show notes, resources or forums, join us on your favorite social media platform or go to parentprojects.com this show is for informational and educational purposes only.
[00:59:07] Speaker A: Before making any decisions, consult a professional.
[00:59:10] Speaker B: Credentialed in your local area.
This show is copyrighted by Family Media and Technology Group, Incorporated and Parent Projects, llc.
Written permissions must be granted before syndication or rebroadcast.
