In this episode of The Future-Ready Advisor, Sam Sivarajan interviews Dr. Jeffrey Funk, a seasoned expert in the economics of innovation, to dissect the current landscape of AI, blockchain, and other emerging technologies. They explore what sets transformative technological innovations apart from the hype and discuss strategies for financial advisors to navigate this complex environment.
This episode provides valuable insights for financial advisors and senior executives to better understand the evolving technological landscape and make informed decisions that prioritize long-term value over hype.
Hi everyone I'm your host Sam Sivarajan. Welcome to today's episode of The Future Ready Advisor. Today I'm here with Doctor Jeffrey Funk, a technologist and leading voice in the world of AI.
::Doctor Funk, welcome to the show.
::Thank you. It's a pleasure to be here.
::Delighted. It is a very timely conversation about AI and technology with everything that's going on in the markets and in the world.
::Let me quickly introduce you to the audience. Doctor Jeffrey Funk is a leading expert on the economics of innovation with over 40 years of experience studying how technology impacts industries and economies. His work has been featured in fast company, slate and ports where he offers clear eyed analysis on the real world.
::Implications of AI, blockchain and other emerging technologies. Doctor Funk has advised corporations and governments helping them navigate technological change, with the focus on creating sustainable.
::Value.
::His insights are invaluable for anyone looking to cut through the hype and understand what truly drives innovation.
::And I think that's a great place to dive in. I think there is and I've seen a lot of your commentary about some of the hype that we're seeing in the in the marketplace.
::Maybe before we dive into that part of the conversation, you've had a a long, distinguished career analyzing the economics of innovation and technological advancements.
::For our audience, could you share some of the key milestones in your journey that led you to focus on the intersection of technology and the economic impact?
:: ng the landing on the moon in: ::Systems was a bit avid reader of science fiction. I ended up studying majoring in physics and then I went to work for a a semiconductor factory, then went back to Graduate School to get my PhD and in engineering and and I I I was one of those people was always looking for the next big.
:: ry interested in Japan in the: :: to take over the world in the: ::When I was dealing with these technology and things so.
::A lot of what I'm doing today is because I realized early in my life that I needed to learn this in order to make better decisions, because it's not just about, well, what are you going to do for your company, what technology and what you do is how much money going to spend them. It's your life, what career are you going to choose? You know, you have to be careful about jumping on the next big thing because sometimes that big.
:: ple think it was. And then in: ::Technology I dealt with almost all these new technologies and still I was a big optimist. I knew that most of the progress was in electronics, but I could see things happen in nanotechnology and superconductors and bioelectronics at Toronto's kind of I could see all these things happening, but after a few years of teaching the course from updating the slides on these technologies.
::Every semester.
:: gies aren't getting better by: ::I.
::Said that was in.
::My slides 10 years ago and it's only a little better.
::And when I saw ten years ago, right and.
::This.
::Is perspective. You have to have, you know, you hear a an announcement. It sounds so great and you think. Ohh yeah, that's just the beginning.
::It's not the beginning. The beginning was a long time ago.
:: rtups were profitable, and by: ::It's.
::Like all these unicorns are getting profitable, I mean, Unicorn are going out of business being acquired or going bankrupt much faster than they are doing IPO's and and becoming profitable. So to make a Long story short, I've just, I've taught myself to be skeptical, partly because I wasn't skeptical when I was young and I had.
::To learn that.
::But I also learned that from working with a lot of companies and learning from what succeeded and what didn't read, I've always been a voracious reader of histories of technology because I like to understand exactly what happened in the details of which products came out when, and could do what.
::So that's kind of a long introduction.
::It was an interesting thing about the history repeating itself like one of the things that reminded me of what you're talking is, and you've seen it many times. Is this chart that Gartner puts out the technology Consultants group about the hype, the hype cycle?
::And how that the hype always leads by months or years? What is actually the the manifestation of the the technology in a commercial?
::Way and that leads me to one of the pieces that you wrote in the American Affairs Journal on Web three and the metaverse that was making the news.
::In the last few years, and in that piece, you argued that these technologies lack practical, useful innovations. Love for you to talk a little bit about that. How do you differentiate between high driven tech trends and genuinely transformative innovations?
::Well, I think that when you think about a technology, you have to connect.
::All the all.
::The technical details and the improvements in the performance and the performance and improving the performance to actual applications.
::In the end, you have to.
::Think about.
::People. And how does this make people's lives better? So I mentioned that I've I've read a lot of history.
::Well.
::You read history of technology from a long time ago. When you read about water wheels and enameling food to be processed faster, clothing to be made faster, lots and lots of things. These are things that people want and and so I have focused on that my entire life and a lot of other people do too. But over the past 10 years, you see the.
::Conversation going off in weird directions recently. I I watched Eric Schmidt, former CEO of Google Talk for an hour and the only application he talked about was music and video. And he said, well, you can steal those from everybody.
::He didn't say anything else. He he just said, well, I think it was called arbitrary action that somehow you you just push the button and all these agents go out and do all these things for you and you didn't talk about any good things. You didn't talk about making products or harvesting crops or treating patients in hospitals. It was all.
::Just kind of.
::Just technical details that he was talking about and we see that in today's world, I don't know why. I think part of it comes from the fact that most of the most successful business over the last 20 years have been kind of outside of.
::The things that most people think about, like food and clothing and appliances and housing and healthcare, most of it has been in Google search.
::Which?
::Yeah.
::YouTube videos. Social media I mean.
::These things that they don't really strike at the core of what humans want, right? I mean, there's been a lot of discussion. So I think that a lot of these tech leaders, they've gone off in this weird direction of we know all this technology is really going to help humans. And so we're just going to focus on the technology and not try to say anything about how it helps humans.
::You make a great point. Even leaving aside things like food and transportation and the day-to-day necessities of life, even if you look purely a technology.
::One could argue that the very first smartphone was maybe a technological innovation, but the next iteration that is a bit smaller or a bit faster, or has.
::One mega pixel more in in the camera is that really an innovation that is going to make a dramatic difference like the the the first one? Did you're talking about not just technologies that are going to make an impact on human life even if we narrow it further down and just talk about productivity and.
::Yeah.
::Increases at a time when productivity is not increasing, does more social media or a faster social media, or a better interface and social media? Does that have any impact on productivity gains for?
::The workforce.
::Yeah, I agree. I think that it's not going to lead to improvements and in fact.
::A lot of.
::The efforts in those areas, just it it'll increase engagement and things, but it's it's not really leading to people coming together to solve bigger problems. And I know that a lot of people will look at the stock market being so high and ohh this is the technology is so great.
::And I say.
::Well, what's going on right now in the election? Do you see happy people?
::It used to be that the Republicans were happy about the free market and about things were getting better and the Democrats were unhappy about and calling things. But now even the Republicans are angry.
::Right. Most strong supporters are angry. They want something really big change so they're not happy. So really, you being to wonder? Well, it seems like more than 50% of the people are unhappy or mad.
::It's only top ten 20% who seem to be happy about how things are going, so it's not just that the productivity figures are poor, it's that people are telling us that their lives really aren't getting better. And despite having the record high stock market.
::Let's go on to that point about the record high stock market. And this is Jermaine to financial advisors. In a landscape filled with buzzwords. And as you we talked about over hyped tech solutions that may not improve the human condition.
::What strategies can financial advisors use to help their clients avoid getting caught up in the hype and instead focus on investments or innovations that can offer real sustainable value?
::This is the focus of your forthcoming book. In October, unicorns, hypes and bubbles. Can you talk a little bit about your new book and what investors should be mindful of?
::Well, first of all, I'm not a finance person. That's not my feeling. So I went to a practitioner book and all the practitioners said you got to have a how to book, you know, just tell us how you work with this company.
::And then you created this billion.
::Company. You know, it's really successful. I said, well, that's the whole point. There isn't any. There's so few profitable startups. There isn't a lot of success. The productivity growth is slowing, the innovation is slowing. No, no, we want a how to book. So I had to.
::Make it sound like I was telling people how to understand the stock market, which I do, but not in the traditional ways, right? I I don't do that at all. And so I talk about new businesses and I talk about the economics of them and why a lot of startups are losing money because they've chosen businesses that really aren't that.
::Right.
::And somehow that builds from Robert Gordon's book of the rise and Fall of American growth. So he he does a masterful job of talking about how all the innovations.
::50 to 120 years ago made people's lives better.
::MHM.
::And I talked about how well the ones we're talking about recently really haven't made people's lives better little. But it's not like they've increased the productivity so that we have cheaper transportation or cheaper, cheaper.
::It's a little more convenient, and so I'm highly critical. I call these low tech businesses, I mean.
::This is very different from the startups of the past, very different from the semiconductors and the computers and the computer software and the computer networking and the the fiber optics that we had many years ago. Very science based stuff that really was much better and gave us great products and services, but also.
::Provided a lot of jobs for people and then.
::The the second-half of the book is more about the technology based startups, so there are a lot of startups that tried to commercialize new technologies. Some of them, I would say call science based technologies like.
::DNA sequencing and things of this type. But the problem with a lot of these technologies is that when you look at what's happened over time, the rate of improvement in the new technology has been very slow. And but but Despite that, the companies have all kind of aimed for the mass.
::OK.
::Trying to have that iPhone moment when the product comes out.
::And it's so great that everybody buys it.
::What they need to do is they need to.
::Find the niche what people used to say in business schools, but now they don't say it. Find the first customer, the second customer, the third person said. Business schools are a general purpose technology and when this happens, everything's going to change.
::Hey, to make it happen, you find the first customer, the customer third customer. So who's that first customer, people who who will pay a lot for it or will?
::Put up with low.
::Low performance. You have to find those people, right? If you're an investor, you have to be looking well. Are they getting finding customers that really like it? They're really going to pay for it.
::And make it profitable.
::Are they dealing with the technology that has rapid improvements?
::And people aren't doing this. And I mean, AI is such a great example because people look and say, oh, it's just improving so fast. Look at all these new products that are coming out. They're all over the place.
::Yeah, but just because lots of new products doesn't mean they're getting better. I mean, the one area where I would see AI getting better is that.
::The video quality right, you say generally and good video quality is getting better. But if you look at the important.
::Measures of earth and by the way, I'm much more optimistic about generative AI for making advertisements. Science fiction portions of movies, you know, particularly science fiction movies where where truth isn't so important, where you can have hallucinations.
::But you get outside some of these applications. Hallucinations are important. What is the frequency of hallucinations? Is it going down well? Not really.
::This is one of the key measures from so if you're trying to judge about a technology, whether it's going to really succeed, one of the key factors is, is it getting better?
::Figure out what the.
::Customer really wants.
::Is that getting better?
::Right. That's the key thing. And so I go through tons of these technologies from delivery drones to VR to AR on and on.
::It's my engineering and science background and I think a lot of these people who are making decisions about stocks.
::They not only don't have any understanding of engineering and science, they just kind of ignore it all. They they just kind of believe in these kind of general statements that tech leaders are making. I mean, I read an article recently where all these board members are making decisions about AI and they're making decisions based on presentations from tech suppliers.
::Come on. Of course, the tech suppliers are going to exaggerate.
::The better product.
::Haven't you ever heard the stories about used car salesman? Right? It's the same thing going on here, right? You you really have to ask?
::These questions just.
::So and so a lot of my book is saying, hey, you don't need the expert to tell you you could do this yourself.
::All you gotta do is think through this in a logical manner. Look what's being announced. Figure out whether there's improvements, and if there isn't, well, then it's a niche product for now, and then you gotta figure out.
::Your point is being on just to use one example. I can't remember exactly when it was that Elon Musk announced that within four years it would be a a soft driving car from New York to LA. I think that four years has come and gone like three times, and we're no closer to that happening.
::But to your point, I think the issue is also that people forget the technology at its core. If it's done right, it's something that should be a a tool that can help.
::Human beings go about their lives, but it's not replacing judgment. And the example that I always use, and it may be too mundane, but it it it would be interested in your opinion.
::Is GPS is a great tool for the average driver and most people don't have anymore sense of direction. They'll just enter the the coordinates into the GPS and go so no one will gain say that it's a great tool. OK, but there's two points to that that that I found interesting #1, there's enough anecdotes every year of people.
::Wrongly following their GPS into a dry riverbed or something because they misread it.
:: his was maybe around the year: ::Put out your GPS satellites and you better have people that learn how to navigate the old fashioned way by stars. So the point I'm making is that tools are important. As you say, people can be equipped to ask is this tool going to add value?
::But use the degree of skepticism to sit there and think, is it really going to do what it says on the box, but more importantly, where and when do I use my judgment to know when to use that tool? What that tool says and when to ignore it?
::Yeah, I agree 100% context is important.
::I don't understand the context you're dealing with and the situation you're in, and I I don't know how many business professors would tell me that I had too many too much contacts in my business slides.
::That's all it is. It's not theory, it's context, it's understanding the context and understand how your business little different. Somebody else is and how the technology applies you, you can't just.
::Do theory, I mean, most business professors? I mean, I talked with these guys at nationals to Singapore. They would just look through all the top academic papers and they would teach those theories.
::And of course, if you do that.
::You don't have any common sense because all the common sense was took another long time ago. Nobody would publish a paper on common sense. This isn't new. This is a novel we we don't need to publish this, we already know.
::And now what you have is you have a generation of professors.
::Who don't have any common sense, they don't.
::Own common sense.
::Because those papers aren't published anymore and as a society we've kind of become this way. And to be fair, you see, I was a nerd who didn't have common sense when I was a kid because I was a math whiz.
::And I learned all that math and did all that, and I didn't have a lot of common.
::Sense and and so I've kind of reversed myself and learned all that stuff and learned how important it is and learned how there are people with common sense. You got to be asking people the right questions and unfortunately the tech Bros, they go past all this and a lot of people. So Rich, you must be so smart.
::MHM, MHM.
::Umm, you know? Or he succeeded in that business. They don't understand that every business is different. And you know, people are are smart in a different way and you can't just assume that one guy was smart in one way. So he's smart.
::In all these.
::Other ways 100%.
::Because that's not the way it works. Everybody is smart in a different way and there's a lot of different skills you need in the world.
::We've got this.
::Educational system that only favors one type of smartness.
::Well, that's a mistake because there's a lot of different kinds of smartness, and we need a lot of different kinds of people. And we're new with new technologies. You gotta be looking at a lot of asking a lot of different people questions, looking from a lot of different perspectives. You can't just be listening.
::To the tech.
::Bros I agree 100% skill in one area doesn't translate because you're a tech pro doesn't mean you're going to be a great politician.
::Leading a nation.
::But but yeah.
::You know, to me the types of problems that we're we're facing now as a society, whether it's climate change or other things.
::Require multiple different types of skills and leadership and thoughts, and we we should remember that the one thing that you talked about and I'd love to dive in a bit more is this whole idea of over hype, particularly from the context of AI, but.
::You talked about Tech Bros, you talk about the hype, you talk about people being aware of it. Why? Why do we fall susceptible to it? Why is the stock market running ahead of itself? Why do these startups? And there's many that we've had over the last 5-10.
::Years. I'm thinking paranoids. I'm thinking we.
::That raised billions of dollars in venture capital from some of the smartest minds.
::That are out.
::There. Yet they were old fashioned frauds or didn't work. Why do people fall victim repeatedly fall victim? Even some of the brightest minds to this hype?
::And not be able to sit there and say that the Emperor has no clothes.
::Well, people want to believe in something positive. They want to believe in a positive future.
::Particularly rich people, they want to believe in positive, you know, things are going to get better and and so we're very prone to believe and optimistic.
::Story you know, a CEO asked a bunch of people for advice, and he or she the CEO is probably going to believe the person with the most often this submission. Somebody says, well, I don't know about this technology.
::They will do kind of OK, but you got to think about these and this and this and then somebody else says, man, this is gonna really succeed. It's gonna make so much money for this company's gonna do this, this.
::Business see.
::Sis.
::Yeah, I I like this. I like this guy. I like this optimism. Yeah, yeah, yeah. This guy, this pessimism. I don't like that. We just fall for that so often, you know, the CEO who's always been successful, probably because he or she is smart, but also because they probably got lucky, right, they they they don't see through that and it's unfortunate.
:: a play on robots back in the: ::And we've been hearing this story about and put everybody out of work and it keeps happening. And myself and my co-author Gary Smith, we've reviewed so many of these studies, they have all these fancy black boxes at malls that they used to judge how many people are going to lose their jobs from robots.
::Because there's all this database on jobs and what tasks are in those jobs and what tasks can be done with the robot they keep using. These things keep predicting. So many people are being unemployed.
::And it's kind of useless, you know, Gary and I, we we say just go back and look.
::At the 1st.
::Application and see is there a first application OK is the technology getting better? OK, how's that gonna help us with the 1st the 2nd to the third? They never do that. They never do a practicality checking and you have people doing this. So we've got all these.
::The elites who are giving advice and they keep giving the same advice that we're going to, everything's going to be automated, right? Remember, rise of the robots. Remember, world without work. Two books that won the Financial Times. Best book of the.
::Here.
::You know what keeps happening and I I realize I'm kind of going around your question because you're saying, well, why does this happen? But people want to believe this and people have been hearing this about LAN robots and they believe in the back of their mind that this is going to eventually happen. And you know what? It probably will. It's just that is it going to happen?
::Now.
::Or is it gonna happen 100 years?
::Let me tell you one final story. Charles Babbage developed a mechanical computer.
:: When you are: ::Hmm.
::You know, you could have said, hey, look at that. He was right. Computers were right. But it took so long.
::That his predictions were kind of.
::Meaningless.
:: an, if you'd invested in CARS: ::You know, let me think about a data point from 10 years ago from 20 years ago.
::From 30, because that's what you.
::Have to do. You have to think about those data points. You can't just think those as now. So by university they've done this and Oh my gosh, it's all just starting, no.
::Wait, wait, wait, wait, wait, wait.
::Compare that to the announcements that we're making by 10/15/20 years ago.
:: , turned it in: ::I made a lot.
::Of those very optimistic predictions and so.
::I've lived through this.
::No, that's a great point. The the Babbage example is a great one and it is not that diminishes innovation or is discovery, but it required a couple of other contributing factors, catalyzing technologies that were able to make this a reality. The other example that comes to mind is and we don't hear about it anymore, but what?
::What was it 10 years ago, 20 years ago? This mapping, the DNA, the human genome was a a huge, huge project and it got lots of headlines and it was done at millions of dollars.
::And I I'm oversimplifying the conclusion, but it is that between us and a baboon, there isn't that much amount of difference in the in the DNA. Yeah. But we certainly haven't been able to commercialize that in any meaningful way. Does that mean that it was not good research and innovation? No. But we probably need one or two more things that are going to happen.
:: Over the next: ::And it will take long.
::For all of that to come together in some sort of a meaningful way to create commercially useful applications.
::Yeah, I agree. And that that's a big part of the book. The Part 4 is on science and it's basically it takes a long time for these things to happen. And so just because some venture capitalist told you that quantum computers.
::Are here and solid-state batteries and all these other technologies that that they spent money on? Well, it probably isn't. It's probably a lot further away than they're saying.
::Ah.
::I want to touch on one more thing before we wrap up and it's bringing it back to the human side of things, particularly from financial advice. But almost everything and you've covered things like radiology and everything else in some of your writings. I happen to believe the human aspect is irreplaceable. There is a judgment and the ability to deal with.
::Context and complexity. We don't have technology or AI or anything being able to do it. We're getting technology that is increasingly becoming a part of customer or client interactions, whether it's chat bots or interactive voice responses.
::And.
::How do you think somebody like a financial advisor who needs the efficiency that comes from an AI tool but still needs the human connection to make a difference? How do they balance both?
::Tensions, if you will, to maintain personalized client relationships.
::We have to think about.
::How accurate a tool is?
::Right.
::You know whether it works 90% of the time, 99% of the time 99.99% of the time.
::Right, and sometimes work all the time. Our calculus work.
::All the time.
::But if you look at the up time for Google or the up time for Amazon.
::It's decades long improvements in that uptime.
::Right. And I don't remember exactly how many nines they have, but I remember the article I read gave some data that said it wasn't yet the six nines, which is what it needed.
::And yet, cloud.
::Strike went down right and Cloud Strike went down and the impact that it had on all of these companies was immense.
::Yeah. Yeah. So, yeah.
::Yeah, and this article was talking about driverless vehicles and how well, there's lots of accidents, but it's it's really high the the accuracy of vehicles in terms.
::So you know how many people die? Obviously, a lot of people don't die because otherwise we wouldn't drive the vehicles. And this is the problem. And. And so when you think about self driving vehicles, you're you're thinking about how are you going to achieve 6 nines.
::And the articles talking about how long it took for Google and Amazon to achieve that in terms of uptime.
::And yet that was a far easier task, as this virtual task doesn't involve the physical world where you know you have a lot of weird things happening, you know fires and things fire trucks and things. There's on and on and on. You know, all these edge cases they call. So you have to think about.
::You know how accurate something is and think about an application that doesn't require a lot of accuracy, so there's lots of things in the AI where you know it doesn't matter. I mean, Rodney Brooks does does talks about this all the time and says behind every AI system there is either a human who deals with it goes wrong or.
::It doesn't matter, you know, like some kind of picture. The wrong picture showed you on your data.
::Yeah, you know, so so you got to think through those those through those cases and think about how accurate do you require the AI.
::To be that's a great point that if you're having AI perform surgery on you, I think you're going to want six nines or something in the accuracy. If you're looking for it to recommend that the next movie that you want to watch.
::Yeah.
::We we're we're using the same set of metrics and tools to assume that.
::Says.
::Netflix or Spotify has been pretty good at recommending the movie that I just saw or the the the the band that I just want to hear that that technology can be equally as robust and and useful for something that has more consequence, whether it's in giving financial advice or.
::Performing surgery, as I said, yeah, I agree. Well, Doctor Platt, this has been a really interesting conversation. We're coming to the end of our podcast. So I have a few final rapid fire questions for you that I asked all my guests.
::So #1 professionally, and I think you've touched on it a bit, but professionally what is the most important lesson you've learned over the years?
::No, that's there's no one important thing. There's so many important things and.
::I suppose if I was to say one, I would say.
::Don't be emotional. I think the big reason that.
::What's his name? Warren Buffett is so successful. And his his assistant, Charlie Mungers, because they were very calm and emotional.
::You know you're going to have to make.
::Unemotional decisions you can't.
::Make decisions about AI because you like AI and oh, I like that company. I I like that CEO take.
::All that throw it out.
::Right, just try to be as objective as you can and it's hard because.
::Once you, once you become emotional, a lot of people just become emotional. Their parents are emotional, so that's how they think they should act in the world. But you really have to try to become very, very objective about these technology.
::In these sense, and.
::Not obviously, not in all life, but a lot of business you have to learn to be try to be.
::As good as you can.
::It's a great point and we see it now with social media and everything there is this echo chamber, this fear of missing out and it it plays havoc on.
::People on everything from what the consumer purchase choices to stock investments, to career, to all of those things. You're being impacted if you let it by the the tyres of human emotion from everyone around you. Yeah. The second question is what is 1 practical tip you would offer listeners keen on?
::Applying your insights.
::A long time ago I decided that.
::Every year, I'd make predictions, and now it's just all the.
::Time I always make predictions.
::But I don't tell anybody, I just say.
::I think this is going to take so and so long, you know, and it used to be when I was younger that I always thought everything was gonna happen very quickly.
::And then I realized it wasn't happy because then I decided I would start to tell myself, ask my tell, think to myself how.
::Fast do I.
::Think this and I began to learn that things were were occurring much slower.
::Then then they were occurring and I think it's very important to do this. You don't have to tell anybody, right? The second thing is that when I was 40, I moved to Japan to live there.
::Full time. I'd been going there a lot before then, but when I was 40 and I told myself, OK, I'm going to be meeting all new people.
::All all these, a lot of these areas where I used to have opinions, I'm not going to opinion because in reality I don't know. I always said I knew because all my friends said they knew and I didn't want to disagree with them. Well, now I want to meet new people, so I'm going to stop saying I have an opinion on that.
::And I'm only going to have opinions when I think that I have a something to contribute.
::Because I think that we have this spirit of debate that everybody wants to have an opinion on everything from education to, you know, political candidates to.
::Capitalism through why don't do that?
::On and on.
::Say well, I don't know. I I'm not sure. I'm still thinking about it, you know? And it's OK. I'm 68. It's OK to say that because you know, there's a lot of hard problems in the world and there's no reason.
::To say you understand, understand something you don't have to understand everything. Even in 68, there's no.
::There's no easy solutions and the the idea of trying to remain humble and being open to different perspectives, especially in from different parts of the world I think is important.
::Great discussion. If listeners want to learn more about you or find your work and where they can find the book and and when it's getting published.
::Yeah, well, you can follow me on LinkedIn. You know, I'm on LinkedIn. I'm easy to.
::Find I have a.
::A relatively unusual name, Jeffrey Font. There are some other people with the same name, but it's not that.
::Common.
::So you can find me there. Follow me. And the book will be coming up from Harriman House.
::You can also Google that unicorns hype and bubbles.
::Awesome.
::Doctor Funk, thank you for joining us on the future Ready Advisor today.