FLYHT's JumpSeat

Dive Into Blockchain and AI's Impact on Industries with Lorne Sugarman on The Jump Seat!

April 24, 2024 FLYHT Season 2 Episode 5
Dive Into Blockchain and AI's Impact on Industries with Lorne Sugarman on The Jump Seat!
FLYHT's JumpSeat
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FLYHT's JumpSeat
Dive Into Blockchain and AI's Impact on Industries with Lorne Sugarman on The Jump Seat!
Apr 24, 2024 Season 2 Episode 5
FLYHT

In this captivating episode of "The Jump Seat," Chris Glass interviews technology innovator Lorne Sugarman, who delves into his extensive career, spanning investment banking to leading tech-driven projects. Lorne discusses his transformative work in disability management through technology, his venture into gaming with branded games for Fortnite and Roblox, and the cutting-edge e-commerce integration that brings virtual purchases to life. 
He also explores the potential of blockchain technology beyond the cryptocurrency sphere, emphasizing its applicability in maintenance and other industrial applications. The conversation then shifts to the implications of AI and machine learning in improving operational efficiencies and future prospects in various sectors including aviation. Lorne's insights into the interplay of technology, regulatory environments, and market readiness offer a profound view of the present and future of industry.

Show Notes Transcript Chapter Markers

In this captivating episode of "The Jump Seat," Chris Glass interviews technology innovator Lorne Sugarman, who delves into his extensive career, spanning investment banking to leading tech-driven projects. Lorne discusses his transformative work in disability management through technology, his venture into gaming with branded games for Fortnite and Roblox, and the cutting-edge e-commerce integration that brings virtual purchases to life. 
He also explores the potential of blockchain technology beyond the cryptocurrency sphere, emphasizing its applicability in maintenance and other industrial applications. The conversation then shifts to the implications of AI and machine learning in improving operational efficiencies and future prospects in various sectors including aviation. Lorne's insights into the interplay of technology, regulatory environments, and market readiness offer a profound view of the present and future of industry.

Speaker 1:

Welcome to another great edition of the Jump Seat. My guest today is Loren Sugarman. Loren, welcome to the pod.

Speaker 2:

Thank you so much, and thank you for taking time to speak with me today. It's my pleasure to be here.

Speaker 1:

So give me a little bit about yourself, give me a little bit about your background.

Speaker 2:

Sure, so I've been a lover of tech for a very long time. I started my career in investment banking. I started my career in investment banking probably close to 30 years ago. I worked at a firm, a small independent investment bank, that was kind of like the Morgan Stanley, the Montgomery Securities T Weisels of the US, really focused on technology. I ultimately worked there for 15 years. I led the technology investment banking team as well as the clean tech investment banking team. I left in 2012 and ran a health services tech-enabled business for about nine years, really focused on disability management, return to work programs. We built software around that, on delivering programs to large corporations Fortune 500, iob, 50 type customers and we provided physical and virtual solutions to these companies using our tech and using people to deliver those services. I left that and sold that to a public company here in Canada. I ran a 3D immersive technology business. That was my fun part.

Speaker 2:

We built games on Fortnite and Roblox, did that for about three years. We recently sold that business as well probably a little bit ahead of our time, frankly, but it was fun. We built, like I said, branded games, so we had customers like DKNY, KB Homes, Forever 21, and many air miles many that I can't think of at the moment, but we were just a little bit of our time. Unfortunately, my largest shareholder was a public company and he was impatient for revenue and things like that. We also built a really cool piece of software that allowed people to transact on the Fortnite and Roblox using a scanning technology, and so people buy skins and all the type of stuff on these games all the time, but this was the first time where you could actually get a physical good.

Speaker 2:

So if you had a nice nike pair of virtual skins or something like that and you wanted the physical good delivered actually delivered to your house, we had built where you can scan that virtual good and get that physical good delivered to your home.

Speaker 1:

So so you see a pair of Jordans in the video and in the game that you're playing and you go. You know what that would look good on me.

Speaker 2:

I'm going to scan it in and get it delivered Exactly so it would pop off we were integrated with, obviously, e-commerce in the background Shopify or other e-commerce solutions and so you'd pop up and get that virtual, that real store and be able to click and deliver that good to your house or the other ways you could do. It is loyalty points. So I love those shoes. I get loyalty points with Nike or whoever that brand is, and the way to the races. So we had delivered some pretty cool technology and I believe, with Apple Vision Pro and many other things, someday that will all really come together as an ecosystem. But, like I said, a little bit early, but that was the fun. It was fun to create amazing emerging technology.

Speaker 1:

Right, and you never know where that's going to lead to, right. That's kind of what creation is all about is seeing where it goes. I remember seeing a presentation on a mobile app and the concept was, as you're moving through the airport, uh you know your app is is telling you, uh, where to go. You can order a latte to be delivered to, uh, the gate that you're going to, or that kind of thing, and just kind of using that um, I guess, immersive technology to kind of supplement what you're seeing out there. And then, with Apple Vision Pro and that kind of stuff coming, you're just going to see that pop up like crazy.

Speaker 2:

So one of the things I used to speak and try and evangelize the industry and one of the case studies I used to talk about. I can't remember all the exact details, unfortunately we didn't do this, but many of these airports these days are built using 3D technologies, right.

Speaker 1:

Yeah.

Speaker 2:

To actually scale and figure out where to put different things, and I think it was the Hong Kong airport that had integrated 3D, immersive technologies, the internet of things, some AI. You know, ai has obviously been prevalent for a long time, but earlier stages, the LLMs and the inflection point that has happened in recent time hadn't happened, I think, at that point in the development thing. But, exactly like you said, you get out, the flow of the airport is much better. You get out, you want to know where your luggage is. It's actually, I'm tagged, it's in my app, I can see where it's coming, I can see when it's coming. Maybe I get that latte delivered. I don't know if they've implemented that there yet, but I can get that latte delivered because it's actually taking a little bit extra time.

Speaker 2:

It's a rainy day or whatever, and the flow of things is just so much better through the airport and through all these technologies converging. So so many cool things to happen.

Speaker 1:

Yeah, and the one thing I found that technology has enabled the airline world to do is save on space when space is so limited. So being able to move through an airport seamlessly without having to wait in line as much, without having as many checkpoints and stuff like that, has tremendous value from a real estate point of view even so, and then, okay, so that sounds like an amazing technology. Then what happened? Then? Where did you go?

Speaker 2:

So that brings us kind of to today, no-transcript. And so I'm kind of at a point where I'm consulting and working, advising some companies and helping them grow.

Speaker 1:

Excellent. So, using all that learning that you've had over the past, you said what 15, 30 years, Getting close to 30 years?

Speaker 2:

Yeah, so I'm hoping I've gained some wisdom along the way. Excellent years Getting close to 30 years yeah, so I'm hoping I've gained some wisdom along the way. And so, yes, I'm trying to provide that wisdom back and some of the learnings I have. I worked with something called and I think it's out here in Alberta, Actually I know it's out here in Alberta Creative Destruction Labs. I'm a mentor there. I work with some early stage businesses there. Currently I'm focused on the Web3 blockchain stream, but looking at other streams as well, I was in the Prime stream. I've been in the Health stream, so really applying that wisdom. This is one example of how I'm trying to give back and trying to share my experiences and see if I can help out and hopefully build an amazing. You know, help support an amazing company and build, help build an amazing company. Not exactly sure what I'm going to do full time on a day to day basis.

Speaker 1:

Next, Right, and it might not be anything.

Speaker 2:

It might just be helping and working with, advising with companies, but we'll see where all that all goes.

Speaker 1:

I'm really glad you brought up the blockchain environment. I don't have as good of an understanding of how blockchain technology is being used today, but I do know it's starting to creep into almost everything. You're starting to hear that used in the maintenance world and airlines. You're starting to hear that everywhere. So give me a little bit about that.

Speaker 2:

Yeah. So I mean, I think blockchain gets what I would say used in so many different connotations and unfortunately, it's had some very negative connotations, but it also has some very positive use cases. So you know blockchain. You're thinking of Ethereum, which is probably where it's getting used. I'm not familiar with how it's getting used in the aviation space today, but it is effectively a technology and a ledger type technology where you can input very easily and it keeps all the information and it takes some of the friction out of what would typically happen.

Speaker 2:

So get rid of those written documents. Get rid of you and I agreeing to written documents. It's there on the ledger, it's been inputted, it's been verified and it always exists, so you and I can go back to it and confirm that it's accurate and that maintenance activity, for example, has happened using that blockchain technology. What I think is we're going to see is those types of applications and supply chain. As an example, call it industrial applications and people don't. I don't think it's as well known that those are happening and it's not publicized out there, which is a shame.

Speaker 1:

Yeah, you always get it in the cryptocurrency world. You are happening and it's not publicized out there, which is a shame. Yeah, you always get it. In the cryptocurrency world you don't get it, but specifically, I've heard of the maintenance world using it for e-tech logs and many different applications like that, so that's a and that's a perfect application because, again, exactly that you have this ledger and I could see how that would work really well and the little bit I'm learning about the e-tech log and the maintenance side is because it is a permanent record that you can go back to and I input that that's verified by the other side and so it's confirmed.

Speaker 2:

You both confirm it in a way to the races and it's seamless as opposed to paper records or other things that are much more hard to verify. There are some issues with it as well, just sometimes time and costs associated with creating that, but it's very logical and very applicable to lots of different areas like that. There is an element, like I said, like you said, actually on the news today all we hear about is Bitcoin, the price of Bitcoin and how it's relevant to gold and inflation and all these other- and then somebody says blockchain in the middle of the thing.

Speaker 2:

Yeah, so, but there are amazing technical things happening, some brilliant people working in the true blockchain space. I also think tokenization is an element where you're actually tokenizing real physical goods. There are some large financial institutions that are working on those things. So there's lots of credible pockets and then there's unfortunately lots of I wouldn't say lots but some negative components. That you know, ftx is the world that unfortunately create a, you know, a black eye over the industry.

Speaker 1:

I do find, though, that, no matter what the industry is, there's always going to be people on the wrong side of the law, wrong side of doing it for the good reasons, kind of thing. So I just find it, with technology, it happens a little bit faster and a little bit more suddenly. But what do you think the big barriers to blockchain technology being used more? You mentioned time and cost, so is that the main barrier?

Speaker 2:

So I think today there are probably a couple elements. So we still have, you know, concern with the SEC and what's going to happen. You know the supply chain applications we're talking about, you know I don't think that really impacts whatever the SEC side, but it's still. Some, especially large corporations, are skeptical or concerned and like, well, yeah, but even if I'm using it in maintenance, what happens if the SEC says, you know, cryptocurrencies are something I can't hold? Well, it's not kind of not relevant because just building on blockchain, but it creates a queasiness around it. I think, like you said, because it was unregulated, some of the nasty elements also create some gun shyness, some concerns around it.

Speaker 2:

But I think the biggest thing is it takes time. Right, it's just time and technology. You know, through my whole career, one thing I've consistently learned and you know I lived through. I was working in technology through the dot-com era. I was there when BlackBerry went public. I was part of the team that got to take that public and so, like I look at that stuff and everyone would say, oh, it's going to happen tomorrow and every piece of technology I've ever been a part of in my life, it always takes longer for things to come to fruition and it just, you know, blockchain technology been around for 15 years. It's still really nascent and early in its evolution, so I think I think it just takes time.

Speaker 1:

I smiled when you said BlackBerry, we were having a technology conversation and I commented how much I miss my BlackBerry. I had a BlackBerry curve and it was just glued to my hand back in the day. Yeah, I had one of the first block pages.

Speaker 2:

I still have it in a drawer at home that, that I don't know where I put it recently, but I was actually. I showed it to my kids. I have a 14 and 16 year old and I showed it to them and they're like dad, are you going to?

Speaker 1:

sell that on eBay or something Like. I don't think so.

Speaker 2:

It's kind of like it's yeah. So it's pretty amazing that where it came from and where we are today, you know, think of your iPhone or whatever phone you're using in your pocket it's just and again, that was well, that was 1999 probably, or 98 that that came out. So you know, that's a long time ago. So think of the, again the evolution, and that was over the Mobitex network and now we're doing all this type of stuff over the, you know, over the phone network and over cellular and Wi-Fi et cetera. So it's such an evolution.

Speaker 1:

You know it's funny that you say only 15 years. It's a nascent technology. There is this slowly then suddenly concept when it comes to technology where once you hit that tipping point, it becomes almost an inevitability and it seems like we're hitting that more and more with different technologies out there. But timing has to be everything You've got to know when, as a company, to invest in that particular technology in order to get the payoff. There must be an art and a science to that timing. So how does a company know when it's the right time, like, for example, we sell a product that's based on the 5G network? Right, you know companies have to make a decision right now between going with a 3G, 4g or a 5G product. You know, how do you know when it's the right time to invest in the latest technology or to be too early, if that makes sense?

Speaker 2:

That makes total sense. I would love to tell you that's a science as opposed to an art.

Speaker 2:

I genuinely believe. It's still an art, unfortunately, and maybe someday we'll all get smarter and it will be a true science. But product market fit for every company that's introducing a new product to the marketplace is a struggle and it's so hard to get that right. And I was talking to someone earlier today who said to me oh yeah, we just opened the business and all of a sudden revenue was growing 100% a year and blah, blah, blah and I'm like wow my jaw hit the table and I was like I've never heard of that and that's not true.

Speaker 2:

I've never heard that before. I have heard that before. But it is so unusual that you get the product market fit so right on the first day. And you know when I I look at my history and I bring up the metaverse, you know, early on we thought we had hit product market fit. We were thought we were so dead on and there was FOMO happening at the fear of missing out from some of these brands that really wanted to launch.

Speaker 2:

Including Facebook and, yeah, many others, and we were there before Facebook, you know, and so you really thought you had hit it and initially the momentum was so good because of that FOMO. And then all of a sudden, you know, companies start to take a step back and go what's my ROI? And you know, where could I put my money? And should I invest in, you know, go back to traditional social media or should I invest in ads on TV or streaming ads or whatever it may be?

Speaker 2:

And at the end of the day, you had to make a business case, no different than you know, I'm sure, as you look at your products here, that 2DG, 3g, as a customer sitting on the other side says they're going to phase out that networks. How much more additional data? What's my additional cost? You know, is my plane going to have to sit while you guys refit it or retrofit it or whatever and all these types of things? And so we kind of went through that same process where the customers kind of said I want to know my ROI and that typically is what it boils down to. And there's a famous saying, and anyone that's worked in healthcare, in my view, is you've got to ask is someone willing to pay for the product?

Speaker 2:

And you find in healthcare it's really tough to find the payer, and the payer in Canada could be OHIP. It could be an actual business. It could be multiple different places that you go depending on private-public. And it's a similar thing I think is lost in the tech world where people don't stop to think who is my customer, who's going to pay for it and what is the business case and what is the ROI Right, and that's a failing of trying to launch the right products. It's also a failing of figuring out product market fit.

Speaker 1:

Yeah, it's one of the it's funny my role other than a podcast host is a product owner and I came from the industry that I'm creating the product for and I've tried to always keep my hat on who's going to be using this and how is it going to improve that experience for that user. And if I can't answer that question, I probably shouldn't be working on that feature. You know I spend my time on stuff that adds more value and and go from there. So I understand that that's uh. That's uh some sage advice and build a good business case, uh. So if you're a company in the tech space, make sure you're able to speak about those business cases and, as a company, if you can build that business case, that's the time when the technology is right for you. Is that what?

Speaker 2:

I get. I think you said it much better than.

Speaker 1:

I did Well, you got me there.

Speaker 2:

But I think that is so true. And again, not to pick on the tech space I love the tech space but sometimes and we're at an interesting point in the tech cycle but sometimes there's so much money thrown at some of these companies VCs line up Again kind of a similar FOMO thing where all these VCs don't want to miss out on an industry cycle and they get hundreds of millions of dollars and they just throw the money at the wall and hope that they're going to get it right, as opposed to when you go through a down cycle, like we're kind of living through, where everyone goes. This is the best time to build a business, and it's a famous cliche, but it's exactly for that reason because you now have much less resources that are available to you. So you really have to think about you know what's the business case. Does it really improve the customer life? And if it does, how much does it increase it? And therefore you know the risk, return, you know proposition from your perspective and their perspective. The customer perspective is extremely important and so all those things play out.

Speaker 2:

And again, the nice thing about doing it is because you're in a little bit of a down market. There's less VC money or less public money out there is. The nice thing is people aren't throwing it at these companies, so your competition can't build this, and so if you're in a great place, you can actually sit, put your head down, build an amazing product and bring it to market and bring it to market, which is a wonderful piece, so hard to believe in what I've just said and such a famous cliche, but just proven to be true.

Speaker 1:

So many times, I think, with the tech sector, we get caught up into what's cool versus what's marketable and what's cool versus what people actually need, and I find myself kind of caught in this trap right now with AI Right. Trap right now with AI right. This is if I don't wake up in the morning and hear the words artificial intelligence or AI 26 times on my way to work, listening to podcasts, listening to news, listening to anything you know, I'm probably not listening, I'm not using my ears that day and I feel sometimes the commercialization of AI is there's no sight line there yet. Like we're in the cool stage of being able to talk to, chat GPT and get a cool story about your cat, versus using that to actually help make decisions or to lower costs or to be more efficient. So where do you think we are in the AI space and I know that's kind of a nebulous question, but where do you think we are and where do you think we need to go before we start seeing AI used more frequently day to day?

Speaker 2:

So you know I think there are. So AI today, you know, taking a step back kind of about, as we talk about 15, you know year old technologies. Ai has been around for a lot longer than most people perceive it to be, a lot longer than most people perceive it to be Gen AI, which is really what's come to fruition in the past, you know, since the launch of ChatGPT at least, as the consumer, public-facing world got to know it, as is really a more recent element, and so it has been around, but Gen AI is and we'll take an easy suggestion.

Speaker 2:

You know you've got a chat bot on your website and so traditional chat bot, you know, can only answer a few questions and it's built the logic is built to answer those types of basic questions. You get a Gen-AI built chat bot. Obviously you can have a much more interactive question and it's not, you know, it's through, you know, it's deep learning capabilities that it's going to answer you and give you a much more detailed answer and actually can replace an individual. And so we're at the early days and I choose that example as giving an example of where we're at the early days where you can actually take individuals that might have been responding to those types of customer questions or Q&A or that first sales call, if someone is inbound on your website, where you can actually use a real chat bot developed by AI and repurpose that individual to go and get once that lead has actually been worked through, their questions and it's a true lead to go and then converse with that prospective customer. So you get to repurpose people into much more value-added work.

Speaker 2:

And so I think we're at the early days of watching many corporations start to implement that type of element where they're actually repurposing. One of the biggest issues which is so interesting with what Flight does is when you implement an LLM. One, a big corporation can't use chat GPT because obviously, as we've learned and read, your information is out there. You don't want that, so you need to make sure. One, I got all my own data and that data is clean and good to implement with that LLM. And two, I'm not doing it with chat GPT. I'm going to either build my LLM or I'm going to build a bridge where it's security wall protected on my own servers where I'm using that LLM. So that's very expensive. That's happening. Takes time. Large corporations like I sat on a panel for KPMG with Walmart, google and one other company probably about six months ago and they're using it.

Speaker 2:

I mean Google obviously would expect to be using it but, Walmart, they had actual examples in supply chain and other elements where it's being used. So we're already starting to see that, but it is early days. I think the difference, or the big difference that I would say, is the way you and I are reading it in mass media as an example. It's going to change the world. It is, but in a very different way. Every company is going to use it and can be impacted by it, but it isn't necessarily a company. It's going to create tens of millions of companies. Yes, there's going to be some brilliant large companies that we've learned about and are learning about today, but it's going to take time for us to implement it in our businesses, make sure our data is clean and start to use it and enhance our employees' lives.

Speaker 1:

Frankly, is when you're looking at big data sets and it takes the human mind so long to comb through something, to find patterns and to find process improvements and to find stuff that a computer machine learning model can actually come up with and figure out a lot quicker. And I could see that being. Another big use for it other than the front-facing technology is kind of replacing some of the data scientist part of you and allowing those data scientists to focus on what to do with the data as opposed to how to find out what the data is telling them. So is that how a company like Walmart is looking to use it? I can see this in the shipping world trying to figure out how to get things. What's the right amount of widgets to order to be at your widget store at the right time, right?

Speaker 2:

So I think you know, I think the element there's multiple elements. So, like you said, in the widget shipping, you know perspective. So you know, from a Walmart perspective you can start to predict. Like you said, you know, using data and data sets and watching consumer behavior you can start to predict what they're going to do and with that you can actually start to make decisions on inventory, on goods and all that type of stuff and improve your processes and improve your supply chain and improve your inventory.

Speaker 2:

Another simple example pick on, you know, is an example is if you were a condo developer or a multi-res developer especially we're talking about certain types of builds here in Canada today is you or I are looking at a condo or to buy a facility or buy a condo and I go into that condo building and I'm clicking on this unit on this floor and I like these, this type of shelving and these types of tables and whatever kitchen.

Speaker 2:

you know stuff and and so, therefore, as a builder, because this is all happening long before the build, I start to realize oh okay, my floor plans are because 75% of the people are looking for one bedrooms by what they've clicked on. 75% want blue cabinets. I'm making this up and I'm not a designer, but yeah yeah, and so those design choices you can start to really build interesting and better models for yourself as a company.

Speaker 1:

And everybody wins in that scenario. The consumer gets what they want and the company builds a more efficient model of how to do things. That's a really good example.

Speaker 2:

And I hope the consumer wins even more, because hopefully might not be the case is the developers passing on cost savings, because if all of it is 70% is blue cabinets, hopefully that developer is getting a cost break from whoever they're buying those cabinets from, and hopefully they're passing at least a portion onto the consumer, and so there are win-wins in those circumstances and, like I said, same thing applies to outbound sales. There are so many different ways where you can look at it.

Speaker 2:

Many people believe that coding again is another example where some of the basic coding that's being done today could be done by AI in the future, and some of the higher value-add coding could be done by AI in the future and some of the higher value at coding will be done still by individuals, but there's elements of all of us that can become more efficient.

Speaker 1:

Yeah, and taking away that mundane coding and that kind of stuff. I always try to bring this back. As you know, this is an aviation podcast, so I want to bring it back to aviation a little bit. But I wanted to touch on something you talked about with that example with the blue cabinets and that in the airline world, parts for the aircraft are extremely expensive. So how many engines do you buy is a multi-million dollar decision. How many engines do you need to have as spares? You know, and the more expensive parts spares, you know, and the more expensive parts, you know. Some airlines can carry up to a hundred million dollars worth of inventory and now they have to carry that in a store as opposed to knowing when something's going to break and replacing it just in time. We're talking millions of dollars that are being spent unnecessarily. So that's one use that I could see that coming. How far off do you think we would be from that use case if it's not already happening already? I'm sure some competitors out there are building that.

Speaker 2:

You know. So I think that use case is a great use case. It makes a lot of sense and, based on the potential cost savings, it makes a lot of sense for you to build data sets around. That Is anyone doing it today. Frankly, your guess is as good as mine.

Speaker 2:

But you know, I would think large airlines, et cetera, would want to build data sets like that. Clearly, you know the question is do they have clean data historically so that they can actually make and start building those, so they can make proper predictions and figure out that piece? I don't know the answer. You probably know the answer better than.

Speaker 1:

I do.

Speaker 1:

I have skepticism around that, but I don't know if that's I smiled because one of our big missions is to leave no data left behind, so to make sure that you have that data in real time to feed those models, one of our previous guests she actually sits on our board my favorite podcast that I've done to date we were talking about climate and we were talking about using one of the products, one of the sensors we build and put on the plane to help avoid contrails in real time in order to limit the effect on global warming.

Speaker 1:

Right, like the fact that we can take that big data set. Tell a pilot hey, if you keep flying at this altitude or at the speed there's a couple of different variations of that you're going to create a contrail, which we're obviously trying to avoid. It's amazing that we're getting to that place, and so it's exciting to be on that end where we're kind of that conduit to provide the information those companies who need those big data sets have. So it's neat to see that come up organically in the conversation. I smiled when you said that.

Speaker 2:

Yeah, it's. You know, I think companies historically didn't like. I think everyone's talked about data and realizes it's very important and so many times in my previous life I've heard people say we'll just sell the data, like the data is so valuable, but no one really stopped to think how clean is my data? How do I make sure it's clean? How valuable is my data? And I think that's going to become more and more relevant today Huge, probably, opportunity for AWS and many other warehousing systems.

Speaker 1:

Of course.

Speaker 2:

But you know, I think that's such a key element of this. I think that's such a key element of this. And once it's clean and you're able to analyze it and use it, the value is so immense and it's exciting. That's one thing about technology. I always think we're in a technology inflection point and I think we continue with that every day. And technology has really impacted our lives consistently and will for the next long time.

Speaker 1:

Right, I love that technology inflection point. I think that's just such a great way to put it. Where do you think AI is going in the next 10 years? When I told my colleagues what we were going to be talking about or where I thought this pod was going to go, one of my colleagues jokingly said well, we won't have jobs in two years because we'll our whole worlds will be run by computers.

Speaker 2:

And I don't think we're there yet.

Speaker 1:

But uh, where do you think the future goes?

Speaker 2:

So I think kind of what I was alluding to before is I think what we'll see is a slow evolution of the next 10 years. We will all have jobs in two years and just like when the internet first came out Sorry, jeff Just like everyone had fear of, hey, I'm going to lose my job, the internet's here. Those fears have existed for as long as I've been working in technology. I think what I'm hoping for, from at least the consumer employee perspective, is that it makes all our lives better, and what I mean by that is if you are in a mundane job or elements of your job, which everyone has elements of their mundane job. I use a very simple example. I used to use Google all the time to search things up. I don't bother with that anymore. I just use ChatGPT.

Speaker 1:

It's way more efficient.

Speaker 2:

It's like it gives me a much better answer and yeah, maybe sometimes I check it with Google because you never know, but it is. It is just makes life so much more efficient.

Speaker 1:

And before Google came along, you know you're using really antiquated search engines, right? So Google displaced them, and now it's being displaced itself.

Speaker 2:

And it's actually it's a real worry that I've read about is, you know, people question the future of Google. Google's got lots of AI. They're just going to be fine. But putting that aside, you know, and my point in sharing that is, it's all about efficiency, and so if we could all spend our day in a little bit more of a value-added way because we're using these different AI models, that makes a ton of sense and you're going to feel better about yourself. It's going to make the economy more efficient, and so everyone's still going to have a job. We're hopefully just going to be that much more efficient.

Speaker 1:

And a job that's that much more meaningful.

Speaker 2:

And rewarding in many different ways, so meaningful rewarding to yourself, all that type of stuff. So I think that's a big piece. And then I look at the consumer's perspective and I'll go back to something that I'm also passionate about, which is health care. So a simple example is and I can get into a lot of detail, so I'll try and keep this at a very high level thing is, choose our biomarkers. So you do. I don't know how many blood biomarkers, but let's for argument's sake.

Speaker 2:

You go to LifeLabs, you get blood tests and you get 30 different biomarkers. At the end of the day, you, as a consumer, wouldn't it be nice that you get your blood back LifeLabs? It goes to your AI assistant, your AI assistant. Next morning you're sitting at the coffee table yourself your wife, spouse, kids, whatever and you're having a conversation. Your AI assistant pops up and says hey, lauren, it could be Alexa, it could be whatever. Hey, lauren, we got your results back from LifeLab. We have a few things to talk to you about. You, lauren, we got your results back from Life Lab. We have a few things to talk to you about. You probably want to follow up with your doctor, but here you go and this biomarker is telling you this and maybe you should eat a little less sugar and cut back on those burgers and get proactive, and you can. Actually, you might not want to listen to it because you don't want to cut back on those burgers or french fries.

Speaker 1:

But at least it's there.

Speaker 2:

But at least it's there and you're getting proactive information that you can live your life for. You know it could profoundly change your life because it's telling you about all these different things. And again, it's up to you personal choice of what you're going to follow or not, but information is just so powerful.

Speaker 1:

So healthcare seems to me to be the perfect industry for technology to improve upon, because it seems we spend money like it's going out of style and nothing ever happens faster, nothing ever happens more efficiently, and we're stuck in this cycle of throwing good money after bad without getting the results. So where do you think health care is going? I know that's a little bit off of uh aviation, but that that is a little off, uh, since I have you and you're an expert on it. I wanted wanted to pick your brain on it.

Speaker 2:

So I'm a big believer in access, and what I mean by that in English is you know, we need to get everyone access to healthcare, and you know, in Canada today, as an example, obviously we read about all the time there's a shortage of physicians and that's a true problem, and so technology is definitely helping with that. When you start to get into telehealth and virtual health, where you can get a doctor and be able to see they don't have to be in your city.

Speaker 2:

Don't have to be in your city and you can get access to them in a very quick manner and instead of trying to find a family doctor that could be very difficult to get access in 24 hours, and you're able to deal with the problem. It doesn't work for everything and sometimes you're required to go into a physical clinic or other things like that, but just as we talked about with the AI example is, you can get sent to a lab, you get a rec, the results go back to the doctor and there's so many amazing things that can happen. We live in a world where in some ways, it's great and in some ways it's not so good. It's a highly regulated world in healthcare and that makes it sometimes difficult to cause change or implement change no different than aviation, frankly, which is a great way to bring it back, and it is a struggle.

Speaker 2:

And frankly, like I said, for nine years I worked in healthcare. I am advising a healthcare business today and I look at it and go. It just moves so slowly as an industry and really there's just so many great things that we could do so many great things to push patients out of hospitals, to reduce our cost, to make it more efficient. Be preventative To be preventative, right, you know, it just goes back to the biomarkers and all those wonderful things that we can do and it just we're just so slow and I don't have a good answer, unfortunately for it. It just, someday I'm hoping it all changes.

Speaker 1:

Now, before we started filming, we were talking about a highly regulated industry that had some success embracing technology. So you brought up Tesla and the example of what Tesla's done. So talk about that a little bit. And then I want to talk about how we could apply that to the airline sector the lessons learned with cars, because cars are as heavily regulated as airlines and healthcare, safety, airbags, all these kind of roles and regulations. So how does that tie in?

Speaker 2:

I mean, it is clearly a very regulated business and we all saw what Tesla did and how it disrupted the marketplace. It really changed many different things. Like you, you shared the example of, you know, being in a autonomous vehicle, self-driving vehicle, a couple of years back. I remember probably five to seven years back, early, like not early Teslas, but have been out. But I got into a friend's SUV in LA and I think I'm trying to remember how far we drove, but we effectively he had it on self-driving, he was watching and I probably shouldn't share this think I'm trying to remember how far we drove, but we effectively he had it on self-driving, he was watching and I probably shouldn't share this and leave him nameless because he probably loses license for this right watching episodes of Colbert on his uh on his computer.

Speaker 2:

He was off the of the front windshield glass while the car was self-driving itself and, frankly, as we're flying along at whatever it was miles per hour, I was kind of having a little, you know, heart issues, as I was stressed about Tough to be an early adopter of the vehicle at the end.

Speaker 2:

Yeah, but it was amazing to see obviously what it could do and obviously what it was doing through sensors. And you know, we've started to see those sensors implemented in more traditional internal combustion engines as examples BMW, others have started to implement that sensor technology. But you give Musk a huge whether you like him or you don't a huge applaud for the way he disrupted that and that's just one example, obviously, how he manufactured the product, even how he sold and delivered the product, he totally upended the whole system of cars and he grew, which no one ever thought he could do. The market share that he's gained is exceptional. Now, yes, byd at Atreina has now surpassed him as the largest electronic vehicle manufacturer, but still, you've got to give the man credit for what he's accomplished.

Speaker 1:

Basically changing the industry.

Speaker 2:

Yeah, he turned it on its head and I think you know, as we were discussing earlier, like someone's going to come out at some point. You know it's really expensive, you need a lot of money to go and do this, but someone's going to come out and disrupt the airline industry for sure.

Speaker 1:

I think that brings us to a natural conclusion. I have a question that I ask every guest on the jump seat, because this is a aviation podcast. Uh, where in the world should I go that you love? Give me a, give me a travel destination that I might not have gone to, or somewhere I need to seek out.

Speaker 2:

So it's, it's a perfect question. I just came back from March break. Uh and uh, we came back from Japan, Uh, we went to. Tokyo, osaka, osaka, kyoto. It was an amazing trip Really. I think I said this earlier, I have a 14 and 16 year old child, my wife, and it was the destination. I think we were all impacted by different things and different things. The culture is so unique, everything is so unique, food is amazing. It's a great place, and so I would highly recommend that.

Speaker 1:

Excellent, and I know there's some great direct flights right out of here in Calgary, so that's excellent. Well, lauren, thank you so much for spending some time with us today. We have some amazing guests coming up on the jump seat in the next month or two. Stay tuned for more information on our LinkedIn page.

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