40. Debunking AI Hype: A Reality Check with Dr. Jeffrey Funk

You might have seen him sharing his insights in MarketWatch, Fast Company, and also in my case, I see him a lot on LinkedIn. Uh, his upcoming book, Unicorns, Hype and Bubbles will be released in October. Welcome, Jeffrey. Dr. Jeffrey Funk: Thank you. Pleasure to be here. Uh, thanks so much for joining me at this very early hours of the day.

Um, this episode is different for me because many of the guests that I've been interviewing for AI marketing and brands are usually sharing an optimistic perspective around the technology and AI. Uh, however, I know that you're a voice of reason and you balance skepticism and optimism. Around the technology, uh, in a good place, in my opinion. So I'm really excited to have this conversation with you.

Like you were one of the first person to recognize the potential for smartphones during the early two thousands. Could you talk a bit about that? And, and while you are talking about it, I would like to also understand how do you evaluate the potential and sustainability of a new technology? Dr. Jeffrey Funk: Okay. Well, I was, uh, got interested in Japan, uh, way back in the 1980s. Japan is number one. I was trying to understand how Japan was doing well.

How could they develop new products quickly? So I moved to Japan. Full time in 1996 and was looking at a number of products, but one of them was mobile phones, and it was just by accident then that when NTT DoCoMo introduced their iMode service in February of 1999, it did much better than any of the services in Europe. Uh, and it was the only country with successful service until Korea launched them a few years later. Uh, but you know, the iPhone didn't really come out to 2007.

It starts, it's going to be 2008. So I was visiting lots of Japanese companies. My Japanese was pretty good. I probably visited hundreds of Japanese companies, asking them about their various mobile phone services. And one of the things I realized is that a lot of it revolved around, you get better phones, you get a better processor, more memory, a better display, the resolution in color, or just. Uh, overall better network speeds, those things enabled companies to introduce new services.

So, uh, there was a very tight link. Your companies were very specific about what they were introducing, you know, why they were introducing it because the phones had gotten better. So that allowed them to give better services and the rest of the world wasn't able to do so well because the standards weren't met. Uh, set very well. The, uh, the network operators and T Docable and others kind of determined what would be in the phones to make sure that the phones worked right?

Uh, and Nokia and other, uh, leading phone makers at the time didn't like that. So, uh, things didn't work out. So that was a very, um, very educational for me in terms of, uh, How markets grow and, uh, the relationship between, uh, the underlying technology and the services that companies were able to offer. In 2007, you taught a unique course on the economics of new technologies.

And then that's also the start about being an early critic about, uh, the startups and also the venture capitals, in my opinion. Dr. Jeffrey Funk: Yeah, I was very excited about that. Uh, what happened in Japan and what I learned. So I wanted to talk about that in this course. Uh, and actually started like 2009. And so I started talking about lots of different technology. And I just, every year I was increasing the number of technology I talked about.

And I had a lot of students, I had, you know, 50 projects a year being done, group projects being done. And so I would learn a lot from the projects because I would require them to go beyond what I talked about in class. So they would talk about something new and then I would incorporate that in the next semester's course. And so I covered just an immense number of technologies. Uh, I taught this up until 2016. And, uh, by then I was doing big data and there was some mentions of AI.

Um, but over that time from like 2009, 2007 years, I was teaching it. I became a pessimist because I began to notice that a lot of the technology I was talking about hadn't really gotten much better. Then when I'd previously taught it, so things like nanotechnology and superconductors for energy and bioelectronics and Toronto's kind. So I, I noticed they weren't getting better. So, you know, and if something didn't get better, then it wasn't going to diffuse.

You know, if it's not being used, it has to get a lot better before it's going to be used. So I began to become a pessimist. I also at the end tail end of that 2016, uh, right after that, I noticed that a lot of these. Startups weren't making money. There was a lot of anecdotal data about losses. So I began to become more pessimistic and, uh, the list of technologies for which I was optimistic became less and less. And that continued after I left NUS in the late 2010s.

You talk a lot about value and progress when it comes to evaluating the technologies. Uh, I think that's something that's really stuck into my mind. So what's the value and what's the progress that technology is progressing and what's the value that's adding to our lives. And from there, I would like to touch base on the marketing side of things. Dr. Jeffrey Funk: Yeah, well, value. What, what, what are the customers getting in the first thing you want to know is, are the customers using it?

And you want to get an idea of there's always going to be somebody using it almost always, uh, you know, maybe some like technologies are too far in the future. Einstein Rosenberg bridge or something, you know, uh, It's too far away that it's not being used, but most technologies are. So you can always find some people using, and then you want to find out what benefits are getting, how much money they're spending. Uh, and then you ask the question, okay, they're using this technology.

They have these problems with X and Y, but they like Z. Okay. Is X and Y getting better? Where's the progress? You have to be very specific. Too many people think. They just see all the products coming out and they just see, Oh, there's so much progress. So much is happening. And they hear all these statements by, uh, the tech bros just saying, Oh, this is going to happen. That's going to happen. And they mistake that for progress. They think that, Oh, there's so much talk about it.

There's so much progress. So wait, you got to be very specific. about the performance metric you're concerned with and whether there's progress in the relevant performance metric. Uh, in March, 2024, uh, Sam Altman, the CEO of OpenAI said, AI will handle 95 percent of marketing work done by agencies and creatives. He also added, uh, it's going to be easy. Instant and almost at no cost. He's giving it five years, give or take maybe slightly longer.

Uh, this is a bold statement and a lot of people in marketing world has been discussing it in non marketing world as well. What are your thoughts about this prediction? Dr. Jeffrey Funk: Well, Sam Altman is not an expert on marketing. He does not have spent his life doing marketing. He has no idea what marketing people do, you know, and, uh, Mira Murati is the same way. She says, wow. It's going to replace all creatives, but maybe those jobs shouldn't have been there first place.

You see that they display this lack of knowledge about the intricacies of work and you you can say that the marketing or you know, a lot of stuff for superfluous, but They're there for a reason. Companies do them for a reason, right? So, and there's a lot of details in there they do for a reason. So you have to understand those reasons. You can make these forecasts. So Sam Altman is trying to sell open AI and he's not really trying to sell you and using it.

He's trying to sell investors on saying it's really big. Because that's how you make money in today's world. It used to be that you started a business, you satisfied some customers, then you made it a little better, you satisfied some more customers, and the revenues grew. And after a few years, people said, Hmm, that's kind of a good technology, you know, and there's a lot of revenues there. That's a good business. Yeah, I think we should increase the value of that, that company.

Uh, you know, either in the stock market or private valuations, but Sam Altman and others don't like that. They want to convince you that it's worth billions, you know, in trillions. I mean, people throw around these terms all the time, uh, trillions of dollars. And, uh, so Sam Altman writes these, these articles, like a few years ago, he wrote one that said the Moore's law of everything, you know, houses and everything was going to get cheaper because of check.

And when people say these, these things. Things, these outrageous things that there's no basis of fact. The logical response is this guy doesn't know what he's talking about, but for some reason, these investors have bought into this. Which of course should lead to the end that well maybe these investors don't know what they're talking about because You know this isn't happening. I mean what you want to do is focus on exactly what's happening with chat GTP What exactly is happening?

Who's using it and why? There are people using it and there are cases where Seems to be offering some value, but you want to focus on that. You don't want to stay at this very broad level of Sam Altman says this is going to happen. And, and therefore we're going to believe him. No, you focus on specifically what's going on right now. What users value users are getting right now, where's the actual progress and you make your own forecast. Don't just believe someone's forecast.

Try to understand their logic and repeat their logic and be able to repeat their logic and make their argument. I think the reason why many people believe in him, well, there are also some other obvious reasons why people believe in him, but marketing, especially in the B2B world, marketing is seen as content marketing, and we have head of content, VP of content acting as if they are the marketing managers or directors of the company. There is.

You know, when you think about generative AI, it's about creating content. And if you think that marketing is creating content, then you would assume that, you know, chat GPT or generative AI would replace the role of marketers. I think that's also one of the reasons to that. And I really like how you start talking about predictive AI versus generative AI and those things.

Uh, because, you know, predictive AI is just, you know, Seeing the future and forecasting it through machine learning, which has been already in, in the lives of so many professors, so many researchers, uh, whereas generative AI is about creating content. Maybe that's, that's my take on that as a marketer. Dr. Jeffrey Funk: Wow. Generative AI is going to have a bigger impact on marketing than a lot of other functions because the output of generative AI is words and images.

It's not going to have a big impact on making cars, or constructing houses, or mining minerals, or catching fish, or even doing healthcare. Because the output of words and images is very different from the output of the industry I just mentioned. There's very different things. And so marketing, yes, it will have an impact. I mean, a lot of marketing is advertising videos. I agree it will help you make videos. I think it also helped make, uh, movies and TV shows.

It's not like they're going to make a whole movie, make a whole TV show, but they help in certain places. And then gradually over time, the contribution from generative gets bigger and bigger and bigger and bigger. So that's simply how I would do the forecast because this is the way technology has changed very gradually. And there's some impact of marketing on words, but you see, when you're using marketing, you're really talking about advertising.

And I would say that marketing is much bigger because marketing does a lot about understanding what the market for something is. That's very hard. That's what we're doing right now for generative eye. We're trying to stand with the market is for that. And I don't see how generative eye is going to help me determine what the market for generative eye is.

The market for generator comes about by having the conversation we're having right now and thinking through what's happening in the market and the uptake and who's using it and who isn't. The other day, a friend of mine, he's a creative director, and we were talking about a commercial and then, you know, just making positive, negative comments and criticizing that. And now he was like, why do we still do ads?

You know, I mean, it's so old school because we know that, for example, paid media, it's not working as it used to be in the past. So things may be evolved, uh, in that sense as well. I mean, of course, marketing is. It's not only about advertising or ads. It's a part of it. But I think things might shift around that. I would like to ask you about your opinion about the role of human creativity in marketing.

As AI is continuing to evolve, do you see like phases of human creativity advancing with AI as the technology improves? Dr. Jeffrey Funk: Well, I'm not an expert on marketing creativity. I mean, I've, I've seen a few movies and things and read some things. Most of it appears like you've got to have some core idea for some words that are going to strive the new product. And then you try to express those words in some images. And so coming up with the idea, it's very difficult.

Now I can imagine that generative AI can help you try those ideas out much more quickly. So you can create some videos, you have some words, and you think this sounds like a good marketing campaign for the product. And then you input the words and you get a bunch of images. And so you can try things much faster with generative. So I, I believe that that's going to happen. That can help. And that, Very good creatives are gonna use it.

Well, I mean, there's gonna be a lot of people trying, but unless you're really creative in the first place, you're not gonna be able to use the generated vibe very well. You know, it's not gonna be very Mm-Hmm. impactful. Mm-Hmm. . I think I see it in a way, for example, you know, Adobe is the creative platform that you can use, you know, generate graphics and so on. And it's a big tool for the creatives, like the designers and so on.

So. When, uh, if we think that way, I mean, a graphic designer was a graphic designer 100 years ago, and it's a graphic designer now, but with the tools of Adobe, then it's more enhanced. I mean, it doesn't necessarily diminish the role and make the role, uh, fight away, but I see this as an enhancement of, uh, the creativity process. Dr. Jeffrey Funk: Well, it'd be very incremental. Think of some of the things that people say, uh, computers, I mean, AI isn't going to replace people.

People use AI, it'll replace people who don't use AI. And they never really talk about what they mean by that. I mean, you think about people who use computers, replacing people who didn't use computers, right? Everybody uses computers now. So obviously they've replaced the people who didn't use computers. You know, the AI people kind of think, Okay. I know AI and all these statistics and all this, and all this has become necessary in the future. And that's going to be the future.

I think, well, wait a minute. The people who are using computers today don't really know computer architecture or know how computers work. They certainly don't know how summit conductors work and all these integrated circuits work. They don't know any of that. They know a bunch of. You know, kind of superficial stuff about computers about, you know, how to use the software and you click here, you click there and it can do this. It can do that. Where do you find information?

You know, all this stuff that. A true engineer would say it's superficial, but it's necessary to do your job. I see AI as being the same way. It's going to require people to understand some, you know, prompt engineering type thing. It may require them to understand something about statistics and things like that, and you know, how often something makes errors, but probably not. It's probably going to be more, well, it makes these kinds of errors, so you have to check for those kinds of errors.

Uh, and, uh, it doesn't make these kinds of errors, so you can usually trust it when it says this. And that will take a while to understand when you can trust it, what type of things you can trust it with, and what type of things you can't. Um, and you get these videos, and sometimes they produce an extra arm or a leg or something like that, which may hurt you. They may also give you some historically, or something inaccurate.

But you may say, well, for these kinds of videos, marketing videos, we don't care about the accuracy so much. You know, it's not like we're doing a documentary where we have to have the people look exactly the way they actually looked 150 years ago. Um, and so these are the kinds of things that I think that. People will have to learn. They'll have to learn when AI makes, you know, what are the advantages and disadvantages? And you can't just say, wow, it's early years of AI.

It's going to get so good and everything. I'm perfect. No, it's not going to get perfect. It's going to get a little better, but not a lot. And so you better understand where it works. And where it doesn't work so well, and that's going to be the challenge going out of the marketing scope for a bit. Are there any specific AI applications that you believe the game changers for businesses? Because.

A lot of companies are investing heavily, uh, on AI without knowing too much about it or like just trying to, you know, jump to the wagon and helping it. Do you see some specific areas that will make the most impact, especially when you look to the one or two years horizon? Dr. Jeffrey Funk: Well, I think these, these advertising videos and then a lot of editing or videos and TV shows is the biggest.

Um, Mm-Hmm, . I, I think the generative I and the tech side will have less of an impact because there isn't a lot, there's books and things, but my understanding is the books that, that are written with generative aren't that good. And, you know, it's really hard to write a bestselling book really hard. Even, you know, lots of smart people can't, it's very hard. So I don't see generated by having much of an impact there. Um, you mean in like, uh, book writing copywriting on those areas?

Dr. Jeffrey Funk: I mean, like, uh, writing a book, like, uh, you know, and helping an author write a book, you know, maybe it can help checking, you know, maybe editing, maybe editing a book, and you're looking for inconsistencies or something, but. I have a feeling that it's not going to be that big a deal. Um, there are some other areas that people like to talk about.

I mean, certainly software code, but appears that software generated by makes too many errors creates too bloated, too much software code. So it proposes solutions that have too many characters. You don't want to have too many lines of code, right? We already have too many lines of code. These software solutions, just millions of lines of code, and then somebody has to check them and figure out where there's a problem.

And so if you're using generative AI that creates more code than a human would to solve a particular problem, It's going to be harder to check. And that kind of gets me to what one of the big things I emphasize, which is process. You know, a lot of these economists and stuff, they, they think it's too complicated to think about processes.

And so they just focus on tasks and well, they have these 10 tasks and, uh, generally I can help you with each task and the user will just go from this tool to that tool. And this isn't the way the world works. This isn't. What enabled productivity to improve. You see, I grew up, I, a lot of my early career was in just in time manufacturing and processes. You know, it wasn't about a person just seeing how many parts they could produce and let them stack up in the corner.

No, it was producing just in time so that there was close feedback between the downstream process and the upstream process in order to make sure things were done right. That's how you achieve lower defects and how you improve the productivity of factories. The same thing was done product development. People looked at this back in the early 90s. Books came out on how Japan was able to develop products faster than other companies in the world because they were doing a lot of things concurrently.

People were collaborating very closely and not just having it passed downstream and then passed downstream in the past downstream. They were doing work at the same time concurrently sharing ideas. Now, I have a suspicion that in the marketing field, there's a lot of collaborative work, a lot of sharing of ideas, right? The, and the good ideas, uh, come partly from collaboration.

There may be some core ideas and, you know, the stars produced, but putting it all together, you know, making sure that it all works well, that message works well, that the advertising video works well, requires a lot of collaboration. So you have to think about process. So you have to think about how is generative AI going to help in that process, that creative process. So understand what has to be done in that creative process, uh, and how you catch errors.

And you know, when errors aren't caught, what's the implications. So this, this is important, I believe for any, Application for AI. It's all about process, understanding processes. And, you know, I'm not the first to come up with this. There was a very, a bestselling book around 1990 called re engineering the corporation by James Champion, Michael Hammer. It was all about this.

And it just had all these simple examples of processes and companies and how there was a lot of work that they realized wasn't really necessary. And other work that was more important and work that needed to be done in parallel. So in order to implement AI really well, people need to think about the processes. What are the processes? Uh, don't just think about my work. You know, that's what a lot of these proponents of generative AI are doing. They're just talking about their work.

Oh, it improves my productivity like crazy. You know, says one crypto CEO. commenting on my posts, you know, and it's like, I wonder what this guy's doing. You know, he's just writing messages on, on LinkedIn and he says, wow, this is, this is really helping me. Um, but you know, it's not getting any work done. It's not improving the productivity of anything. Uh, and so we need people to think in depth about this. And I know people are, there's people, but there's a lot of people aren't.

And one of them is Sam Altman, right? Cause Sam Altman doesn't understand any of this, or at least his comments suggest he doesn't, Miramarati doesn't, uh, her comments suggest she doesn't understand it and there's a whole lot of people who aren't talking about this. And, you know, even economists, I have problems with a lot of economists who they do these studies and they, they, they don't refer to these things. They just talk about, Oh, the average.

Person in a call center was able to use general IT rat faster than they used to. They don't talk about what happens when they make an error, right? When they make an error and something gets transmitted to a client, it's wrong. There had, there's, there's a process by which that has to be fixed. We're not talking about that. Right. But yet these processes are important when there are errors. How do we deal with them? There's a process, right?

And you have to think about how is generated AI going to impact on the process as a whole. Um, the other day I was reading, uh, another professor's note, which says, uh, marketers need to know what's going on. Uh, learn how to talk to a machine, how to talk with generative AI, because SEO, you know, search engine optimization, uh, would not work as it is working right now.

So you have to understand how to work with generative AI, which means people start to use per pixelity, uh, chat GPT to do search. And he says that this is different than. How we used to do SEO. So what's your thoughts on that? Dr. Jeffrey Funk: Well, some people use the term prompt engineer. You need to know what to prompt it with. And I think that's way too simplistic. I mean, what they're really saying is what I said earlier.

You have to understand when it makes errors, when it doesn't, when you can trust it, when you can't. Um, you know, we all did this with, with Google search engine, right? We all look for information with, with the search engine. And we know that if we ask what's the population of Australia, then most likely the number, first number it gives you is correct. But if you're asking about something more complicated, like who should I vote for Donald Trump or, uh, Kamala Harris.

Well, there's going to be some controversy in there. And you know, a lot of things are in between those two, but nevertheless, you're going to have to understand when you think the generator guy gives you, when you can trust the answers and when you can't and, uh, and how you ask things such that you're more likely to get a more accurate answer. So you have to understand the technology, which I was mentioning earlier.

For example, I, I started doing some search, uh, when I'm using ChatGPT or Perplexity, uh, so I started doing search on brands saying, okay, what's the best brand for milk, oat milk, those types of things. You know, in order to understand how the search option works. Uh, but the thing is that. It's not like the search that we have at Google right now. Of course, Google search is also quite screwed because of all the, you know, a CEO, all the branding and ads, uh, but it's not there yet.

So I think it's just like a game off of, you know, all these seven companies trying to win, uh, you know, because Google search is a big thing. And now People are using, suddenly using Chachapiti or Pyrexite to do search. Uh, your book is coming up in October. Uh, how long does it take for you to write the book? Dr. Jeffrey Funk: Well, writing is very easy. I mean, if you spend your life writing, it's very easy to write. It's, it's hard to get a book published.

So I, much of this book was written, Three years ago, I was trying so hard to get published because see, I noticed these things so long ago, I was warning about the startup losses back in 2018, 2019, because I had anecdotal evidence that most startups were losing money and over time I got better and better data, but you know what people don't care, you know, the VCs and the startup companies, they don't care because they want to hide this.

And the professors who teach entrepreneurship, they want to hide this, they all want to hide this and it hasn't blown up because there's so much easy money. So these startups, they can't make money. I mean, 90 percent of these unicorn startups are losing money. They can survive because they just cut back on their growth. They just cut back, but they're not ever going to make money. And people use this term zombie.

Company, company that has, uh, losses, big losses, uh, but it has enough revenues to pay for the interest on the debt, uh, they're not going to recover. So this is what I've been dealing with and trying to convince publishers this is an issue. I mean, publishers are like, you know, academic publishers, first of all, are hard because you, uh, they will publish these kinds of books.

But if you're not really famous, it's not only that they don't want to publish you, they can't get anybody to review your book. Because a famous professor isn't going to review a non famous professor. So then you have to go to the business books, the how to books. But you have to how to do something. You see, so my book is about how to Avoid, uh, investing in bad companies and bubbles and things like that. I'm not an investment person.

That's not my expertise, but I had to, to write this kind of book because that's what published what they want to, how to book, how to do something. So I'm trying to tell people how to interpret market signals and things. So I will have two questions about that because you are often highlighting the excessive hype of AI and the book is about unicorns, hype, and bubbles. Uh, do you foresee a crisis, uh, stemming around the overhype of AI, uh, in the coming years?

Dr. Jeffrey Funk: Well, I mean, if you, if you add up the increase in market capitalization for the top tech companies since January, 2023, You come up with the figure of 10 trillion. Now, I'm the only person that noticed this, I guess, because I never see anybody mention it. Because when I say 10 trillion out there, a lot of people say, where'd you get that number? Where'd you get that number? Because no one else says it. But it's 10 trillion.

I mean, all you have to do is go through Microsoft, Google, all these companies. I mean, it's huge. I mean, Microsoft share price has almost doubled since January 2020. You add it up, it's 10 trillion. That's a lot of money. And you look at, uh, you know, the revenues for this AI. I mean, yeah, the cloud company revenues, but the actual sophomore revenues are very small.

You know, and other people notice that with, uh, that the biggest is probably a few billion for, uh, open AI, but none of these other companies and, um, Microsoft just announced some earnings. And they, they don't say anything about co pilot, number of co pilot users, number, amount of co pilot revenues. Uh, and of course that's what caused Alphabet stock to drop last week, was they didn't say anything about revenues. They didn't say probably need details.

Um, and so people are beginning to notice. So wait a minute We we expect to see these kinds of details We just don't want to hear about well, your advertising revenues went up 20 since last year, which is that's pretty good most companies but the problem is that microsoft's I'm, sorry. It was uh Microsoft revenues had gone up 20 percent in the last year. Um, and that's pretty good. But the stock price doubled Yeah You know, it's up like 2 trillion in market capitalization.

We're looking for bigger numbers than just a 20 percent increase. We're looking for something that suggests that all of this hype about AI, this increase in market capitalization, 10 trillion is warranted. is justified. So that's what the market's looking for. So at some point, the market's going to say, well, it isn't there. You know, I know some people will say, well, they're just not talking about the co pilot number, co pilot users and revenues, but they're there. They're going up.

And one thing I've learned through my life is that companies will brag if they get the chance. If they have something to brag about, they're going to brag about it. So if there were some good numbers there, they would be talking about them. They wouldn't be shy. People aren't shy. These companies aren't shy. They're concerned about their share price. It's their primary concern. They're going to do anything to move that share price up.

So what, you know, if they had these numbers, if they had good numbers for copilot, Microsoft would talk. I mean, on my side, from the advertising world, I'm expecting that open AI will soon, will start. Getting ads, uh, for the search results that they are just like Google search, you know, you get to pay that's, uh, and I'm waiting for the moment that these companies, uh, generative AI companies are now turning into advertising companies, uh, taking ads.

Dr. Jeffrey Funk: No, that's a very good point. I mean, I, some of us raised that year, a year ago when people talking about opening, I is going to eliminate, you know, Google search because it's going to be able to end better. You know, the first question is, well, how are they going to monetize it? One question is how are they going to monetize it? Are they going to charge people for it? If not, how are they going to offer ads?

You know, and so those kinds of details, they never came out and when they don't come out, what do you conclude? Well, they don't have an answer to it. They don't have one. Sam Altman is again just talking around the issue. Uh, it's not that you have a bad question that you're misunderstanding things. No, you're right on. You understand it. That's the problem. That's the question you got to keep asking.

And the reason that Sam Altman and Mira Murati aren't answering the questions 'cause they don't have a good answer. They don't know how to do it. Uh mm-Hmm. . And I imagine that they're not gonna come up with a good way to do it. Um, the second question and the last question about the book is, uh, what are the insights, what's one insight that you can give, uh, to avoid the, these pitfalls, uh, about. Hypes on bubbles. Dr. Jeffrey Funk: Well, what I say is you have to understand.

You just don't listen to people's Forecast examinals. You have to understand them. You have to be doing the forecast yourself. You're understanding the logic behind the forecast uh, and so, um One part is about startups and all these startups are losing money and a big reason they're losing it because they didn't do a technologic, sophisticated business.

And when you look back, all the successful startups over the past 50, 60 years, it was like some companies like networking companies, computer companies, software companies. It was all something technologically new that enabled this new startup to succeed. You can go through any from Oracle, Microsoft, they all did something radically new. There wasn't being done that was much better. Well, that's not the case with a lot of these food delivery startups and, uh, even health care startups.

There is nothing really new. It's kind of something very small. Um, for the companies that did offer new technology, they tried for the main market. So think about VR and AR. We've been hearing about VR and AR for I mean, I've been hearing about for 30 years and certainly with startups, I mean, you go back to our Oculus Rift. It was acquired by Facebook more than 10 years ago. People have been talking about this a long time, you know, and here we are, even Apple can't do well with it.

So my conclusions, they all kind of assumed this was easy. And my book goes into the reasons why it's not easy. So in a lot of ways, my book goes into how the progress is very slow in these technologies and the companies should have been aiming for a much simpler thing. You know, some niche user, right? You got to understand that niche user, someone who's willing to pay a lot of money, uh, for something that isn't that great. Now, this is the case all the time with new technologies.

You have to find that niche user who's willing to pay for something that's not that good. And, uh, but they didn't. And so I show that the progress is very slow on all kinds of these technologies. And now I know that a lot of marketing goes, I don't want to go into this stuff, you know, and you know, whether it's progressing or what, but, but, you know, that's the core of understanding whether it's going to be big. Right? Is it progressing?

You know, so, when I was, you know, a young man, in graduate school, you know, personal computers were big in the early 80s, and I wasn't really following it very closely, but it was hard to avoid because I was at Carnegie Mellon, and I was in the news, uh, we had to use computers to write our articles, write papers and things. You know, people were talking about Moore's Law all the time, and about how it was, you know, the computers would get faster and faster and faster.

Because there's a direct link between the better transistors and the faster computers. So that was very easy to forecast. And now you look at generative AI and you think, well, are the frequency of hallucinations going down? You know, people talk about all these new products and, oh, they have higher resolution and, oh, I can use these inputs to get these outputs and, but that's not the core question.

To me, it's all about what is keeping people from using more generative AI for text or even for video. It's hallucinations. So are the frequency of hallucinations going down? I see a little impact, not much. And so that's what the book is about. It's about all these performance metrics, about thinking about a technology, you know, like drone delivery or. You know, even Starlink thinking about how much faster, how much better is it getting? How fast is it getting better? That's a core question.

If you want to think about a new technology, it has to be getting better really fast or else it's not going to go from little use to lots of use. I mean, I feel that I'm also on the correct path of asking those questions because I was interviewing with someone and then she says that now I can, instead of creating. One post in an hour, I can create a hundred posts in an hour. And I said, I mean, why would you need a hundred posts? What's the reason to that?

I mean, like, there's only like a few people that you can talk and those people can consume that much of content. Why would you need to produce hundreds? I mean, I don't want to produce that. Uh, so I'm happy that, uh, I was able to talk to you because, uh, I also, you know, watch a lot of your videos and that's. Also shifted out of thinking, uh, two last questions about more lifestyle. What is one book that you would recommend, uh, reading Dr. Jeffrey Funk: about this topic?

Well, I'm sure that, uh, Gary Marcus's book is going to be very good. It comes out in September. I like Emmanuel Maggiore's book, Silicon, which comes out in September, but he also wrote a book last year, Smart Until Dumb, about AI. They're very funny books. I mean, I read the book, Silicon, that's coming out. He sent me an advance copy. But they're very funny books, you know.

So my book isn't funny like that, because he has been working with these, These people and these projects, and he's talking about the things they say and a lot of these crazy things where, you know, they, they, they, they didn't need AI to solve a problem, but they used AI because it would look better on the resumes and it looked better as a project description.

And, um, and so he's talking about really source of the hype, um, you know, that, that people want to say, talk about AI, because it makes them look good. You can put it on the resume, makes them look like they're really advanced. So those books are good. There are others.

I mean, you can read, uh, Darren Acemoglu's new book this year, uh, but it's more academic, most, most practitioners don't want to read academic books, it's got too much theory and stuff, uh, so these kind of funny books are better. And the last question is all about, uh, every time coffee, uh, in Singapore, uh, do you have a favorite coffee place? Because I have one in Singapore.

Dr. Jeffrey Funk: Well, I don't drink coffee, but I, uh, there's a place down the street from me that I meet a lot of people because I don't walk very well. So I say, if you want to meet, you got to come to near my house. And, uh, so I meet at this place, Tiong Bahru Bakery that has coffee that people like. I seem to like it. I usually drink, just drink some juice or something. That's good. I mean, coffee is one of my favorite things. So, I mean, I don't drink too much.

I just drink one per day, but it's an important moment for me. Uh, thanks so much for joining me this morning in Singapore and I hope to talk to you again maybe after the book is released. Dr. Jeffrey Funk: Okay, my pleasure.