From CIO to CTO: Tech Evolution, Temptations, and AI’s Impact Part 2 with Brian Singer, CIO & CTO at Propio Language Services

(Intro Narrator at 00:00:01) Today, we're bringing you the second part of our conversation with Brian from Propio Language Services, and we're talking all about the evolution of technology from the perspective of a CTO. You're listening to Joel Beasley, Modern CTO.

(Joel Beasley at 00:00:17) CTO.

(Brian at 00:00:19) Then, you know, of course, now recently with ChatGPT getting so much play, now everybody's thinking, "Oh, we won't even need you in a year." And I'm like, hold your horses. It's a lot of fun, though, to play with it. But, you know, I just see things totally transitioning, and that's just in my career. When I was growing up, essentially, in the business world, especially working at a place like the Chicago Mercantile Exchange, our CIO wasn't a technologist. Our CIO was a business person. And it wasn't, you know, until two years after that it went into more of a technology-driven organization. And I've seen that repeatedly where you get really good business people and they do very well, but it's a different industry. You need to have that technology background. But at the same time, us as technologists have to understand business. We have to get more adept at the financial components of what we do and understand, you know, intricately what we do as a business in order to build the right products. And so it's a little bit of a transition where, you know, the dominance of business over tech has flipped on its head to tech over business. And so that's intriguing to me, and that makes this a hell of a lot of fun because I look at myself as a, you know, a business technologist more so than anything else. I'm not one of those people that just says, "Hey, there's a new AWS service. We've gotta go build that." It has to make logical sense, if you get my drift.

(Joel Beasley at 00:01:47) Well, I see it converging. So I see the business people having to become technologists and the technologists having to become business people. I also have seen so much that it's hard for me to even talk about titles anymore.

(Brian at 00:02:00) Oh, I know. Right? Yeah.

(Joel Beasley at 00:02:01) Right? Because I just say titles are the way that the team chooses to label themselves to the outside world, you know, because it's so different, the different roles that you'll have. And to your point too about the business people, I used to sort of rag on some of the, you know, just collegiate business management type people because they were really bad at technology, and I'd constantly see them making bad decisions. But I have run into a pocket of them where they're so good at leading and putting people in the right places along with having that MBA type financial aspect to it that they have success. So I rag on them only 5% less now.

(Brian at 00:02:47) No, you know what? Spot on. Part of what makes this company successful is the fact that Marco and Joe have expanded their horizons. They take pride in the fact that they learn about the technology as a complement to their expertise in the business side of things. And I enjoy that as well. And it makes us all stronger as a team because, you know, I'll plead ignorance when they're talking about certain things that are related to the business, wanting to know more. And then they ask a lot of excellent questions around, you know, "Why are you doing this? Why is it taking so long? What does it mean to do X versus Y?" We're actually handling something today where, you know, a calculated risk we took—it didn't come back to haunt us, but one of the risks that we knew we'd have to mitigate has arisen. Right? But everybody knew about it. We'd already discussed it. We already knew about it. And now it's just an opportunity for us to, you know, go left and make sure we're taking care of it. But the benefit of that conversation was we already had it, and it wasn't a gotcha. Everybody understood it. And we can do that as a collective at an executive level, which not a lot of places can do. And frankly, that's where the distrust comes in. Right? Because just as much as if I don't extend my knowledge of the business and the financial components of it, or, you know, some of the business folks don't extend their knowledge on the technology, it becomes very difficult to build that trust. Right? Because you don't really know what everybody else is saying, and, you know, it just becomes somewhat confusing. And you always gotta have this kind of hesitancy to just execute. And I've seen that happen before. And it's not a fun situation to be in because at that point in time, you're turning into more of a salesperson than you are, you know, an executive leader that's trying to get things done because you're trying to influence your direction and influence your way as opposed to taking the business case and explaining it out to say, "This is technologically why we should be doing this approach because of the return on the investment." Right? The return to the business. And I'm a big champion of looking at ROI, using objective KPIs to measure, you know, expected results and the actual results. I want the investment to prove valuable back to the business. I don't wanna just do things that sound cool. It doesn't—at the end of the day—

(Joel Beasley at 00:05:26) We can figure out how to make them both happen, though.

(Brian at 00:05:28) Well, for sure. You know, there's always that. But, you know, I'm very cost conscious too. Right? You know, no doubt in my mind, I have the most expensive organization in the company. Right? I'm very, very honest about that. And most IT organizations are the most expensive to the company. But I also wanna be really frugal on how I use that. Right? And just saying I'm gonna go build some stuff because it's a cool technology, that's not gonna translate into—

(Joel Beasley at 00:05:59) Do people do that, though? Do people do that? Is it really happening a lot? They do it without business? They're just like, "Oh, we're just gonna go do this because it's hot"?

(Brian at 00:06:07) Oh, yeah. For sure.

(Joel Beasley at 00:06:08) Right?

(Brian at 00:06:08) Yeah. Or they do it beneath the covers. Right? They do it under the covers, and it's like, "Oh, yeah. I'll solve this problem." The next thing you know, they're implementing new technology, new unproven technology to try and solve that problem. And I've had some recency with this. That fails. Right? Because you don't know enough about the technology for it to be scalable. You don't know enough about the technology you're using to understand its pros and cons. And then it takes more time than you originally estimated because you estimated it based off of technology that you know. That's great for an R&D function. Like, you should absolutely have an R&D function that's constantly looking at new innovative ways to make your software more performant, better efficient, solve better business problems. But with the speed that we're trying to run at, introducing new technology at the same time you're trying to solve, like, instant or immediate business problems is, in my experience, been a disaster.

(Joel Beasley at 00:07:07) Well, yeah. I'm curious to dive into the R&D function a little bit because when I first saw ChatGPT come out, I was like, "Eh." And then I started talking with it, and then we started using it in our business, and then it was saving us, like, half of our time in production because—I don't know if we've talked since then, but we started making shows for other companies. Do you know about that?

(Brian at 00:07:32) Yeah.

(Joel Beasley at 00:07:32) Okay. So we do, like, fifteen, sixteen shows for other companies. And so we have producers, and they have to prep the episodes, you know, the whole process you go through with Josh and everything. That happens across all of our shows. Right? And we started using ChatGPT to help us with the prep. So we feed ChatGPT your bio, and we feed it the goals of the conversation. We feed it the notes that Josh takes from your prep call, feed it all of that information, and then we start probing it to come up with good questions and things like that or give us ideas. It is phenomenal. It saves us so much time. So when I saw that, I said, "Okay, I'm always scared to go down rabbit holes." Because to your point of not building stuff because it's cool, you have to be really disciplined there. And I think I've been lucky in my trajectory of my career because the majority of things I was doing was with my money. I kept it close as possible to the business thing. So I didn't really develop a bad habit. I never worked at a Fortune 500 company where I developed a habit of getting to be the king and just building stuff because I thought it would be cool. So whenever I hear you say—I hear other people say it, and I'm always like, "Who are these people?" Because I wanna stay away from them.

(Brian at 00:08:44) Oh, man. I'm with you. It's a completely different—like, when you have your own money and it's your own business, you think completely differently. And at the same time, working for Amazon makes you think like an owner. Right? That's their leadership principles. I love the leadership principles. They matter to me to this day. You know, somewhere in my desk, really quick, I have got the one-pager of all the leadership principles, and I still talk like that. Right? It's a big part of how I interview. It's a big part of how, you know, we chat at the executive level. But, you know, I wanna be cognizant of the fact that there's the right time to introduce new technology, and then there's the wrong time. So it's a balance. If it's immediate, you know, if you don't have the time—like, for example, just to use some rudimentary analogy. If you don't have time to do a spike story, right, you can't really look at introducing new technology into the workflow because there's gonna be immediate risk to whether or not you can deliver. If you can, that's a different story. By all means, you know, if you're looking at a problem that you're not really sure of the solution, and it does require you to actually learn some new technology or investigate something new to solve that problem, by all means, I'm 100% for that. And we definitely do that. Voice recognition is a really good example of that because part of our IVR prompting allows for voice recognition. And we use—it's no secret—we use Twilio as one of our partners. And they, out of the box, supply some voice recognition, but it's not working for us because we have obscure languages that just don't translate well, depending on who's speaking them. And it caused a business problem for us because due to the fact that the voice recognition that Twilio was supplying us wasn't recognizing the language that somebody was speaking, it would default to "language not found," and then it goes through this completely other process that takes more time to connect a client to the interpreter. And so we're like, "Great. We gotta fix voice recognition." And so we started digging into it and digging into it. And it turned out that, you know, by the way, Twilio does use Google as their backdrop, but it's not perfect. And if you teach yourself Google's proprietary language for responding to voice recognition, you can actually solve this problem yourself. So that's what we did. We said, "It's a newer technology to us. We don't really know it, but this is the way that we have to solve the problem because we tried all the different things that we could find that were recommendations to tweak Twilio's voice recognition and their utilization of Google's voice recognition." So, "All right. Yeah. Beat them. Join them." So, yeah. That was a part where we had a business problem—in order to solve that business problem, we had to pick up a new technology. It took longer than we wanted it to, but we're in the process now of releasing those changes. So, absolutely, there's certain times where you can actually, you know, build for that case and scope out and project the times for that case. The stuff that I'm talking about is more along the lines of, you know, coming out of, like, AWS re:Invent and seeing these fantastic new services that are there and immediately, you know, incorporating them into your next sprint. That, to me, is the foolhardy approach. You got to do that. And your example is exactly, like, it's a great balance. It's like, "Well, we've still got this stuff that we're doing over here, but we can play with ChatGPT to see if we can, you know, optimize and save time." I love it. I mean, I frankly really wanna get into using ChatGPT for code reviews and documentation because that's the part every engineer hates.

(Joel Beasley at 00:12:30) Yeah. Yeah. Because I think the Codex is the specific language model that was trained on all the different GitHub code, and ChatGPT is an offshoot from DaVinci. I've been learning a lot about it now because I just thought it was ChatGPT, and I realized, "Oh, this is a small subset spinoff from DaVinci, and then there's these different models that are pre-trained neural networks, and then you can fine-tune them." And all of this information, I was just blown away by it. And the biggest reason is because I'm also a consumer just as you are. So I go about my life. I see deepfake stuff. Right? That's something I think every technologist has seen, obviously to varying degrees, the quality, but it's getting significantly better year over year. And then because I'm in audio, we found this—oh, man. It is so cool. It basically does a better job editing the audio quality than an audio engineer. Josh is gonna hate me. Don't hate me, Josh. But we took—we wanted to test this. Right? Because Adobe bought this startup, and they called it, like, Adobe Podcast now. I don't know if they're out of beta or whatnot, but we uploaded our worst background noise quality conversation we've ever had, the source of it, into the system. This wasn't one Josh edited, but we uploaded it into the system, and then we took the completed file that was edited by a human, and then we took what came out of the Podcast app, and it was better than what the human had edited. And I was blown away. So obviously, that's just one small part of the workflow—it's just improving the audio quality and reducing background noise, and you have to, you know, clip for content. There's all these other things you have to do, but just to see that we're on the path. So here's my question to you. When I saw the deepfake, I also, at the same time, saw this thing where I could upload several hours of my voice, which we have because these are separate tracks, and then it could mimic from text with inflection and all of this stuff. Creepily accurate. And so I said, "Okay. Well, they've got the video, and I've got hundreds of hours of video of me and my face and my movements. And I've got hundreds of hours of clean, crisp SM7 audio. How long until I can make a digital twin of Joel that could run an interview with ChatGPT questioning, and the other person doesn't know?"

(Brian at 00:14:51) Wow.

(Joel Beasley at 00:14:52) Because I wanna see if I could put myself out of business. Right? Like, how do you do that?

(Brian at 00:14:56) So that's an interesting thing. That's the biggest fear. Right? With AI, everybody's afraid of losing their jobs. And I was talking to somebody about this this week. In fact, the interview candidate that I was talking to—I said, "Hey, how do you think AI is gonna disrupt your industry?" And I said, "It will. There's no doubt about it." And for things that don't require legal terminology, medical terminology, it can be very disruptive right now. But what I said was—and it's exactly along the lines of what you just said—is this is only gonna help us do other things.

(Brian at 00:15:27) Right? So, you know, go back to like Multiplicity, the movie. What you just described as Multiplicity. You're like, well, crap, I can run my business based off of a deepfake of me with all this audio asking the right questions. And at the same time, I'm gonna be over, you know, having family time or doing the next adventure or the next business that I wanna start.

(Brian at 00:15:48) That's how I look at it too. Robots have been replacing humans forever, and yet we talked about this earlier, yet we're at 3% unemployment, which is unheard of. So it's not replacing everything. We're coming up with different ways to better use our time. And so I just look at AI as the quintessential automate the manual processes.

(Brian at 00:16:15) Right? Anything that's manual and repeatable, you should be looking at automating. That's a portion of it. Like, it's certainly a stretch to say that, but if there's ways in which I can have ChatGPT or the next evolution of that start to replace certain functions of my life, hell yeah, I'm all in. Right? Because, you know, my brain works 20-plus hours a day, and I'd love to be doing, you know, I'd love to be putting my mind to other things with the knowledge that I can execute more effectively by using a software system such as that to do some remedial tasks.

(Joel Beasley at 00:16:50) Have you bounced ideas off of GPT?

(Brian at 00:16:52) Like, problem solving?

(Joel Beasley at 00:16:53) Did it come up with anything good or no?

(Brian at 00:16:55) It came up with some high-level stuff. So I've been toying with building something on my end. So I'm an avid collector. I'm a huge vinyl collector, and I used to always catalog everything. And I've gotten really lazy in my cataloging because I'm rarely home, and it's something that takes my focus because I'm super meticulous. Like, you know, vinyl comes with inserts and all this kind of stuff, and the way that I catalog everything, I wanted to be very specific about exactly what I have, including condition. And so I wanted to start developing a QR code system to where as I receive it, you know, it's basically an inventory management system. I can produce a QR code based off of the UPC, if there is one, or potentially based off of scanning the image of the record itself, and then automatically converting that into, essentially, the database record for my inventory on an AWS S3 bucket. And so I asked ChatGPT and said, build this for me. And I was really shocked at how detailed and step-driven it got. But in the matter of 15 seconds, I had 25 different steps of how to go about configuring it in the console, recommendations on the specific AWS services that they would use, that you should use to be able to build it. And from a high-level architecture, it was pretty damn accurate.

(Brian at 00:18:32) So, and that was a pretty ambiguous ask. You know what I mean? So I was digging it. And that's why I said, you know, that's why I started looking. I'm like, well, crap, like, let's start using this as code reviews. Code reviews is one of my biggest blockers. You know, it's a resource constraint. Nobody wants to do it. It's administrative work. If I could use that as my code review engine, I'd save, you know, at least 15 hours a week of engineering productivity. So that's where I wanna get into it. And then plus, you know, like I said, documentation is always a challenge. So, you know, I'd love to be able to just automatically produce documentation for our architecture and software management.

(Brian at 00:19:05) Good documentation. Right? Documentation. Yeah. That basically just automatically generates a knowledge base for any engineer that's coming on board. And it's like, by the way, go over here. Done. You don't have to worry about spending time with another engineer, saving me some pair programming time, all that kind of stuff. So I see definite opportunities of incorporating that into our natural workflow.

(Joel Beasley at 00:19:37) So when I saw this and played with it, I had a week of, no shame, like, the sky is falling.

(Brian at 00:19:44) Yeah, right?

(Joel Beasley at 00:19:45) Right? Of course. Because I'm very single-minded at times, and so I wanna figure out, like, how do I rationalize what's going on around me and then figure out how to take action and move myself forward, right? And it took me, usually I can do that in minutes or in hours or in a day, but this took me basically a week. And so here's my takeaway from it. It's an advanced technology that is doing amazing things.

(Brian at 00:20:10) Mhmm.

(Joel Beasley at 00:20:10) It's gonna continue to progress faster because now we have better tools to help us build better tools, so that's just gonna continue to progress even faster. The technology is not where it's at today for off-the-shelf deepfake interaction. Maybe three to five years it'd get there, or if we really tried hard and put an engineering team on it, we could get something close and progress it. But then I fell back to principles. And so the way I've dealt with all of this is the following. I said, every time from my first project in the early 2000s where I helped with some real estate accounting software and some other types of real estate software, what I saw was when you went in and there was a group of people, whoever was curious and was like, hey, what is this? What's going on? They're the ones who stayed when the department got optimized, plain and simple.

(Joel Beasley at 00:21:00) Right? They learned how to use the tool. They were, then we don't wanna have an on-site situation. We wanna train up, you know, we're putting software into a company. We wanna train up experts inside the company. So we'd find two or three, it would optimize the department, 20 people end up moving elsewhere, and then those two or three people stay, and they run the system now. And so that's the principle I have seen my entire life. It's whoever's curious, whoever starts playing with the technology, whoever starts understanding it, those are the people that stay regardless of how much stuff gets wiped out.

(Brian at 00:21:33) So—

(Joel Beasley at 00:21:34) As long as I stay curious and as long as I keep playing and checking in and all of that, like, that movie Will Smith, I, Robot. Yes. Yes. So I rewatched it on the road trip, and I thought to myself, like, man, this is just so likely. I don't think I could be convinced we're not on this path. It's either we get there or we blow ourselves up first.

(Brian at 00:21:56) No, I don't disagree with you on that. I think, we're looking, humans are lazy. Think about that, right? Like, we're all trying to make our lives easier. And this is all stuff that makes our lives easier. Look, you can go back to everything. Go to the car, right? Went from horses to cars. Everybody thought we were nuts. It was to make our lives easier, right? And that's the real, the success of businesses is based off of, are you really solving a problem that matters? And this solves time problems. And again, I like what you said. Like, it's a curiosity thing. And that's one leadership principle that we specifically brought over from Amazon: learn and be curious. Are you constantly learning? And something that takes work away from me enables me to learn other new things. So I don't fear it as much as I wanna see it evolve.

(Brian at 00:22:53) I think the biggest challenge with AI right now, and it's still, I mean, it's easy to prove this, right, is the voice recognition component of it. It's the ability to actually have an audio verbal conversation. Typing things in is obviously producing results. I mean, you could look at Google as the big game changer in that, because back in the day when Google first came out, it could take five words and give you exactly what you were looking for, right? But when it comes to voice recognition and being able to have that verbal conversation, I think that when that happens, that's when this is a mature technology. And it's not far away, right? To your point around your explanation of that, the audio software and being able to look at inflection and facial recognition are not that far away. And deepfakes obviously prove that that's getting there, at least from the one-way conversation. I don't know about the actual receiving of the verbal communication and then being able to produce, like, a conversation. Oh, I've tried with Alexa. Don't, you know, she's not that great of a conversationalist.

(Joel Beasley at 00:24:03) There is somebody that had a ChatGPT interview another ChatGPT.

(Brian at 00:24:08) No kidding.

(Joel Beasley at 00:24:08) I think they did it on a podcast. I wasn't sure because I didn't listen, but I read some of the transcript, and they are basically saying, hey, act like an expert here and then have this view, and then act like an expert here, have that view. And then they had them have a short conversation. And I was just blown away by it. I mean, it's—

(Brian at 00:24:25) It is really cool. My, Marco loves it. He was all in on it. And, you know, it got me more intrigued with it because originally I was kinda like, oh, yeah, alright, cool. And then I started to play with it. And, you know, it's super disruptive right now for education. You know, people having that write their documents and things like that. But—

(Joel Beasley at 00:24:48) It's amazing.

(Brian at 00:24:49) I like, I said, I just, again, lazy, right?

(Joel Beasley at 00:24:53) Yeah.

(Brian at 00:24:53) Our cultures are, we're a natural lazy race. We wanna only have to do what we have to do.

(Joel Beasley at 00:25:01) Exactly. And it also, I've been watching another one that's curious to me is they've got these cooking hands, like the hands that can cook, and they will take chefs and they'll have them record the dishes, and then they could play it back. And when I saw those hands, I saw Jeff Bezos a few years ago, that's when I got introduced to them. He put on these gloves and then the hands, similar to those very expensive surgery machines. And so I said, it's just a matter, we don't even need to get to humanoid before you get a Roomba with a pole on it and then a set of hands. I mean, you could go help so many people in like their later stages of life with—

(Brian at 00:25:38) Oh, yeah.

(Joel Beasley at 00:25:39) For sure, common chores and all of that. And I just imagine this call center, there'll be these call centers of these humans that are operating these remote android-type things inside of different people's houses as a service. It's like you got your house cleaner and there it is.

(Brian at 00:25:55) Yeah. Why not? I mean, not to go from that to something completely opposite, but, I mean, warfare has already been changed by this stuff, you know?

(Joel Beasley at 00:26:04) Oh, yeah.

(Brian at 00:26:05) The fighter pilot is almost a nonexistent role anymore. You've seen all these movies. You've read all this stuff. Like, most of this is handled by a video game controller in Vegas. And so you see that all along. And it is those types of advances. I don't mean to like compare war and natural days, but it's a huge advancement in technology. And again, what makes our lives simpler? How can we do more with our available time? And that's just what we're trying to accomplish here. Like, if it becomes possibility for me to leverage ChatGPT in a medical conversation, I absolutely want that a part of my system. Absolutely. Because it can, it, you know, I'll get more out of it. It could be potentially more reliable, more consistent, right? And it would save me capacity. It would allow me to do other things. It would enable me to scale countlessly, right? Not worrying about finding all these different people across the world that speak in particular languages, but instead, you know, I've got one source who can communicate in 300-plus languages.

(Brian at 00:27:19) I mean, it makes a whole lot of sense. And then, again, like I said, I don't look at machines as replacing humans. I look at machines or artificial intelligence saving humans time to go do other things.

(Joel Beasley at 00:27:30) So if you take it to the ultimate of let's stay on the human as lazy path, and we create technology to help us do things faster and be lazier, which is great. Let's take that all the way to the end, hundreds of years into the future. If we were to look back and say, what are the humans building? We're all building towards something. I build a component, then you use my component to build something better, and then someone else uses that to build something better, and we just keep layering and layering and layering. When we get to the end, everything's been done. What do you think that thing is that we've built?

(Brian at 00:28:01) Cyberdyne. Yeah. Um, that's a really difficult question. Wow. I never even thought of that. I mean, you're getting into some, like, space-age stuff to where, you know, we've probably built a community where we could live anywhere in our universe or any universe for that matter. It doesn't matter. And if we're really truly human, right, and our goal is to survive, that's the other thing. We're lazy and we wanna survive. It would be basically building Earth to where it sustains itself, and then we've created a planet that doesn't need humans anymore, and then we go find the next planet that we have to build this all over again.

(Brian at 00:28:41) I mean, that's common. If you look through history, right, all the different civilizations, all the different advances of civilizations that could do a lot of the things that we were doing now that, you know, for some reason or other disappeared. I mean, why not? That's what Bezos and Richard Branson and Elon Musk are doing right now to try and get into the space race and go, you know, build a habitat on Mars. It's knowing that what we've done here may be at its max, and then now we just gotta go do the same thing somewhere else. So I just, Star Trek-y a bit, you know?

(Joel Beasley at 00:29:16) It's a bit heady.

(Brian at 00:29:18) Well, because—

(Joel Beasley at 00:29:18) Sure. I first got this a couple years ago when I was watching some, I don't know, it's outside, and I was watching some ants build some stuff. And I just thought to myself, popped in my head, I said, I wonder if I walked up to that ant and I tapped it on the shoulder and I said, do you know the bigger thing that you're building here? Or do you just really like to go from A to B because of whatever reasons you've decided you like to go from A to B? And then I looked into it a little bit more and I came across these ant colonies that build these massive underground structures, and people will pour the concrete into them and then extract them. And I'm like, they know how to do this stuff? This is crazy. They're clearly all working together, but they're not connected, right? If there's hundreds of thousands of these ants and they're on different sides, they're building something together, but they're not connected.

(Joel Beasley at 00:30:03) And it's, to me, it's fascinating because I wanna know where is that information encoded. Like, there's gotta be, it's gotta be somewhere, right?

(Brian at 00:30:11) Some kind of neural transmission that they have that we don't, for sure. Yeah. Yeah. There's an extra sensory.

(Joel Beasley at 00:30:17) I think, okay, look, I'm gonna get crazy here, alright? And then we can wrap up. This is probably the craziest thought that I share publicly. I'll give you an example first. If we go back to the 1900s, right, and I were to tell you that there's this light that humans can't see, bugs can, it's this light, and you would be like, you're crazy, right? But it's infrared, and it always existed around us, and we just, it took us time to get the right technology. I think it's a stupid position to take to imagine that we've detected every possible field around us.

(Brian at 00:30:52) Oh, yeah. Right? We, there's way more than, you know, the five senses, right?

(Joel Beasley at 00:30:57) So I think we'll get there. I think we'll get to a point where we ultimately create some sort of technology or figure out how we're all connected in a different way than just like, oh, we're just meat and bone bags. We're walking around.

(Brian at 00:31:08) For sure. I mean, there's already a lot of published documentation that says we use a small portion of our brains, right? So think about the fact that we might use 10 to 15% of our brain. How do we untap that?

(Brian at 00:31:21) That, to me, is also game changing, right? If we can figure out ways to untap the rest of our brains... You know, I like to consider myself smart, but shit, if I'm only using 15% of my brain, man, I wonder what else I could do with the rest of the 85%. And there's gotta be ways to do it. I mean, look at all the geocoding, or, you know, the DNA decoding that we've been able to accomplish already.

(Brian at 00:31:46) CRISPR.

(Joel Beasley at 00:31:47) Yeah, CRISPR. Yeah.

(Brian at 00:31:48) CRISPR is awesome. Again, could be used in bad ways, but also could fix a lot of, you know, genetic diseases in people, to extend people's lives. So it could help us cure cancer. You know, that's an amazing technology that I've been staying in tune with for quite a while. And that's, in a way, it's a start of being able to, you know, tap into unused portions of the human body and brain, because we're very complex people.

(Brian at 00:32:19) And, you know, what is it that we can invest in? What is it that we can do to pull even more of that out? There was that movie, it was an Albert Brooks and Meryl Streep movie. I kinda can't remember the title of it, but they're in their afterlives. And, you know, they're reviewing their lives on camera, right, and showing all of their fears and stuff like that. And the only way they could pass through is if they prove that they were fearless. But everybody in this world, the business people in this world, were utilizing, you know, 40 to 80% of their brains.

(Brian at 00:32:53) And they were that much smarter, that much more advanced thinkers that, you know, able to see ahead of certain reactions or, you know, the effects of causes. And that's part of what intrigues me as well. It's like, could you think about what we could do to be able to free up our minds? And again, going back to ChatGPT, that could be a reason, right? Because we don't have to think about, you know, some of the simpler tasks. We could just use that to respond to the simpler tasks so that we're using the complexity of our brains to actually go solve less trivial problems. And so that gives us our capabilities to go back in and, you know, really solve cancer, look at ways to produce clean water for the entire globe, get rid of, you know, plastics and come up with creative ways to recycle, you know, pull carbon emissions out of the air and, you know, figure out a way to recycle those as well and use those as fuel or power. Those are things that are all taking place right now, but they're so small that we're not able to make the impact that we could.

(Brian at 00:33:57) And if we just were able to free our brains up and not worry about some of the remedial tasks that we deal with on a daily basis, maybe we could do that stuff.

(Joel Beasley at 00:34:05) I agree. That would be amazing. Did you hear the the episode? I know we do a lot of content, but did you hear the amputation episode? If not, I'll give you, like, the brief.

(Brian at 00:34:14) I did not. I did not.

(Joel Beasley at 00:34:15) Alright, alright. So it's worth the two-minute story. So this guy, brilliant guy, infinite degrees from a young age, Harvard, this, that, the other, right? Scientist, researcher, not businessman, researcher. And I had him on the show because they found this discovery when he was doing regenerative limb research. So he was taking newts or some sort of small thing that could regenerate its tail, cutting the tail off, understanding it, trying to figure out the source of this. Why can some animals regenerate and others can't? And so what he ultimately found was he was a specialist in bioelectrical signaling between cells, cells communicating with each other.

(Brian at 00:34:59) Mhmm.

(Joel Beasley at 00:34:59) And he was able to record the... and I'm butchering it a bit, but he was able to record the bioelectrical signals that are transmitted in the animal who could regenerate, record those signals, and take them to another animal who can't regenerate, cut its limb off, play the signals back to the limb, and it regenerated.

(Brian at 00:35:22) Oh my gosh.

(Joel Beasley at 00:35:23) So what he found is the following. He found that you have to do it within 24 hours. So the cells make the decision within 24 hours of whether or not to just, like, you know, heal the wounded area or to regenerate it.

(Brian at 00:35:40) Oh my gosh.

(Joel Beasley at 00:35:41) Yeah. Isn't that crazy?

(Brian at 00:35:43) That's amazing.

(Joel Beasley at 00:35:44) Yes. Because our DNA contains the elements of how to build our body.

(Brian at 00:35:48) Right.

(Joel Beasley at 00:35:48) Every piece of DNA does. So, like, it knows the layout for my arm because it's what... every cell regenerates every seven years or something like that. So it's constantly rebuilding itself. So it has this knowledge encoded in it, and it's this bioelectrical signal. So then what they're doing is he sold it or he's doing something where some business group is taking it to market for humans. So when they get to an accident, you know, car accident, someone's arm gets crushed in the door, they can cut it off, you know, right there at the site or at the emergency room, and then do this bioelectrical signaling back to it, and then they can regrow their limbs. They're not there... I don't think they're doing the human trials yet, but they've successfully done it to the point where he's completed that project, and it's being taken to market now.

(Brian at 00:36:30) That's absolutely amazing.

(Joel Beasley at 00:36:31) It's bonkers. But here's the sad part, and I'm gonna take it down a little bit. So he gets these emails all the time from amputees.

(Brian at 00:36:40) Oh, yeah.

(Joel Beasley at 00:36:40) That just see the headlines. You know, when the science magazines, they make it seem bigger than it is and write these really catchy headlines, and these amputees see it. And then they'll write them these, like, sad emails, like, "Hey, my marriage has ruined from this. You've gotta... I gotta be a test subject." And then he has to, like... I don't know what he does, but we talked about it a little bit on and off. I don't know which parts made it on, but basically, you know, they don't dig deep enough to know that 24-hour aspect.

(Brian at 00:37:06) Twenty-four hours. Yeah.

(Joel Beasley at 00:37:07) And it's just it's tough, man. Because, but I gotta... you gotta love this guy because he's doing difficult things both scientifically and emotionally. Because, I mean, he has to field those emails still, you know?

(Brian at 00:37:17) Oh, it's, like, exciting, amazing, and heartbreaking all at once.

(Joel Beasley at 00:37:23) Oh, I know.

(Brian at 00:37:24) I know. Da Vinci's gotta be, like, rolling in his grave saying, "Why didn't I think of that?" Maybe we could fly then, right?

(Joel Beasley at 00:37:33) Oh, man. We made a podcast. How do you feel?

(Brian at 00:37:36) I feel great. It's good conversation.

(Joel Beasley at 00:37:38) Thank you so much for listening. And if you found this episode useful, please share it with a friend or colleague who you think would get value from it. And if you have topics that you'd like to hear discussed on the podcast, either add me on LinkedIn or send me an email, [email protected]. Every time I get an email or LinkedIn message, it absolutely makes my day and inspires me to keep going.