WEBVTT 00:00:00.000 --> 00:00:03.080 Welcome to Milestone Moments, the show where 00:00:03.080 --> 00:00:05.960 we explore the journeys that lead to success. 00:00:06.599 --> 00:00:10.220 I'm Sheila Slick, your host and founder of Five 00:00:10.220 --> 00:00:13.859 Milestones. In every episode, we will bring you 00:00:13.859 --> 00:00:17.100 insights from the minds of entrepreneurs, leaders 00:00:17.100 --> 00:00:20.800 and experts who will share not just their expertise, 00:00:20.879 --> 00:00:24.120 but the milestone moments that have reshaped 00:00:24.120 --> 00:00:27.059 their journeys and led to significant achievements. 00:00:27.960 --> 00:00:30.379 So if you're looking for motivation, you're in 00:00:30.379 --> 00:00:33.560 the right place. Subscribe now and discover the 00:00:33.560 --> 00:00:40.259 milestones that mark the path to success. Welcome 00:00:40.259 --> 00:00:43.859 to another episode of Milestone Moments in Business 00:00:43.859 --> 00:00:46.700 and Leadership. I'm Sheila Slick, your host. 00:00:46.939 --> 00:00:51.520 And joining us today is Mike Tedasco, a seasoned 00:00:51.520 --> 00:00:55.320 expert in innovation and leadership. Mike is 00:00:55.320 --> 00:00:58.479 currently a visiting fellow at the James Silberrod 00:00:58.479 --> 00:01:01.460 Brown Center for Artificial Intelligence at San 00:01:01.460 --> 00:01:05.099 Diego State University. Previously, he served 00:01:05.099 --> 00:01:08.760 as the Senior Director of Innovation at PayPal, 00:01:09.060 --> 00:01:12.540 where he led transformative initiatives in technology 00:01:12.540 --> 00:01:16.870 and business strategy. With a wealth of experience 00:01:16.870 --> 00:01:20.390 in fostering innovation and empowering future 00:01:20.390 --> 00:01:24.150 leaders, Mike brings valuable insights on leadership, 00:01:24.510 --> 00:01:27.489 workforce development, and the role of technology 00:01:27.489 --> 00:01:30.989 in shaping the future. Welcome to the show, Mike. 00:01:31.370 --> 00:01:35.129 Sheila, thank you for the kind intro. Let's try 00:01:35.129 --> 00:01:38.090 and empower your audience today. Let's do that. 00:01:38.390 --> 00:01:41.480 I'm excited about this chat. Me too. I don't 00:01:41.480 --> 00:01:43.359 even know like where to start. So let's start 00:01:43.359 --> 00:01:47.620 with PayPal, right? Because we're in an era where 00:01:47.620 --> 00:01:52.280 innovation and AI is such a big part of our lives 00:01:52.280 --> 00:01:54.299 and a lot of people don't know how to navigate 00:01:54.299 --> 00:01:58.359 it or they have fear. So tell us a little bit 00:01:58.359 --> 00:02:01.239 about what you do and what you did. Yeah. Yeah. 00:02:01.299 --> 00:02:02.859 Well, let me let me start with PayPal and then 00:02:02.859 --> 00:02:05.540 we'll get more on what I do today after that. 00:02:05.659 --> 00:02:09.479 So I joined PayPal after a failed startup. I 00:02:09.479 --> 00:02:13.419 was out of my MBA program while everybody else 00:02:13.419 --> 00:02:15.360 was getting a job as a consultant or whatever. 00:02:15.460 --> 00:02:17.939 I'm like. i'm gonna start a comic book company 00:02:17.939 --> 00:02:22.099 because why not um that was literally my plan 00:02:22.099 --> 00:02:25.500 after that and after doing that for two years 00:02:25.500 --> 00:02:27.180 i'm like this is not getting me to where i want 00:02:27.180 --> 00:02:29.360 to be like there was you know many successes 00:02:29.360 --> 00:02:32.479 but like you know it's always you know a step 00:02:32.479 --> 00:02:34.599 forward and two steps back with it and after 00:02:34.599 --> 00:02:36.629 a couple years of doing i'm like okay I need 00:02:36.629 --> 00:02:39.770 to find something else. I was a customer of PayPal. 00:02:39.949 --> 00:02:41.810 That's what I was using to process my payments 00:02:41.810 --> 00:02:46.009 on the e -commerce site that I built. And it 00:02:46.009 --> 00:02:49.129 was very logical. I had a lot of classmates that 00:02:49.129 --> 00:02:51.509 worked there. So when PayPal had this job on 00:02:51.509 --> 00:02:54.969 the mobile team, this was back in 2011, I was 00:02:54.969 --> 00:02:57.370 like, cool, mobile is exciting. There's a real 00:02:57.370 --> 00:03:00.169 future in that and so forth. So I jumped on it. 00:03:00.270 --> 00:03:03.490 And for whatever reason, they hired me. And my 00:03:03.490 --> 00:03:06.590 plan was to be at the company for a year. I wound 00:03:06.590 --> 00:03:10.250 up being there for 11 years. And the first half 00:03:10.250 --> 00:03:13.650 was in various roles within the product world. 00:03:13.889 --> 00:03:15.789 And I could talk more about what that means. 00:03:15.990 --> 00:03:20.099 And the back half was running innovation. And 00:03:20.099 --> 00:03:22.879 which was super fun. As I like to tell people, 00:03:23.000 --> 00:03:26.240 like every Sunday night, I was basically just 00:03:26.240 --> 00:03:29.099 excited to go to work the next day because it's 00:03:29.099 --> 00:03:31.020 like the job was awesome. It was so exciting, 00:03:31.039 --> 00:03:35.159 so much fun. And I just I loved it. And I just 00:03:35.159 --> 00:03:38.569 had a wonderful 11 years there. Well, 11 years 00:03:38.569 --> 00:03:41.990 is a long time. So let's go back to that failure 00:03:41.990 --> 00:03:44.409 that you spoke about. And I want to bring that 00:03:44.409 --> 00:03:48.449 up because even today, right, with AI, you have 00:03:48.449 --> 00:03:51.189 so many people either looking to start a side 00:03:51.189 --> 00:03:54.870 gig or wanting to go into entrepreneurship. And 00:03:54.870 --> 00:03:59.729 I see software as a service just growing and 00:03:59.729 --> 00:04:02.210 growing and growing and growing. And I see a 00:04:02.210 --> 00:04:06.069 lot of founders wondering. How do I take this 00:04:06.069 --> 00:04:08.990 to that next level? And we all know that startups 00:04:08.990 --> 00:04:13.889 have a very high failure rate and failure isn't 00:04:13.889 --> 00:04:16.970 always bad. So tell us a little bit about that 00:04:16.970 --> 00:04:20.670 and how you overcame it and how you see failure 00:04:20.670 --> 00:04:23.509 in general. Failure isn't bad as long as you 00:04:23.509 --> 00:04:26.009 learn from it. And that's the big thing. And 00:04:26.009 --> 00:04:28.589 I think within organizations, I think that's 00:04:28.589 --> 00:04:32.730 often tough because failure impacts your bonus. 00:04:33.560 --> 00:04:36.339 Failure impacts the perception that others have 00:04:36.339 --> 00:04:39.180 with you within the company. And I'll get to 00:04:39.180 --> 00:04:40.399 my start, but one thing that we were actually 00:04:40.399 --> 00:04:43.000 doing at PayPal, in fact, this was right before 00:04:43.000 --> 00:04:45.920 COVID, we were building something that was inspired 00:04:45.920 --> 00:04:48.959 by Ben & Jerry's. Ben & Jerry's at their headquarters 00:04:48.959 --> 00:04:51.160 out in Vermont, they actually have what's known 00:04:51.160 --> 00:04:55.079 as a failure graveyard or an ice cream graveyard. 00:04:55.319 --> 00:04:56.879 So in front of their headquarters, they have 00:04:56.879 --> 00:04:59.720 like little tombstones set up for all of the 00:04:59.720 --> 00:05:01.699 flavors of ice cream that they no longer make. 00:05:03.000 --> 00:05:05.379 Why do they do that? Well, it serves as a couple 00:05:05.379 --> 00:05:07.639 of things. One, it's almost ceremonious to be 00:05:07.639 --> 00:05:09.420 able to put that out there. Like, you know, it's 00:05:09.420 --> 00:05:11.540 like, hey, it's OK. We tried something and, you 00:05:11.540 --> 00:05:14.079 know, it's putting it out there. And it's also 00:05:14.079 --> 00:05:16.660 like a little bit of a reminder that it's OK 00:05:16.660 --> 00:05:19.040 to do these things. Like we want to be a company 00:05:19.040 --> 00:05:22.779 where that's allowed, because if you're not failing, 00:05:22.980 --> 00:05:25.279 you're just not trying hard enough. Like, look, 00:05:25.379 --> 00:05:28.879 if you're applying to colleges and you get into 00:05:28.879 --> 00:05:32.389 every school that you apply to. uh you probably 00:05:32.389 --> 00:05:34.250 should have actually tried to apply to some other 00:05:34.250 --> 00:05:36.930 colleges maybe maybe the next year above that 00:05:36.930 --> 00:05:39.490 or something like you know i mean for the most 00:05:39.490 --> 00:05:41.649 part or like you're so great that you should 00:05:41.649 --> 00:05:43.810 just apply to the one and gotten in i mean you 00:05:43.810 --> 00:05:46.410 did something wrong in the process there like 00:05:46.410 --> 00:05:49.310 failure is part of just everything that we do 00:05:49.310 --> 00:05:51.449 and it's just again as long as you're learning 00:05:51.449 --> 00:05:54.269 from that it's just a signal for everything else 00:05:54.269 --> 00:05:57.689 so paypal we were literally making Like we one 00:05:57.689 --> 00:05:59.470 day went to the store, we bought like these like 00:05:59.470 --> 00:06:01.949 model train size people and all that. And we're 00:06:01.949 --> 00:06:04.589 building a scaled down version about the size 00:06:04.589 --> 00:06:07.350 of a large conference room table of the PayPal 00:06:07.350 --> 00:06:09.889 campus where we're going to have QR codes of 00:06:09.889 --> 00:06:11.569 all the different failed products of the past 00:06:11.569 --> 00:06:14.430 with the founders. Sorry, the creators of those 00:06:14.430 --> 00:06:16.829 products telling the story about them. And so 00:06:16.829 --> 00:06:18.949 that was going to be our little failure graveyard 00:06:18.949 --> 00:06:21.730 that we had there. And it was very resonant with 00:06:21.730 --> 00:06:24.629 me. I was on a product at PayPal called PayPal 00:06:24.629 --> 00:06:27.949 Beacon. And it was an amazing technology. It 00:06:27.949 --> 00:06:29.850 got me into the world of patents, got me into 00:06:29.850 --> 00:06:32.110 all this stuff. It was way, way, way ahead of 00:06:32.110 --> 00:06:34.790 its time. If anybody goes on YouTube, type in 00:06:34.790 --> 00:06:36.769 PayPal beacon and you could see something from 00:06:36.769 --> 00:06:39.470 12 years ago where we were building this and 00:06:39.470 --> 00:06:42.290 was basically a hands -free way to pay for stuff 00:06:42.290 --> 00:06:45.519 in stores. You know, you literally didn't have 00:06:45.519 --> 00:06:47.000 to take your phone out of your purse or your 00:06:47.000 --> 00:06:48.680 pocket. You would walk in, it would identify 00:06:48.680 --> 00:06:51.360 you. If you're going to a Starbucks, it could 00:06:51.360 --> 00:06:54.620 even just see that you're pulling into the parking 00:06:54.620 --> 00:06:57.319 lot and maybe you get the same thing every time. 00:06:57.319 --> 00:06:59.160 And it would anticipate that through machine 00:06:59.160 --> 00:07:02.519 learning techniques and, you know, and have your 00:07:02.519 --> 00:07:04.540 coffee ready for you before you even walk into 00:07:04.540 --> 00:07:06.680 the store. A lot of interesting things like that. 00:07:07.259 --> 00:07:10.790 It wasn't the right time. Like we demoed this 00:07:10.790 --> 00:07:13.269 at Stanford University, right up the street from 00:07:13.269 --> 00:07:15.629 PayPal office. A lot of tech friendly people 00:07:15.629 --> 00:07:18.930 there on University Avenue. We had relationships 00:07:18.930 --> 00:07:22.850 with a few of the merchants on the streets. And 00:07:22.850 --> 00:07:24.730 when I would talk to students about it, they're 00:07:24.730 --> 00:07:26.670 like, why would I ever use my phone to buy something 00:07:26.670 --> 00:07:28.980 in a store? That was literally the answer that 00:07:28.980 --> 00:07:31.920 we were getting again and again in 2013. It failed. 00:07:31.939 --> 00:07:33.959 It failed miserably. The world wasn't ready for 00:07:33.959 --> 00:07:35.939 that. It was cool technology, but we weren't 00:07:35.939 --> 00:07:38.199 solving a problem that people had at that time. 00:07:38.699 --> 00:07:41.040 But, you know, if you remind people of that, 00:07:41.259 --> 00:07:43.860 you know, if I was at PayPal today, I'd be like, 00:07:43.959 --> 00:07:45.480 hey, remember that thing we did 10 years ago? 00:07:45.540 --> 00:07:47.259 Why are we not doing that today? The world's 00:07:47.259 --> 00:07:48.980 a different place. Like, can't we learn from 00:07:48.980 --> 00:07:51.300 that and do that? Like, that's why you just don't 00:07:51.300 --> 00:07:53.379 sweep these under the rug, act like these things 00:07:53.379 --> 00:07:56.240 don't happen, because, you know, a lot of failure 00:07:56.240 --> 00:07:58.600 is just timing. I mean, Apple was not the first 00:07:58.600 --> 00:08:00.879 company that came up with a touchscreen for a 00:08:00.879 --> 00:08:03.319 phone device and so forth. Like, you know, there 00:08:03.319 --> 00:08:06.699 was General Magic did this in the 1990s. The 00:08:06.699 --> 00:08:08.920 90s were not a time. The cell phone networks 00:08:08.920 --> 00:08:10.959 were not ready for this. Like there was, you 00:08:10.959 --> 00:08:12.480 know, I mean, it was just timing. But if you 00:08:12.480 --> 00:08:14.920 kind of repackage that in a different time, a 00:08:14.920 --> 00:08:18.639 failure turns into a huge success. Yeah, even 00:08:18.639 --> 00:08:21.779 in social media, when I see TikTok, I'm thinking, 00:08:21.800 --> 00:08:26.180 well, this was Vine like a decade ago. Vine, 00:08:26.180 --> 00:08:28.759 like it existed and then it ceased to exist. 00:08:28.920 --> 00:08:32.159 So I'm like, is it the algorithm? What makes 00:08:32.159 --> 00:08:35.100 a very similar product succeed versus, you know, 00:08:35.100 --> 00:08:36.960 the other one? And Vine, I think was from Twitter. 00:08:37.059 --> 00:08:40.139 And so it wasn't like a little tiny. Their price, 00:08:40.259 --> 00:08:42.279 Twitter was pretty big at the time when they 00:08:42.279 --> 00:08:44.539 introduced Vine. Yeah, and you never know. I 00:08:44.539 --> 00:08:46.340 mean, and that's why you have to experiment because 00:08:46.340 --> 00:08:49.580 there isn't just one solution of, hey, this is 00:08:49.580 --> 00:08:50.879 how I'm going to build a product that's going 00:08:50.879 --> 00:08:55.139 to succeed. Hey, this is the type of video or 00:08:55.139 --> 00:08:57.299 post that the algorithm is going to love that's 00:08:57.299 --> 00:08:59.639 going to get me, you know, 100 ,000 likes or 00:08:59.639 --> 00:09:01.259 whatever it is, whatever it is you're going like. 00:09:01.799 --> 00:09:03.759 There's always experimentation. Frankly, that's 00:09:03.759 --> 00:09:05.740 what makes all this stuff fun. But if you're 00:09:05.740 --> 00:09:08.059 not experimenting, if you're just doing the same 00:09:08.059 --> 00:09:10.740 thing and so forth, you're going to miss a lot 00:09:10.740 --> 00:09:13.320 because the world that we're in now is changing 00:09:13.320 --> 00:09:17.379 fast. I was teaching an AI class earlier this 00:09:17.379 --> 00:09:21.320 week. Two sessions, a Monday session and a Wednesday 00:09:21.320 --> 00:09:26.259 session. On Monday, I presented one deck. Wednesday 00:09:26.259 --> 00:09:29.580 afternoon before I was teaching, I actually had 00:09:29.580 --> 00:09:33.200 to go back and change about 10 % of all the content 00:09:33.200 --> 00:09:36.360 that I had in there because in the last 48 hours, 00:09:36.580 --> 00:09:38.759 the world changed enough. I'm like, oh God, that 00:09:38.759 --> 00:09:40.120 stuff I was talking about on Monday is now out 00:09:40.120 --> 00:09:42.879 of date. And I'm not joking. And I told the class 00:09:42.879 --> 00:09:44.480 this, I'm like, you are actually getting different 00:09:44.480 --> 00:09:47.600 material than on Monday. Like that's the world 00:09:47.600 --> 00:09:49.399 that we're in. And frankly, if you're always 00:09:49.399 --> 00:09:51.360 just assuming, hey, what we're doing is fine. 00:09:51.580 --> 00:09:53.419 We're not experimenting. We're not doing all 00:09:53.419 --> 00:09:55.679 this other stuff. You are. going to miss out 00:09:55.679 --> 00:09:58.700 on these vast quick quick changes that we're 00:09:58.700 --> 00:10:02.740 going to start to see in our society so let's 00:10:02.740 --> 00:10:04.559 talk a little bit about those changes i'd love 00:10:04.559 --> 00:10:07.059 to pick your brain because i think it's more 00:10:07.059 --> 00:10:09.960 important than ever to adapt it's disrupting 00:10:10.440 --> 00:10:15.080 at an unprecedented pace, the technology. I personally 00:10:15.080 --> 00:10:18.399 had heard machine learning. I don't know that 00:10:18.399 --> 00:10:20.480 I quite understand machine learning. It's kind 00:10:20.480 --> 00:10:23.240 of like the machine continues to learn on its 00:10:23.240 --> 00:10:26.940 own, right? Like it's going from A to B and it'll 00:10:26.940 --> 00:10:29.919 just keep testing how to get from A to B faster. 00:10:30.240 --> 00:10:32.679 That's how I understand machine learning. So 00:10:32.679 --> 00:10:36.919 if you can explain some of this AI so the general 00:10:36.919 --> 00:10:39.379 population that's not a techie, we can understand. 00:10:40.220 --> 00:10:42.220 And I'm not a techie either. That's a great thing 00:10:42.220 --> 00:10:44.080 about that. Again, I started in finance and accounting 00:10:44.080 --> 00:10:47.779 way back in the day. So that's why I love to 00:10:47.779 --> 00:10:50.519 explain things to, as I say, normal folks like 00:10:50.519 --> 00:10:54.360 myself who might not be engineers. So I think 00:10:54.360 --> 00:10:56.799 there's traditional computing, and then there's 00:10:56.799 --> 00:10:58.659 kind of artificial intelligence, machine learning, 00:10:58.799 --> 00:11:00.539 all of these things. Those are the two buckets. 00:11:00.940 --> 00:11:03.879 Traditional computing, you tell a very specific 00:11:03.879 --> 00:11:07.080 code, and you say, you know, print hello world, 00:11:07.179 --> 00:11:10.100 and the words hello world will show up on your 00:11:10.100 --> 00:11:12.460 screen. And it goes down to binary and all this 00:11:12.460 --> 00:11:14.399 stuff, but that's how traditional computing works. 00:11:14.539 --> 00:11:18.220 It is going to do that 100 % of the time when 00:11:18.220 --> 00:11:19.580 it is running that code. It is going to give 00:11:19.580 --> 00:11:21.639 you the exact result that you were looking for. 00:11:22.000 --> 00:11:24.960 The world that we're in with AI and machine learning 00:11:24.960 --> 00:11:27.580 today, and specifically with large language models, 00:11:27.779 --> 00:11:30.399 this would be ChapGPT and Claude and all those, 00:11:30.539 --> 00:11:34.159 they work differently than that. How they work 00:11:34.159 --> 00:11:36.799 is they're trained on a whole bunch of data. 00:11:36.919 --> 00:11:38.960 Like imagine just all the data that's on the 00:11:38.960 --> 00:11:40.940 internet. Every single word that's ever been 00:11:40.940 --> 00:11:43.080 written on the internet is trained in these models. 00:11:43.419 --> 00:11:45.139 What they're doing is they're finding patterns 00:11:45.139 --> 00:11:47.399 in there. And they do this through something 00:11:47.399 --> 00:11:49.759 called tokens. So it's kind of like a representative 00:11:49.759 --> 00:11:53.919 for a word, largely speaking. And they just look 00:11:53.919 --> 00:11:57.279 at patterns in this. So if I said to anybody, 00:11:57.659 --> 00:12:01.820 Mary had a little blank, most people are going 00:12:01.820 --> 00:12:04.440 to say, well, the next word should be lamb as 00:12:04.440 --> 00:12:06.320 part of that, because we know that. That's well 00:12:06.320 --> 00:12:09.759 known. Mary had a little lamb and so forth. The 00:12:09.759 --> 00:12:12.039 AI model will know this too. You could type in 00:12:12.039 --> 00:12:13.919 Mary had a little, what do you think is the next 00:12:13.919 --> 00:12:17.500 word? And any AI model is going to return lamb, 00:12:17.700 --> 00:12:19.960 but it's not always going to return lamb. It's 00:12:19.960 --> 00:12:22.460 going to return it 99 % of the time or something 00:12:22.460 --> 00:12:25.679 like that, because this is all mathematical calculations. 00:12:26.679 --> 00:12:30.200 So, because sometimes people have, and this is 00:12:30.200 --> 00:12:31.559 all based on what people have written in the 00:12:31.559 --> 00:12:34.620 past. They may have written Mary had a little 00:12:34.620 --> 00:12:38.220 Volkswagen Beetle or something or whatever it 00:12:38.220 --> 00:12:40.960 might be. And it's just looking at these connections. 00:12:41.080 --> 00:12:44.080 It's the next word prediction. Now, it's doing 00:12:44.080 --> 00:12:48.539 that to the nth degree. I mean, 15 years ago, 00:12:48.600 --> 00:12:51.519 it was revolutionary when it would predict your 00:12:51.519 --> 00:12:54.460 next word in an email and that you could actually 00:12:54.460 --> 00:12:56.940 do that on an iPhone. I think SwiftKey was one 00:12:56.940 --> 00:12:59.059 of the first companies that did that. And you'd 00:12:59.059 --> 00:13:01.000 be typing and it would say, OK, here's the next 00:13:01.000 --> 00:13:03.690 word. This is what it's doing is saying not just 00:13:03.690 --> 00:13:05.990 the next word, here are the next thousand words, 00:13:06.190 --> 00:13:08.250 here are the next whatever. It's making, it has 00:13:08.250 --> 00:13:11.710 become so much more advanced. But these are just 00:13:11.710 --> 00:13:14.710 all mathematical probabilities. It's a mathematical 00:13:14.710 --> 00:13:17.990 probability based on data that it's seen of what 00:13:17.990 --> 00:13:20.309 the next word is going to be. And that at a very 00:13:20.309 --> 00:13:23.629 basic level is how the large language models, 00:13:23.990 --> 00:13:26.909 ChatGPT, all of those that everyone uses today, 00:13:27.029 --> 00:13:30.210 that's how those things work. So how can we better 00:13:30.210 --> 00:13:33.370 prepare ourselves today for the next, I don't 00:13:33.370 --> 00:13:35.289 even know, 10 years, right? Can we just talk 00:13:35.289 --> 00:13:37.990 maybe five years? What should we be doing as 00:13:37.990 --> 00:13:41.929 small business owners or as professionals to 00:13:41.929 --> 00:13:45.110 make sure that we're still relevant? Let's talk 00:13:45.110 --> 00:13:47.590 five months even, just to be completely honest. 00:13:48.090 --> 00:13:50.750 Let's start there. So here's what I would say. 00:13:51.019 --> 00:13:52.700 And again, I always like to put out this disclaimer. 00:13:52.919 --> 00:13:56.220 I don't own shares in OpenAI or Anthropic. I 00:13:56.220 --> 00:13:58.820 intentionally don't. So I have no stake in this. 00:13:58.879 --> 00:14:00.840 It sounds like I'm a salesperson for these companies. 00:14:01.039 --> 00:14:02.580 There's a lot of good they do. There's a lot 00:14:02.580 --> 00:14:04.379 of downsides in this. We could get to that later 00:14:04.379 --> 00:14:07.600 if you want. But I just do want to preface with 00:14:07.600 --> 00:14:10.559 this. That said, you need to be using these tools, 00:14:10.779 --> 00:14:14.840 full stop. If you are not already using ChatGPT 00:14:14.840 --> 00:14:18.019 or Claude or whatever it is in any of these aspects 00:14:18.019 --> 00:14:21.110 of your business, you're falling behind. And 00:14:21.110 --> 00:14:23.649 that's the honest truth. These models are going 00:14:23.649 --> 00:14:25.909 to get better, but like you need to play with 00:14:25.909 --> 00:14:27.750 them. You need to kind of understand how they 00:14:27.750 --> 00:14:30.269 work and how they operate to see how they're 00:14:30.269 --> 00:14:32.370 going to be able to help you out. One of the 00:14:32.370 --> 00:14:34.990 hard things about this type of software versus 00:14:34.990 --> 00:14:37.669 all the other software you've had before is that 00:14:37.669 --> 00:14:39.350 the possibilities that you can do with these 00:14:39.350 --> 00:14:41.850 models are infinite. And when most people have 00:14:41.850 --> 00:14:44.210 infinite possibilities, they just freeze up. 00:14:44.289 --> 00:14:47.490 They decide to do nothing. You know, Excel didn't 00:14:47.490 --> 00:14:49.750 have that. Well, you type something in this one 00:14:49.750 --> 00:14:51.509 and this one, and there's a formula here. You 00:14:51.509 --> 00:14:53.470 can kind of see how things are connected to that. 00:14:54.029 --> 00:14:57.470 There are just unlimited possibilities with what 00:14:57.470 --> 00:15:00.009 you can do with these models. So what I always 00:15:00.009 --> 00:15:03.409 tell people, start with your personal life. If 00:15:03.409 --> 00:15:05.940 you're not familiar, just like literally. Make 00:15:05.940 --> 00:15:07.980 it your default search engine. Take a company 00:15:07.980 --> 00:15:11.500 like Perplexity, make that your default search 00:15:11.500 --> 00:15:15.480 engine. It's an AI model. It's great. And you 00:15:15.480 --> 00:15:18.159 will find, oh, you can ask much more elaborate 00:15:18.159 --> 00:15:20.240 questions. You will be able to do this. You'll 00:15:20.240 --> 00:15:22.039 be able to do all these other things instead 00:15:22.039 --> 00:15:24.080 of searching in Google as you traditionally did 00:15:24.080 --> 00:15:27.200 in a way that's much more advanced. Sign up for 00:15:27.200 --> 00:15:30.580 the $20 a month ChatGPT version and you can get 00:15:30.580 --> 00:15:32.639 something called Advanced Voice Mode. It's amazing. 00:15:32.840 --> 00:15:37.000 I use it all the time. I use it for driving in 00:15:37.000 --> 00:15:40.120 the car to school. I will have it question my 00:15:40.120 --> 00:15:43.059 kids have a test or something. And I'll say, 00:15:43.139 --> 00:15:45.879 hey, my daughter has a test, fifth grade level, 00:15:46.059 --> 00:15:49.299 U .S. history, Revolutionary War, ask increasingly 00:15:49.299 --> 00:15:52.279 difficult questions, make a multiple choice, 00:15:52.679 --> 00:15:56.159 have her answer them, go. And we'll do that and 00:15:56.159 --> 00:15:57.379 we'll have it going through the speakers in the 00:15:57.379 --> 00:15:59.460 car and it'll just start asking these questions 00:15:59.460 --> 00:16:01.940 for that. Whatever you want to do. I will go 00:16:01.940 --> 00:16:05.029 on long walks with it. Ask it questions. Brainstorm 00:16:05.029 --> 00:16:06.769 things. Think about what's on my to -do list 00:16:06.769 --> 00:16:08.909 or there's a problem I'm trying to work through. 00:16:09.570 --> 00:16:11.950 And the great thing is it transcribes everything. 00:16:12.389 --> 00:16:14.450 So I can even say at the end, hey, can you summarize 00:16:14.450 --> 00:16:15.990 everything we talked about? Can you give me just 00:16:15.990 --> 00:16:18.330 the key takeaways of everything that we discussed 00:16:18.330 --> 00:16:21.730 as part of this? And it will bring all of that 00:16:21.730 --> 00:16:25.049 together in one place. Again, it's, you know, 00:16:25.049 --> 00:16:28.090 or you're a small business owner. You get a bunch 00:16:28.090 --> 00:16:30.850 of contracts coming in. One of my favorite things 00:16:30.850 --> 00:16:32.990 to do whenever I get a contract, I'll throw that 00:16:32.990 --> 00:16:35.490 into something like Claude and I'll say, hey, 00:16:35.669 --> 00:16:38.830 I just got this contract. Is there anything unusual 00:16:38.830 --> 00:16:41.809 in this? Is there anything that is not custom 00:16:41.809 --> 00:16:45.850 in this contract or out of the ordinary? And 00:16:45.850 --> 00:16:48.029 it knows that kind of stuff pretty well and might 00:16:48.029 --> 00:16:49.570 say, well, this is a little bit weird, but like, 00:16:49.629 --> 00:16:50.950 yeah, for the most part, this is a pretty standard 00:16:50.950 --> 00:16:53.669 contract. I'm like, great. Now, if this was like 00:16:53.669 --> 00:16:56.509 a $10 million contract I'm going to sign, I am 00:16:56.509 --> 00:16:59.639 probably going to hire a lawyer, but. For most 00:16:59.639 --> 00:17:03.059 things, like to get an answer in 30 seconds on 00:17:03.059 --> 00:17:05.759 that, like that's pretty incredible. Like, OK, 00:17:05.880 --> 00:17:07.900 I'm not going to read through that. I'm going 00:17:07.900 --> 00:17:10.460 to do this. If it doesn't, you know, if I'm concerned, 00:17:10.819 --> 00:17:12.819 I might throw it through a couple different models. 00:17:12.900 --> 00:17:17.359 I might ask ChatGPT and Claude and Grok and whatever 00:17:17.359 --> 00:17:19.960 the exact same question and just kind of triangulate 00:17:19.960 --> 00:17:22.319 and see, does anybody notice anything wrong here? 00:17:22.970 --> 00:17:24.890 But like, those are all things you can start 00:17:24.890 --> 00:17:26.589 to do. And again, the problem is it's infinite 00:17:26.589 --> 00:17:28.450 things you can do. And that's why you just have 00:17:28.450 --> 00:17:31.650 to start working for that with them and find 00:17:31.650 --> 00:17:34.309 out what is the best thing for you and dealing 00:17:34.309 --> 00:17:36.190 with these models and how it's going to help 00:17:36.190 --> 00:17:38.509 you most. Because these are just tools for us 00:17:38.509 --> 00:17:42.609 to use. So that's the now. And where do you see 00:17:42.609 --> 00:17:46.269 this in five years? The only job that I know 00:17:46.269 --> 00:17:48.910 that's going to exist in five years is a solopreneur. 00:17:49.390 --> 00:17:52.009 That when I talk to students two years ago, when 00:17:52.009 --> 00:17:53.829 I was at, you know, talking to students that 00:17:53.829 --> 00:17:56.190 were graduating, I would say to them, hey, just 00:17:56.190 --> 00:18:00.549 learn these AI tools. It's 2023. Learn these 00:18:00.549 --> 00:18:03.250 tools and you're going to go in there and your 00:18:03.250 --> 00:18:05.369 coworkers are going to look at you like a god 00:18:05.369 --> 00:18:07.869 because you're able to do all these magical things 00:18:07.869 --> 00:18:10.549 in a fraction of the time that they can. Like 00:18:10.549 --> 00:18:13.630 right now in coding, for example, if you're not 00:18:13.630 --> 00:18:17.650 using AI to code, like I. I don't know what to 00:18:17.650 --> 00:18:20.170 even say because it's just going to be that much 00:18:20.170 --> 00:18:24.130 more difficult. It's not perfect. But the new 00:18:24.130 --> 00:18:26.349 Gemini that Google has put out, we were doing 00:18:26.349 --> 00:18:29.049 this just last night in our class. We had people 00:18:29.049 --> 00:18:31.349 coding up games that they were playing within 00:18:31.349 --> 00:18:34.049 three minutes. And they were just putting in 00:18:34.049 --> 00:18:36.170 prompts. This is vibe coding. They're just talking 00:18:36.170 --> 00:18:38.049 in English. They're doing this. They're seeing 00:18:38.049 --> 00:18:39.809 that. And they're seeing the magic behind this. 00:18:40.089 --> 00:18:42.650 Now, it's not as complex as a game that you're 00:18:42.650 --> 00:18:45.549 going to pay $30, $40, $50 for or something like 00:18:45.549 --> 00:18:47.900 that. but it's something and it's customized. 00:18:48.319 --> 00:18:50.079 Like somebody was actually making a game. She 00:18:50.079 --> 00:18:51.819 was making a game for her boyfriend. She's like, 00:18:51.859 --> 00:18:53.380 oh my God, he's going to love this. Like, and 00:18:53.380 --> 00:18:54.900 it was like, oh, it was super personal. Like 00:18:54.900 --> 00:18:58.079 you can do that kind of stuff now. All of these 00:18:58.079 --> 00:18:59.880 tools, sorry, I'm getting totally sidetracked, 00:18:59.880 --> 00:19:01.839 Sheila. I mean, I get excited about this. What 00:19:01.839 --> 00:19:04.900 was the question again? Bring me back. You had 00:19:04.900 --> 00:19:07.240 me like in a daze, just learned it. No, it was, 00:19:07.240 --> 00:19:10.000 where do you see it in five years? Yeah, five 00:19:10.000 --> 00:19:12.460 years from now. Sorry, sorry. Solopreneur, that's 00:19:12.460 --> 00:19:15.049 where I was going. Thank you. But when I talk 00:19:15.049 --> 00:19:18.910 to these students today, I say like, you are 00:19:18.910 --> 00:19:20.789 going, I mean, you already have the concept of 00:19:20.789 --> 00:19:25.329 AI agents and these work decently well. And the 00:19:25.329 --> 00:19:27.750 difference between like chat GPT and an agent 00:19:27.750 --> 00:19:29.690 is effectively an agent. You're just going to 00:19:29.690 --> 00:19:32.210 give like high level guidelines and say something 00:19:32.210 --> 00:19:36.349 like, Hey, I need you to research the Minneapolis 00:19:36.349 --> 00:19:42.369 market for me on. Houses that are under the Zillow 00:19:42.369 --> 00:19:46.150 value within 10 miles of this location, within 00:19:46.150 --> 00:19:50.210 this kind of school district, and they have no 00:19:50.210 --> 00:19:53.529 pink inside the house. Whatever it is, something 00:19:53.529 --> 00:19:55.750 like that. There is no way you could do that 00:19:55.750 --> 00:19:57.369 with a search query. And to actually do that 00:19:57.369 --> 00:19:59.430 would take a ton of time. But these AI agents 00:19:59.430 --> 00:20:01.849 can do that. And probably within 30 minutes, 00:20:01.990 --> 00:20:05.079 they would take... two days of work come back 00:20:05.079 --> 00:20:07.279 to you and say like, okay, here are the results. 00:20:07.440 --> 00:20:09.200 And you look over those results. It might only 00:20:09.200 --> 00:20:12.460 be 90, 95 % accurate, but it's going to save 00:20:12.460 --> 00:20:15.980 you a ton of time with that. This is growing 00:20:15.980 --> 00:20:19.859 exponentially right now. Taking what I described 00:20:19.859 --> 00:20:23.339 there, you would be able to then apply this kind 00:20:23.339 --> 00:20:25.440 of agent concept to just about anything. It's 00:20:25.440 --> 00:20:28.359 like, hey, this file, or actually you could probably 00:20:28.359 --> 00:20:30.740 even say within a couple of years, hey, in my 00:20:30.740 --> 00:20:33.960 email are all of the receipts I have for invoices 00:20:33.960 --> 00:20:36.319 that I've received over the last year. I want 00:20:36.319 --> 00:20:39.460 you to go through my email, find all of those. 00:20:40.340 --> 00:20:42.819 categorize them in proper categories, put them 00:20:42.819 --> 00:20:47.039 into our accounting ledger and go ahead and do 00:20:47.039 --> 00:20:51.059 a first draft of my taxes. That's probably a 00:20:51.059 --> 00:20:54.500 year or so away, maybe two years, like literally 00:20:54.500 --> 00:20:56.920 what I just described there. So that's why when 00:20:56.920 --> 00:20:59.480 I tell students now, the only job that I know 00:20:59.480 --> 00:21:02.240 that's going to exist in five years, it's probably 00:21:02.240 --> 00:21:05.190 something like, you know, a solopreneur. The 00:21:05.190 --> 00:21:07.950 example I gave last night is like, say your passion 00:21:07.950 --> 00:21:12.349 is golf course maintenance. Like you can build 00:21:12.349 --> 00:21:16.309 a piece of custom software that is going to specifically 00:21:16.309 --> 00:21:20.009 serve, you know, the maintenance needs of golf 00:21:20.009 --> 00:21:22.890 courses. Like nobody is probably building that 00:21:22.890 --> 00:21:25.089 software today. It's too hard, too difficult, 00:21:25.150 --> 00:21:27.630 too whatever to do. You can do that. You could 00:21:27.630 --> 00:21:30.450 package that. You could customize that and you 00:21:30.450 --> 00:21:32.809 could sell it to, you know. a fraction of the 00:21:32.809 --> 00:21:35.829 golf courses across the US, you'd be hyper -focused 00:21:35.829 --> 00:21:39.269 on serving their needs. If anything goes wrong, 00:21:39.430 --> 00:21:41.990 and this is one of the key things, because if 00:21:41.990 --> 00:21:44.309 something goes wrong, like if they built that 00:21:44.309 --> 00:21:46.230 themselves, if something goes wrong, they're 00:21:46.230 --> 00:21:48.890 not going to call Sam Altman at OpenAI and say, 00:21:48.970 --> 00:21:51.849 hey, Sam, this is broken. Like they got to figure 00:21:51.849 --> 00:21:54.450 it out. The agent's got to figure it out. Often 00:21:54.450 --> 00:21:56.390 people want to have, and that's not going to 00:21:56.390 --> 00:21:57.910 change. People are going to want to have a human 00:21:57.910 --> 00:22:01.210 at some point in the loop to talk about. And 00:22:01.210 --> 00:22:03.549 that's why I really believe like a solopreneur 00:22:03.549 --> 00:22:06.009 who is hyper -focused on building a solution 00:22:06.009 --> 00:22:10.549 for a specific customer set is going to be the 00:22:10.549 --> 00:22:13.970 one business that I know is going to exist five 00:22:13.970 --> 00:22:16.190 years from now. Everything else is kind of up 00:22:16.190 --> 00:22:19.029 in the air. What about physical robots? So even 00:22:19.029 --> 00:22:22.069 that same golf course, it needs the grass cut 00:22:22.069 --> 00:22:26.089 and the computer, that little AI agent can't 00:22:26.089 --> 00:22:31.220 cut the grass. How far are we from seeing more 00:22:31.220 --> 00:22:35.319 robots taking over some of the actual labor involved 00:22:35.319 --> 00:22:37.799 in some of these sessions? Sheila, I'm going 00:22:37.799 --> 00:22:40.299 to show my age here. My first house that my wife 00:22:40.299 --> 00:22:45.880 and I bought was in 2004. And this was in Ohio. 00:22:46.240 --> 00:22:49.140 And there was a company called Friendly Robotics. 00:22:49.140 --> 00:22:51.859 They were based out of Israel. And I had them 00:22:51.859 --> 00:22:55.579 shipped to me a grass cutting robot in 2004. 00:22:56.019 --> 00:22:58.460 So this was over 20 years ago. I actually had 00:22:58.460 --> 00:23:01.460 one of these. As you can imagine, this was like 00:23:01.460 --> 00:23:05.299 in Cincinnati, Ohio in the suburbs. I was the 00:23:05.299 --> 00:23:07.519 weird guy on the street because I had a grass 00:23:07.519 --> 00:23:09.680 cutting robots while everyone else was pushing 00:23:09.680 --> 00:23:11.980 their things. I would hit a button and the thing 00:23:11.980 --> 00:23:14.180 would just go kind of like a Roomba out there. 00:23:14.299 --> 00:23:16.420 It didn't do a great job, but this is also 20 00:23:16.420 --> 00:23:20.000 some years ago. Fast forward to just last week, 00:23:20.180 --> 00:23:23.480 I was at NVIDIA's GTC, which is their big conference 00:23:23.480 --> 00:23:26.599 that they have here in San Jose, like 25 ,000 00:23:26.599 --> 00:23:29.180 people there. I could not even tell you the amount 00:23:29.180 --> 00:23:31.759 of different robots that I saw there. All of 00:23:31.759 --> 00:23:34.240 these companies building these robots and so 00:23:34.240 --> 00:23:37.759 forth. Figure Tesla with Optimus. You know, there 00:23:37.759 --> 00:23:40.980 was a Disney robot that Jensen Wong, the CEO 00:23:40.980 --> 00:23:44.339 of NVIDIA, had on stage. There's a lot coming 00:23:44.339 --> 00:23:46.900 in robotics, for sure. It's a little bit further 00:23:46.900 --> 00:23:50.400 off than the software side because there's some 00:23:50.400 --> 00:23:53.579 more risks to robots. You know, if the robot 00:23:53.579 --> 00:23:55.599 falls on somebody or whatever. Like there was 00:23:55.599 --> 00:23:57.359 a company called Nightscope. They're still around. 00:23:57.619 --> 00:24:00.640 They had a security robot. Several years ago 00:24:00.640 --> 00:24:03.619 at the Stanford Mall, the security robot rolled 00:24:03.619 --> 00:24:05.839 over a kid's arm. Like the kid was lying behind 00:24:05.839 --> 00:24:08.180 the robot or something. They didn't plan for 00:24:08.180 --> 00:24:10.500 that. That's hard. But that's also a real problem 00:24:10.500 --> 00:24:14.180 to have that. There's much less risk in software 00:24:14.180 --> 00:24:17.680 than there is with robots. So robots will come. 00:24:18.279 --> 00:24:20.240 You know, I would say if you're in something 00:24:20.240 --> 00:24:24.440 that really requires non -repetitive physical 00:24:24.440 --> 00:24:27.660 work in some way, that's hard. I was talking 00:24:27.660 --> 00:24:31.940 to a founder recently who was working on a robot 00:24:31.940 --> 00:24:34.259 that would be doing stuff like cleaning. And 00:24:34.259 --> 00:24:36.940 he was telling me how hard it is to get the thing 00:24:36.940 --> 00:24:42.759 to fold sheets, like to make a bed. Super difficult. 00:24:43.140 --> 00:24:44.880 I mean, if you really think about how precise 00:24:44.880 --> 00:24:48.220 that is and he's like that to him is the holy 00:24:48.220 --> 00:24:51.779 grail is to be able to actually make a bed for 00:24:51.779 --> 00:24:53.920 that. And, you know, and, you know, because there's 00:24:53.920 --> 00:24:56.559 just so many variables in that and have it do 00:24:56.559 --> 00:24:58.700 it somewhat efficiently and not just take like 00:24:58.700 --> 00:25:02.700 a half hour to make a bed. Those robots will 00:25:02.700 --> 00:25:05.400 get that, but that's probably a little bit further 00:25:05.400 --> 00:25:09.650 away. That probably is like. five plus years 00:25:09.650 --> 00:25:12.750 away to like get to that level it will happen 00:25:12.750 --> 00:25:16.190 in our lifetimes not as quickly as some of the 00:25:16.190 --> 00:25:21.670 things that are more software related so since 00:25:21.670 --> 00:25:25.369 you have evangelized creativity to employees 00:25:25.369 --> 00:25:28.829 of every nation what is one effective technique 00:25:28.829 --> 00:25:32.509 that you can recommend to spark innovation in 00:25:32.509 --> 00:25:36.640 our everyday work So here's one thing I believed 00:25:36.640 --> 00:25:39.019 when I was at PayPal. It became our slogan, something 00:25:39.019 --> 00:25:43.559 that I believe strongly to this day. We are all 00:25:43.559 --> 00:25:46.519 innovators. Everyone can innovate is what we 00:25:46.519 --> 00:25:49.279 would always say. And it didn't matter what your 00:25:49.279 --> 00:25:51.960 function was, what your background was. We are 00:25:51.960 --> 00:25:55.539 innovators by just like the nature of us as part 00:25:55.539 --> 00:25:58.180 of our species. This is how we got to where we're 00:25:58.180 --> 00:26:01.680 at today in society. The key to innovation often 00:26:01.680 --> 00:26:04.700 is just having. The freedom to make mistakes, 00:26:04.980 --> 00:26:07.859 as we talked about before, and even just the 00:26:07.859 --> 00:26:11.119 constraints or even the incentives around creating 00:26:11.119 --> 00:26:14.480 an environment of innovation. If you're not going 00:26:14.480 --> 00:26:16.859 to be rewarded for this, if you're going to be 00:26:16.859 --> 00:26:19.180 knocked for failing or for whatever it might 00:26:19.180 --> 00:26:24.880 be, there is not going to be creativity. I think 00:26:24.880 --> 00:26:27.900 Maya Angelou has a quote saying that we're all 00:26:27.900 --> 00:26:30.539 creative people until the age of eight when we 00:26:30.539 --> 00:26:33.529 basically had it. knocked out of us, beaten out 00:26:33.529 --> 00:26:35.609 of us, or whatever the quote is from her. And 00:26:35.609 --> 00:26:38.029 like, you think about that, like schools often 00:26:38.029 --> 00:26:40.349 do that. I mean, it's always like, there's an 00:26:40.349 --> 00:26:42.210 answer. There's one right answer. Like, you know, 00:26:42.210 --> 00:26:44.069 there's, you know, not all teachers are like 00:26:44.069 --> 00:26:46.089 that, but a lot of just the regiments of school 00:26:46.089 --> 00:26:48.829 and so forth does that. And look, I think that's 00:26:48.829 --> 00:26:50.769 good to have in life, but I think it's, there's 00:26:50.769 --> 00:26:54.150 also time for creativity. And so one thing I 00:26:54.150 --> 00:26:56.730 would recommend, actually, let me, I'll tell 00:26:56.730 --> 00:26:58.150 a story. In fact, somebody I used to know at 00:26:58.150 --> 00:27:00.730 PayPal, this guy was straight out of college. 00:27:01.579 --> 00:27:04.039 I was running innovation. One of the things in 00:27:04.039 --> 00:27:08.039 the innovation we did was file patents. And he 00:27:08.039 --> 00:27:11.559 was like, well, I want a patent. Like, that seems 00:27:11.559 --> 00:27:13.859 cool. I want to be able to do that. So what he 00:27:13.859 --> 00:27:18.779 did was he put aside 30 minutes every day to 00:27:18.779 --> 00:27:22.759 just come up with ideas for stuff. And he would 00:27:22.759 --> 00:27:25.519 actually do this while watching episodes of The 00:27:25.519 --> 00:27:28.200 Office. That was like his mental thing. I think 00:27:28.200 --> 00:27:30.279 he had seen the office many times. So it was 00:27:30.279 --> 00:27:32.440 almost mindless for him. So he would put on the 00:27:32.440 --> 00:27:34.940 office. It was kind of chill time. He had a notebook 00:27:34.940 --> 00:27:37.960 and he would just write down ideas. And, you 00:27:37.960 --> 00:27:39.559 know, at the end of that 30 minutes, he would 00:27:39.559 --> 00:27:41.339 send a few to me. He's like, hey, I got anything 00:27:41.339 --> 00:27:44.519 here. From what I remember, like, I think the 00:27:44.519 --> 00:27:48.670 first 10. 15 things I'm like no no this is not 00:27:48.670 --> 00:27:51.170 it like like more of this less of this more of 00:27:51.170 --> 00:27:52.930 this less of this more of this like okay okay 00:27:52.930 --> 00:27:56.269 and he just kept iterating again and again and 00:27:56.269 --> 00:27:59.049 again just through each part of the process and 00:27:59.049 --> 00:28:01.269 had you know sort of a coach in me to just kind 00:28:01.269 --> 00:28:03.630 of like give little Little tweaks of guidance, 00:28:03.829 --> 00:28:06.289 but he's stuck with it. He's persistent. A lot 00:28:06.289 --> 00:28:08.589 of innovation is just being persistent with something, 00:28:08.710 --> 00:28:11.210 to be completely honest. But, you know, he did 00:28:11.210 --> 00:28:14.569 this for probably months and he got his first 00:28:14.569 --> 00:28:16.950 patent. And you know what? He kind of started 00:28:16.950 --> 00:28:20.950 to unlock the code of that. I think within probably 00:28:20.950 --> 00:28:24.819 six months of starting... He had actually filed 00:28:24.819 --> 00:28:28.059 like 15, 20 patents that have been granted since 00:28:28.059 --> 00:28:30.700 by the U .S. Patent Trademark Office. Within 00:28:30.700 --> 00:28:32.940 like a year from the point he kind of figured 00:28:32.940 --> 00:28:36.460 it out that next year, he was just able to do 00:28:36.460 --> 00:28:39.359 all these amazing things. And it comes from just 00:28:39.359 --> 00:28:42.160 persistence. So, you know, finding a way, like 00:28:42.160 --> 00:28:45.940 prioritizing it, setting some time aside where 00:28:45.940 --> 00:28:49.099 he can actually do that, prioritizing that work, 00:28:49.180 --> 00:28:51.529 getting a little bit better every time. Like 00:28:51.529 --> 00:28:53.589 if you're not making, you know, 1 % improvements 00:28:53.589 --> 00:28:55.369 in what you're doing, then it's not going to 00:28:55.369 --> 00:28:57.970 be helpful. Put all of those things together 00:28:57.970 --> 00:29:00.809 and you got somebody who is, you know, able to 00:29:00.809 --> 00:29:03.890 do his goal and much more within a relatively 00:29:03.890 --> 00:29:07.009 short amount of time. Consistency. Persist. Yeah. 00:29:07.109 --> 00:29:10.849 Yes, absolutely. Absolutely. Well, so what is 00:29:10.849 --> 00:29:15.549 your next milestone? My next milestone? Wow. 00:29:17.259 --> 00:29:20.039 The thing I'm working on right now, and I'm almost 00:29:20.039 --> 00:29:22.279 finished, I'm super excited about, I'm actually 00:29:22.279 --> 00:29:25.039 writing a series of children's books. And for 00:29:25.039 --> 00:29:27.400 me, so I have a publisher, they're going to release 00:29:27.400 --> 00:29:31.319 those in late 2026. So they're quite some time 00:29:31.319 --> 00:29:34.700 out, but they've been a little bit of a, they 00:29:34.700 --> 00:29:38.920 go deep into the sciences. So it's actually, 00:29:39.059 --> 00:29:41.910 they're fables about the periodic table. It is 00:29:41.910 --> 00:29:45.990 literally called Periodic Fables is part of that. 00:29:46.049 --> 00:29:47.630 And there are three different stories they're 00:29:47.630 --> 00:29:50.369 going to release. And for me, that's going to 00:29:50.369 --> 00:29:52.809 be a huge, exciting thing, being a published 00:29:52.809 --> 00:29:57.630 author in an area that I'm not a chemist by any 00:29:57.630 --> 00:30:00.009 stretch. So I had to learn a lot through that. 00:30:00.029 --> 00:30:01.529 It was just wonderful just going through that 00:30:01.529 --> 00:30:04.230 whole process. And to me, life is a bunch of 00:30:04.230 --> 00:30:06.150 these little experiments where you learn stuff 00:30:06.150 --> 00:30:08.250 and you bring it to other things in life. And 00:30:08.250 --> 00:30:11.700 I just love that. So I guess that's my next milestone. 00:30:12.140 --> 00:30:14.599 You had done comic books. That's how we began 00:30:14.599 --> 00:30:17.079 the conversation. How is it different than comic 00:30:17.079 --> 00:30:19.599 books? And what are you going to apply from that 00:30:19.599 --> 00:30:22.660 failure of the comic book to the children's book? 00:30:22.980 --> 00:30:25.839 Such a good question. So the comic book business, 00:30:25.900 --> 00:30:27.799 I wasn't actually creating. I'm not an artist 00:30:27.799 --> 00:30:30.099 either. I'm not an engineer. I'm not an artist. 00:30:30.240 --> 00:30:33.819 I'm just a jack of all trades, master of none 00:30:33.819 --> 00:30:36.380 is basically what I am. But what I was actually 00:30:36.380 --> 00:30:40.400 building back in 2009, it was called SketchMaven. 00:30:40.400 --> 00:30:42.720 It was a marketplace for comic book artwork. 00:30:43.119 --> 00:30:44.759 So it was a place where artists could actually 00:30:44.759 --> 00:30:47.539 come, sell their artwork and so forth, and people 00:30:47.539 --> 00:30:50.059 would buy them and so forth as part of that. 00:30:50.279 --> 00:30:53.019 But one of the things I learned just, and frankly, 00:30:53.119 --> 00:30:55.440 spending a lot of time in this world was just 00:30:55.440 --> 00:31:00.029 like layout, design. I've looked at... Thousands, 00:31:00.130 --> 00:31:02.329 tens of thousands, hundreds of thousands, maybe, 00:31:02.410 --> 00:31:04.230 I don't know, of comic pages in my lifetime. 00:31:04.349 --> 00:31:07.349 And just understanding the layout, how to tell 00:31:07.349 --> 00:31:10.990 a story, things like the passage of time within 00:31:10.990 --> 00:31:14.130 a comic book. I think in the great book, if anybody's 00:31:14.130 --> 00:31:16.849 interested, Scott McCloud's Understanding Comics. 00:31:17.210 --> 00:31:20.549 It's probably came out in the 90s. But, you know, 00:31:20.589 --> 00:31:22.950 I remember this so well, like McLeod talks about, 00:31:22.970 --> 00:31:25.809 like, literally the space that you have in between 00:31:25.809 --> 00:31:28.349 panels conveys different things to the audience, 00:31:28.609 --> 00:31:31.309 you know, and so that actually might convey more 00:31:31.309 --> 00:31:33.950 of a passage of time versus less and all these 00:31:33.950 --> 00:31:37.369 things. It's a completely different and unique 00:31:37.369 --> 00:31:40.769 art form that, you know, nobody out there has 00:31:40.769 --> 00:31:43.029 mastered. There are so many different techniques. 00:31:43.210 --> 00:31:45.269 There are different cultural perceptions in this 00:31:45.269 --> 00:31:48.359 world. And for me, yeah, I think just spending 00:31:48.359 --> 00:31:50.599 a lot of time with artists, with people in this 00:31:50.599 --> 00:31:52.640 world has given me a whole appreciation that 00:31:52.640 --> 00:31:55.759 I'm trying to, as a writer, convey some of that 00:31:55.759 --> 00:31:57.839 to the wonderful artists that I'm working with 00:31:57.839 --> 00:32:01.480 on the piece. Interesting. Well, it was a marketplace. 00:32:02.480 --> 00:32:06.880 I love the chemistry because so many kids struggle 00:32:06.880 --> 00:32:11.039 with science or chemistry. I did. I surely did. 00:32:11.299 --> 00:32:14.839 I love math and I love technology. And in the 00:32:14.839 --> 00:32:18.680 sciences, it's not my forte, right? So I'd probably 00:32:18.680 --> 00:32:22.420 be a great candidate to perhaps try the periodic 00:32:22.420 --> 00:32:26.440 fables to see if they stick with me, where my 00:32:26.440 --> 00:32:29.259 daughter right now is getting a PhD in integrative 00:32:29.259 --> 00:32:33.000 biology. And I'm like, whoa. Yeah, I'm constantly 00:32:33.000 --> 00:32:35.869 reminding her. And I'm like. The key is to be 00:32:35.869 --> 00:32:37.869 able to explain to me what you do, what you're 00:32:37.869 --> 00:32:40.309 studying and the effects and just the basics. 00:32:40.609 --> 00:32:42.910 And, you know, when did I study the periodic 00:32:42.910 --> 00:32:46.309 table? I think I was in 10th grade. Well, I mean, 00:32:46.309 --> 00:32:47.809 and that's something that comes over time. And 00:32:47.809 --> 00:32:51.150 I think Richard Feynman. scientist has a quote 00:32:51.150 --> 00:32:53.210 about this of like you know mastery of a subject 00:32:53.210 --> 00:32:55.430 is being able to explain that to anybody you 00:32:55.430 --> 00:32:57.609 know and that is one of the things large language 00:32:57.609 --> 00:33:00.789 models do amazingly well you could put a document 00:33:00.789 --> 00:33:03.490 into something like google's notebook lm and 00:33:03.490 --> 00:33:06.289 say hey I don't get this. This is a white paper 00:33:06.289 --> 00:33:09.670 about dark matter or something like that. I don't 00:33:09.670 --> 00:33:12.190 understand any of this. Explain this to me as 00:33:12.190 --> 00:33:15.390 if I was in sixth grade. And it could do that. 00:33:15.430 --> 00:33:17.089 And you're like, okay, I think I get it. Now 00:33:17.089 --> 00:33:19.930 let's do ninth grade. Let's do that. And that's 00:33:19.930 --> 00:33:21.890 one of the wonderful things about AI tools is 00:33:21.890 --> 00:33:24.210 they're infinitely patient. You can just keep 00:33:24.210 --> 00:33:26.410 on doing this with them until you really get 00:33:26.410 --> 00:33:28.150 it at the level that you're comfortable with 00:33:28.150 --> 00:33:31.089 as well. And that's a technique I still use all 00:33:31.089 --> 00:33:33.369 the time. I was just asking it the other day. 00:33:34.340 --> 00:33:36.099 about, wait, what was I asking about? I asked 00:33:36.099 --> 00:33:38.920 it about how things work all the time. I was 00:33:38.920 --> 00:33:41.279 asking about how toilets work the other day because 00:33:41.279 --> 00:33:43.000 I was like, oh, I actually really don't know 00:33:43.000 --> 00:33:45.359 how a toilet works. And you know, it's almost 00:33:45.359 --> 00:33:48.740 embarrassing, but I'm like, I don't know. And 00:33:48.740 --> 00:33:50.680 I was even asking it the other day, how does 00:33:50.680 --> 00:33:53.180 a calculator work? I have no idea. You just push 00:33:53.180 --> 00:33:54.799 numbers in there and somehow it gives you the 00:33:54.799 --> 00:33:56.500 answer. Well, how does that actually happen? 00:33:57.069 --> 00:33:59.890 For people who are curious and gosh, like I hope 00:33:59.890 --> 00:34:01.730 everybody out there is curious. That's why you're 00:34:01.730 --> 00:34:04.049 listening to this pod and watching it and you're 00:34:04.049 --> 00:34:05.930 learning. You want to learn more. You want to 00:34:05.930 --> 00:34:08.030 make yourself better. Like for people who are 00:34:08.030 --> 00:34:10.590 infinitely curious, like these tools are amazing 00:34:10.590 --> 00:34:13.150 to be able to use to just ask questions about 00:34:13.150 --> 00:34:16.030 like, I'll be walking around and I'll see something 00:34:16.030 --> 00:34:17.809 like that looks industrial. I'm like, what the 00:34:17.809 --> 00:34:19.590 heck is that thing? I'll take a picture of it 00:34:19.590 --> 00:34:22.030 and say, what is this? Is this like for water? 00:34:22.150 --> 00:34:24.309 What does it do? And I'll explain it to you. 00:34:24.349 --> 00:34:27.949 Like, it's great. Well, thank you so much for 00:34:27.949 --> 00:34:30.949 joining me today, Mike. Pleasure. Pleasure, Sheila. 00:34:31.070 --> 00:34:32.570 No, it's great having you. Great conversation. 00:34:33.150 --> 00:34:36.590 And thank you all for tuning in to another episode 00:34:36.590 --> 00:34:39.030 of Milestone Moments in Business and Leadership. 00:34:39.210 --> 00:34:40.389 Until next time.