Episode Transcript
[00:00:00] Speaker A: Welcome to ID the Future. I'm Andrew McDermott. Today's episode comes to us from our sister podcast, Mind Matters News, a production of the Discovery Institute's Walter Bradley center for Natural and Artificial Intelligence.
You can learn more about the show and access other episodes at mindmatters.
[00:00:19] Speaker B: AI.
Greetings and welcome to Mind Matters News. I'm your entrepreneur wannabe host, Robert J. Marks.
I'm an entreprene want to be because today we're going to talk to a real entrepreneur in artificial intelligence and I'm excited about that. You know, we continue to experience the impact of AI technology in the world.
The future of the use of AI belongs in the hands of entrepreneurs, not academic or business nerds like myself. We're fortunate to have as our guest an AI entrepreneur, David Cops.
Personally, I. I've always wanted to be an entrepreneur, but every venture I explored eventually fizzled. I have three patents and all were stillborn because we didn't have the entrepreneurial wherewithal to get them going.
God didn't gift me to be an entrepreneur. God gifted me to be an academic nerd, which is what I am.
But I'm always fascinated to talk to successful entrepreneurs. David Copps, our guest today, is such a person and it's going to be fun to talk to him. Dave is a renowned entrepreneur to technologist and thought leader with over two decades of experience pioneering advancements in artificial intelligence and other emerging technologies. He's the founder and CEO of a company called Worlds. Dave is at the foremost of AI driven innovation. We're going to talk to him about that and right now he's creating new solutions that merge real world data and digital environments.
Before he was the CEO and founder of Worlds, Dave founded Brighton Space Corporation.
The company is a global leader in machine learning and advanced analytics. I met Dave when he visited Baylor University during Baylor's AI Week. He gave a great talk and we'll link, we'll link that talk on the podcast Notes. David, welcome. It's good to have you.
[00:02:15] Speaker A: Thanks so much. Glad to be here. Robert. Yeah, I was really thrilled to meet you when I came down to Baylor and I think it was a real highlight for me to kind of share the stage with you and just, oh, it was fun.
[00:02:25] Speaker B: And by the way, you didn't respond the way that I instructed you to.
I was gonna say, david, welcome, it's good to have you. And you were supposed to say, bob, it's good to be had. But I didn't know you heard that.
[00:02:38] Speaker A: I thought you were joking.
[00:02:40] Speaker B: Actually, I was, but that's kind of interesting. Look, before we talk about AI and your business, I wanted to talk about something which I didn't talk about in my introduction of you, and I wanted to talk about brain. We're going to be picking your brain, so I want to talk about that brain that I'm going to be picking.
I'm very interested in neuroscience that is revealing more and more evidence that the mind is more than the brain alone. You've underwent a corpus callosotomy operation. I think that. I pronounce that right. Callistomy.
[00:03:19] Speaker A: That's. That's right.
[00:03:20] Speaker B: Okay. It's.
It's brain surgery where the right and left hemispheres of the brain are severed apart. They go down and they separate the right and left brain hemispheres. And the reason they do it, I understand, is because of seizures.
You have a signal on one side of your brain that is communicated to the other side of your brain, which causes the seizure. And by doing the corpus callosotomy, the brain separation, you disrupt that communication path and it takes away the seizures.
[00:03:55] Speaker A: You know?
[00:03:55] Speaker B: A good friend of mine and senior fellow at the Bradley center is Dr. Michael Ignore. He is a neurosurgeon and he occasionally hosts the Mind Matters podcast. Mike is a neurosurgeon and often performs corpus callosotomies. Dr. Ignor wrote a chapter in a book I just co edited called Minding the Brain that addresses whether the mind is more than the brain. Are we more than computers made out of meat?
After a corpus callosotomy, your brain hemispheres are separated and you have kind of in effect, two brains. Yet you don't.
You don't emerge from the operation, though, as two people. You're still you with a single mind. That suggests that what defines you, what defines you is more than the brain.
So, Dave, you've underwent a corpus callosotomy brain surgery, and said it really influenced your outlook. And I'm sure you don't come through that operation the same person that you went in with. Could you. Can you share more about how that event shaped your approach to life and work? And when did you have it? How many years ago was that?
[00:05:00] Speaker A: This was a long time ago. It was 1987. So really, just right after. Right when I was going into college, you know, and the longer story was I had my first seizure, my first grandma seizure when I was four, my fourth birthday party. So I was at my house and I fell on the ground. Everyone thought I was being a joker and was laughing. And my dad was this ophthalmologist. And eye surgeon. He knew it was happening, and over the years, we. He kept me very connected with the medical community on the latest techniques and things that were happening. And I think when I started college, I started having a lot more seizures, and so.
And we elected for brain surgery, I like to tell people, as elective brain surgery. But, you know, it's. There was an incredible maverick surgeon in Dallas named Dr. Bruce Mickey, and we actually flew all over the country looking for a surgeon and found him right here in Texas and Dallas, and. And Dr. Mickey was fantastic.
But, you know, it's. Everybody has something. Something you can kind of look back on and reflect on your life and where things really change for you. And this is a big one for me, you know, because, actually, it's interesting. I guess I did pass away for 18 seconds, you know, after the surgery. And I didn't know this until afterwards. You know, I didn't. You know, I didn't have any of the.
Flying over the table, and people say, come back, Dave. Come back. Didn't have any of that.
[00:06:22] Speaker B: So you were clinically dead for a little while?
[00:06:25] Speaker A: Well, I flatlined for about 18. And the crazy thing was I heard the flatline, you know, so that's something I'll never forget.
[00:06:31] Speaker B: And you heard the flatline?
[00:06:33] Speaker A: I heard the flat line, yeah.
[00:06:36] Speaker B: Okay.
[00:06:36] Speaker A: In the. In a crazy, crazy, crazy thing. But, you know, I think the experience absolutely changed who I am.
Some of the moments I'll never forget, you know, were coming home and looking at myself in the mirror for the first time after surgery and kind of just. I don't know if you've ever done that, just stared in your own eyes for a while, but it's a. It's a strange, interesting experience just to kind of see yourself alive. And I don't think that's something people think about, but, you know, it's. I realized a lot of things after that. Like. Well, one that, you know, I. In my closet, I have my brain scan, my MRI hanging up there, and I have it. It's the first thing I see every morning when I. When I wake up and go in my closet just to remind me that I'm kind of. I got a second chance, you know, and. And I'm here. So I. I feel like I was put on this earth to do something, you know, And I think some of the breakthrough thinking for me was that it's just not about me. Like, I'm here for other people, like, who I am is a possibility. And I kind of went through this for a while why am I here? You know, you start to question a lot of things after you go through an experience like that. And, and I was convinced that there's something bigger for me, that there's a reason I'm here. And, and I'm going to spend the rest of my life trying to figure it out.
[00:07:49] Speaker B: Have you figured it out yet?
[00:07:51] Speaker A: Well, you know, kind of. I did realize it's not about me, you know, and I think that's something I hope people get that, you know, that when you go through life, it's not about you, it's about who you are for other people.
And so I did come up with this thing, you know, I, I decided I was going to recreate myself as a possibility, like if I could emerge as a possibility from this, like, who am I as a possibility for other people? Is kind of the question I asked myself. And, and I came up with that who I am is the possibility of greatness in every person I meet. So I want, when I meet people, I want to inspire greatness. And I don't look at them for who they are today. I look at them who they could be if I stood for their greatness, you know, so. And that's been something I've been practicing literally every, every day since the surgery. You know, not since the surgery, but maybe a couple months after when I was kind of going through this, this inquiry, you know, but so that's who I am. I've decided that I'm here on life to help surface greatness in other people.
[00:08:45] Speaker B: That's fascinating. So this was something that you didn't experience before, but afterwards. Because I've heard that people that have undergone this procedure do emerge with changes in their life. You can't undergo an operation like that and not be changed.
[00:09:01] Speaker A: That's right. And I think what made it real, really real for me was my brother had passed away. He graduated cum laude from Stanford and he actually was in a car wreck. And he passed away about a year before my surgery. And so I was, I was very sensitive to going into the surgery because, yeah, you're sitting there in the, in the pre op and they, they make you sign all these papers and this chance of death, that chance of death, I added it up, it was like 400% chance of death. And so I was serious.
[00:09:31] Speaker B: As I say, you, you, you beat the odds, didn't you?
[00:09:34] Speaker A: Yeah, I told the doctor that, and he just laughed and said, lawyers, you know, and.
But I did, because of the experience with my brother. I wrote letters to all my best friends and said, hey, if I don't make it, I want you to know these things.
Boy, that's an experience.
You start realizing that every day counts. Who you are for other people really matters.
So I think that kind of helped me kind of see what was next for me.
[00:10:03] Speaker B: Okay.
[00:10:03] Speaker A: And I burned the letters afterwards, by the way, so no one got them.
[00:10:09] Speaker B: You burned them? Yeah.
[00:10:10] Speaker A: I didn't.
I didn't think it was appropriate. You know, I made it and I had the conversation. I had a conversation with him, but I didn't. I didn't give him the letters. The letters were for if I didn't make it.
[00:10:21] Speaker B: I see. And you probably gave that to a third party to mail for you. Okay. Oh, my goodness, that's amazing. Now, you said that you flatlined for quite, quite a bit of time and you didn't have a. What I've heard called a near death experience, where people have out of body experiences or they. They go to the. Go to the front por. Porch of heaven or the front porch of hell.
But nevertheless, you said you heard the flatline, so you were still.
Even though you were flatlined, you were still cognizant. But when you flatline, does that mean both your body and your brain or just one?
[00:11:02] Speaker A: I don't know. And this is kind of what I was talking to a doctor afterwards, and he didn't think that would be possible. And I. I just. So I don't know. All I know is kind of what I remember. And what I remember is hearing that and then, you know, darkness. And then that's all I remember. And then I woke up. And so, yeah, I didn't. I always think I should make up a great story about it. You know, I flew over the bed and decided I had more to do and flew back in my body.
No, but anyway, just. But yeah, like you said, though, you can't emerge from that experience as the same person.
You have to pay attention. And part of me, you know, I think you hear a lot all the time how people grew up, you know, in adversarial conditions and it affected who they are. And this is really just another version of that, a more extremic version of that. But I. I don't wish death on everybody, but. But I do wish they could have that experience to understand how important everyone else is. Like, who you are is really expressed by all the people around you.
[00:12:01] Speaker B: Fascinating. You know, there's a great book by a guy named Grayson, and it's called After. Grayson was a medical psychiatrist that dedicated his life to studying near death Experiences.
And first time I heard about near death experiences, I said, oh, come on.
That's just a bunch of baloney. But there's so many anecdotes, and there's more anecdotes today than ever before because we have the medical wherewithal to bring people back from these flatline experiences.
And Grayson spent his life doing that and accumulated a lot of evidence. He started the first journal associated with near death experiences, the first conference associated with it, and it's still an ongoing investigation. And his bottom line at the end of his book, after spending his career doing this, was that he had no idea why these things happen, why these near death experience things happen. It's just. It's just fascinating. So, yeah.
Okay, well, let's talk about something else. You and I have something in common. You play guitar, right?
[00:13:10] Speaker A: I do.
[00:13:11] Speaker B: Okay. Did you play guitar before the operation?
[00:13:14] Speaker A: Oh, yeah.
Yes, I did.
I've been playing since I was 8 years old or so, and just. I love it. It's. It's changed over time. Of course, when you're in high school, it's all about being a rock and roll star, you know? And I think now for me, it's a way to relax and to kind of, you know, find peace and just kind of a great way to be. I like to be alone with my guitar. It's just kind of fun, you know?
[00:13:39] Speaker B: Yeah, me too.
Tell me, did you put together a band?
[00:13:43] Speaker A: Yeah, we've had this ongoing band for 20 years. We just. A bunch of guys have been playing together for a long time. We call ourselves the Brothers of Other Mothers. Brothers of Other Mothers. And we don't ever practice. We just kind of get together and jam, and if somebody wants us to play a party, we'll go play a party without practicing and really more fun, you know, It's a very, very improvisational.
[00:14:10] Speaker B: What kind of music do you do when you get together?
[00:14:13] Speaker A: That's mostly rock and classic rock. I kind of like the new alternative stuff that's coming out and the new R and B that's coming out, like the Allen Stone and Teddy Swims and Lawrence and things like that. But we don't play any of those things.
[00:14:26] Speaker B: Okay, so tell me. I was. Okay. I was reading about your musical.
Your musical things that you were doing, and it mentioned you had a band called the Fish Boys.
[00:14:37] Speaker A: Oh, wow. That was college.
[00:14:38] Speaker B: Yeah, that was college. Okay.
[00:14:41] Speaker A: Yeah, that was my band in college. We could call it the Fish Boys. I think our first CD was called Get Hooked, you know, or Just for.
[00:14:49] Speaker B: That's Right. That's right. Well, I read that, and I had some. I had a good. I had a good cover that you could do. You could do Hooked on a Feeling. What do you think?
[00:14:59] Speaker A: I was surprised we didn't do that.
[00:15:01] Speaker B: Yeah. Yeah, I. Sure you did.
Okay. So. Yeah, that's fun. You know, I think a lot of people wanted to be rock. You know, people don't want to be rock stars anymore. The kids don't want to be rock stars. You know what they want to be? They want to be influencers.
Yeah, they want to come out. Yeah. And they want to come out on YouTube and influence people to do this and that, et cetera, et cetera. So it's. It's really changed. Yeah, I. I wanted to be a rock star at one time in my life, but. Yeah, it just. Just didn't work out. So I went with the other one.
[00:15:34] Speaker A: Turned out okay, though. Robert.
[00:15:35] Speaker B: Yeah. So. So. So you still play and this is an ongoing thing, is that right?
[00:15:39] Speaker A: Oh, yeah, yeah, for sure. I was actually up in my jam room last night. We built a house about four, five years ago, and I told my wife, I only need two rooms. You can build the rest of the house, but I need a jam room and I need a big garage.
So really, I have my. Have my jam room upstairs. It's got five amps and about, I don't know, 15 guitars on the walls and electronic drum set and just a PA system. And so the guys can. My goal is my friends could come over without bringing amps. Just bring a guitar and plug in, you know.
[00:16:09] Speaker B: Do you do the recording and the mixing and the. The.
All the stuff you have to do to finalize it? No, not really.
[00:16:15] Speaker A: Not really? No. We just play.
[00:16:17] Speaker B: So do you have any illusions of grandeur by putting your music on something like Spotify or something?
[00:16:24] Speaker A: You know, I used to. Now I kind of just want to. I. I'm into the enjoyment of it, you know, I just. I love it. It's therapy for me. I just love playing guitar and love playing in a band and just. It's a. It's really a part of who I am, you know?
[00:16:38] Speaker B: Okay. Okay. Well, let's talk about your education. You have a. You have an interesting background in terms of your education to be an entrepreneur. I read that at the University of North Texas, you studied anthropology and cultural corporate culture, I believe it is. I can see corporate culture being something important for a background for an entrepreneur, but anthropology, that's kind of disjoint from entrepreneurism. How did these studies influence your Entrepreneurial journey, if you will.
[00:17:09] Speaker A: Yeah, it's funny. I was a business major at unt and I was kind of bored with it, you know, and I. I dropped in on a class. I literally just kind of dropped in. I saw this thing called or Industrial anthropology, corporate culture. And so I dropped in on the class and I was fascinated by it.
The teacher was Ann Jordan. She. She leads the anthropology department now. But I just love the idea that, you know, people are what make companies. It's not the technology, it's not the product, it's really the people.
And I ended up going to every class even though I wasn't signed up for it. And she at one point kind of called me out and said, who are you? I said, I don't see you on my roster. And I said, I'm not on it. I'm just. I just kind of like your class.
And we became really good friends after that and ended up changing my major to Industrial anthropology and minor in business. So it was. But it's a. It's been a fantastic experience for me, I think, you know, especially in startups now. I actually do talks on startup culture, so I kind of have a talk that I'll give it at startup events and things like that. But it's. It's really, you know, to me, it's. It's one of the most important things about building a small company. It's. It's not.
It's. People look at me and they think, oh, you're a technologist technology company. And I said, no, I'm really not. I'm kind of a people person. You know, what we create is technology. But I love the people side of business. I love seeing what people who are kind of similarly inclined and motivated can accomplish together, regardless of what other barriers other people might see. I just love that. And it's become a real important part of my starting businesses.
[00:18:42] Speaker B: You know, I've always wondered about this.
Let's talk about this. There's all of these apps that are Headhunter apps. You have somebody for your company, you have an opening. You go to this Headhunter app and they give you a bunch of.
A bunch of people. And I would think that just hiring these people based on their resume might be a big mistake, that you got to know these people and know how they're going to. To fit into what. What happens. So I'm not sure what these apps do that just bring in people.
[00:19:11] Speaker A: You know, they're. They don't.
It's. We use recruiters, but we also probably the most probably the best way to find people for us is through our networks because when you walk into our company, you feel it. I had a funny experience. You'll like this. We hired a controller and this guy came in and his first day we had our stand up meeting where we all stand in a circle, we do things and we talk. Someone had a birthday. So we sang the Viking. We sing the Viking birthday song, which is kind of this, Happy birthday, Happy birthday. People dying, children crying, happy birthday. And he looked around with this look of horror in his eyes.
[00:19:48] Speaker B: You know, they go back, go, go, go back. What is this birthday song?
[00:19:53] Speaker A: We call it the Viking birthday song.
[00:19:55] Speaker B: The Viking birthday song.
[00:19:57] Speaker A: It's kind of a joke. We. But we, whenever there's a birthday, we sing happy birthday the regular way. But right afterwards we all go, happy birthday. Happy birthday. People dying, children crying, happy birthday. And then we go, yay.
He was, he was horrified by this and he quit. Yeah, he quit. And it was. But that's culture. That's culture in action. Like, he was not made for this company. And the great thing was he quit. And that day I hired Kristen Frost, my. My now cfo. I've had her for two companies now, and I would never have found her if he wouldn't have left because the Viking birthday song.
So I think, you know, culture. Culture is important. You know, someone can come in no matter where you get them from, recruiter, whatever. But the first thing that happens here is you. You experience culture, like who we are together. And my wife told me once, she said, I walked into your office, I had to tell you this. I came home one night, she said, I have to tell you this. I walked in your office today because we were going to sign some papers, and I just looked around and I felt this buzz, like there's people over here working on something, people over here working on something, and everyone's happy. And she goes, I just, that's your culture. And I said, yeah, that's it. It's something you feel when you walk in the door. It's not what something's written on the wall or in a booklet somewhere, you know, it's what you feel when you walk in the door.
So big on culture.
[00:21:15] Speaker B: Wow. Isn't that interesting? So you're really concentrating on the people aspects. And I'm sure you're interested in their talents and how they can contribute too. But that alone is not enough. I work with a lot of jerks, and it's hard to work with jerks.
I've worked with some people that are really, really nice. You know, I work at Baylor University, and to work at Baylor University, you. You, as a faculty member, you need to be a Christian. And one of the reasons that we have such a great culture is this Christian attitude and the sort of idea that you need to minister and care about other people. I mean, that's fundamental to the Christian message. And because of that, we have an incredible culture.
I've enjoyed working at Baylor because of that. So that's really, really interesting.
So a word I ran across in looking at you was.
You're going to have to help me on the pronunciation. Ubuntu.
[00:22:10] Speaker A: Ubuntu, yeah, Ubuntu.
[00:22:12] Speaker B: Ubuntu. And you've mentioned in relationship to your company, Ubuntu, that sounds African. I'm not sure what it is, but can you elaborate on what that means and how you apply it to your work? Ubuntu.
[00:22:27] Speaker A: Yeah. For any geeks out there listening to this, they'll think, oh, that's Linux, right? There's a version of Linux called Ubuntu. But yeah, I ran into the word. It's actually Swahili. So you're right, it's a Swahili word that loosely translated means, I am who I am because of who we are together.
And I just was affected by. I took that, I said, oh, my gosh, that's the culture I want to create, you know, so. So now we kind of tell people, when you join worlds or if you join brain space, the thing that. And people remember this, I get, I get texts and emails from people years later saying, oh, I thought about Ubuntu today because of this, because of that.
But we tell people that, like, you know, when you come into this company, we have an anti diva policy. I don't, I don't want any divas. I'd rather have pay two or three people that aren't divas and one person is a diva because their divas are disrupted. They think they're better than everybody else.
[00:23:16] Speaker B: And is that the definition of diva, by the way? Somebody that thinks they're better? Somebody that thinks they're better?
[00:23:20] Speaker A: Well, for me it is.
For me it is. Yeah.
But, yeah, we want people to come in and I tell them, the first thing I want you to do is to look at everyone around you and ask yourself, who can I be for them? Like, who can I be for them such that they would be successful? And by the way, everybody's gonna think the same thing for you. And so if you have a whole company just trying to lift that lifts each other up. Good things happen. There's a concept we call CO elevation. You know, and CO elevation is never rise alone. Take somebody with you. You know, like if you're doing something great, go grab somebody, bring them with you. And, and there's things like that in our culture. We want people to understand that you, we don't want you to be as good as you say you are. We want you to be 10x that we're going to create an environment where that's possible. You're going to have a lot of people that want to support you in your greatness, but you're also going to be in a place where we don't celebrate. We don't even recognize failure.
We don't even recognize that it's a human thing. We're all there is here is iteration, recast. Failure is iteration. It's not about something worked or not, it's about what happened and what are you going to do next.
And that unleashes people, you know, and one of my favorite emails I ever got was from a guy that worked at my last company. And after we sold it, about six months later, I get this email and he says, hey, I'm at another place now. And it wasn't until I started working there I realized what culture is because we had it and this place doesn't.
But he said, thanks for being batshit crazy, you know, and let me, letting me fly, you know, I just, I almost got teary eyed, you know, because that's, that's what you want, right?
[00:24:51] Speaker B: Wow. Yeah. You know, I think probably some of the hardest places to work are some of the lower level jobs. Like. Yeah, that I don't see that I don't see this camaraderie, this community sort of spirit. Like at McDonald's, everybody comes in and the boss thinks they're their boss and they, you know, there isn't this relationship that is develop between them and the employees.
So yeah, that's really interesting.
I want to talk to you today about starting a company and I know that you have a lot of experience in doing that and have a lot of very firm thoughts in doing that. One of the things I know about starting a company is you can't go in kind of half motivated. I think that if you go to. No, if you go to startup people and say, give me some money and they say, well. And you say, well, I have another job and I can put 20 hours a week in it, they're not going to be interested in that. You got to be Whole in. So let me begin with a question. How do you identify an idea that has the potential to become a successful company? There's lots of good ideas out here. I think that, you know, some of the artificial intelligence stuff is really, really good. But having it come from academicians and companies, which we'll go into detail, I'm not sure that they have a good business plan. That's not the way to do it. You have to. You have to have idea of what forming a successful company is and what constitutes a successful company. So. And the other, I guess a related question is what role does passion play in choosing the right business to start?
[00:26:25] Speaker A: It's a great question because I think sometimes I mentor a lot of entrepreneurs now, you know, because I can tell them all the things I did that didn't work, save them some time. But I think I don't particularly go looking for ideas.
Well, usually that's not what comes first for me, it's always been the problem comes first. Like, you know, what problems are out there that need to be solved? And how could you, as an entrepreneur, start to take those, Take what you know and what you could. Could create to solve those problems in a way that's not evolutionary, you know, like.
And so that's, for me, that's kind of the way it works. You know, it's like, I also spend an inordinate amount of time trying to predict the future.
I'm kind of a. I'm a voracious reader, so I consume podcast content and I. I watch more YouTube than probably anybody in the world. And because I get to direct what I watch, you know, and. And when I hear about new technology, what excites me is not about the technology itself, but how exciting it could be applied towards a certain problem.
So that's why I'm so interested in AI and kind of fell into it 15, 20 years ago, and now things are just kind of going nuts. But I've always had this thought that this technology could change the world, and it's certainly doing that.
So I think the short answer to that was I don't chase ideas. I become really engaged in problems and then start to. In my way out of the problem is to think about it with technology. Like, how could we utilize technology? Things that exist today and maybe don't exist yet, like, that could exist if we put the right people on it. And that's probably the most exciting part for me. I like building things that haven't been built before. Like, it's. There's no recipe. There's no cookbook. Right. There's just a. There's just you and possibility and some smart people in a room trying to figure out how to make this thing fly. And that's my favorite part, I think. I think I don't. Like, I'm not very good at following recipes and that. Not even. I really mean that. Like, my wife laughs at me.
I'll never pick up a recipe. I always wing it with. With the. When I'm cooking.
It's probably the same way I build companies.
[00:28:31] Speaker B: So that. That comes from an. That comes from an innate talent, though, doesn't it?
[00:28:35] Speaker A: I think so. You spend your life thinking about things and learning things and trying things. And so you walk into these situations informed, you know? And I think where I probably have a sickness is I think entrepreneurship chose me. I don't think I chose it. I think I have a very high tolerance for risk, which is maybe unhealthy.
I'm not happy unless. Unless we're trying. Unless we're. There's some risk, you know, Like, I think it's sort of oxygen for a startup, you know, like, if there's no risk and you have the right people, they're bored. You know, risk actually creates kind of an urgency to figure something out. And so I like that. I think it's.
My wife says I'm unemployable, and so that's why I start companies.
[00:29:20] Speaker B: Okay. Okay.
[00:29:21] Speaker A: It's probably right. She's. I think she's right. I mean, a terrible employee.
That's because I'm always trying to think of a different way, a better way, not just do the current one, you know, so.
[00:29:31] Speaker B: So I think what. I think what you're saying is that you like these dopamine hits from. From this idea of danger. You're probably like. Like the bungee jumping guy who's ready to bungee jump. And you have all of this danger and uncertainty in front of us, front of you, and all of this dopamine comes up, and it feels kind of really, really interesting. And then you jump, and you just have a release of such great, great feelings, you know, I face my risk. I did it. And that reward has to be something in itself.
[00:30:04] Speaker A: Yeah. 100%. Bungee jump is a pretty good example. Pretty good analogy, too, because you do have that. There's trust. Right? Like when you leap in a startup, part of. Part of what makes that leap so easier is you trust everyone around you. Like, we can do this.
I know we can do this.
[00:30:21] Speaker B: I think doing a startup is like jumping and not sureing that the bungee cord will work.
So that would be.
That would be kind of interesting, I don't think.
[00:30:35] Speaker A: I would never jump unless there's a
[00:30:37] Speaker B: good chord, but yeah, okay. Yeah, me too. Me too.
[00:30:41] Speaker A: That's a different kind of risk.
[00:30:44] Speaker B: So let me ask you this. You know, forming a company, a new entrepreneur that has never formed a company really has a lot of obstacles in front of them. They don't have the reputation to fall back on.
And so what were some of the biggest challenges you faced when you started your first company? And what advice would you have for young budding entrepreneurs to start a company? That has to be difficult. That has to be the biggest hurdle to job, I would imagine. I don't have the experience like you do, but.
[00:31:15] Speaker A: But no, you're right. I think I'm the kind of a person that, like some people, you'll ask that question, they'll get very tactical with you. And I'm not that. I'm more kind of a mindset guy. Like, I think a big portion of what you do as a startup leader has to do with mindset. Not just yours, but everyone around your collective mindset, which is culture. Right. And so when I, the challenges for me, like when I started my first company, that's the first, the hardest one is the first one, 100%, because you don't know anything you're trying. Everything you're doing is new, and everything you're trying, you know, could or could not work. You're not smart yet you know, you know about what you're, you know about what you're doing, but you don't know how to, to create it as a business. And so for me, the first ones are the hardest ones. That's when you're finding out who you are as a leader. It's where you discover your, what I call your winning formula. Like, everybody has a winning formula. It's what you do when you're faced with difficult situations. There's a winning formula. There's something you do that always works for you, and you have to build your winning formula. And that happens when you're building your first company, you know, because you're going to find adversity.
If you want to, you want to learn how to deal with adversity, do a startup.
Because there's a lot of things that can go wrong, you know, but, you know, if you have the persistence, I, like, I heard someone say once, and I've really kind of taken it with me that persistence is omnipotence, you know, like when times get tough, focused, persistent attention and constantly iterating as you learn will lead you to greatness every time.
And so if you want to try to get somewhere in life and in business, don't stop until you get there and don't be married to your idea. That's the other thing I would tell people is that one of the things I tell startups, that I mentor them early startups is don't fall in love with your idea. If you create a three year vision and three years from now you hit it, that means you weren't paying attention.
Really, you should have learned things along the way that had you changed, you know, so that's, that's probably not a very. Most people wouldn't say that. But I think especially now, as fast as things are moving, long term visions are, you know, not in a startup, are kind of ridiculous. You have to pay attention now when you get more established and now you have a product that does a certain thing, you can be a little bit more predictive and things like that. When you're starting out, you really have to listen more than you, you talk like just what are markets telling you? What are clients telling you?
How can you change? Like is the product maybe going to be different? Are you going to build it differently because of what you're learning? Because really when you put something out there, all it is, is it's an idea. It's not a, you know, you don't put out something that you know you're going to be doing 10 years from now in a startup. You put something out as an idea and then almost think like it's the way that AI works. Right. With AI we have what we call reinforcement learning, human feedback. Right? Same thing with a startup. You throw something out there and you want to see what people, people think. But markets think, you know, and client potential clients think. And that's when you start the real learning. It's not when you build the product.
[00:34:09] Speaker B: Okay, so I think the biggest challenge for new entrepreneurs is raising capital.
What strategies would you recommend for raising capital as a new entrepreneur? Somebody without this track record?
[00:34:22] Speaker A: Yeah, it's a great question because I think again in your first ones, it's a lot harder.
I don't take for granted my situation right now. I raised $10 million in a series A for this company, Worlds and we didn't have anything but a PowerPoint presentation, we had no technology. But it was only possible because I've built a couple successful companies. My partner and I, Chris Rode, we built a couple successful companies and People wanted us to do another one and we wanted to do another one. So I don't take that for granted. And your first ones, you really have to do unnatural things to raise money.
[00:34:57] Speaker B: Unnatural things.
[00:35:00] Speaker A: What I mean is just you do whatever it takes, you know, like I like strategic investment. Like whatever you're building, like what industry will it affect? And are there companies in that industry that have corporate venture capital funds? And so I like that idea, like trying to align with strategics and early because they have a vested interest in your success. Like find people that will have a vested interest in your success and get them as investors, you know, so that's one thing I would tell people.
And another one is don't chase money. I think the mistake that most startups make is they, they raise money for money's sake. Like, they raise money because it's there.
That's not the reason to raise money. I'm very picky with my investors now. I don't, I won't work with anyone unless I feel like they can really add and be a multiplier for our company.
Because, you know, for me, money is everywhere.
It's now, who do you want to partner with to create greatness together? You know, that's why I'm very picky about investors. But in your first ones, you can't be so picky. So try some strategies, like go to a strategic and definitely get an incubator, like, you know, the capital factor thing or in health wildcatters and deck and things like that. But it's important to get involved in communities and find investors and mentors and, and things like that. The more networking you do, the better. I kind of tell the startup CEOs. You've got to become a storyteller. If you're going to raise money, you have to tell a good story.
And I'm not saying story like a fake thing, I'm saying like a real story. You need to be able to paint a picture of what the world looks like today and what it'll look like after your company is in the market.
Cause investors don't just buy technology.
The biggest mistake I see startups making when they try to go to investment is they, they focus on how, here's how it works, right? Because we're all technologists. So here's how it works. This happens and that happens. And investors don't care. They do care, but they care later about how. What they want to know now is what are you doing? Why is it important?
Who will it affect?
How are you going to go to market who's going to buy this? You know, those things are most important. If I can get through those, then we'll talk about the how. But entrepreneurs tend to start with the how. Don't start with the how. Start with what and why.
[00:37:15] Speaker B: I would imagine that networking, as you mentioned, is fundamental to raising initial capital.
I tell my kids, for example, that it is who you know in terms of your success, but you control who you know.
And in doing that, you can do great and wonderful things. I also tell them that if you're in a room and you have somebody that you're scared to talk to, say the governor walks in, all of a sudden, there's this inherent fear that you don't want to talk to him. I say pick out the person in the room that you're most afraid of. Force yourself to go up and engage in a conversation with them. And it might be awkward for the first few sentences, but eventually it'll get down to a good conversation. And I would imagine again, that the networking was very important. Important in terms of doing this, in terms of raising capital.
And I'm not sure, I'm not sure good ways to do that. In terms of researching it, how would you research it? How would you research that?
[00:38:16] Speaker A: Well, I'll say right off the bat, what you just said is brilliant. That's exactly what you should do.
I told both my sons that when you're in your 20s, now it's time to start to plant seeds. If I could do anything different in my career, looking back on it, it would have been, I planted more seeds earlier on because I'm here to tell you they always come back. Like, if there's somebody you can help do something or have a conversation, later on, that conversation is going to come up and you're going to get a phone call. And so plant seeds, lots and lots of seeds. And I love your idea of being brazen about it. Like, if you think if you're scared of something, the best thing is to go talk to them. Because I think what you're going to find out 9 out of 10 times is that person really appreciates that you came up and had the courage to talk to them. And they might even ask you a question, you know, like, it's. I think people are a lot more willing to speak with you than you think they are. And so I give the same advice. It's like, who are the best people you could be speaking with right now? And reach out to them. Do it.
[00:39:19] Speaker B: And I think what's interesting, if you go to Somebody, then they don't necessarily have to be a.
A rainmaker or. Not a rainmaker, but a source of capital at the time. I'll tell you a little story that happened to me when I was in Seattle at the University of Washington. I worked with a guy named Hal Philip. Now, how. Philip was this great entrepreneur, and I'll tell you a little bit more about him in a little bit. But he was a great entrepreneur. And all of a sudden he got sued by Fluke. Have you heard of Fluke?
[00:39:50] Speaker A: No.
[00:39:50] Speaker B: Fluke Manufacturing Company. Okay. They make. They make kind of electronic equipment. And he went into this partnership with them where they were jointly developing an oscilloscope with new technology, and they were very litigious. And they later actually got sued and lost for. What do they call it? It's when you over sue somebody. I forget what it's called, but they got accused and convicted of that. But that was happening to how he spent all of his money on attorneys.
He foolishly signed that he had to go to binding arbitration. And he went in, and he didn't have money for a lawyer, so he went in himself.
And the lawyer for Fluke came in. And what they do is they assign another attorney to sit there and make the judgment for what happens. Well, he came in and the Fluke attorney came in, and the arbitrator said, hi, Frank. How you doing? How's the kids? You know, it was. It was totally. It was totally, totally cooked. And he went bankrupt, and he went into hiding, and I got involved in it. I actually got subpoenaed to give a deposition about his whereabouts, and it was just terrible. And we were friends. He was bankrupt, but he left the United States. And the reason I did it was because it was Right.
[00:41:07] Speaker A: Right.
[00:41:07] Speaker B: It was. He was in the right, and I wasn't looking for, you know, anything. And he ended up picking up his stuff and moving to Europe, and he started a company there called Quantum Research. Now, it turned out Hal was a great inventor. Okay, you ready for this, Dave? He invented modern touchscreen.
[00:41:28] Speaker A: Really?
[00:41:29] Speaker B: Yes. And he invented modern touchscreen and he licensed it all over the place. Apple came out with the ipod, and they were using his technology. And he sued Apple and he won because he had the wherewithal. He picked himself up after all this adversarial stuff. And it's just an incredible case. But what was the feedback for me, I wasn't doing it looking for any reward, but it turns out he gave me, I think, a quarter of one share of his company when he sold it. For millions of dollars, I got enough money to pay my house off.
[00:42:05] Speaker A: Wow. That's fantastic.
[00:42:07] Speaker B: Yeah, it's an incredible story. So I think a lot of what you're saying, and I agree with you, is, you know, do the right thing all the time. And see, the thing is, Hal and I still remain friends. And why is that? Because he knew I was friends with him when he was down and out. Now, when people approach him, they might think, well, you know how I want your money.
They might come up to him in a friendly, you know, in a friendly way, but maybe they have an alternative motive. So. But he knows with me that we were friends because we were friends. And that was. That was really good. So I think that's an example of the sort of stuff you're talking about.
[00:42:45] Speaker A: That's right. And you said something that hits home with me is just always do what's right. Even when it's hard, always do what's right.
[00:42:50] Speaker B: Yes, yes. In fact, I saw in the Babylon Bee advice for the New Year and ones from Satan was, follow your heart. Do what is in it for you.
And I think that the alternative to that is do what needs to be done when it needs to be done, whether you like it or not.
And we know what's right, we know what's right, and we need to go ahead and pursue that. So that's great advice.
So looking back at the businesses you founded and you've touched on this a little bit, but what leadership qualities are most essential for a founder? If I want to start a business and I want to be an entrepreneur, what leadership quality should I have? Because the founder has to be a leader.
[00:43:34] Speaker A: Yeah, it's a great question. When I saw that on the list, I was thinking, why am I thinking so hard about this?
But my leadership styles really changed over the. The years, and I go back to what a good leader does best, is inspire people and to guide an organization in a way that people want to be involved, they want to work hard, they want to be part of it. You've got to create that environment.
You can't deal with people without creating a good environment. I think that's one thing that people miss. It's one thing to sit in a room with somebody, but what is. What's the environment? What company? What. What have you created around them? You know, and so I focus a lot on creating an environment. So we do several things. Like, one of the things we do is we. We try to take out all distractions. Right. So one of the distractions is, of course, things like healthcare. So I'm a. I don't want people thinking about that when they're here. I want to take that off the table. And so we are a startup that pays 100% of healthcare.
It's unusual. And when I get investors, I tell them that I said my, my people costs are going to be really high because I want people thinking about, you know, what they're inventing and innovating on, not, you know, not worrying about health care. So we do 100 of health care, we pay market or better salaries and you know that we build a culture that people, a place where people want to be there. You know, we have a 98% retention rate.
It's crazy. Like people don't leave when they come on board. But I think that's kind of part of it. Like you've got to create an environment where people can fly and if you don't, then all the conversations you have with people are empty. You've got to create that environment where not only it gives your, your words meaning, like when you say something, you, they can see it in the culture that you really care about people and you care about them being able to do things they couldn't do anywhere else. Like you.
I love talking to developers, engineers because, you know, probably better than anybody, engineers are very right brain. Like it's.
You start to talk foofy on them and you lose them.
[00:45:41] Speaker B: Yeah. In fact, engineers, you can tell them because their heads lean slightly to the right. Yes.
[00:45:49] Speaker A: Yeah.
But I love it because I get challenged on stuff like when I tell people that failure doesn't exist in this company. I remember one time I was doing my startup talk at a tech wildcatters and this engineer stood up and raised his hand. He challenged me on it. He said, hey, I think that's wrong. I said, okay, what do you think?
Because I made the statement that failure doesn't exist in nature. All there is is what happens and what happens next. And he came out and said, well, I'll give you an example of failure. And he said, like a pack of elephants, herd of elephants is going in there, he's challenged by a lion, and the lion kills the leader. And I said, okay, well what happened was a lion killed an elephant.
Your interpretation of that is that he failed. I could make a different interpretation that he was a hero.
So all that matters in startups and I believe in life is understanding what happened and then what are you going to do next? Like that's all that matters, what happened and what you're going to do next.
Whether that was a failure or a success doesn't matter.
You know, I go into companies where they really put an emphasis on failure, like whose fault was it? You know, And I don't care about any of that. If we're, if we're, if we had a culture that gave attention to failure, we'd all be depressed because we're building things that have never been built before. And so things won't work. Every day, every day something breaks, every day we fall down, you know, so you have to kind of say, I got it. It's just about what happened. What I'm choosing to do next, recast failure as iteration, then iterate and iterate, iterate until you reach awesome or choose to stop.
I didn't say fail in there anywhere. And I get the game. It's a mindset. Right. But that's a tough one for engineers.
[00:47:32] Speaker B: It is. And I think that that's one of the secrets of Elon Musk and listening to his biography.
He liked to do things and he liked to look at the over engineering and then cut back and cut back and cut back and keep cutting back until it failed and then add a little bit on. And that's what, that's what you need to work. So he celebrated failure and he said, every time, every time you fail, you learn something. And I think this is what you're saying too.
[00:47:56] Speaker A: Well, it's not a new concept. I mean, Thomas Edison, right?
[00:48:00] Speaker B: Oh, yes.
[00:48:02] Speaker A: He said, I didn't, I didn't fail, but I found 1500 ways that didn't work.
[00:48:06] Speaker B: Yes, but you know what Tesla said? Tesla said Edison was really stupid because if he would have been familiar with chemistry and electricity, he would have reduced the number of things that he was going to test to maybe 500 or so. So, yeah, so there is that too. So we've talked about some of the things that are necessary for a new entrepreneur that wants to get a startup company.
Let's do the negative. If you could go back to your first startup, what would you do differently? What mistakes that you've made have you made that you would advise other people not to make?
[00:48:44] Speaker A: Oh, boy.
I think my short answer to that is I wouldn't change anything. Right. And the reason I say that is because who I am today is a result of that experience.
Not just what worked, but what didn't work. And so I don't know that I would change anything, but I learned a lot. Does that make sense like I.
[00:49:03] Speaker B: It does.
[00:49:05] Speaker A: I don't wish it to be different because if it was Different, I wouldn't have learned what I've learned. So it's more to me. The question to me is more about what have I learned from that and what would I do different next time? And so, you know, that list is long, right? I mean, there's a. There's lots of things that I wish I did that I now know I could do better, you know, and. Because I've learned so much, but I don't think there's anything that I regret or wish was different.
[00:49:29] Speaker B: That's interesting. I used to ask my dad, I would say, what would you do different if you went back in life and you had to live it over? And he gave the same response you did. He says, I wouldn't do anything different because I wouldn't be married to your mother. I wouldn't have you as a son. I wouldn't have Ray, my brother, as a son. He said, I would not do one thing different because it would change what I have now. And what I have today is exactly what I want. I am blessed.
[00:49:52] Speaker A: That's right. I kind of have this also to pile on top of that because I think that's brilliant.
I think that this is partly getting back to my surgery and. And what I learned from that. And, like, perfect is what's happening right now.
Whether you like it or not is not as relevant. But understanding that what's happening right now is perfect, and if you believe that, then you're free to change it.
[00:50:19] Speaker B: Yes.
[00:50:20] Speaker A: You know, I made up this funny slide in my startup deck about perfection. I said, you know, one of the things that kills startups is that is the pursuit of perfection.
Perfection to me is like trying to teach a bear karate, because if. Well, it's really, really hard, and if you're successful, it will kill you.
So I think that's. I just.
Perfect is what's happening right now. Whether you like it or not, it's perfect. Now. What do you want to do to change it? You know, I think sometimes we live a little too much in that space between where we are today and where we wish things were.
And that's not. You know, it's great to be informed by that, but not to live there. Right. Be happy and understand that what's happening right now, regardless of what it is, is perfect. And if you believe it now, you're free to change it.
[00:51:09] Speaker B: Okay, well, let me. Let me ask you a question about, again, qualities that entrepreneur and a CEO need. You have to live a very disciplined life in order to succeed.
So for the budding entrepreneur, what Personal habits or routines have helped you succeed as an entrepreneur.
[00:51:34] Speaker A: Yeah.
It's funny because I was picturing when you said that, that if some of my friends who know me really well heard that you had to be very disciplined, they would just crack up laughing because I'm.
[00:51:46] Speaker B: I'm not that guy.
[00:51:47] Speaker A: I'm not that guy.
[00:51:48] Speaker B: Interesting. Okay. But.
[00:51:50] Speaker A: But I. But I am obviously the older and the wiser I get, I think. But. But some of the things are understanding what you're not good at. You know, I think I. When I met my partner, Chris, you know, he and I are very different, but we're incredible yin and yang. Because I am the. Think about the future. What's possible for you, what's possible for people. Like, that's my. The lens that I use when I look at the world. World. And Chris is the get shit done guy. He is the one that's like, okay, great, but what are we gonna do to make that real in the world? And he's the one that goes out there and just, you know, step by step makes it real in the world. And so we're a great partnership. We are Ying and true yin and yang. And so I think that's one thing is understand what you're not great at. And if it's something you want to be great at, then, sure, go learn it. But there are things that, like, for me, it's, it's. It's like business operations. I'm not an operations guy. I'm a. I'm a leader. But operations and how you structure, you know, a company for hyper growth, that's a. That's a real skill. I have a coo, Todd Stiles, he's just fantastic at that. And he's second company together. You know, he's really good at that. My c. My cfo, Kristen, she's incredible with numbers. She can, she can do things with numbers that I could never do. And I would never do a company without her because I just. She can. And she makes numbers sing. You go to investors. And so those are all things that if I wanted to, I could try and do myself. But understand what you're not great at and go find that in other people and get them in your business. And so that's a. I think that's a big thing. I think also, just don't chase money.
It won't get you anywhere. Money follows. Like, if you do something great, money will follow.
[00:53:29] Speaker B: That's really interesting, you know, because there's a parallel here in academia. In academia, currently, you are rewarded if you publish papers and you're a rainmaker. A rainmaker in the sense that you bring in external funding and you have a lot of people, a lot of professors, a lot of my colleagues that are interested in putting on their cvs the fact that they attracted all of this money. And so they do, they chase money. But I tell you, the big giants in the field, the people that do great things, stick to. To what they're good at, and they, they don't chase money. So I think that there's a parallel there in academia for what you're seeing in business. Gosh, the guy that won the Nobel Prize in neural network. Well, in physics last year, Jeffrey Hinton, he just stayed with neural networks all the time. That's exactly what he did through the AI winters and everything else, and wasn't a chaser of money and developed a great.
Yeah, a great legacy of accomplishments, so.
[00:54:29] Speaker A: That's right.
[00:54:29] Speaker B: That's. That's true. That's interesting because it's, you know, it's.
[00:54:32] Speaker A: I'm one that strongly believes that leadership is less about strategy and more about being like, you know, there's, there's only one great measure of a leader, and it's not about who you are individually, but rather who you are for everyone around you.
[00:54:45] Speaker B: Yes.
[00:54:46] Speaker A: And so it's who. Who are you being? Every day now, I'm using being as a verb, such that every person around you is free and empowered and encouraged to explore their greatness. You know, and so I'm happiest when I'm testing the boundaries of what's possible with a team that's motivated to figure it out.
That's when I'm happiest, you know. And so I'm more interested in what's possible for people than a technology, because the technology will follow, the money will follow. All that stuff will follow.
[00:55:13] Speaker B: Exactly. Because once you develop the reputation by staying, if you will, on the area that you want as opposed to chasing money, you develop a reputation.
[00:55:24] Speaker A: That's right.
[00:55:24] Speaker B: And then eventually people are going to come to you. And that sounds like your experience that now you've developed this, that you've developed the reputation that indeed people will pursue you because you haven't chased the money.
[00:55:36] Speaker A: That's right. We call it a honey pot. Like create the honey pot. Everyone's attracted to the honey pot.
[00:55:40] Speaker B: Exactly.
[00:55:41] Speaker A: Employees, investors, everybody.
[00:55:43] Speaker B: So let me ask you one final question as we wrap up here.
What legacy do you hope to leave? Do you think about your legacy? What legacy do you hope to leave in the entrepreneurial adventure the tech world
[00:55:53] Speaker A: personally, you know, if I were to put something on my tombstone would be. It would be that he was somebody that sought greatness in every person he met. Like, I want that. I want. I want to be remembered for helping people be great, you know, and that. That I lived a life that wasn't about me, it was about who I was for other people. Like, that's what I want my legacy to be. And then as a company, I'm hoping Worlds in particular will be remembered for being a company that built AI for good. That we're a company that built AI that helps people.
So it's a company that helped people. They're very, very best at what they do because they partnered and used Worlds. I think that's a legacy we want as a company.
[00:56:35] Speaker B: Okay, that's a good legacy. Yeah, I think about legacy all the time. I think, though, that a lot of people that are really great don't think about their legacies. They're more interested in doing what. What needs to be done.
[00:56:48] Speaker A: That's right. All about doing. It's more about being.
[00:56:52] Speaker B: Let's do more.
[00:56:52] Speaker A: Be.
[00:56:58] Speaker B: Let's talk about your companies. Was your first company Brainspace?
[00:57:03] Speaker A: I actually did one before that, but it was a small one called Ingenium. But Brainspace was the most recent before Worlds.
[00:57:10] Speaker B: Okay, so tell me what Brainspace did. I think you ended up selling it, Is that right?
[00:57:15] Speaker A: That's right. Yeah.
We really created one of the world's first semantic search engines. So it was an AI engine that could ingest literally hundreds of millions of documents and start to connect the concepts and thoughts and ideas together into what we called collective intelligence. And so a lot of what's happening with ChatGPT right now, but in a much different way. We were using latent semantic analysis. They're using transformers, of course, but I don't think we had quite the scale. We were dealing in hundreds of millions of documents. They were dealing with.
[00:57:41] Speaker B: With.
[00:57:41] Speaker A: They're dealing with, oh, my gosh, billions and billions, right? Different, but it was the same idea. Like, could we. Could we take a raw text, unstructured information, and learn from it without any human intervention? No lexicons, no synonym lists, no thesaurus, anything? And that's what we did. We built an engine that could do that. And the first place that we saw real value in having that was an E discovery, like these large litigations when they have hundreds of millions of docs and they have no idea they were trying to find the bad guys who did what, when, and they typically would literally Take boxes of paper, and then it was computers and sitting around hundreds of lawyers sitting around tables. And we essentially turned that into an exercise that could be done by five people.
We could take all the docs and instantly start to find connections between documents. Even if they didn't use the same words, the system could conceptually relate things. So it wasn't a keyword engine by any means. You might find a related document that doesn't even have the same words, but it's related because it understands the concept of what things are about. So it was a fun company.
[00:58:43] Speaker B: You know, the evolution of this technology is interesting. I used to do expert witnessing for a company, and we were talking with the lawyers and we said, you know, we have the technology now. This was back in the 90s, I think, 1990s. And I said, we have technology now where we can actually take a document and do a word search on the document. It used to be that they took a bunch of beginning attorneys, they stuck them in a room and had them pour over pages and pages of documents. And I told them that, and their eyes just got big and they said, man, this is the best thing in the world. And looking back, that's really old technology.
But brain space came along, it sounds like, and it was able to not only do the word search, but actually do the semantics and in the words in order to look for things which weren't related by simple words.
[00:59:35] Speaker A: That's right.
[00:59:35] Speaker B: And then you had, of course, ChatGPT, the generative AI based on transformers that can do great and wonderful things, but even they're being challenged. Have you heard of. What is it called it?
[00:59:48] Speaker A: Deep Seek.
[00:59:49] Speaker B: Yeah, Deep Seek. I don't know. I've played around with that. That's pretty impressive.
I'm just wondering how that's going to affect OpenAI's business, because now they're doing incredible things.
[01:00:00] Speaker A: Yeah, it's bringing up some really important conversations because, you know, the rumor has it, of course, we've been embargoing all the chips, and so they can't have them, and so they did it anyway. And I've thought for a long time that these new AIs right now, or the algorithms we're building are pretty archaic. I mean, they're good, but they're not great. And that's why we force everything through with computer. And so when you take the chips away from Deep Seq in China, they just had to build better algorithms. And so in a way, kind of wonder if we got a little lazy because we had all the compute.
Yeah. But the bigger question is here's a Chinese company that created an open source model and here we are with OpenAI, which is a closed source model and Claude is closed source.
So I think the next battle you're going to see out there is going to be open source against closed source AI, these foundation models.
[01:00:54] Speaker B: What's interesting in that too is that necessity of course is the mother of invention. The Chinese did not have access to the chips. I have read, but I haven't explored or going into depth about it, but that the Chinese figured out a more efficient way to train these transformer chatgpt, large language sort of models that didn't require apparently the high power chips that we embargoed from them. So something happened there.
[01:01:24] Speaker A: It was kind of, and I understand it's having larger models train smaller models was kind of the technique which is kind of where things are going. You don't need these large generalized models. What you really want is a model that understands your particular area of interest pretty well. And so in the future we're not going to see these large, and it may be already happening now, I think you're going to see lots, collections of smaller models, models connected together so that you can go deep in any one topic and not have just such a generalization, you know.
[01:01:54] Speaker B: So is that what you think deep, deep SEQ has done is kind of fused a number of models, possibly open
[01:02:00] Speaker A: source models and I'm just guessing, right. But I think that, I think they're using the large models to train smaller models and then connecting those together and. But what's interesting to me is it's about the algorithms now. It should give us hope because it means we can, we have so much more we can do than where we are today, like with better algorithms and better ways to learn and better reasoning. Now reasoning is happening on two levels. It's happening not only at the LLM level, but it's also happening now on the gentic level. So you can have reasoning in multiple areas and reasoning will help training. And so there's this kind of a recirculation that's happening that's going to get better and better and better and better. We're going to see crazy progress, I mean, just unbelievable progress in the next few years.
[01:02:41] Speaker B: So do you think that this new approach is going to help with power consumption? You hear about Google wanting to buy a nuclear power plant to power their computers and this half a billion dollar thing that Donald Trump has put together with AI giants. And one of the things they want is these supercomputers which are going to consume a lot of power. I'm going to Memphis later in February.
And they're all concerned about the impact of their infrastructure on the construction of these big AI sort of plants.
It's going to be interesting to see what the future is and see if there's a way that we can get around, if you will, this large power consumption. Maybe there is no way, but maybe there is.
[01:03:28] Speaker A: Yeah, I think there is. And it's funny, everyone kind of, I think we like to freak out about things, but when we freak out, we figure out how to do things better. And right now we need more power. So how are we going to do that? There's all this focus on nuclear and it's appropriate, but there's also a focus on making these models and the chips more and more effective with less power. And so Nvidia's Last chip is 40%, uses 40% less power. You know, one version.
Yeah. And you start to look at the things that are happening with Deep Seek and you're, you realize that we can do a lot with algorithms. If we just create more effective algorithms. We can do a lot with power. We can affect power consumption a lot as well. So all these things together are going to make a difference. I don't worry too much in the future. I would worry about if we're stubborn and not making the changes in the algorithms or the chips and then having to. If that was a state thing, then yeah, you're going to have power problems. But I think we're going to get more and more effective, exponentially more effective over the next few, few years. So I think that'll all these things together will, will create a better picture, I think.
[01:04:30] Speaker B: Yeah, it is going to be interesting to see what happens in the future. I, I think it was Niels Bohr, he, he quoted an old Danish saying that forecasting is dangerous, especially if it's about the future, was his joke.
Yeah, so that's really interesting. So I, I look back historically after World War II, if you'd asked people what needs to be done with electronics, they would say, well, we need better vacuum tubes, we need better filaments in order to increase the reliability and the lifetime of the, of the tubes. Not seeing, of course, semiconductors right around the corner.
And so you never know. I think OpenAI thought that they had kind of a pseudo monopoly on this large language models. Along come these other competitors and now China.
And nothing remains static. It's always changing. It's kind of like an, it's an arms race in artificial intelligence.
[01:05:26] Speaker A: So, yeah, unfortunately you're right. I mean, it is an arms race.
The next arms race is AI.
So that's something we all got to be cognizant of for sure.
[01:05:37] Speaker B: That is true. Now, you sold getting back to Brain Space.
You sold Brain Space. Are you still involved with the company at all?
[01:05:44] Speaker A: No, I'm just their biggest fan. Of course we've sold the company and it's still the standard in the industry. So for you, really. So it's done really, really well in the seven years since we sold it. But very proud of that effort. I think what we created changed the industry and now it's going to change again with Transformers. So Transformers are going to really change that industry.
[01:06:05] Speaker B: So Rain Space is keeping up with the technology, the transformer sort of models. I see. You'll get good, Good, good, good. Isn't that something?
[01:06:13] Speaker A: Yeah.
[01:06:13] Speaker B: Our algorithms are replaced by better and better algorithms. Let's talk about your current company. You started Worlds. What motivated you to start Worlds? You probably had a non compete clause from your Brain Space cell and this had to be orthogonal to what Brain Space did. And so what motivated you to start Worlds and what is World Worlds about, if you will?
[01:06:37] Speaker A: Yeah, so Worlds is. Has built the AI platform for the physical world. So unlike Brainspace, which is a back office AI company, we're taking AI out of the back office and bringing it directly into physical operations.
So we're connecting directly into the cameras and sensors that are in place at today's largest companies and using our AI engine to be the transformation engine. So we're essentially turning the real world into a live data stream, what's happening in the real world into a live data stream. And then you can now use that data to solve problems and create more efficiencies and productivity and safety. And so it's really, when you think about it, it's like we're finally giving people the ability to measure the real. To measure and improve the real world.
So it's a. I love this. To me, it's way more exciting, you know, with back office AI, even ChatGPT and things like that. You're limited. Right. What we're learning, what we're figuring out, is that to teach AI really deeply about the world, we have to go beyond text and images like we have to.
Ideally, we want AI to learn about the world like we do by experiencing it. And the best way to do that today is through the cameras and sensors and the Iot that's in the environments that we serve today.
[01:07:50] Speaker B: So you look at the environment and you use it to update your artificial intelligence, Is that right?
[01:07:56] Speaker A: Yeah. So it is a learning system, right? So as it brings in data, we're able to take a learning from one environment, say, and to use that in another environment. So there's this transfer learning.
But you're hitting on something that was kind of why we really created the company. Like we looked at Computer Vision, this is now four or five years ago, and it was really broken. I mean you create these static models, but the world is dynamic. So you'd create your model and as soon as you create the, the model, it's outdated. And so we came up with this idea, well, what if we could actually create machines that could see and sense the world like people do, but at a scale that's not humanly possible.
And to have that be something, have the learning be something that's almost instantaneous. And we're getting there. Like we created a breakthrough technology we call World's nq. Because the thing we saw that was really broken about AI was the training. It takes forever. And so we had this thought about, well, what if we could actually create a system where you could just turn the cameras on and it instantly creates an index of everything it sees.
[01:08:55] Speaker B: Okay.
[01:08:56] Speaker A: And we did that. But then the second thing is, okay, well how do you then teach it about the things that are important to you?
And so NQ is more like a, almost like a visual search and clustering. Like if I touch an airplane and say show me all the planes and it shows me 1500 planes from all these different frames and videos and I can touch that and say plane. Now I just tagged 1500 images in literally two seconds. That's the equivalent of somebody going through hundreds of hours of video and drawing boxes around every plane they see. So we literally created the, took the AI training industry and flipped it completely upside down. So from a top down manual, human in the loop process, companies like OpenAI have 100,000 people around the world. Low wage workers drawing boxes around things to teach AI about the world. We flip it upside down. So now it's a bottoms up, fully automated AI system which allows you to accomplish with one or two people what normally would take hundreds.
[01:09:53] Speaker B: That is so interesting now in your learning as you observe the world and you continue to teach the AI about what's happening.
You said it was, I got the idea that it was open loop, but no, you're saying that it is supervised by people. I would be concerned about an open loop system, that it would get off track very easily.
[01:10:18] Speaker A: Yeah, and that's a bigger concern too, in AI in general. Like we're starting to now that we've used all the data in the world. Right?
[01:10:28] Speaker B: Yeah.
[01:10:29] Speaker A: How does an AI learn? Well, one, it can create its own data, but that in itself is kind of incestuous. And then.
But what we're finding out is that there's more data than we've ever imagined locked inside of real world environments right now. So if we can be the company that can extract that.
[01:10:45] Speaker B: That's interesting. Yes.
[01:10:46] Speaker A: Yeah. Then we're not having to create synthetic data. We can just learn from the real world. And so the better we get at that. So. But it creates some special problems. Right. Because now you have to kind of create some sort of a system that can take data from multiple sensors, not just cameras, but, you know, wetness sensors or door sensors and things like that.
And how do you connect all these sensors together in a meaningful way to give a. To really form a clear picture of that environment and what's happening? And so we had to kind of come up with some new ideas. Like, one of them was like one of the big challenges with computer vision is it only sees what you teach it to see. Like, if you had a crosswalk and it knows about the crosswalking guard and students, it'll see all them. And it sees the street and it sees the markings, but if an elephant walked by, it wouldn't see it because it wasn't trained to see it.
And so that's an extreme example, but you get the idea. Like, if something can only see what you teach it to see, you're always going to, it's always going to break. And so we came up with this idea of aberration detection. Like, what if we can actually teach a series of cameras to understand what's normal just by watching, and then let us know when something abnormal happens.
[01:11:55] Speaker B: That's called an anomaly filter, right? Sure.
[01:11:57] Speaker A: Anomaly detection. Yep, exactly.
[01:11:59] Speaker B: Okay.
[01:12:00] Speaker A: So anyway, that's some of the different things we're doing, but it's introducing a new kind of a model. They're called large world models. And so where language models are today, it's more images and text. Now it's going beyond that to AI models that automatically convert the data from cameras and sensors into a live data stream that can be used to solve real world problems.
[01:12:22] Speaker B: I think this is really fascinating. I just, it just dawned on me exactly what you're doing, that the corpus of written material in the world has been essentially exhausted. And what you're saying is that this corpus of written material is just part of it, because there's a lot of information and training data available in reality. And that's what you're tapping.
That's really good. So you're increasing what AI can be trained with.
[01:12:52] Speaker A: Yes.
[01:12:53] Speaker B: Let me ask you something.
This is a little technical. Marvin Minsky, who hated neural networks, he just didn't like them at all. But he said something interesting. He said that AI yet is unable to count. Now, this is AI, this is neural networks. This is not image processing, that it's unable to count the number of objects within an image.
So when I went to OpenAI, they many times checked to see if I was human. And what they would do is they would say, here are three. Here's a picture of a can opener, for example. Which of these pictures has three can openers in it? And so I would scroll through a number of different images until I got the one with, there were three can openers in it. And I would say, this is the one. There's three can. There's three can openers in it.
So I wanted to see if OpenAI could hack itself. In other words, I did a capture of these objects. I presented it to ChatGpto and I said, how many objects are in this image? And it screwed it up. It didn't get it at all. I would imagine that you would have similar sort of challenges in your image recognition for the real world, is that right?
[01:14:10] Speaker A: Yes. And it gets even more complex when you have multiple sensors and multiple cameras. Let's just take cameras, for instance. Like if I have three cameras pointing to the same environment, same area, but one camera has an obfuscation of a column or something, and it might see five people, but the one with no obfuscation sees eight people. And so which one's right?
Yeah, so, yeah, so it. Actually, it's a much harder problem than people give it credit for. So we're doing some things about that. So it is interesting, you know, you now that we can train AI so quickly, we can train it on people, and so we can do a pretty good job of counting. But if I were to, I would be lying to you to say that it's 100% every time because of some of the things I just told you. So we're. We're deploying lots of different types of models, you know, to try to help and understand. And we're also including even Iot stuff. So we have an environment, for instance, where people have badges, you know, and so the badges are. Can be. Can be used for reporting that A person's in a certain place now, you might still need a camera for a location or the wear like you think about their new raw material for understanding the world is live spatial data. So think about what's being sensed, regardless of what sensor it's coming from, when it's being sensed, which is usually handled by time series data in the sensor and where it's being sensed and where it can be a lot of different things. Where it could be distance models, it could be depth models, it could be a digital twin, it could be long lat coordinations from Iot sensors. And so there's lots of ways to do where.
The question is, which method should you use for a particular environment? So those are the kind of problems that we're solving every day. You know, but we, but our view is that if we can store the world as if we can represent the world as live spatial data, then we can use AI as a transformation engine to build agents and applications on top of the platform that can solve lots of different problems.
[01:16:02] Speaker B: Wow, that's really interesting.
The other thing that you talked about was the use of augmented reality. I tell people whimsically that Donald Trump said I should stop name dropping.
That's a joke. Dave, by the way.
[01:16:17] Speaker A: Got it.
[01:16:20] Speaker B: I work with a guy at Boeing, his name was Tom Caudell. And if you Google augmented reality, you'll find out that he was the originator of the term. And what he did at Boeing was he wanted engineers to come in, look at engines, and then have overlays of the part that needed replaced and how it was going to be replaced. So how do you use augmented reality in your work to augment what's going on with artificial intelligence?
[01:16:50] Speaker A: So we're not doing it yet. We're waiting for technology to catch up. So, okay, the world for us is going to be when you're in a warehouse and you're wearing some glasses. And the glasses aren't these come with a belt that has a 10 pound battery on it or something.
So when it's possible to have glasses on, what we love about AR over, over VR is that you're, you're now overlaying on the real world. So if I'm wearing my AR glasses and I'm the warehouse security guy and I walk to a certain door, I can look at that door and I can see information about that door. Like, so what AR does for us is it gives information, location. So I could look at that door and if I'm the security guy, it'll pop up and Say, oh, it's locked right now, it was unlocked this time, blah, blah, blah, things like that. If I'm a maintenance guy, it's like, you know, go over here, there's a broken, whatever forklift or what have you. So the glasses I have have a different view. The information that shows up is different. So we're excited about AR right now. We're just using cameras until AI AR kind of hits its stride. But I love the idea of information having location.
I'll tell you, I'll give you a little peek into kind of where we're taking things is that we are going to be collapsing large language models with physical AI. And our, our vision is that you can talk to the world around you and it will talk back.
So imagine having a video and at the bottom of the video, while it's playing, it's being transcribed in real time. And then how you make that transcription more specific instead of being more generalized, you know, is the secret sauce. And we've got ideas for that. But, but the idea is I could walk, you know, with AR glasses, I could walk into the facility, I could look at a door and say, hey, why are you open? And the door would kind of talk back to me and say, hey. Well, I was closed until Robert came in and unlocked me last night at 5 o' clock and didn't leave me, didn't lock me, you know. Okay. You can literally have a conversation with the world around you and that's kind of where we're headed.
[01:18:45] Speaker B: That shouldn't. Because current AI doesn't do that, does it?
[01:18:48] Speaker A: No, I think there's, there's, there's video to text stuff, but in the way I'm describing it to you and having it be specific for a specific environment is, there's definitely not, that's definitely not there, but we will make it there.
[01:19:01] Speaker B: Let me ask you what your vision is for Worlds in the next, say five to 10 years. What companies are you looking to impact? Who's going to be your customers? I've noticed on your website that you already have some customers. You're affiliated with Microsoft and that's kind of cool.
So what is your vision for Worlds the next five to ten years?
[01:19:21] Speaker A: Yeah, well, kind of like what I said earlier, I don't make 10 year visions or even five, maybe three or so, especially in the market we're in. AI is changing so fast. There's, it's. Anyone that tells you they can see the future five years from now with AI is a liar.
[01:19:35] Speaker B: Okay.
[01:19:35] Speaker A: But I do think, you know, we have a bigger direction of where we're headed. Like I just told you, like, we're going to start to fuse models together. And we want people to be able to speak to the world around them and then let the world talk back. And so having a conversation with, with the world around you is kind of one of our, our visions. And so AI becomes an enabler for you. It helps you with your job, helps you be more efficient, more productive, safer. You know, like, wouldn't it be great if like you're working in a steel plant and you're in an area you shouldn't be in, if the system can kind of buzz your phone and say you need to move, you know, this is a dangerous place to be, you know, but having technology that's always got your back, I think we, we want, what we want for people is that they feel like they want to plug into worlds immediately when they come in because they're better.
You know, they can see things that they can't see. They can see through walls. They can, you know, because if there's a camera on the other side of the wall, we can help them see through the walls, things like that. So it's a, it's a. I think that's something we're really excited about is to being a technology that when people plug into it, it just makes them better. You know, probably I'll leave it there and if you talk to me a year from now, different answer.
[01:20:39] Speaker B: Okay. And you'll, you'll see what happens.
Okay. Well, yeah, this is great. Now I. We had a conversation recently with Gary Smith. He's an economist. And the thing you look at in companies is the. What is price to earnings?
I don't know if you have stock yet, but it's the price to earnings ratio. And I also know that for startup companies, many times you get venture capital that allows you a certain Runway to go down before you run out of Runway in order to launch the plane. And how you doing in that area? Great.
[01:21:14] Speaker A: You know, that's really the. Where it falls on my shoulders, you know, so I kind of tell. When I mentor entrepreneurs, I said the number one rule in a startup is don't run out of money.
That's the number one rule. Do not run out of money. And so, you know, I think we, as an entrepreneur, I'm always, I'm always raising my. This is something, one of those things you asked me earlier. What would I change in my earlier days?
[01:21:38] Speaker B: Yeah.
[01:21:39] Speaker A: Now I know, now I know that you should never stop raising money like ever. Like 100% of the time, as you're a founder of a company, you're always raising money. So what I mean by that is, even if I just raised around today, tomorrow I'd be on the phone with investors letting them know how that went and what's coming.
So during the course of the year, I'll speak to 100 or so people about my company and what's happening and letting them know the inciting things that are coming up. And I never stop. And so I think the biggest mistake that young entrepreneurs make is they only raise money when they need to raise money. And then it's really hard because you don't have any previous conversations. You're starting from scratch. And so when I talk to people before a raise, it's like, hey, we've been talking for a couple years now, and I just want to let you know we're about to go after a raise, you know, and so it's not starting from scratch. I know if they're interested or not, so I don't have to vet them. And so it's a. It's just a part of your every day, all the time. You're always raising.
[01:22:34] Speaker B: Okay, we talked about chasing money versus raising money.
I guess there's a difference there. I guess when you raise money, you have to convince people of what you're doing instead of them telling you what to do. Is that basically the difference between raising money and chasing money?
[01:22:50] Speaker A: Yeah, I never chase money. So I get a lot of calls from people that want to talk about giving me money. And a lot of times I'll just say, I don't think we're a match, but I appreciate you calling in and I'll be glad to keep you updated because I don't. I don't think, you know, they're in the right area for us or they can't bring enough to the table. Money, you know, and I don't say this lightly. I. I realize it's different for me than most people. Like, I. When I'm in an area with AI and I've got a couple companies under our belt, so we've done some good things. And so we have a different situation right now. We're raising money. There's a lot of people that are interested and. But I don't. I don't take that for granted. I know that's not normal, but again, it's part of what happened over the years as I've kind of taken these stories, and my stories are companies essentially, and taken the stories to Fruition. Now I've got another one. You know, my. In Worlds is perhaps the most exciting thing I've ever done. I mean, it has more promise and potential than anything I've ever done. And that's one of my messages to people. It's like, if you, like we did before, you're going to love Worlds because this thing has a boundless potential.
[01:23:53] Speaker B: I think I have an idea. But why did you choose the word worlds as your company name?
I know you really have to choose the name of a company very carefully.
[01:24:07] Speaker A: I think it's kind of funny because I think the name kind of fit better. Later, as we built the company, the name started to really go, oh, wow. We picked the right name because we are building worlds for people. So we walk into a company and they have an environment where we come in. We build that world as a virtual world. And sometimes it's a twin of an environment. But I think the name itself implies that, listen, we can help you create your worlds so that you can now perceive and manage multiple locations simultaneously in ways you could never do before. Because I can create virtual versions of your worlds that allow you to measure and understand and build automation into those areas all at the same time. So it's. It's kind of a superpower. Like, we give you the ability to see, understand, measure, and build automation into multiple environments simultaneously. It's kind of a real dream for some companies. Like when you get to the point where you have 100 locations or 200 locations, do you really know what's going on in all those locations?
No, we have something we call the 100% rule. People tell us what they think is happening, then we connect our software to their sensors and we show them that it's not what's happening. And that happens 100% of the time.
[01:25:22] Speaker B: Okay, well, as we wrap up here, let me ask you to give kind of a summary, maybe even repeating some of the things that we talked about, of what Worlds is doing and why people should be interested and how you're going to change the world, not the world's.
[01:25:41] Speaker A: Yeah. So we are building the AI platform for the physical world. So if you're a company that's managing multiple locations and you want to understand what's happening, if you want to be able to measure those locations and to analyze what's happening there and build automation, then we're the company you should be talking with. I think when you look out at the market today, what you see are a lot of point solutions, you know, so. So I'm kind of making the argument for platforms over point solutions, where a point solution might be a computer vision company that can see guns.
That's all they do.
We've actually created capabilities in our platform. So instead of trying to stitch together a bunch of point solutions, adopt one platform that allows you to teach the AI about anything very, very quickly. Like I mentioned before about worlds in Q, so we're able to teach AI about an environment in minutes and hours, not days, weeks and months. And so we've created the platform that can help any large company, any company for that matter, measure, analyze, and improve those environments in motion. You know, so I think one of our advisors is Ken spangler, the former CIO of FedEx. And.
[01:26:49] Speaker B: Wow.
[01:26:49] Speaker A: He likes to say that we're actually helping people see the real world in motion and understand the real world in motion.
And I love the in motion part of that because it's not about watching the tape later. You know, it's about when something's going wrong, we'll tell you what's going wrong as it's going wrong, you know, so it's a. It's almost like this ability, the superpower to see and sense everything simultaneously. And that's a.
That's what we're all about.
[01:27:19] Speaker B: Great. Well, thank you. This has been a great conversation.
I should mention that, but I am personally impressed with David Copps and his entrepreneurship.
I would encourage people to check out worlds. And you should know for full disclosure that there's been no compensation. Right, David?
[01:27:35] Speaker A: That's right.
[01:27:37] Speaker B: No compensation, damn it.
No, no, no. That would be you paying me. That's what I meant by compensation.
Made no money. No money doing this.
[01:27:50] Speaker A: And I appreciate it. It's been a real pleasure.
[01:27:52] Speaker B: Yeah, it really is. I thought it very fortuitous when we met at the Baylor conference, and that was a lot of fun. So it's been really fun getting to know you, David.
[01:28:01] Speaker A: Likewise. Like I said, when I came home from that experience at Baylor, you were one of the persons I just really thought about a lot after we met, because it was a real privilege to share the stage with you and to talk with you, and this has been great. So thank you.
[01:28:13] Speaker B: Well, thank you. Yeah. One of the things David and I was. We're on a panel that talked about AI and we're going to make that video available also on the link. So if you want to watch that and you haven't got enough of David and I, you can.
You can hear more there. So thank you, Dave. Appreciate it. We've been talking to entrepreneur David Copps who has over two decades of experience pioneering advancements in artificial intelligence and other emerging technologies. He's the founder of, founder and CEO of a company called Worlds. And if you want to check them out, it's Worlds IO. Worlds IO.
So, until next time on Mind Matters News, be of good cheer.
This has been Mind Matters News with your host, Robert J. Marks. Explore more at MindMatters AI.
That's MindMatters AI.
Mind Matters News is directed and edited by Austin Egbert. The opinions expressed on this program are solely those of the speakers. Mind Matters News is produced and copyrighted by the Walter Bradley center for Natural and Artificial Intelligence at Discovery Institute.
