Transcrição completa de From the Frontlines to the Forefront: Revolutionizing Public Safety with Technology w/ TJ Kennedy

numbers that you're rattling off both are impressive from a business standpoint, but then at the same time, like you're really talking about saving people's lives here and like the impact that you can have on the time that it takes to, for somebody to receive service. 00:04:39.093 --> 00:04:45.704 But additionally I could imagine that you have some great stories about the people that have been impacted by these systems you've been a 00:04:45.803 --> 00:04:59.204 Yeah, one of the cool things about it is, as a first responder, you get to respond typically to one person or a few people that need help, and you might save their life, you might not, but you're always going to have, I think, a positive impact on the outcome for that person's life. 00:04:59.223 --> 00:05:04.163 And to me, that was one of the most rewarding things I've ever done in my life, is being a part of a team. 00:05:04.538 --> 00:05:10.999 And that's the cool part about being a lifelike paramedic or being a firefighter and a paramedic is you work on a team. 00:05:11.009 --> 00:05:14.718 You're always there with a team to help make somebody's worst day better. 00:05:15.298 --> 00:05:16.548 And that's incredible. 00:05:16.689 --> 00:05:29.738 And the only thing I think that's better than that is if you could help, thousands or tens of thousands or hundreds of thousands of first responders, make and just save more lives and be empowered to do their job in a more effective and efficient way. 00:05:29.788 --> 00:05:34.668 And that's what I get to do now is, we get to help even millions of first responders make a difference. 00:05:34.689 --> 00:05:37.228 And just super proud of the ability to try to. 00:05:37.613 --> 00:05:39.014 Get them the tools that they need. 00:05:39.014 --> 00:05:44.853 I think one of the things I saw most as a first responder is we're really good at getting by with good enough. 00:05:45.184 --> 00:05:47.423 But that often means you don't get the best technology. 00:05:47.423 --> 00:05:51.084 We were always, 10 years, 15 years behind the latest technology. 00:05:51.084 --> 00:05:52.264 And I didn't think that was right. 00:05:52.324 --> 00:05:59.454 I didn't think it was fair that first responders were using, 90 year old radio technology rather than something a bit more modern than that. 00:06:00.204 --> 00:06:01.303 It was always amazing. 00:06:01.303 --> 00:06:18.803 I was working in the vending industry and we briefly talked pre show about like proliferation of like cell phone connections with your project with AT& T, but at the same time, like we were always like a generation or two ahead of what the first responders were using. 00:06:18.805 --> 00:06:23.553 And always found that fascinating, given that literally we were giving out candy bars, right? 00:06:23.593 --> 00:06:25.163 Like candy bar and Coke products. 00:06:25.194 --> 00:06:28.194 And at the same time, first responders were the ones that were. 00:06:28.639 --> 00:06:31.408 We're keeping the older networks in play. 00:06:32.079 --> 00:06:35.869 So I love that you're working to bring better technology into that. 00:06:35.869 --> 00:06:36.288 space. 00:06:36.619 --> 00:06:39.869 What are you most excited about being implemented today? 00:06:40.788 --> 00:06:45.338 I think the future of AI is really going to change public safety for the better as well. 00:06:45.658 --> 00:06:48.689 If you think about it, now that first responders in the U. 00:06:48.689 --> 00:06:48.908 S. 00:06:48.908 --> 00:06:57.478 and other countries are now trying to catch up as well, they have access to 5G and robust, ubiquitous 5G that covers more of the country than any other network. 00:06:58.103 --> 00:07:07.684 Right now, the First Responder Network Authority, with the FirstNet Network, based on the background of AT& T, has the broadest coverage by hundreds of thousands of square miles more than anybody else in the U. 00:07:07.684 --> 00:07:11.153 S., and they have priority preemption encryption all the time. 00:07:11.213 --> 00:07:18.843 Built in, there's no in the old days, we used to have to do a number like star 272 to be able to get access to priority, basic priority services. 00:07:18.843 --> 00:07:20.504 And some networks still do that today. 00:07:20.504 --> 00:07:21.084 It's crazy. 00:07:21.084 --> 00:07:21.903 It's very archaic. 00:07:22.293 --> 00:07:26.244 And instead with FirstNet, it's like you have a device and you just look in the upper left hand corner. 00:07:26.244 --> 00:07:29.963 It says FirstNet and magically you always have priority and preemption. 00:07:29.963 --> 00:07:52.088 And what that means is If you're running applications on your devices, and not just phones, it could be in vehicle computing, it could be tablets, it could be all sorts of IOT devices that firefighters might wear or fire equipment and apparatus, or police and EMS as well you always have this HOV lane in the sky on the network, where you're actually on a network that feels like it's completely on throttle. 00:07:52.444 --> 00:07:55.494 You, you have unlimited bandwidth for what you're trying to do. 00:07:55.934 --> 00:08:06.204 And that means that we can do the really cool things not just, edge computing, which is important, and I think a big part of the future, but also you can run massive applications that really use a lot of data. 00:08:06.564 --> 00:08:10.223 And during an emergency, you might have 100 or 200 responders in a small area. 00:08:10.663 --> 00:08:16.754 My local police department here had an officer involved shooting last night after a road rage incident on the local highway. 00:08:17.223 --> 00:08:23.173 And you end up with 20 or 30 officers in a very small area in a town that's not a massive metropolitan area. 00:08:23.504 --> 00:08:26.564 And that's going to overload the network in a typical sense. 00:08:26.584 --> 00:08:31.144 But in a FirstNet sense, it acts like it's completely empty because of priority and preemption. 00:08:31.454 --> 00:08:34.214

They're able to keep the commercial traffic out of the way. 00:08:34.408 --> 00:08:36.879 So that all the communication needs of that local agency. 00:08:36.879 --> 00:08:45.629 So if you're flying drones and helicopters with live video downlink, and you have many different command and control applications running, all of that is available to you. 00:08:45.629 --> 00:08:49.869 And so instead of being 10 years behind technology, we can actually be first. 00:08:50.328 --> 00:09:04.428 And so if we look at that, I'm super excited about the situational awareness capabilities brought by drones, by drone swarms, by, All sorts of new modern video technology and things that just would not have been even imaginable before a FirstNet network existed. 00:09:04.428 --> 00:09:04.839 I 00:09:05.589 --> 00:09:06.158 It's incredible. 00:09:06.158 --> 00:09:18.688 We were talking about the existence of 4G as being one of the things that proliferated like Instagram, TikTok, and that network as being necessity for those devices and applications to go. 00:09:18.688 --> 00:09:19.979 And it's amazing to hear. 00:09:20.469 --> 00:09:30.729 How, stuff that we don't hear in the commercial space, but that this first net system will actually enable, more effective responses from our public services. 00:09:31.048 --> 00:09:31.938 That's amazing. 00:09:32.438 --> 00:09:39.208 Is another use case of AI that you see as being like impactful for that firefighter, for that police force 00:09:40.269 --> 00:09:40.818 mean, I'll give you 00:09:41.428 --> 00:09:41.729 Yeah. 00:09:42.259 --> 00:09:43.808 two examples that I think are unique. 00:09:43.808 --> 00:09:47.009 One in the drone space is having the ability to have swarm. 00:09:47.058 --> 00:09:50.609 Multiple drones being flown by one firefighter, one police officer. 00:09:50.879 --> 00:09:57.619 Today that's a very costly, expensive thing if you have to have one person trained fully to be able to fly one drone. 00:09:57.619 --> 00:10:00.469 But what if you could fly 100 drones with one individual? 00:10:00.869 --> 00:10:03.918 The second thing is, I think flying drones by voice. 00:10:04.139 --> 00:10:08.298 So one of the things that large language models gives you the ability to do is you get to speak. 00:10:08.634 --> 00:10:20.374 And have that translated into commands that then is digested by that drone or that drone swarm, where it could be like, Hey, look over these rooftops in downtown for a shooter with a rifle, because that's the call that we just received. 00:10:20.714 --> 00:10:41.984 And rather than flying, manually to go look at that, Those drones can go find that shooter with a rifle on a rooftop because of object recognition and knowing the geography and because of GIS you have the ability to geo fence that area for where it needs to be and in 30 seconds you might find that shooter something that would have taken 10 minutes, 20 minutes before and could have a catastrophic outcome. 00:10:41.984 --> 00:10:42.813

So that's one to do. 00:10:42.974 --> 00:10:44.254 Really unique example. 00:10:44.254 --> 00:10:45.714 Same thing for school shooting. 00:10:45.714 --> 00:10:49.234 Let's say where typically 70 percent of the shooters are outside the school. 00:10:49.634 --> 00:10:53.504 And if you respond with police officers, you're just as much ground as you can cover. 00:10:53.514 --> 00:10:57.933 But what if you could send 10 drones that go find the shooter very quickly. 00:10:58.403 --> 00:11:02.374 In a less severe kind of sense, think of there is currently some AI being developed. 00:11:02.394 --> 00:11:07.734 For officers to be able to find information more quickly for a police officer, just on regular duty. 00:11:07.764 --> 00:11:25.553 And so think of a Siri for police where they can look up traffic codes, they could look up policies and procedures on how to deal with a particular incident or officer involved shooting, like I talked about earlier, and having that just on the lapel and a microphone and a speaker of an officer where they could be like, Hey, look this up, go find this. 00:11:25.553 --> 00:11:26.994 What's our policy and procedure? 00:11:27.408 --> 00:11:31.828 Help me find the nearest homeless shelter because I need to drop somebody off that we're giving a ride to. 00:11:32.249 --> 00:11:39.129 Things that today would require somebody to Google it or look it up and takes time and, one of the things is officers, are driving a lot. 00:11:39.139 --> 00:11:47.889 It's pretty hard to use some of this technology if you're driving without kind of that voice and AI, large language models built in that can help you find things and track them down. 00:11:48.448 --> 00:11:49.479 So that's another one. 00:11:49.479 --> 00:11:52.208 A third one is, think of automatic license plate readers. 00:11:52.208 --> 00:11:55.614 If you've ever seen a patrol car, With these little cameras on the back. 00:11:55.644 --> 00:11:57.864 What they're looking at is they're mostly reading license plates. 00:11:58.589 --> 00:12:02.349 And it's often finding cars that are stolen or people that are wanted. 00:12:02.678 --> 00:12:07.129 But, what about using that data to find a missing child or to find a missing person? 00:12:07.139 --> 00:12:13.808 We have, silver alerts, which is when sometimes you have Alzheimer's patients that walk away from their home or walk away from a nursing home. 00:12:14.183 --> 00:12:18.813 What if we could use the cameras that are already up in the town to be able to locate that person more quickly? 00:12:19.014 --> 00:12:22.943 These are things that I think AI is going to have a big impact on public safety. 00:12:23.693 --> 00:12:29.933 I think that's fantastic to hear that we can have so much of an influence on really just the safety. 00:12:29.933 --> 00:12:31.744 and the help that we can give to people. 00:12:32.494 --> 00:12:46.139 What kind of controls do you see necessary For, essentially protecting the private citizens rights or any privacy as well as just basically like we're looking at this is the nuclear energy of it. 00:12:46.668 --> 00:12:47.899 your take on the nuclear bomb? 00:12:48.019 --> 00:12:51.599 Yeah, I think we have an obligation to have ethics and advisory boards. 00:12:51.599 --> 00:12:54.239 I think we have an obligation to have police oversight boards. 00:12:54.328 --> 00:12:57.619 I think that it's a, it's upon us regardless of AI. 00:12:57.629 --> 00:12:59.229 I think AI is a piece of that. 00:12:59.229 --> 00:13:01.078 I think there's broader elements. 00:13:01.109 --> 00:13:03.649 I also think we need to start with the easier stuff. 00:13:03.649 --> 00:13:04.668 And I'll give you an example. 00:13:04.668 --> 00:13:16.068 I was speaking with a police chief in New Jersey recently, and he has a drone program today, a traditional drone program where they went out and just bought two drones and they fly them with one police officer each, typical kind of startup program. 00:13:16.989 --> 00:13:27.308 And I said to him, what, if you had the ability to have AI and to be able to fly multiple drones at once, and to be able to do it from a police operations center rather than the field and fly beyond visual line of sight. 00:13:27.609 --> 00:13:28.879 What would you want to do with it? 00:13:28.918 --> 00:13:30.958 And what about privacy and other things? 00:13:30.958 --> 00:13:32.489 And he had the right answer. 00:13:32.558 --> 00:13:37.339 And the right answer was, the number one issue for police chiefs today is recruitment and retention. 00:13:37.538 --> 00:13:39.129 We don't have enough police officers. 00:13:39.129 --> 00:13:41.938 We don't have enough to backfill the officers that are retiring. 00:13:42.219 --> 00:13:45.359 The last couple years have been very difficult on law enforcement recruiting. 00:13:45.428 --> 00:13:54.219 And I need them to do the mundane, boring things that police officers end up spending a lot of time on. 00:13:54.229 --> 00:14:01.298 So one of the examples he gave was every morning he has to send physical police officers to every school crossing guard location in his jurisdiction. 00:14:01.673 --> 00:14:06.364 Because school crossing guards sometimes just don't show up, and that creates a hazard and a problem for kids. 00:14:06.364 --> 00:14:09.923 It happens every school day, year round, in these communities. 00:14:10.303 --> 00:14:15.423 And he said, we've just had too many instances where they just don't show up, and kids can get hit by cars, and there's a problem. 00:14:15.423 --> 00:14:21.234 And so every day, he has officers driving at different times of the day, because there's different elementary, school, and other hours. 00:14:21.703 --> 00:14:23.854 And he goes, it's taking officers off the street. 00:14:23.854 --> 00:14:26.114 It's also not the most fun thing to go do. 00:14:26.379 --> 00:14:29.572 He goes, what if we could have drones that are scheduled every morning at 7. 00:14:29.572 --> 00:14:30.273 15 and 7.

00:14:30.273 --> 00:14:30.972 45 and 2. 00:14:30.972 --> 00:14:32.249 12 and 2. 00:14:32.298 --> 00:14:36.139 48 to go check all these and look to make sure the crossing guard showed up. 00:14:36.149 --> 00:14:41.428 And if they did, we can validate that, we just saved a couple hours of time across the city. 00:14:42.009 --> 00:14:49.119 Where all of those crossing guard validations are in place, and that's a very mundane thing, but he's you've just given us hours back to the day. 00:14:49.609 --> 00:15:15.158 Another one they do in their particular town in New Jersey gets flooded a lot when it rains, is what if we could fly and the two things they have to check every time it rains is they have to go check all the major grates near the low lying areas of town for debris, and they literally look to see are there sticks and other debris that are on there, and it's something you would think public works would do, but they don't have a big enough public works department, in the rain, in the horrible weather, the police officers go and look at hundreds and hundreds of grates every time out in the rain. 00:15:15.688 --> 00:15:20.899 He's could we fly those with a drone that automatically knows with GIS where every grate is? 00:15:21.293 --> 00:15:26.124 And then automatically has the object video capability to see if it's covered or not with debris. 00:15:26.124 --> 00:15:27.974 And if it is, we can send somebody out to clear it. 00:15:28.264 --> 00:15:31.573 But now we're looking at two or three drains rather than a couple of hundred. 00:15:32.124 --> 00:15:41.594 The other thing they do is every 15 minutes during a rainstorm, they drive to the local river and there's painted lines of how high is the river flow against the the river where it might overflow. 00:15:41.874 --> 00:15:43.943 Into town and floods, hundreds of homes. 00:15:44.193 --> 00:15:55.553 He's what if we could send a drone every 15 minutes and just go and look at how high the river is now we're not sending officers, which is actually dangerous out next to the river where it might be flooding to go look at how high it is every 15 minutes. 00:15:55.854 --> 00:16:02.453 So these are just examples where we may not think about the impact that technology can have on staffing and on morale. 00:16:02.583 --> 00:16:09.724 Nobody wants to do those particular things over and over again, versus, saving somebody's life or doing something that might be more critical, but they need to be done. 00:16:10.308 --> 00:16:18.798 And so I think those are cool things where they're mundane, not a whole lot of, I think, a chance for abuse or bad use of video or what have you. 00:16:19.099 --> 00:16:20.828 And also, they can be pre programmed. 00:16:20.839 --> 00:16:25.249 It's something that doesn't even require a pilot to operate manually what's going on. 00:16:25.249 --> 00:16:29.578 So I think those are good examples where almost every city in America could do things like that. 00:16:30.328 --> 00:16:42.408 I think that's a really beautiful example of like how we can apply AI to make both the human responsibility handle the things that they actually need to be handling versus like you're saying the mundane tasks. 00:16:43.038 --> 00:16:49.058 And as well doing it in a responsible way that doesn't impact really too much. 00:16:49.458 --> 00:16:52.188 So that's, I think a really great path. 00:16:52.639 --> 00:16:57.219 Where do you see AI having the largest impact on your own personal life? 00:16:57.969 --> 00:16:59.328 Boy, that's a loaded question. 00:16:59.448 --> 00:17:00.928 I think at the end of the day, I think. 00:17:01.339 --> 00:17:03.649 Once again, replacing mundane tasks. 00:17:03.708 --> 00:17:09.558 I believe that AI is going to take out some of the administrivia that we all deal with every day. 00:17:09.578 --> 00:17:14.278 And whether that's, helping to write correspondence, whether that's helping to read correspondence. 00:17:14.818 --> 00:17:16.239 I'm a data hungry person. 00:17:16.239 --> 00:17:23.483 I love to read and digest all this information and I'm starting to use different tools to, how can you read through All this information. 00:17:23.483 --> 00:17:29.023 I just had a friend of mine publish a new book that's in the SaaS revenue space that's, it's huge. 00:17:29.034 --> 00:17:30.203 It's 900 pages long. 00:17:30.203 --> 00:17:36.983 And one of my friends who's in the AI space with me just said, hey, I'm happy to pay you the price for this book because your knowledge is invaluable. 00:17:36.983 --> 00:17:37.923 And it's an expensive book. 00:17:37.943 --> 00:17:38.773 It's 90. 00:17:39.144 --> 00:17:47.979 But he said, I'd really rather buy a PDF and have It's, it digested and all the key points shared with me and being able to search and find things in it. 00:17:48.269 --> 00:17:58.598 And that's what happens in 2024 that wouldn't have happened in 2021 is the PDF of that book might be more valuable than actually reading the book or the hard copy of the book because what we're going to do with it. 00:17:58.598 --> 00:17:58.608 I 00:17:59.243 --> 00:18:10.443 I really can't tell you the amount of times that I've taken a PDF and then just started asking questions after putting it into an LLM because it is now a, the search and retrieval is much more better. 00:18:10.443 --> 00:18:14.653 The understanding, the comprehension is there, right? 00:18:14.683 --> 00:18:21.233 It's still leaving a little bit to be desired, fails on some places, but at the same time, absolutely amazing. 00:18:21.858 --> 00:18:28.659 mean, just think, I'm a kind of person that my whole life has used a notebook like this to take notes, right? 00:18:28.979 --> 00:18:40.669 But what if we started taking all of our notes in Remarkable or some other digital format of tool, but an LLM could take all of TJ's notes for the last 30 years in public safety and technology. 00:18:40.973 --> 00:18:41.763 And I could search them. 00:18:42.013 -->

00:18:49.124 I could find, hey, what was that meeting in Greece 20 years ago with the Hellenic police chief where we talked about X, right? 00:18:49.403 --> 00:18:52.403 And having that data in my fingertips, I have a notebook with it, right? 00:18:52.433 --> 00:18:55.854 But am I going to be able to go find it and go look on what page is it? 00:18:55.854 --> 00:18:57.933 It's got some dates on the front of the book, but right. 00:18:58.223 --> 00:19:02.693 And then what if I want to write a book about all those amazing experiences in public safety and technology? 00:19:02.923 --> 00:19:08.644 Would it be better to search for, the five years of working on FirstNet, for instance, and just all the cool. 00:19:08.898 --> 00:19:17.848 Information we digested and turned into a great strategy, but what about that strategy meeting we had where we figured out the business model for a hundred billion dollar public private partnership? 00:19:17.919 --> 00:19:20.078 Boy, that'd be great to find those notes. 00:19:20.489 --> 00:19:21.378 I know I have them. 00:19:21.378 --> 00:19:23.919 I don't know where they are right now, but they're on our shelf somewhere. 00:19:24.358 --> 00:19:29.878 But I think those are the kinds of things that are going to empower, TJ to write a book a whole lot faster than I could without it. 00:19:30.628 --> 00:19:31.269 It's funny. 00:19:31.269 --> 00:19:44.919 It's like some of those use cases that you're talking about, I've implemented some of them, like all my notes are in a markup format and I have an open AI connection that parses through it to look for similarities between notes, right? 00:19:44.919 --> 00:19:48.808 What are the, what are something that I may cross reference at a future date? 00:19:49.499 --> 00:19:52.169 Previously, you needed to tag everything. 00:19:52.169 --> 00:19:53.838 You needed to give it structure. 00:19:53.868 --> 00:19:54.298 Whereas. 00:19:54.683 --> 00:20:01.693 Sometimes journaling or note taking isn't a very structured process, but you know that you want to retain that information. 00:20:01.693 --> 00:20:07.304 And so we now have an LLM that can go about and create that connections for us. 00:20:08.003 --> 00:20:09.203 Yeah, you're hitting on a key thing. 00:20:09.203 --> 00:20:13.844 I think unstructured data has always been the death of finding good information, right? 00:20:13.844 --> 00:20:20.314 And really until LLMs have gotten to be as prolific as they are today, I think unstructured data was a black hole. 00:20:20.314 --> 00:20:28.403 And I think we have a chance to not only retrieve what we do now, maybe even the past, if we can put the last 20 years of unstructured data into what we have. 00:20:28.403 --> 00:20:37.409 I think for those of us, who, Our mid career or later in our career, we have an ability to really leverage all of that great data that we've created or have access to. 00:20:38.003 --> 00:20:38.663 Exactly. 00:20:38.874 --> 00:20:41.753 And then the other side of it is you may have some amazing notes. 00:20:42.003 --> 00:20:42.473 as well. 00:20:42.483 --> 00:20:46.243 And we're collaborating on something for me to have access to. 00:20:46.243 --> 00:20:46.473 that. 00:20:46.473 --> 00:20:55.644 I may not have known about the Helsinki connection that you had, but those notes could bubble up and actually pop into our frame of reference. 00:20:55.894 --> 00:20:56.273 Absolutely. 00:20:57.078 --> 00:21:04.828 looking at what businesses are doing for the next five years, what do you think are the importance of having an AI strategy? 00:21:04.848 --> 00:21:06.878 What are the things that you're looking out for? 00:21:07.094 --> 00:21:11.574 Why as you're having like board level discussions around like where you're directing the companies that you're 00:21:12.324 --> 00:21:16.923 Yeah, I think the key for any board directors today is you have to have an AI strategy, right? 00:21:16.923 --> 00:21:20.604 I think you can't ignore it in the tech world that we're in today. 00:21:20.604 --> 00:21:23.874 I think everyone has to have one, just like you have to have a cybersecurity strategy. 00:21:24.433 --> 00:21:29.784 And if we look at what's happened in the public markets, I've been on public company boards with NASDAQ and New York Stock Exchange. 00:21:29.784 --> 00:21:33.124 You have to You know, you have to have a cyber board focus. 00:21:33.124 --> 00:21:36.574 You have to have a cyber committee looking at your cyber risks. 00:21:36.574 --> 00:21:38.584 You have to have people with cyber experience. 00:21:38.584 --> 00:21:41.324 And, I get a lot of calls about that on boards today. 00:21:41.693 --> 00:21:44.013 And I think the same kind of mentality has to be with AI. 00:21:44.384 --> 00:21:49.013 You need to have board members that understand AI, and it doesn't mean we're all world experts. 00:21:49.013 --> 00:21:54.423 I'm not the world's biggest expert on AI, but I'm actively involved and I'm on the boards of companies with AI. 00:21:54.423 --> 00:21:55.064 Okay. 00:21:55.134 --> 00:21:56.364 And we're using it. 00:21:56.463 --> 00:21:58.884 And to your point, I think we learn from it every day. 00:21:58.963 --> 00:22:01.453 And I think that you have to make it an agenda item. 00:22:01.493 --> 00:22:04.884 How can we be disrupted by AI tomorrow? 00:22:05.183 --> 00:22:08.193 And what are we doing to leverage it rather than fight it? 00:22:08.798 --> 00:22:10.788 And I think that's a really important question. 00:22:10.798 --> 00:22:17.358 Even in just the average SaaS company how we develop today is very different than how, software developers are going to develop tomorrow. 00:22:18.163 --> 00:22:27.733 absolutely, I know we saw the release of Devin a couple of days ago and that was, an exciting time to see that we have an AI that could actually fix. 00:22:27.844 --> 00:22:30.084 I think it was 7 percent of GitHub issues. 00:22:30.683 --> 00:22:41.923 From the standpoint of creating an AI strategy, do you see

that there's any different paradigms that companies need to be looking at how they're implementing AI versus the way that they looked at technology before? 00:22:42.673 --> 00:22:51.763 I think similar to the point I made earlier, if you're looking at LLM as an AI in general, I think you need to look at solving the mundane issues rather than the wild and crazy, more radical. 00:22:51.939 --> 00:22:52.648 Kinds of things. 00:22:52.648 --> 00:23:00.598 And I think just like looking for code bugs and other things that are pretty mundane, but we spend a ton of time on and we spent a lot of time testing and fixing. 00:23:00.999 --> 00:23:11.048 That's a great example, separate than the public safety example I used earlier, where it's let's fix all this mundane administrivia kind of things with AI, which allows the big things to happen. 00:23:11.108 --> 00:23:18.969 Thinking of our human interactions to, to be more thought of and strategy and focus and direction of where we're going with technology. 00:23:18.969 --> 00:23:26.679 And I think finding the way to be to elevate the role of our talent is something we have to think about every day. 00:23:27.098 --> 00:23:29.868 And I think that we also shouldn't just be scared of AI. 00:23:29.868 --> 00:23:30.868 I'm not in the. 00:23:31.189 --> 00:23:35.469 Believer that it's the apocalypse someday or the Robocop of technology. 00:23:35.469 --> 00:23:39.749 I think a lot of that is blown out of proportion and instead we just need to get smarter. 00:23:39.749 --> 00:23:44.679 I'm a huge fan of Andrew Ng and Coursera and people just understanding AI. 00:23:44.679 --> 00:23:49.558 I think everybody on a board should take the basic understanding AI course from Andrew. 00:23:49.739 --> 00:23:52.219 It's out there, it's simple, it's easy to access. 00:23:52.554 --> 00:23:58.814 And I just think we just need to get smarter and understand what it really does and what it doesn't do is also really important. 00:23:58.864 --> 00:24:04.953 I think there's a misperception for some of the more negative things that really aren't as prolific as people think. 00:24:05.703 --> 00:24:14.223 Yeah, I can share that sentiment that it's good to be thinking about how terrible it can be, but also it's going to take a lot of leaps to get to that point. 00:24:14.273 --> 00:24:17.023 And we all, I think. 00:24:17.034 --> 00:24:23.144 AI alignment comes down to really the challenges that we have in humanity as well with alignment. 00:24:23.644 --> 00:24:27.443 So they're the same problems just really blown up into different regards. 00:24:27.634 --> 00:24:29.614 So having a, an eye on it. 00:24:29.969 --> 00:24:30.449 Okay. 00:24:30.449 --> 00:24:33.318 But at the same time, there's so much value that can be created. 00:24:33.318 --> 00:24:36.909 There's so much freedom that can be enjoyed by taking care of the mundane. 00:24:37.308 --> 00:24:40.439 We had an implementation where we were working with the services company. 00:24:40.439 --> 00:24:42.259 They do about a hundred invoices a day. 00:24:42.259 --> 00:24:43.459 They were all handwritten. 00:24:43.864 --> 00:24:45.624 What we did is we took the handwritten notes. 00:24:46.048 --> 00:24:55.058 Used an AI to process them and then spit out like more professional looking saved each one of their texts, 20, 30 minutes a day. 00:24:55.419 --> 00:25:05.828 And what they were doing gave the customer a better experience, but also allowed the text to focus on what the relationship was with the customer instead of worrying about the mundane. 00:25:05.828 --> 00:25:09.929 So I think you're on the right path around focus on the mundane another area. 00:25:09.959 --> 00:25:11.159 And I'm curious your thoughts. 00:25:11.493 --> 00:25:22.134 When we're designing out implementation for AI, we're looking at creating a process and almost earmarking humans at every point of who's going to be doing this task. 00:25:22.634 --> 00:25:26.443 And then our AI analysis is, all right, what is the mundane that we can take out of this? 00:25:27.183 --> 00:25:35.173 And treat the AI as if it is that, Sally doing this task instead of, thinking that it's just a piece of tech that's going to handle it. 00:25:35.923 --> 00:25:43.048 No, I think you're right, and I think that we have to be more deliberate about What tasks we have our team doing today and how to automate. 00:25:43.048 --> 00:25:44.169 It's really simple. 00:25:44.209 --> 00:25:47.598 Automate the mundane and take out the repetitious thinking. 00:25:47.598 --> 00:25:52.568 I think back to the easy example of, Steve jobs always wearing the same outfit to work every day. 00:25:52.818 --> 00:25:56.038 He did that to save on the brain power of what am I going to wear today? 00:25:56.038 --> 00:26:01.679 What shirt, what clothes, what sneakers, and at the end of the day, just wear the same basic uniform, if you think about it. 00:26:02.088 --> 00:26:08.788 And coming out of a uniformed first responder world where we did wear the same uniform to work every day, it does make your life a lot simpler. 00:26:08.788 --> 00:26:14.219 And I think we haven't taken that same approach to every job or role that works for us or on our teams. 00:26:14.648 --> 00:26:19.298 And, what is that mundane set of things that happens the same way every day at work? 00:26:19.669 --> 00:26:20.818 That can be automated. 00:26:20.929 --> 00:26:33.143 And and I think that, and manufacturing we got there over the last 10 or 20 years, especially with a lot of robotics, you're placing the most mundane things, whether it was gluing components together or looking for differentials off of spec or. 00:26:34.174 --> 00:26:36.588 Testing and QA ing product that was being built. 00:26:37.028 --> 00:26:48.628 I think on the software front, we're starting to see that really take off as well, I think though, just for business operations, and it doesn't matter what kind of business you run, to your point, it could be a services business,

it could be government activities. 00:26:48.709 --> 00:26:56.068 I would say probably the area that's most rep to be disrupted today is government because government is very old fashioned in the way that they operate. 00:26:56.828 --> 00:26:59.999 I recently had to get a permit in the county that I live in. 00:27:00.459 --> 00:27:03.659 And I got an I tried to go by the office to get a permit. 00:27:03.659 --> 00:27:05.479 And they're like, oh no, you like, you have to make an appointment. 00:27:05.838 --> 00:27:06.598 I'm like I'm here now. 00:27:06.608 --> 00:27:07.169 Let's just do it. 00:27:07.169 --> 00:27:07.528 They're like no. 00:27:07.528 --> 00:27:08.278 Like we're backed up. 00:27:08.308 --> 00:27:09.558 And I said how long are you backed up for? 00:27:09.558 --> 00:27:10.528 They're like, about two months. 00:27:11.413 --> 00:27:13.003 I said, I have to wait two months to get a permit. 00:27:13.003 --> 00:27:15.763 Now I'm just gonna write a check and drop off my paperwork. 00:27:15.763 --> 00:27:16.574 And paperwork's done. 00:27:16.574 --> 00:27:19.913 It was three pages of paperwork and they're like no, you have to make an appointment to come in. 00:27:20.263 --> 00:27:22.489 And then and it's and you can go online and do that. 00:27:22.489 --> 00:27:23.808 Or I guess I can make one for you now. 00:27:23.808 --> 00:27:26.898 And she was nice enough and made me an appointment, but it was like for March for something. 00:27:26.898 --> 00:27:30.769 I went in January and then I said how long will it take after I actually do that? 00:27:30.769 --> 00:27:31.669 Oh, probably two weeks. 00:27:31.673 --> 00:27:32.044 And then you'll get it. 00:27:32.544 --> 00:27:41.453 That's a great example where a hundred percent of that should be automated and there probably shouldn't be humans doing all but the most specific tasks that are unique to that. 00:27:41.884 --> 00:27:47.584 And, that was probably a four minute task, four minutes when I looked at it. 00:27:47.659 --> 00:27:51.398 that absolutely that's a perfect example of the things that should be automated. 00:27:51.828 --> 00:27:58.078 The other question that I have for you though, is that there's somebody who takes their time in that's backed up for two months, right? 00:27:58.088 --> 00:28:00.078 And then takes two more weeks to respond. 00:28:01.118 --> 00:28:04.999 What do you see that person doing after the fact, right? 00:28:05.088 --> 00:28:15.558 Yeah I think there are the reason why if I went to her boss and said, you know Why is this person backed up two months and complained which I thought about but I didn't think it would have an impact quite frankly 00:28:15.909 --> 00:28:16.328 yeah. 00:28:16.778 --> 00:28:23.213 I think they would have said we just don't have enough staff We don't have enough people and they have too many things to do that answers your question. 00:28:23.223 --> 00:28:25.824 They do have too many things to do, and they don't have enough people. 00:28:25.834

--> 00:28:35.854 So if you were to take 80 or 90 percent of that role and automate it you would then have 80 or 90 percent of that person's role to do the other things that they're too busy doing that this isn't getting done. 00:28:35.854 --> 00:28:45.159 And so there's enough human work and this was a law enforcement agency, quite frankly, for them to do Where it wouldn't be that hard to reapply their work. 00:28:45.489 --> 00:28:54.019 Another great example, I think, for this is we're starting to see 911 centers or, emergency operation centers that take calls from the public worldwide. 00:28:54.028 --> 00:28:56.519 It's 111 and 000 in other countries. 00:28:56.519 --> 00:28:57.759 We think of it as 911. 00:28:58.239 --> 00:28:59.659 That are becoming much more automated. 00:28:59.669 --> 00:29:05.148 There's a lot more AI being utilized to route a 911 call and to share video and text and data. 00:29:05.733 --> 00:29:11.943 And automatic repositories of information that can share medical information or pictures of an incident at a scene. 00:29:12.604 --> 00:29:15.384 And in the old days, we had two roles in a dispatch center. 00:29:15.384 --> 00:29:23.034 One was a call taker who answered the landline phone and wrote down everything and asked all the questions that now we already all know through your smartphone. 00:29:23.064 --> 00:29:29.094 Your smartphone can give me more data than you could ever tell me in five minutes of talking to a call taker. 00:29:29.528 --> 00:29:43.338 Then that call taker would type it all into a computer aided dispatch system that would then send it to a radio dispatcher who would have to read all that information and then push buttons on a console to tell somebody over a 90 year old radio system to go respond to a scene. 00:29:43.949 --> 00:29:52.729 The community I live in now has what's called Live 9 1 1, where literally you could have somebody calling in with a suspicious person that is trying to break into a home. 00:29:53.138 --> 00:29:55.229 And that live call could not only be. 00:29:55.423 --> 00:30:26.733 Bypassed by the call taker and bypassed by the dispatcher could be sent to the closest officer who's three blocks away And we'll know that through the automatic vehicle location on the person and on the police car and be able to have them talk to The individual who's saying hey, I'm following a person in a red shirt and blue jeans He's trying to break into my house And here's where they're at and tell me where you're coming from and boom catch the person in 10 seconds and the whole call Is over And so between AI and automation, we're now taking roles that were very mundane and very hard to fill. 00:30:26.804 --> 00:30:30.054 The average 911 dispatcher lasts about six months in that role. 00:30:30.054 --> 00:30:40.483 It's a difficult role, it's high stress, it's mundane, you're dealing with life crises where you can't fix the problem, somebody else has to fix the problem, and it's a really tough job. 00:30:40.903 --> 00:31:02.398 What if we could automate a lot of the parts of that information sharing, so that those individuals could be trained as public safety operations center, leaders, that could look at all the data, Make sure it's all getting to the right places and have value add and fixing and solving problems and making decisions rather than doing process automation or data entry. 00:31:02.689 --> 00:31:08.348 And I know their job is much more than that, but there's a lot of data entry and process that's being done in that. 00:31:08.618 --> 00:31:10.598 And so there's so much work. 00:31:10.969 --> 00:31:13.868 That would make the lives of saving people better. 00:31:14.088 --> 00:31:15.398 That is not data entry. 00:31:16.148 --> 00:31:17.368 absolutely. 00:31:17.368 --> 00:31:25.828 So the one thing that struck in there is basically, even if you remove 20 percent of a person's job like that still frees them up because there's more work that's coming in. 00:31:26.419 --> 00:31:32.128 We've done a lot of projects where the efficiency game comes out and says, you can cut half of your labor force kind of thing. 00:31:32.439 --> 00:31:35.888 The funniest part about that is even though it comes in the financials. 00:31:36.328 --> 00:31:42.759 I've never had one customer cut a job because of what we're doing because of that exact reason. 00:31:43.489 --> 00:31:45.439 There's always more work to be done. 00:31:45.449 --> 00:31:47.969 There's always improvements that you can be making. 00:31:48.398 --> 00:31:59.969 The role shift, and I think you were saying this as well, is As that person's mundane tasks go away, they become more of an architect in their processing and their automation. 00:32:00.068 --> 00:32:16.519 And so one of the skills that we've identified as being important is that you need to be developing managerial skills in even your baseline employees, because now they're working with an AI in a month and to handle the mundane tasks and get that feedback and going back and forth. 00:32:16.808 --> 00:32:21.509 What other skills do you see as being necessary for your employees and 00:32:22.259 --> 00:32:28.898 I think what you're hitting on kind of the magic that's in this change and it's this higher thinking that comes into it, right? 00:32:28.898 --> 00:32:33.088 And so we need to train our teams to be able to upskill their ability. 00:32:33.118 --> 00:32:35.028 And it doesn't have to be college training. 00:32:35.118 --> 00:32:36.558 It doesn't have to be a master's degree. 00:32:36.558 --> 00:32:37.358 It has to be. 00:32:37.644 --> 00:32:49.864 Live on the job training that takes somebody who's making$20 an hour and doing a difficult data entry, mundane kind of job to be a 30, 40,$50 an hour thinker, an employee that's gonna add a ton of value to the business. 00:32:49.864 --> 00:32:51.788 And it's also something that can scale. 00:32:52.118 --> 00:32:57.374 So one of the things that I think AI and this role changes we're

gonna scale businesses faster. 00:32:57.663 --> 00:32:59.703 And scaling doesn't always just have to be to do more. 00:33:00.219 --> 00:33:05.019 But it could be to do it more efficiently so we can accomplish more and cover a greater area. 00:33:05.048 --> 00:33:22.469 I think, we still have massive pressures on unemployment because it's so low in America to have the right skills and the right talent that we need to have that I think we need to really look at what are the right ways to train and upskill teams to do these higher level roles that are now empowered by AI. 00:33:22.469 --> 00:33:27.179 And the great news is they're going to be higher paying, they're going to be higher value, they're going to be more engaging. 00:33:27.528 --> 00:33:29.723 And nobody would really be against that. 00:33:29.824 --> 00:33:37.173 I think it's just, it's such a great chance to upskill our people so that we can scale businesses and improve the way services are delivered. 00:33:38.148 --> 00:33:43.818 I'm really curious about your take on job satisfaction today, right? 00:33:44.038 --> 00:33:49.038 Most people are miserable in their jobs, and it's just a fact, right? 00:33:49.118 --> 00:33:54.898 I think the number comes in somewhere between 60 and 75 percent of people who are not satisfied in their employment. 00:33:55.648 --> 00:34:10.449 Given that there's going to be so much change that comes about with the inclusion of AI, and depending on how fast that comes into the workforce, what do you see as the opportunities to improve, our daily existence when it comes to our own employment and satisfaction? 00:34:11.199 --> 00:34:20.364 I think we need to encourage people to do a lot of what I think you and I both have done individually, which is build the roles you want to have rather than just go apply for a job. 00:34:20.983 --> 00:34:23.744 And you need to ask to do the work that you want to do. 00:34:23.744 --> 00:34:38.224 Ironically, if there's something you're really good at and you're really passionate about, and you have skills, if you go and talk to businesses that need your capabilities, the likelihood that you're going to work yourself into a job, and we used to call this like networking for a new job. 00:34:38.224 --> 00:34:40.103 I don't think that was the right way to describe it. 00:34:40.443 --> 00:34:41.264 It's actually. 00:34:41.554 --> 00:34:49.083 Knowing where you can add value and then going and working with those people where you can add value and turning it into what people refer to as a job. 00:34:49.724 --> 00:34:56.934 I don't know if I would call it a job rather than a passion, but it's not just follow your passion, it's actually using your skills to add value. 00:34:57.338 --> 00:35:03.369 And, people will hire people that will add value to a company, a corporation, an organization. 00:35:03.798 --> 00:35:07.389 And it's not always the job that's posted on Indeed, right? 00:35:07.389 --> 00:35:13.728 I'm just not a huge fan that's the way in most industries to find that next role for anybody at the lowest levels coming out of college. 00:35:13.778 --> 00:35:16.858 I get asked a lot, what would you tell your 22 year old self? 00:35:17.259 --> 00:35:21.358 And it's go do the things you want to do and go work with the people you want to work with. 00:35:21.634 --> 00:35:32.054 I had a gentleman yesterday, funny story, I just came out of getting my hair cut and he walked up to me and I have a fun pickup truck that it's super fun and most guys would dig it, right? 00:35:32.054 --> 00:35:35.773 And I just like it and anyway, he came up to me and he said, I want to work for you. 00:35:36.083 --> 00:35:37.204 And I said, why do you want to work for me? 00:35:37.204 --> 00:35:38.744 He says, I want a truck like that. 00:35:38.744 --> 00:35:43.614 And right out, he was walking down the street and he was dead serious, 00:35:44.134 --> 00:35:44.534 Yeah, 00:35:44.878 --> 00:35:46.278 I said, I love your attitude. 00:35:46.278 --> 00:35:47.969 I said, what, tell me more about you. 00:35:47.969 --> 00:35:48.628 What are you like? 00:35:48.628 --> 00:35:49.889 What are you what are your capabilities? 00:35:49.889 --> 00:35:50.878 What are your skill sets? 00:35:50.878 --> 00:35:57.909 And whether you work for me or work for somebody I know, the fact that he was willing to walk up and be that bold I'm willing to be your apprentice. 00:35:57.909 --> 00:35:59.599 I'm willing to do whatever you're doing it right. 00:35:59.748 --> 00:36:00.619 I want to be a part of that. 00:36:01.148 --> 00:36:05.918 And I thought that was like the right attitude to your point of like, how do people find that job? 00:36:05.918 --> 00:36:10.768 If you see people doing fun things that you would like, go ask them, like, how do I do what you do? 00:36:10.789 --> 00:36:11.889 And I want to be a part of that. 00:36:12.639 --> 00:36:13.338 I love it. 00:36:13.798 --> 00:36:18.719 I think some things to highlight here is a connection to passion, right? 00:36:18.768 --> 00:36:24.148 As far as at least understanding what it is, the value that you really want to be contributing. 00:36:24.309 --> 00:36:31.384 And I think that's the key differentiation of today we have a We have jobs that have a lot of mundane tasks to them, and you accept that. 00:36:31.384 --> 00:36:44.884 with it, but we're getting into a point of one, we, freelancers are accelerating in the economy as far the number and the percentage of of the workforce, which means you're basically choosing the role that you want to play. 00:36:45.094 --> 00:36:52.213 The digital creator type of universe and being able to put out there all your work to an audience rather quickly. 00:36:52.469 --> 00:36:53.639 has continued to accelerate. 00:36:53.639 --> 00:36:58.268 I think Gen Z is really leading the charge on differentiating between that. 00:36:59.148 --> 00:37:13.498 But then also that human connection of being able to say look, I see that this person

has charted a path that I would like to take and having that, like the so many references are just poorly worded in this moment. 00:37:13.878 --> 00:37:17.518 But at the same time, seeing those people and saying, you know what, I want to learn from you. 00:37:17.914 --> 00:37:20.103 And creating that human connection as well. 00:37:20.164 --> 00:37:23.724 There's only so much that we can learn from a screen or from it. 00:37:23.724 --> 00:37:28.664 And I think the importance of getting back to that human connection can be really significant. 00:37:29.713 --> 00:37:33.153 I think that human connection with the willingness to fail, right? 00:37:33.164 --> 00:37:34.603 The willingness to take a risk. 00:37:34.903 --> 00:37:41.853 And it doesn't have to be a massive risk, but I think to get what you really want out of life, you have to take calculated risks and you have to take. 00:37:42.873 --> 00:37:49.664 Hey, I'm willing to work hard and do something different to become what I want to be or to be a part of something I want to be a part of. 00:37:50.193 --> 00:37:56.804 And I think we've lost that a little bit with the way hiring and jobs have been in the last 20, 30 years. 00:37:56.804 --> 00:38:02.039 And I think that to your point, I think Gen Z is going to push this change because they want different work life balance. 00:38:02.039 --> 00:38:04.528 They want different kind of roles to be a part of. 00:38:04.918 --> 00:38:06.268 And I think you have to make it fun. 00:38:06.318 --> 00:38:11.128 I think some people have lost the fun in work to go to your question about like dissatisfaction. 00:38:11.128 --> 00:38:12.168 I love what I do. 00:38:12.568 --> 00:38:13.809 I love every part of what I do. 00:38:13.809 --> 00:38:15.418 And if I don't love something, I stop doing it. 00:38:16.009 --> 00:38:17.898 And I think that, you have to get better. 00:38:17.898 --> 00:38:18.978 And I've learned this over time. 00:38:18.978 --> 00:38:21.938 I used to say yes to everything, which I think is the great thing to do in your twenties. 00:38:21.938 --> 00:38:23.719 You should say yes to almost everything. 00:38:24.188 --> 00:38:26.228 But I think as you grow in your career. 00:38:26.458 --> 00:38:32.099 You need to learn to say no to things that might take away opportunity costs to focus on the things you really enjoy. 00:38:32.708 --> 00:38:38.978 And so both saying yes, I think when you're younger in your career to a lot of exciting things that may lead you to different places. 00:38:38.978 --> 00:38:40.708 Public safety led me to technology. 00:38:40.978 --> 00:38:43.659 That is not a normal charted path for most people. 00:38:43.838 --> 00:38:45.338 Public safety led me to leadership. 00:38:45.338 --> 00:38:48.809 I have an MBA from Johns Hopkins and most people, you wouldn't think of firefighters. 00:38:48.809 --> 00:38:50.338 That's the path you're going to take, right? 00:38:50.648 --> 00:38:53.548 But it leads you to other things and how you get there. 00:38:53.889 --> 00:38:59.418 And then also, I think, as your time becomes more valuable for yourself, you also need to make time to go skiing. 00:38:59.438 --> 00:39:00.849 You need to make time to go paddle boarding. 00:39:00.849 --> 00:39:03.978 You need to make time to go out in the outdoors and do the things you want to do. 00:39:04.398 --> 00:39:08.429 And you may need to change your job or your role to facilitate that, right? 00:39:08.429 --> 00:39:14.748 And to allow you to live in a place where you get to do those things in schemes 20 minutes away or whatever that may happen to be. 00:39:15.088 --> 00:39:17.309 And you have to make time for the things that you want to focus on. 00:39:18.059 --> 00:39:23.969 I think that's an amazing point is that, what our identities can get so consumed in the work that we do. 00:39:24.648 --> 00:39:26.298 And that really isn't the point. 00:39:27.153 --> 00:39:41.014 And like you're saying, we, what you were saying about making your work fun reminds me of an Alan Watts quote, which is basically like, you need to, I'm paraphrasing, you need to make your work look like play so that nobody can tell the difference. 00:39:41.898 --> 00:39:44.528 Between when you're actually working or when you're playing. 00:39:44.708 --> 00:39:45.789 Absolutely. 00:39:45.824 --> 00:39:46.554 such a good point. 00:39:46.554 --> 00:39:48.143 And I think I've been able to. 00:39:48.673 --> 00:39:53.963 Guide my own career, especially in the last couple of years to where, work and play are definitely intertwined a lot more. 00:39:54.264 --> 00:39:57.273 And I think vacations and work trips are intertwined a lot more. 00:39:57.284 --> 00:39:58.603 And people say you work on vacation. 00:39:58.603 --> 00:40:02.353 And the answer is absolutely I do, but I'm also vacationing in cool places. 00:40:02.353 --> 00:40:05.143 And I'm also, getting on calls at 6am from Hawaii. 00:40:05.143 --> 00:40:07.594 If you're on a trip and doing a couple of hours of work. 00:40:07.594 --> 00:40:13.034 And when I come back from a trip like that, I'm not backed up because I've done the work every day while I've been away. 00:40:13.393 --> 00:40:14.954 But it's in a way that I'm having fun. 00:40:14.954 --> 00:40:17.114 If work is fun, it's okay. 00:40:17.114 --> 00:40:23.443 And if you still get to go enjoy the things you want to do and you get to go sailing and you get to go do cool things, it's all a good day. 00:40:23.443 --> 00:40:28.083 And I think the traditional Monday through Friday, eight to five is not ever. 00:40:28.833 --> 00:40:36.583 Simple as people think it is I think I work really hard and I probably put in a lot more hours than that, but it's not always on the traditional schedule anymore that maybe it used to be. 00:40:36.983 --> 00:40:41.704 And that allows you to work on a weekend or allows you to work at night or in the morning or other things. 00:40:41.704 --> 00:40:42.619 But I, I. 00:40:43.039 --> 00:40:45.369 Recently

did something that I wish I would do a lot more of. 00:40:45.378 --> 00:40:48.518 We had over 50 inches of snow here in a couple of days. 00:40:48.559 --> 00:40:51.989 And it was a Tuesday and it was just like the sun came out. 00:40:51.989 --> 00:40:55.119 It was blue skies and 50 inches of snow in the last three days. 00:40:55.498 --> 00:40:58.528 And I literally had the powder flu, just take over me. 00:40:58.539 --> 00:41:05.438 And I had to adjust my meetings for the afternoon and I went skiing for four hours in this fresh powder and it was spectacular. 00:41:05.903 --> 00:41:08.614 And it's the kind of stuff you did probably more when you were in your 20s. 00:41:09.014 --> 00:41:14.143 And it's not a bad thing to catch the powder flu on a day when you get a lot of snow and the sun comes out. 00:41:14.143 --> 00:41:15.184 And we just have to do that more. 00:41:16.048 --> 00:41:16.889 No, I think you're right. 00:41:16.898 --> 00:41:33.478 Like we need to really take a look at like the balance that we have between work and life and really making an integration and an understanding that like, Hey, the powder flu comes about, you've got to catch it and got to go out there and enjoy life and like really bring a little bit of joy to yourself. 00:41:33.994 --> 00:41:40.083 Because you are taking that flexibility And you're waking up at six o'clock in the morning in Hawaii in order to get a couple hours of work in. 00:41:40.083 --> 00:41:43.983 And the other side of that is, let's go ski on Tuesdays. 00:41:44.733 --> 00:41:46.853 And by the way, there were no lines and it was spectacular. 00:41:47.153 --> 00:41:47.923 Oh my God. 00:41:48.164 --> 00:41:52.563 I'm jealous just a little bit, but I do my own thing. 00:41:53.543 --> 00:41:56.543 Now I'm really enjoying talking to you here today. 00:41:57.563 --> 00:41:59.543 Is there anything that we could do for you? 00:42:00.164 --> 00:42:03.054 Or is there anything that the audience could share in your passion with? 00:42:03.804 --> 00:42:15.844 No, I think the only thing I will throw out there is I think everybody in the technology world should sit back and put a challenge to your team of what can we do to empower public safety to save more lives. 00:42:16.353 --> 00:42:18.114 And it doesn't matter what your technology is. 00:42:18.114 --> 00:42:19.744 It could be anything in the AI world. 00:42:19.744 --> 00:42:21.373 It could be anything in the software world. 00:42:21.373 --> 00:42:23.114 It could be hardware technology. 00:42:23.114 --> 00:42:25.623 But I think we build a lot of things for consumers. 00:42:26.148 --> 00:42:31.778 And what I would just like to say is, challenge your team, regardless of technology to say what if this was in the hands of a paramedic? 00:42:32.188 --> 00:42:34.028 What if this was in the hands of a firefighter? 00:42:34.539 --> 00:42:37.228 What if this was in the hands of a public safety agency? 00:42:37.418 --> 00:42:42.599 What could they do to serve the citizens of their community better with your technology specifically? 00:42:43.048 --> 00:42:47.664 And if you don't know the answer, Take your technology to your local firehouse and ask them, right? 00:42:47.864 --> 00:42:58.114 Take your technology over to the police station and, maybe bring along some coffee or something and say, Hey, we'd like to share our technology and say, how could we possibly make this work and help your job easier? 00:42:58.434 --> 00:43:05.574 And I think that's pretty cool to think about because it, the reason why most people get passionate about work is they're passionate about their mission. 00:43:06.554 --> 00:43:18.463 And one of the reasons I've always, made my life so easy in public safety and technology is the mission is so valuable and you can make, have such an impact on thousands, if not millions of people by having better technology for public safety. 00:43:18.853 --> 00:43:42.003 I think even for tech companies, you can have the same approach and, I know the head of public safety over at Apple, for instance, and if you think of the Apple watch and you think of the different things that are built into this now, for emergency alerting and fall detection and RapidSOS, which is a company I advise, has built the technology that every Android and iOS device has for notifying 911 and being able to share location data. 00:43:42.344 --> 00:43:49.664 And what I love is, Gary posts all the time about all these saves that have happened because somebody happened to be wearing an Apple watch or using an iOS device. 00:43:49.664 --> 00:43:54.483 And they drove off a cliff and they would have never been able to call 911 because they were unconscious. 00:43:54.483 --> 00:44:12.403 But that crash detection, Call 9 1 1 and a helicopter went in there and saved them before they ever even like regain consciousness, which would have never happened with a single individual driving off a cliff before, or falling in a national park having satellite connectivity that actually goes to these devices off the grid for emergency SOS. 00:44:12.403 --> 00:44:16.753 And if you think about that, talk about the most rewarding thing for Apple or other. 00:44:16.938 --> 00:44:25.849 Technology companies when they're doing things that are saving their customers lives because of a capability in the technology How can that not be good? 00:44:26.599 --> 00:44:27.688 That is fantastic. 00:44:28.028 --> 00:44:35.739 I do love how everything that you've been doing ties back to saving somebody's life or making it a, a much more better place for people. 00:44:35.798 --> 00:44:37.009 And so it's really commendable. 00:44:37.009 --> 00:44:39.989 And thank you for dedicating your life to this work. 00:44:40.833 --> 00:44:42.884 I appreciate that but it's also it's so rewarding. 00:44:42.884 --> 00:44:54.331 It's hard not to do It's just it's a it's a rewarding element and I think of you know My days as a firefighter as a flight paramedic and You know, they're the most rewarding days I've ever had, or even as a state trooper, when you can help somebody. 00:44:54.760 --> 00:44:57.041 And there's not a value you can put on that. 00:44:57.041 --> 00:44:59.990 It's probably the most fun I've ever had going to work. 00:45:00.360 --> 00:45:05.911 And I think being able to do that on a broader scale with technology is what makes it exciting still today. 00:45:07.005 --> 00:45:07.695 Fantastic. 00:45:08.014 --> 00:45:10.105 TJ, again, thank you for being here today. 00:45:10.204 --> 00:45:13.565 If anybody wants to reach out to you, is there a way for them to get ahold of you? 00:45:14.650 --> 00:45:16.110 Yeah, one, I'm on Twitter TJPublicSafety. 00:45:16.751 --> 00:45:19.650 Also, you can email me at TJ at PublicSafety. 00:45:19.690 --> 00:45:20.210 Network. 00:45:20.391 --> 00:45:22.231 And more than happy to connect with anybody out there. 00:45:22.815 --> 00:45:23.965 Oh, that's fantastic. 00:45:24.574 --> 00:45:25.485 Thank you again. 00:45:25.594 --> 00:45:28.045 And everybody, thank you for listening. 00:45:29.505 --> 00:45:35.695 Thank you for tuning into The Human Code, sponsored by FINdustries, where we harness AI to elevate your business. 00:45:36.114 --> 00:45:41.764 By improving operational efficiency and accelerating growth, we turn opportunities into reality. 00:45:42.735 --> 00:45:47.885 Let FINdustries be your guide to AI mastery, making success inevitable. 00:45:48.594 --> 00:45:50.864 Explore how at FINdustries. 00:45:50.945 --> 00:45:51.264 co.