Gary Melling - Bringing Artificial Intelligence to life

Time is precious and so are our pets, so time with our pets is extra precious. That's why we started Dutch. Dutch provides 24/7 access to licensed vets with unlimited virtual visits and follow-ups for up to 5 pets. You can message a vet at any time and schedule a video visit the same day. Our vets can even prescribe medication for many ailments, and shipping is always free. With Dutch, you'll get more time with your pets and year-round peace of mind when it comes to their vet care. Hi everyone, it's Bill Black, the exit coach from the Exit Coach Radio show. You know, one of the biggest questions I get on the show is what exactly goes into a business exit plan and when should I start creating mine? Well, I always tell people that the best time to start was 5 years ago, but the next best time is now because you never know when you might need it. So we put together a free report that describes what an exit plan is and what you should know. You can get it free by texting exit plan with no spaces to 442-22. That's exit plan to 44222. Again, text exit plan to 44222. Welcome to the Exit Coach Radio show, the show for baby boomer business owners who are looking for cutting edge information as they plan their 3 to 10 year business succession and exit. Every week we interview top professional advisors for. The best tips, strategies, and precautions so you can be well planned. And don't miss our one minute exit coach tip of the day on exit coachradio.com. And now here's your host, the exit coach, Bill Black. Well, hey everyone, thanks so much for joining me today. It's always a pleasure to have you with me and you know, I have such great guests. I'm very blessed in that regard, and I hope you enjoy today's interviews. My first guest is Gary Melling today. He is with Acquired Insights Inc. The co-founder and CEO of that firm, and Gary is an interesting individual. He's going to be talking about bringing artificial intelligence to life. We can go a lot of different ways with that, but here's what's, let me tell you a bit about their firm. They're a strategic management consulting and systems aggregator firm. Focusing on delivering applied artificial intelligence and machine learning, predictive analytics, cybersecurity, cryptocurrency, blockchain, humanoid robotics, chatbot, and 3D avatar business solutions resulting in immediate, measurable, and scalable value for our clients through better real-time business decision support. Now we only have a 20 minute show here, so we better get right into it. Gary, welcome to the show. Thank you so much for joining me today. Thanks for having me, Bill. Gary, uh, all the things that I just mentioned, I'm sure our listeners are scratching their heads going. Are you lost me at artificial intelligence. The rest of it is future-based things that we're seeing all the time, of course, cybersecurity is with us a lot, cryptocurrency, etc. But where would you like to start, because I'd love to learn more about how you started acquired Insights Inc. and what your background is, and then let's get into the conversation. Oh, thank you. Um, well, I'd like to talk a little bit about AI and machine learning and really provide maybe some basic definitions of what they are, so we have a platform to, to build on. Um, and, and as far as my background goes, um, I've been doing this for a long time. Back in the early 80s, I was involved in classified military projects where we were actually working on technology that was very similar to what you see today. And we take for granted when we think of Google Earth, for example, being able to take a look at an airplane flying, you know, over 30,000 ft and being able to read the newspaper over somebody's shoulder. This was what we were doing back in the 80s. So I don't pretend to be up to speed on what's going on now, but certainly it's, it's, it's, it's gone a long way since then. Uh, I've worked in management consulting, some of the big five firms, um, been an entrepreneur, involved in startups in the AI space and just general tech. So it's a passion of mine. I really enjoy what I do and I work with a great team. Well, terrific. So, uh, artificial intelligence. Let's, let's start with that. Where are we and where are we going with artificial intelligence in this, this term machine learning? Well, I think, to be brutally honest, we, we are, it's like the wild wild west right now. When we think of artificial intelligence, keep in mind it's been around for the better part of 50 years. It hasn't been commercialized until more recently, but there's been a lot of really good work done in R&D in artificial intelligence and machine learning for the last several decades. I would suggest that while it's come out of the US and Canada, Um, you know, there are mega centers and clusters whether it's Silicon Valley or the Research Triangle Park or Atlanta area. There are a variety of different hubs in Canada we have Toronto and Montreal, and I think what we've seen over the last decade is an emergence of technology and special interest in artificial intelligence. That's sort of gone worldwide. So now of course we have hubs in India and Eastern Europe and the UK, and it's really become much more of a staple. The challenge is that it's a footrace and you have a lot of startups where you have on the one end of the spectrum, you'll have companies that are startups of recent grads, and I'm sure they have a very fine education and, you know, shiny new laptops and so on. Um, but the challenge for a CFO or a chief risk officer in a financial services institution as an example is that in the absence of functional experience or business experience, particular and relevant to financial services, it's really hard for an executive to trust their business continuity to a startup where they don't have that kind of experience. On the other hand, you have companies that are, you know, perhaps very deep and rich in experience. Uh, our AI team has over 18 years of experience and, and working as a team as well. Uh, so we're in a kind of a unique position, but there to the, to the potential buyer, it's confusing. And so I think that what we're going to see in the next 12 to 18 months, particularly in North America, is a faster way for corporations to qualify startups. Most startups are not in a position where they can, they can wait a year to navigate through the procurement and legal system of a potential client organization that may be a Fortune 2000. They don't, they don't have the bandwidth or the resources to wait that one year out while all the processing happens. So one thing that corporations are going to have to get much, much better at is recognizing when they're working with startups and whether it's an AI or other areas, they need to create a way to fast track the due diligence because these companies just again don't have the resources to be in an endless loop of qualification. As far as adopting the technology goes. What we're seeing is that organizations traditionally have been, I call it vacuuming the ocean for data. Um, they've got so many data sources and they continue to gather more and more and to feed the machine, to feed the beast, um, but often what's lost is understanding which data is important, which data is predictive, which data can be used for, uh, meaningful decision support. And so I think we're going to start to see fine tuning of the kind of data that's gathered because while it's great to be able to buy memory relatively inexpensively, the data can clearly get out of hand, and when you have that much data, you really have to take a look at is the data clean? Does it need to be scrubbed? Is it complete? Are we missing something, something germane to making specific decisions in a specific part of our business? And then of course there are all the privacy issues, and we have the GDPR regulations on data privacy access, we have cybersecurity. I think that what we're seeing in the next 12 to 18 months is not only a firmer grasp of trying to identify which data they need to capture versus capturing everything. I think what we'll also see is more and more organizations moving to predictive behavioral data. Right now, um, most organizations are working with what we call structured data. And let's just make it all really simple. Structured data is the kind of data that a corporation would keep in a large computer system, an enterprise resource planning system, ERP system, so they might have Oracle or PeopleSoft or a handful of the other large ERP systems, and the challenge with that kind of capturing that kind of data is, is relatively easy because it's all accessible. It's usually the same data just being updated over and over again. Um, what we're also seeing though is while that is structured data, I know it was research came out about 2 years ago suggesting that 90% of all the data that has ever been created in the world has been created in the last 24 months, and 90% of that data is what we call unstructured data. So unstructured data is not the kind of data we just talked about a moment ago. It's not the kind of data you'll see in a large computer database system. It's things like emails. Voice recordings, photographs, videos, think of social media. Uh, so that's an excellent example of the kind of unstructured data that we're seeing. Now if you add on top of that. What we believe is where the real secret sauce is going to be. It's in the behavioral data, and behavioral data is a subset of that unstructured data, and we've all probably had some familiarity and examples with behavioral data, for example, if you order something on Amazon. And it says to you, oh, by the way Bill, people who bought this book also bought the following 6 books. So it's using, you know, some, some predictive analytics and some behavioral data. It's, it's monitoring your purchasing habits. It's logging all of that information. And it's being able to refer to it again to say, Aha, OK, Bill's visiting again. The last time he was here, he bought this book. So we're going to see much more of that. We're only scratching the surface right now. And when you start to think of that being applied, let's say, in healthcare, retail, manufacturing, mining, telecom, uh, the customer experience can be tailored and tailored in real time. Uh, to just about anybody in any industry anywhere in the world. So I think we're going to see a lot more of that. But the first, the first segment is going to be to, I think, transition a little bit from the structured data more into using the unstructured data when corporations are only using 20% of their available data, that's the structured data. And you know companies like ours can unlock the access and capacity to use that other 80%. It's going to provide them with tremendous insights on the customers, on the competitors, market analysis, and so. It's fascinating and it's it's a new frontier of, you know, 50 year old new front overnight success right that it's been working on for a long time. Yeah, what, what, what always interests me is the fact that what you're and what you're explaining so beautifully, it's very clear to me, but that there's been a lot of logic based data available, but and especially we're Talking about um cars that drive themselves, etc. etc. how do you program in that the person next to you just dropped a soft drink or a cup of coffee in their lap and they're going to swerve the, you know, the unexpected, unintentional or emotional type of uh issue that can come up for us as humans and how does artificial intelligence get programmed to, um, take, you know, prepare for that unexpected swerve. Great, great question. Well, I think there are in just general terms, there are probably a couple of topics we would probably touch on, and one would be the nature of bias. So whenever we take a look at anything to do with computers, if we try to replicate anything, for example, you know, again, artificial intelligence, it's really It's a branch of computer science dealing with the simulation, the simulation of intelligent behavior in computers. Now, before we can engage in artificial intelligence, what typically happens is we start first with machine learning. And machine learning focuses on the development of computer programs that can access data and use it to learn for themselves. So before we actually engage the artificial intelligence, we have to start with the machine learning. And let's say for example, the example you just gave, uh, in a car, um, as we pull up to a stop sign, uh, we don't want to be right half the time. We want to be right all the time. We want to be sure the car comes to a complete stop. Uh, when we take a look at the stop sign, it's, it's an eight-sided figure. It's red, it's got letters in it. Uh, and on a beautiful sunny day and with an unobstructed view, it should be very easy in machine learning to train that computer system to recognize a stop sign. But where it gets a little bit sticky is let's imagine now it's an overcast day. Let's imagine there's a bit of a breeze, and the breeze is blowing a rat in front of the stop sign. Well, that stop sign might not now be quite so easy to delineate as a stop sign. So we then go from, from, sorry, machine learning to deep learning, and in deep learning we basically offer hundreds, maybe even thousands of more scenarios of what this stop sign might look like given all these extraneous conditions. So there are ways that we can approach solving some of these problems, whether it's using um machine learning, deep learning, or whether we're actually starting to focus on elements of self-bias, cognitive biases. When we're human, as we begin to program computers, one of the things that happens, and we, we don't necessarily do it consciously. Um, as we start to take a look at, including some of our values, some of our reasoning into the logic. Again, it's, it's more subconscious than, and these are called cognitive biases, and there have been a variety of different papers written on them, um, you know, I just read one recently where we talk about 24 different cognitive biases that are potentially warping perception of reality. And when we use this. These, these, um, subconscious, uh, cognitive biases, we can skew how the artificial intelligence or machine learning is actually learning. And so it doesn't necessarily give us a pure answer, the answer that we might be looking for. It could be just somewhat biased, just as the names. Well, one of the things about artificial intelligence is if we can identify that bias is going on. And if we're aware of the different classifications of bias, we can actually start to build algorithms that challenge the artificial intelligence to see if in fact bias has been built in to how it's operating. So this is where artificial intelligence can actually be used on itself. To clear the deck, so to speak, of that kind of potential problem. I don't know why I just said, wow, I mean, as humans we do this all the time, right? I mean, we're, we're, we've got the supercomputer in our brain, I guess and I guess one question in for instance in financial services which you mentioned earlier, which of course is is robotics, um robo trading is all the rage right now. One of the one of the key benefits of a Human beings stockbroker, for instance, is to talk somebody out of a bad idea and if, if for instance you were to get online and say the market's falling, sell right away, the computer would likely, I would imagine, follow your instructions instead of saying, hey, are you sure, because This, this is gonna come back or I, if, if I, you know, so and the art of and even if the computer were to do that, I guess the bigger psychological question is will humans ever cede over the authority, um, to say, ah, no, ah yeah, you, you've got this, you take this computer. I, I trust you. In a way we do this many times and sometimes we've been burned if our, if our old MapQuest. Ended us at the end of a dead end street and said you're you're home, you know, that type of a thing. And so the the forward based question is, will we ever trust a car with no steering wheel that we can't something we can't grab a hold of to because well, we'll, we'll mostly trust a computer to get us where we want to go. It's the old trust but verify type of a phrase I guess. I think we will, uh, you know, it's not going to happen today or tomorrow, but I, I think we're headed down that road already. If we think of what it was like 100 years ago and, and commercial flying, people talk about people flying in the sky, um, or, or traveling at high speeds on trains or Henry Ford thinking about asking, you know, general population, what is it they'd like to see in transportation? They would have said faster horses, you know. Um, when we take a look at how all this technology evolves, I don't think it's a matter of if. I just think it's a matter of when. So if, if it's 5 years, whether it's 20 years, I really do believe that as the artificial intelligence, machine learning, predictive analytics, the data sources become more refined. The updating of those data sources is basically real time. We'll be in a position where I think it'll just become second nature. Yeah, and good point. And as a new generation is born and brought up with the technology at hand, they don't fear it. They're, they embrace it from the beginning. So what can the average person do to get prepared for the changes that AI and machine learning will bring? I would say um Anything you see on the TV, anything you hear on the radio, any, any book that you have in a magazine article, anything that is really discussing the topic of artificial intelligence or robots or computers in general, read it, follow it, get engaged. There's, there's so much out there now, not all of it. Necessarily makes sense, and there are obviously people within the same field that would debate the validity of one point of view versus a different point of view, but the only way you can actually get, you know, to a point where you're familiar enough to have those kinds of debates is to start with a baseline of information and turn that into knowledge and then be able to apply it in a forward thinking. And, and that all starts with a single step. So I would say, you know, even if you're a person isn't necessarily the first one to pick up an article in a magazine or, or to watch a news item or see something on, on their computer screen about artificial intelligence, whether it's an ad or a video, take the time. Um, it's coming. It's, it's, I, I say it's coming, it's here. Um, the challenge is that most people tend to be thinking that it's so far off in the future you don't really need to worry about it, and I can tell you that there are different pockets in the world where they not only accept artificial intelligence and machine learning and robots, they run towards it. A concern I currently have about North America is that if we compare, let's say, South Korea, Singapore, Hong Kong, to what we're doing in North America and as far as adopting artificial intelligence and how we do our banking, and how we, we, we, uh, interact with a variety of different quote unquote machines, we're, we're kind of delayed here in North America, um. In, in some of the countries I've mentioned, every element of an individual's banking is done on their phone. They have a chatbot that they talk to. They can go into their profile and configure someone who looks and sounds like them as their avatar. Um, they can that avatar, you know, can can service that client's needs, take a look at their credit reports and and loan applications or lines of credit or whatever it is, and they can actually tie it to rewards programs and where they have rewards in place they can automatically, this is all done through artificial intelligence allow that person to be followed through in a day in the life and have that entire journey supported by artificial intelligence. Now that's clearly the more advanced ways that it's being used, but here in North America. On the other hand, while we've got a good base and, and there's certainly been some as as well as in Canada, we've done some R&D that is world class, I think for the most part there are, there are exceptions, but for the most part, uh, we've rested on our laurels of the R&D while the rest of the world has been actually implementing it and embracing it. Um, so when here one of the things we have to do, I think, is make it part of of and recognizes that robotics are already part of our day and have been for a very long time, and people will say to me, Well, how can you say that? You know, I don't have a robot in my home, and I'll say, Well, of course you do. Well, do you have an automated coffee maker? Yes, programmable, yeah. Do you have a printer for your computer? Yeah. Do you have a remote control and a garage door opener? Yeah, well, those are all robots. They might not take a human form. They might not be sophisticated in the sense of being empathetic or using some of the more recent technology and facial recognition and, you know, all that other stuff, but the essential role of a robot. is to do work and, and all of these machines that I've just described, photocopiers, they're, they're doing printing. They're, they're actually replacing a human in a printing press and, you know, all the things that we used to see in the old days. So there's been this very slow recognition that they've been here for a while and what I think we're starting to see because of press stories and news items and so on, we're starting to see things that are that are startling us. There are applications of AI in pharmaceutical and biosciences and synthetic skin and you know, all kinds of things that are being worked on and No one thing is going to solve all the world's problems, which means that we need to be generally speaking just more aware, and I think that awareness is going to come from reading and hearing and listening and watching as much as we can about it and and trying to put it in a context where we understand what does it mean for us as individuals, what does it mean for our town or city? What does it mean for our state or province? What does it mean for our country? There was an interesting quote. Um, I saw that really kind of fascinated me, and it was actually said in September 7th of 2007. The quote is artificial intelligence is the future not only for Russia but for all humankind. It comes with colossal opportunities but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world. And that was President Vladimir Putin. Well, there are other countries and pockets around the world where they truly, truly Understand the implications of artificial intelligence. Now, do they have all the answers? No, but they're in the pursuit of those answers. And, and I think as a general society in North America, we just need to be more engaged and, you know, I, I, I can see having discussions about artificial intelligence or the application of artificial intelligence at a dinner table. Um, those are the kinds of discussions that, that, you know, the people that I work with them on a regular basis are having, and um, I don't think we're that far off from those being commonplace. Well, if I were starting that conversation at a dinner table, I certainly hope you would be there with me because I think it'd be a very interesting conversation, and it's been fascinating to talk with you about this, Gary, and I note that for for active progressive business owners that qualify, your firm offers an online business continuity risk profile assessment followed up with a complimentary confidential 30 minute telephone consultation, and I take it that that's That's aiming towards the cybersecurity side of things, but I think it would behoove any of our listeners to get in touch with you, and I note that your website is www.aiinc.cloudinc.cloud. Gary, it's it's been fascinating to talk with you and, you know, I really think I'd love to get Another interview schedule with you as quick as possible because we just started to scratch the surface, but we laid down a very nice foundation for future conversations so thank you. Thank you, Bill. It's been a pleasure. Thank you for listening to Exit Coach Radio. Time is precious and so are our pets, so time with our pets is extra precious. That's why we started Dutch. Dutch provides 24/7 access to licensed vets with unlimited virtual visits and follow ups for up to 5 pets. You can message a vet at any time and schedule a video visit the same day. Our vets can even prescribe medication for many ailments, and shipping is always free. With Dutch, you'll get more time with your pets and year-round peace of mind when it comes to their vet care.