 Live from the JSA Podcast Studio, presenting Data Movers, showcasing the leaders behind the headlines in the telecom and data center infrastructure industry. Welcome to Data Movers, our podcast series. I'm Jamie Skado-Cutaya, founder and CEO of JSA. And with me as always, and so best to have my co-host, top feet of the social media influencer, the fabulous Evan Christel. Hey Evan. Hey, good to see you as always. And welcome everyone to Data Movers, where we sit down virtually with the most influential folks in our leading telco and data center and cloud world supporting the network infrastructure requirements of this new normal. But before we jump in, Jamie, were you a big investor in Facebook? I hope not. I thankfully, yeah, missed that one. Yeah, I'm watching these headlines. And that's- I'm glad to see, yeah. It was a pretty brutal few weeks for Facebook, AKA Meta. Meta. I think they lost about $170 billion or thereabouts in market cap. And looks like we have achieved peak Facebook. Yay. By the way, it's my personal opinion coming through. What about you? Do you still use Facebook and Insta and all the Meta? You know, what's that, products, services? Not the way I think I should have been, could have been, would have been. It's like I put a, it's like you put a flag in the sand. Like you're there just in case people are looking for you. You kind of want to know if someone's talking about you, but it's not something I go to. It's not my fun platform for me. It's not my- Yeah, not too much fun happening. I would agree. And even the cool kids now have moved on to TikTok and people like us and B2B are on Twitter and LinkedIn. So what do you think? Is there a role for Facebook, AKA Meta moving forward in our world, let's say of enterprise and B2B tech? I mean, it needs to kind of screws itself up a bit. You know, I think I heard Zuckerberg in an article say, oh, well, there's two reasons for this. One is that, you know, there might be a max of all the people like they just haven't gotten new users lately. And two, he sort of started blaming TikTok, which was a weird thing to see a CEO do kind of. So, yeah. And I take it you're not a heavy- I think it's not to go to TikTok, right? That's, I don't know. I'm not understanding a strategy there, but with everything on the internet, especially these days, you know what Meta is a cool concept. I wonder how long there's like a few years, I think, until we're actually there. So is he a little ahead of his time? Who knows? Never discount him, I would say. I'm guessing you're not wearing a Oculus VR for hours a day, if I'm just guessing. That's my hunch. I mean, no, and it's hard enough for a 20-year-old to get her out of an iPad for like three straight. So, I mean, that's scary, you know, like people are putting ads on the sidewalk because people are looking down on their phones. And, you know, I think maybe also the pandemic forcing folks to like regroups, you know, stay back, spend more time with family, maybe take a little shift in like balance, need for balance. I don't know, but it's all cutting edge, technology's gonna drive us forward. And actually that kind of brings us fabulously to our guest because we are talking to a futurist today. So, yeah, can I, should I just, all right. Let me bring him in and he's amazing founder, CEO and chief scientist at AGI Innovations in Igo.ai. We're talking with Mr. Peter Boss. Hey, Peter. Hi. How are you? Excellent, excellent. Yeah, we have summer coming back here in Los Angeles, so that's nice. Welcome Peter, good to see you. Good to see you. We cannot beat these LA weather. It's fabulous, but you can't leave SoCal. Once you get here, it's like, just soak it up and this is, plant your home here. Okay, rub it in, rub it in. Sorry, sorry, sorry. But back to Peter. Peter, you are of course a serial entrepreneur, an engineer, an inventor, a pioneer in artificial intelligence. And so of course, studying intelligence, that's pretty, it's an intelligent thing to do and how to replicate it within software back when AI was in a very conceptual phase. So actually, that could be a good tie-in with Metta. What do you think about all this and what drove you to specialize in this type of research? Yeah, so I actually started out as an electronics engineer. So I understand hardware and then I fell in love with software. And my hardware company, my electronics company turned into a software company. I developed an ERP software package. That became quite successful. We grew rapidly to 400 people, did an IPO. So that was super exciting. But it's when I exited that company, I thought, what do I really want to do? What big project do I want to tackle? And what struck me is that software really is quite dumb. And I'm saying that I was very proud of my software that we developed, you know, was excellent software. But still, if the programmer didn't think of some scenario, the software would just give you an error message or crash maybe. There's no intelligence inherent in software. There's no common sense. Software doesn't really learn. So that is what struck me. And I want to say, can we solve that problem? Can we make software intelligent? Can we have software that can actually have common sense, that can have deep understanding, that can learn from, you know, from how you interact with that and so on. And that is what got me started on studying intelligence and artificial intelligence. I actually took off five years to deeply understand intelligence from many different aspects, you know, starting with even philosophy, epistemology, theory of knowledge, you know, what is reality? How do we know anything? How can we be certain of things, you know, and how do we achieve knowledge? How do we achieve certainty? How do children learn? How does our intelligence differ from animal intelligence? And what do IQ tests measure? All of those different aspects of intelligence to really deeply understand the concept of intelligence to be able to then introduce that into software, to build software that has intelligence. And so after, you know, about five years of doing my own research, I then started off my first R&D company and then implementing these ideas and these insights that I got. And this then over many years transitioned into a commercial product, a conversational AI product. And that was my first commercial AI company. And, you know, we learned a bunch from that. I exited that company and we went and developed the core technology further and we've now commercialized the second generation of this technology in IGOR.ai, basically intelligent conversational AI. Yeah. That's fantastic. And I actually just learned today that you personally are known in the industry for coining the term AGI, Artificial General Intelligence, which I'm excited about because I am waiting for my personal Jarvis, you know, from Ironman. This is Robert Downey Jr.'s personal assistant. I just can't wait to have one. So, but describe what AGI means, how it's different from AI and when am I going to have Jarvis? That's the most important thing. We're working on it. We're working on it. But it would help. It would actually help if you could maybe, you know, give us 50 million or so that would definitely accelerate. What's your Bitcoin wallet? I will get that. Yeah, near you are going to turn it into. OK, I'll send that to you. Right. So, yes, AGI, I coined the term in 2002 together with two other people. And the whole idea behind, you know, why do we need this new term, Artificial General Intelligence or AGI? And how this came about is if you actually go back 60 years, 60 plus years when the original term artificial intelligence AI was coined, it was really about building machines that can think and learn and reason the way humans do. So it was having human like human level intelligence and, you know, the original founders thought they could track this in a few years. You know, and this was in, I think the 50s, late 50s or early 60s, I don't remember. And of course, it turned out to be much, much, much harder than that. So what happened over the decades, the AI really turned into what is narrow AI. And it's actually sort of a subtle shift, but it's very, very profound and very important. So what happened is people picked one particular problem that kind of they thought, well, this requires intelligence. Let's solve this one problem and call this AI, you know, that's AI. And that's really what AI has been doing over the last 50 years or 40 some years is solving narrow problems. But the profound difference there is that it's not actually the AI solving the problem. It's the programmer or the data scientist solving the problem. So for example, one of the big breakthroughs we had was IBM building Deep Blue, the world chess champion. And it was really the programmers who figured out how they could buy specific programs to use the power of computers, the vast number crunching capabilities of computers and utilize it in a very clever way to play a really good game of chess. But the chess program doesn't really have any intelligence in the way we understand it in humans. It was able to play chess, but it couldn't even play checkers, you know? And if you change the rule slightly off chess, it would, you know, fall down. And this is really what's been happening in AI is solving very narrow problems, but they are actually solved by the intelligence of the programmer and the data scientist. And we are still there today, you know, even with, you know, the go world chess champion or protein folding or all of the fantastic breakthroughs we are having in AI today. It's narrow AI. It's not really what the original idea of artificial intelligence was. So in 2002, I realized this and got together with some other people who had similar ideas and we decided to publish a book on the topic to get back to the original dream of AI to build thinking machines. And we decided we really needed a separate term to distinguish what we're doing from what everybody else in AI is doing. So we came up with artificial general intelligence and, you know, it surprised us actually that the term sort of caught on and now it's, you know, very commonly used to describe human level or human like intelligence. And that's what I've been working on really for the last 20 plus years. And so kind of begs the question, but can you tell us about any of the AI technologies you're currently working on at Igo.ai? Oh, yes, absolutely. There's actually, I can give a very quick rundown in terms of, you know, also the differences in how narrow AI is done by pretty much everybody in the field of AI and how AGI needs to be done. DARPA came out with a presentation a few years ago that they called the three waves of AI. And what the three waves of the first wave is what's also called good old fashioned AI. Those are basically primarily logic based approaches. So, you know, formal logic and it's all about logic reasoning. And again, deep blue, the chess playing system was a good example of that. So that was the first wave of AI. Now the second wave of AI is basically big data statistical systems, also deep learning, machine learning. And that second wave hit us like a tsunami about nine years ago when some of the big companies like, you know, Google and Amazon and IBM Facebook figured out how they could use masses amounts of data and masses amounts of computing power to build these AI models. And that's really what deep learning machine learning is. And that's given us, you know, tremendous breakthroughs in terms of image recognition, speech recognition, and of course, the trillion dollar business of targeted advertising, you know, which is driving this whole deep learning machine learning. But that's the second wave of AI. So first and second wave are really narrow AI. The third wave that DARPA described is a cognitive architecture where your starting point is what does intelligence, you know, human like human level intelligence require the flexibility that we have. And so you then build a specific architecture that encompasses the requirements of intelligence. And, you know, that's basically what our approach has been. And so we have a cognitive architecture that has the ability to learn interactively as you're interacting with the world. It can reason about it. It has some common sense and so on. And so currently you're sort of working on that third phase. And then what has that process sort of taught you about intelligence in the brain? Yeah, so, you know, one of the things that, I mean, there are quite a few sort of technical aspects to it, but one of them is that common sense reasoning and common sense knowledge are really an important part of it. And that's very fuzzy. And, you know, the information we get from the world is often contradictory, it's incomplete. And, you know, it's not clean knowledge like you would expect out of a database. So you need the system to be able to deal with that kind of incomplete contradictory knowledge and knowledge that changes and can change all the time. And for that you need metacognition, you need to be able to know when you don't know something or when you're not understanding things. So those are some of the, you know, sort of more technical aspects of intelligence as such that we, you know, we understand better. So your system needs to be able to deal with the messiness of the real world. Yeah, it's funny, I have a 20 month old and I feel like her sort of her intelligence as she ages, it's like it's almost following like the path of AI. Yes, there are definitely parallels in terms of making sense of the world, you know, and learning. So, yeah, that's really what we found. And, you know, we've now incorporated that into our, you know, commercial product. Fantastic, can't wait to try it. Well, you know, many people say the AI and hyper personalization is the future of marketing as well to where I live and to take it a step further, you know, customer engagement, support, customer service. I just want a bank that actually knows who I am without my mother's maiden name and entering my account and phone number in for the eighth time. But how do you think AI, you know, can offer sort of hyper personalization in these contexts? Yeah, I mean, that's very, very much in our wheelhouse, you know, what we are focusing is conversation, hyper personalized conversational AI. And, you know, the way we describe it is a chatbot with a brain. Now, you know, people are used to chatbots, but they don't normally have a very good opinion of them because often you don't have them. Yeah, they're pretty terrible, I'll say it. Yeah, and the reason for that is because they don't have a brain. So we have a chatbot with a brain, you know, that can actually deeply understand what you're about, use the context of, and, you know, use short-term memory, use long-term memory. So it'll remember what you said, you know, earlier in the conversation, or it'll remember what you said last week or last month or last year. And it can reason about things and ask you to clarify things if you don't understand them. So at the moment personalization is pretty much done statistically. You basically fit a certain demographic, you fit into a certain bucket, you know? Oh, people with your profile also like this or also want that. And we know that's pretty awful because, you know, just the number, you're not just a statistic. And even though quite a few of the things may match the profile, they ask very specific things. You say, well, no, I really don't like this or I've already bought this or I really like something else that wouldn't really normally be in my profile. So having hyper-personalization, personalization at the individual level is definitely the future. So, you know, one of our big customers is 1-800-FLOWERS. And they're actually a group of about 12 companies, Harry and David and popcorn and chocolate and so on. And the founders of the company actually came to us and they said, when we started the company, we were just one shop and we knew all of our customers. Now we have over 10 million customers. How can we give that kind of personalized service to an individual? And that's what we can achieve with this chatbot, with the brain, this hyper-personalization that basically when you engage with IGO at 1-800-FLOWERS or companies like that, you can then say, I want to buy chocolates as a birthday gift for my cousin, Jane or something. And the system will then know that you buy chocolates for a birthday, for a cousin and cousin is called Jane. And that information should now be remembered for you specifically and be available later on in the conversation and future conversations, maybe a year later, well, it's the birthday coming up again, that she liked the chocolates and so on. So that is really absolutely the future. That's what people expect, not that they're just a demographic and you just get bombarded with things that people like you may like. It's your individual personality. Yeah, and I'm a customer of 1-800-FLOWERS and I can tell you, they draw me back in because they'll be like, what's coming up? So it was birthday and I'm like, all right, yes. And remember last time you sent this, you want to do it again? I'm like, yes, click, good, done. It reminded me of the thing that should be on my to-do list and then they helped me cross it off. I'm in. Yeah, and we're adding the sort of conversational part of that now that we are introducing there. But we see that's really the future with all companies that we're working with. That's the kind of service they want to provide. And then of course, on the other hand that you mentioned support, giving support and call centers. I mean, all big companies are having a hell of a time getting the right, the qualified staff, correctly trained staff to be available at peak times. I mean, we're all experienced where you try to get support and you wait for 20 minutes, 40 minutes, an hour. Whereas with the right kind of AI, the third wave and intelligent AI, there's no wait time. And it's as if you're talking to the same agent when you call back and the agent actually remembers what you were talking about last time. So it's actually, it's not just about, it's not really just about saving money. Yes, you save money, but you're actually providing a better service than the human can. This episode is brought to you by 1-800-FLOWERS. Nothing, nothing, nothing. No, no. I mean, this is also so current though. I mean, I was literally like on healthcare. I put down in my number and they were supposed to call me back. They never called me back. I, you know, I could, and anyway. It's every, it's every industry, it's airlines. Yeah, and then we can, we can do better. The technology exists now and companies just need to step up and, you know, use chatbot with a brain. And you know what? This kind of brings us to our rapid fire part of our data movers, which I love, where we ask you crazy questions and the first answer that comes to mind, spread it out. And, you know, I'm thinking about AI and it really has just moved its way into the big screen. Many Hollywood films, of course. And for, you know, quite some time now. So tell us which one is your favorite movie or TV series, but we're not a particular. But which one that features AI in a storyline that we love? Well, there's actually quite a lot of them that I really, really liked. It's hard for me to remember all of them. A bicentennial man, I thought was really well done. And then of course, her, a lot of good movies. But I always get very disappointed. I mean, Bicentennial Man and Herb, I like the first part of the movie and I hate it, the ending. And Bicentennial Man are the second part of it. And the reason I hate the ending is it's either AI is the bad guy, you know? That's what it turns out. Or the AI wants to become a human and become mortal, you know, or something like that. And it's just so wrong. I mean, it's not the way I see AI. I think in Japanese culture, you have a much more positive view of robots and AI. But yeah, I liked her in terms of that personal assistant. In fact, I just want to elaborate a little bit in terms of where I see technology going. So the one is, you know, we're talking about corporations, the hyper-personalization you were asking about, hyper-personalization at the corporate level. But there is another phase which we're also working on. And that is what we call a personal personal assistant. And it really could be called a personal personal assistant. And the reason for that is three different meanings of the word personal, personal that you own it, it's yours, it serves your agenda, not some mega corporations agenda. Secondly, it's personal that it's hyper-personalized or hyper-customized to you. It knows what your preference are, your history and so on. And the third personal is the privacy issue, that things are personal that you can trust, entrusted your deepest secrets, basically, and you decide what you share or what it shares with whom. So that is where the personal assistant it basically becomes yours. Because right now, you know, we have Siri and Alexa and so on, but you know, Siri is probably not going to tell you about the latest Samsung phone, you know, and Alexa is probably not going to tell you about the special at Walmart, you know. And they, you know, they are owned, you get them for free, but you're selling your soul. And I think we need to get away from that. I'm going to go re-watch Wargames with Matthew Broderick back in the 80s. That was a great AI movie with the kind of optimistic ending. But it's a fun topic. I could spend three hours talking about AI in movies. I have to do another episode. Shifting gears, what advice would you give to young tech entrepreneurs who are just starting out? Yeah, if I think back of, you know, sort of the biggest regret I have is I started my first business when I was 25. I wish I would have started 10 years earlier. You know, I think if you want to be an entrepreneur, if you want to, you know, have your own business, if that's in your DNA or whatever, wherever it comes from, the sooner you can start the better because there's nothing like actually doing it. You know, if you're doing it part-time or you're partnering with somebody, but if you're a owner or part-owner, you know, you have that responsibility, especially in a small company, and you just have to figure out how to do things, you know, how to deal with suppliers, people, customers, you know, and yeah, the sooner you can learn the better. The other thing is it's really, really helpful if you can have one or two partners in the business that you really trust and that, you know, obviously, they all need to contribute, but having a partner in the business or two partners, one or two partners is really, really helpful. What about advice to old entrepreneurs like myself? No, just kidding, we'll just leave with the young folks. No, it's a thing like here in California, I'm looking at preschools that feed into elementary schools and they have entrepreneurial class on Mondays. I'm like, sign her up now. Is that like crypto for toddlers? Is that what's going on there? And it's not for everyone. It's not, you know, it's not for everyone to be an entrepreneur, but it's more and more, you know, obviously now it's not that you get a job at GM and you spend the next 60 years there or 50 years or 40 years and then retire with a gold watch, you know, I mean, it's now people do take much more responsibility of managing their careers and so, yeah. And with entrepreneurism, is that a word? Yes, and AI aside, what other modern technology could you not live without and why? Oh, you know, obviously computers. But yeah, I mean, we're so used to so many things. I mean, the internet is, you know, going back now and not having internet, not having computer, that'd be pretty weird. You know, I think about my college years, which didn't really have that. Like, you know, I think I brought a word prep. Now we're really dating myself, but and I'm thinking, oh my goodness, how are these, how do you not get an A these days? You have your little laptop in class. You can just bring up any answer quickly. Like, it's a whole new world. Oh, Jamie, you're older than you look. Wow. Oh God, wow. Yeah, the camera, the angles, the lighting. Yeah, I mean, it's just amazing the technology that we have. You know, I started, when I started business, there wasn't even such a thing as a PC didn't exist. You know, and yeah, I wouldn't, I wouldn't want to go back there. Yeah. So Peter, just diving a little deeper. What, what three words would you use to describe yourself? There's a bit of a trick question. I'm passionate. I'm passionate about what I'm, what I'm doing. I'm, I'm driven. I'm curious and I guess a fourth one adventurous. You have to say innovative. Well, yeah. Only three words. We only have. Okay. All right. You pick them and you pick them. And last question, last question, then we will stop torturing you, but what is your favorite activity or hobby when you really just wanted to disconnect from technology? Fast motorcycles. Wow. Would not have expected that. Wild side with Peter. I like that. I like that. Yeah. That's fine. Well, thanks so much Peter for joining us. That was really fascinating. I personally could spend another couple of hours doing a deep dive, but we'll have to leave that for another time. Yes. Yes. Yeah. Thank you. Absolutely. So, Hey everybody, if you enjoyed this data movers podcast as much as we both did, be sure to check out JSA.net slash podcast for upcoming episodes every other week on Wednesday mornings and be sure to follow us. Check us out. Can they go Mr. Evan? Yeah. Evan Kerstel on Twitter and Jay Scott on Twitter. And it's actually us. We actually will respond. So tweet us. Yeah, absolutely. And as always guys, stay safe and happy networking.