Are we in an AI bubble?

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Welcome to another episode of the Practical AI podcast. In these fully connected episodes, where it's just Chris and I without a guest, we like to explore some topics from trending AI news or or things that are being discussed in the community. Hopefully we learn along the way, and and our listeners learn along the way, and and we help you all level up your AI and machine learning game. I'm Daniel Whitenack. I am CEO at Prediction Guard, and I am joined as always by my co-host Chris Benson, who is a principal AI research engineer at Lockheed Martin.

How you doing, Chris?

Hey, doing good today, Daniel, just, uh, cruising along, chewing some bubble gum, doing my thing.

We? We both, uh, we both needed a a sugary but not sugary caffeinated drink. I think you've got a Pib Zero, I've got a Coke Zero. There you go, It's been a a long day of work and and now we get to talk about some some fun things. Uh, uh, hopefully we won't pop the uh ai bubble today, but um, certainly,

it's okay, we'll, we'll clean up the situation if we have to.

yeah, exactly it. It's interesting, Chris. Um, I was looking around. Of course, we're always seeing things, or people are forwarding us various things in the in the news related to AI. One one this week that I saw was maybe an kind of interesting one with a humanoid looking robot. But I'd rather maybe discuss this, this, uh, this other stuff, which I think a couple of these things that I saw connected. And Chris, uh, a little while ago, we kind of did a a hot takes and debates type episode.

I think today there's certainly on this topic, there are various sides of this topic and and strong opinions about it, and and we can just talk through some of those. Um, certainly there is a debate going on. And uh, this is really the question, are we in an AI bubble? which is seems to be talked about all the time. Like people see something in the news and they're like, Oh, we're definitely in an AI bubble. Or people are like, Oh, this isn't an act actual AI bubble.

It's it's different than maybe the dot com bubble, Chris, you hear similar anecdotes. And and maybe what is your m? Maybe just the general concept of of bubble, uh, we're not talking about bubble gum, but

Yeah, I mean, the general notion of a bubble, uh, uh, you know, is it's really a financial uh concept where the valuation of an organization, uh, exceeds what its actual value is. In other words, what it's putting out in terms of product and services and the returns that are yielded by those. And so, you know, and a, you know, if you're talking, for instance, about the dot com bubble. And for those of you who may not have, uh, depending on if if you're in the younger skew of our audience, um, around 2000 ish.

And and that there was all this internet, uh, craze and rage and hype, um, not dissimilar from the hype we've been seeing in recent years over AI. And a lot of companies came about and, um, new startups and stuff, and they got valued very, very high, but they had very little, in some cases no revenue and thus no profits available. And so big valuation, uh, by the market, uh, with absolutely nothing coming out of them, uh, of value, and so it.

There's a point where the market kind of realizes that and corrects, and, uh, and the the giant dot com, you know, facade came falling down and kind of led into a recessionary period around the globe. And so it was kind of a big thing over several years, and so through this entire period of of AI buildup, that's been a concern that has come up regularly. This is not the first time, you know, we've been hearing about AI bubbles and stuff.

So, um, I don't think there's a year that's gone by that we've been doing this podcast where it hasn't been raised as an issue. What do you think,

maybe so, yeah. And and I think there is, you know, genuine concern because previous bubbles that have burst, uh, have actually caused real harm. As you mentioned, whether that's economic kind of recession, certainly, it distorts the way people invest, or maybe what they invest into, uh, which kind of has an effect potentially on retirement or 400, one kays. Um, there's, you know, uh, reduction, uh, in trust, I in in certain types of organizations or financial institutions, or technology companies, that that sort of thing, and it could be companies, it could be assets.

Like, you know, a lot of times people talk about crypto as an asset that you know, or or I. I remember not too long ago talking to tons of people about NFTs, right? And this really chaotic time with with NFTs. And there's a lot of people that that lost a lot of, a lot of money in that.

indeed?

So it, it is a it is a valid concern. And and th. I I think the question that's on people's mind is, are we in an AI bubble? And one of the interesting articles that that I saw this week, Chris was that, uh, Powell, the Federal, uh, Reserve chair, uh, uh, Jerome Powell in the in the US. for for those that, uh, aren't, aren't listening or are aren't listening from the US. Um, that's the uh, federal Federal Reserve chair, Jerome Powell.

Um, often can kind of it, it, it, anything that's said about the economy by whoever's in this position is taken with a lot of weight. Because, uh, well, Chris, you, you may, uh, you may have comments on this, but I, I'm not an economist. Um, but generally it is a. It is a sign of of at least an intelligent opinion on things where where there's a lot that's gone on, or a direction that, you know, the Federal Reserve wants people to think So, so, towards.

the 2 s background, without going off on a a track, is Jerome Powell. And his capacity is responsible for a particular committee at the Federal Reserve. And they are responsible for monetary policy, which the Federal Reserve sets, as opposed to what the President and Congress together set, which is fiscal policy. And one of the tools, the largest tool that they mainly do that with, is through the setting of interest rates, which trickles through the entire economy in a whole bunch of different ways.

And I don't want to go into any more depth than that. But they they thus slow down or speed up the economy to either tackle, uh, an underperforming economy or inflation on the opposite side, and they're trying to balance it between the two. And so, yeah, Chairman Powell noted that there was actually revenue associated with AI expenditure, and thus it wasn't bubble like in his view, which and he is certainly an expert, uh, in a lot of ways.

I I think, I I think that there are some other considerations in there, but um, it's definitely a powerful statement coming from, you know, that particular individual.

Yeah, yeah, the the title of the article in Fortune, which which we'll link, is Powell says that, unlike the.com boom, AI spending isn't a bubble. And the quote is, I won't go into particular names, but they actually have earnings now. I guess we could speculate on this podcast. I don't know what names he's, he's talking about. I'm assuming it's some of these larger names that would be whatever, OpenAI, Anthropic, Cohere, you know what, whatever the the the ones are that that people would think of.

I imagine some of those are quote the names, but he, he says, they sort of actually have earnings. Um, the other interesting piece that I saw, Chris, which is maybe on the other side of this argument. And we can talk, maybe after this, about, you know, the different ways that people argue that we are or aren't in an AI bubble. But this other one was from the New York Times, which, uh, which is reporting that Nvidia is now worth $5 1 trillion as it.

Uh, and this is the quote from the article as it consolidates power in AI boom. Uh, so it's the subheading. The AI chipmaker has become a linchpin in the Trump administration's trade negotiations with Asia. So there's there's a, you know, some policy and and political angle to this article. But the general idea with the article is that this 5 trillion dollar valuation maybe is is part of an AI boom. So, yeah, that that's certainly interesting.

it is, it, it is, um, a, and and I think we're seeing that, you know, going back to those names that were left unsaid. You, you named a few of those names. And you know, I think any of the, uh, large cloud service providers that are offering, uh, a collection of AI services, probably, you know, round out some of those names. One of the things, uh, one of the distinctions that I think is interesting to to weigh as we talk about.

This is the fact that while he noted, meaning, uh, Mr. Powell noted that, uh, some of these uh organizations, uh, have earnings. And we are seeing, you know, that reflected in AI related stocks that are just dominating. S. P. 500 re returns, uh, to the to the degree of about 75% of those returns, um, eighty of earnings growth and ninety of capital spending growth. I mean, those are phenomenal numbers when you think about that in terms of percentages of total markets that are out there, you know, or of these at least exchanges that are representing markets.

So, I mean, that's really shocking, but I think one of the things that is n that that he did not say. Um, and speaking as someone who has nowhere near the economic expertise of Mr. Powell, but did, uh, did have some university studies in economics. That, you know, those, uh, those numbers are concentrated in a tiny fraction of companies, uh, overall. And so, uh, my question, uh, that I would ask is for for some of those giant companies that are that are making huge earnings from, uh, many, many, many thousands of customers spending huge amounts of money on AI growth.

We have also talked about the fact that there is, uh, there's also, uh, in the media, quite a bit of questioning of ROI on a lot of those AI investments, uh, at various companies. And so, you know, if you're the cloud provider making beaucoup's of money, um, that's great. But if you're one of the companies out there that maybe is spending on that, but maybe not seeing an ROI on that expenditure, uh, that is a different story right there.

And so, you know, I, you know, maybe it's boom for one and a bubble for another, uh, maybe it's not just a universal bubble, but, uh, depends on who you're talking to, to some degree.

Yeah, and I guess that's where maybe this is murky, is the some some people might define bubble differently. I think that that it is one of the kind of key arguments for the kind of affirmative of this, that we are in an AI bubble. Is this kind of valuations and speculation? I mean, we've highlighted a few stories over time, the last couple years of these crazy valuations, where essentially there is an unproven revenue model. Um, so I'm looking at at one source here that's that's saying, uh, over 50 of VC funding in in Q2 of this year, 2025, went into AI companies, and there's, you know, VC is is risky, of course, as as an investment model, most of those

businesses will fail. That's kind of always expected in in the AI space. But also this year, just from looking around at different folks, you know, raising these companies are getting much, much higher multiples or higher valuations. So, um, for people that that need a reminder, sometimes your your company might receive a valuation that's a certain multiple of the revenue that you're bringing in. And so that that may might be fifteen, twenty, twenty, five x thirty x for, uh, you know, plus for an AI company where other companies kind of your normal run of the mill SaaS company.

I in tech that's raising, isn't definitely not raising at those multiples. Um, right right now, so that that would be, I guess, the argument, or an argument for that affirmative, is these kind of, uh, speculation and valuation that's maybe reminiscent of that dot com era.

Yeah, uh, and by the way, another term, just to connect kind of that financial world with with, you know, what we're talking about in terms of observations is, um, those of you who invest, some of you may have heard, uh, the notion of a beta, uh, which is, um, essentially a a multiple of valuation against your earnings. And so if you have a very high beta, that's saying you're being valued very high against what your actual real life earnings are.

And a lower beta, which would be considered less risky, would be, um, that that valuation is not so extravagant. And so, I guess, and that's another way of of looking at. This is if you're looking at a company's, um, you know, portfolio analysis, you know that some analyst is doing, um, and there might be a beta number attached. If you're is, is that? And this was pointed out in some of the articles, is that the betas of today, while high, are not nearly as high as the betas of the dot com era.

Um, and so, you know, that's another sign. Well, you know, is there some bubble? Maybe? uh, is it as bad in terms of the sheer speculation of the dot com era? Maybe not, you know, uh, is. That's one metric by which we can, uh, evaluate.

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Yeah, Chris, I I think you were starting to get into maybe something we've alluded to, which is the the other side, the the uh, negative side of of saying, you know, we're not in a a bubble. Corresponding to this first argument of the speculative investing, which is that, you know, maybe the the earnings or the kind of business fundamentals or the scale is, uh, you know, the diversification is a bit stronger. Um, in this particular, uh, time than in the dot com time, so, you know, on the one side, Jerome Powell talking about, uh, talking about real earnings, right?

Which is maybe different from some of the dot com era. On the other side, there is there does seem to be a diversified set of of, uh, revenue streams in the AI space. So it's it's not just AI models, for example, there's infrastructure related to this, there's chips, right, GPUs, and even like unique types of chips that are being developed for for AI. There's service offerings, um, on top of AI. Um, we've talked a lot on this show about how the service providers, um, the large consultancies, are are doing quite well in the in the AI space.

Um, and and those things are things that are already scaling, whether that's, uh, chips or the service offerings, et cetera, cloud, cloud offerings around these things. And I guess this this is something I wasn't aware of, and maybe it's connected to what you were talking about before. But this, um, the magnitude of the investment relative to kind of the GDP, um, is still relatively low compared to other kind of. If you wanna think back to actual, you know, other transformative revolutions like railroads or electrification and and and that sort of thing.

So this, uh, this kind of counterargument would be no. There's, there's really something more here in terms of the earnings and business fundamentals, with a lot of these AI companies, where there's earnings, there's diversification, and the magnitude of the investment is is kind of different.

I think, uh, I agree with that, though, once again, on kind of on the other. If you're countering that just a little bit, then I think that you're gonna find that. There's a selection of companies that absolutely fit that, uh, that profile that you just outlined and stuff. But I think that there's still also quite a few out there to balance that that have no earnings and stuff like, you know, or or very little, um, and that the business model is is still quite questionable, uh, and thus leading into kind of that hype based speculation and stuff.

So I think I definitely feel like we're seeing both sides of that. And it kinda comes back to something I mentioned at the beginning of the call of like, you know, the the the bubble esque nature. If we're, if we're, if we're in that kind of dot com internet, um, period, a as an eva, you know, like, as our contextual reference, that it doesn't quite fit that and it it's. It seems to be very much in like, how you're engaged and what you're, you know, what your idea is.

Do you have customers? are you providing services and thus have earnings that that support that, uh, versus the ones that are not? And and I think, w- you know, we've spent so much time on the show over the years, really, um, trying to cut through the hype cycle, um, sometimes quite literally, you know, we'll get the it, we'll, we'll get the current year published hype cycle and start talking about some of that. And I think, uh, if you're deeply engaged, uh, as we and our listeners and the people who listen to the show regularly are, it's probably easier to do that.

But I also think that there's probably a lot of folks out there that are doing investing that don't have, that don't have as much, you know, knowledge of that. Um, I had a conversation earlier today, uh, with someone, um, who was that person and was kind of asking about some stuff, and I was kinda doing a little bit of mentoring, maybe, um. But I realized, just, you know, that there are a lot of people out there that still really don't know much about it.

And all they hear is the hype and they they have very little ability to get through it. So, you know, is I? If they're looking to invest, it's almost a a little bit of a flip of the, uh, of the coin. On whether or not they look into the profile that you were just describing, or that other one where it's a little bit less substantial.

yeah, I think it's definitely definitely good points. I think part of the reason here that things are hard to parse through, which we've also talked about on the show, is just that it. It's kind of hard to pin down at this point. What AI means, and what is part, what, what is actually part of what would be considered the bubble and and what is not. Part of that is there's a lot of companies that are trying to ride the hype cycle, right?

And their product really is not AI powered at all, but they feel the pressure to tack on this is an AI powered thing. Maybe they have a, you know, a linear regression model or even a rules based thing, and it's say this is AI, and they're riding that hype cycle. And so on the one side, they're kind of riding that. On the other side, there's, you know, very sophisticated, whatever, you know, computer vision systems and other things that maybe are not viewed as part of the AI hype cycle because they're not generative AI or or something like that.

And so it's it's kind of hard to tell what, what fits there. And in addition, you no one really knows, kind of at the application layer, what the kind of end highest value things that are gonna come out of the AI world are gonna be. I, I, you know, we've talked about this on the show. I certainly don't think it's a general chat interface. There's much more valuable things already, um, in terms of some of the agentic and verticalized things.

And so there's a lot of just diversification, both in terms of people trying to ride the wave, but also in terms of defining what is AI and what is not. Cause it could range from a chip producer that's making a very unique, uh, chip that is specialized for AI workloads. All the way to a very thin wrapper on top of the OpenAI API to a proprietary computer vision model. That's taken 20 years to develop to a SaaS platform that has actually no AI component, but is labeled AI because it they can sell it for more money, right?

So maybe that all of that just feeds into this bubble, but also I think it creates a lot of, a lot of confusion, which may maybe is not. I, I guess in thinking about it, it's not it. It is similar to that dot com era, cause it's like everything related to the web, right? And you did have servers, you did have hardware, you did have kind of websites or platforms and that sort of thing.

Yeah, I mean, even then people were buying hardware and and platforms and software, and, you know, left and right, you know, during that period. But again, the kind of the winners out of that dot com era was a fairly small group of companies. You know, that were that, that were feeding the f, the the purchase frenzy during that. And I think that is a that is a similarity we have to today, where you have a small group of companies that are that are providing a lot of of capability and stuff.

Um, I think, you know, when it comes to the others, you know, in in that, like you just identified, just, you know, with the the AI label being so marketable and yet having almost no meaning. Because of the the immense diversity of possibilities that you could apply AI labeling to, um, it really comes down to solving business problems that are real business problems, as opposed to trying to put an an AI thing out there. Um, you know, and I think, um, I, I know that the the you and I, uh, I, in our in our roles hosting the podcast here, we get pitched by a lot of companies, um, a lot, and so we see a lot of, uh, uh,

a lot of different, you know, uh, positions and possibilities out there. And I think, you know, if you look at that, probably the ones that really catch our attention are the ones, uh, that aren't the most glammy. AI things, necessarily in terms of how they're marketing, but where you can really see that they're using, uh, these technologies to solve business problems in novel ways that hadn't been addressed before. And I think, you know, that's probably, you know, the basis for our own, uh, way of doing these evaluations.

I wonder, you know, how the general population, who is not, uh, just living and breathing AI every minute of every day? How they're looking at some of these different things that are coming at them in every advertisement, uh, and marketing effort. Um, you know, how do they? how do they tell the difference? You know, I I think I think that has a lot to do with with bubbles as well. Is just that inability to understand the difference between a great investment and something that is really, really sketchy and risky, and not being able to tell the difference between the two.

Yeah, just just anecdotally, it kind of has gone. I, I remember, I don't know if th- you had this similar experience, Chris, but, uh, obviously we've been doing this show for quite some time. We talk about AI here for the most of the time of this podcast. We didn't really talk about AI or or AI was not a kind of topic of general, you know, general discussion and was not represented. Kind of, I don't know, in the environments in which you walk through day to day, like a airport or something.

I remember seeing the first, I think it was an anthropic ad when I was in, uh, I forget what airport it was, an airport in Europe somewhere. And I and I saw an anthropic ad and I was like, Whoa, there's an AI. And and you know, I don't live in, I don't live in San Francisco. you go, uh, like, San Francisco is different, you go to San Francisco. It's all like on the billboard is advanced monitoring for your Kubernetes cluster billboard, uh, which, you know, wouldn't work anywhere else in the US.

But outside of, outside of, uh, San Francisco, it's like, you don't, you don't see that sort of thing, right? And so I, I thought, Oh man, like, this is crazy now. And that was in like a major airport in some hub in Europe. And I'm like, okay, well, that makes sense. But I just got back from a trip this morning and I I. As I was walking through the Indianapolis airport, there were, uh, multiple billboards and banners that I saw that all had some AI slant related to a a product or service.

So it's pervasive now, and it is kind of the soup that that we that we live in.

Y- it is, um, you know, so, like, you know, as we are trying to navigate that world, I think it's funny. Uh, you know, you mentioned how long we've been doing this and and a lot of our listeners that have been with us for for years going through this, uh, evolution with us are probably seeing similar, you know, takes on this and that they're, they're watching it. But I've also, I've also, uh, come to realize that, um, there's still quite a massive segment of our general population that is only in these last few months really becoming aware of this stuff and are still trying to take it in early on.

Uh, and so, uh, they are, they are suddenly, uh, I w- I mentioned that conversation I had earlier today, and that individual said, This AI thing seemed to have come out of nowhere. And you know, that's about as far from my experience as as you could possibly be. But I I. It made me realize that that's, that's quite common, and more recently, uh, I mentioned, you know, that that my mom in her mid eighties was was now talking about AI and stuff.

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Well, Chris, I I think one if we just kind of bring out another argument here, uh, that that people are making at at this time. And I'm curious to know actually your your opinion on this. We might might as well give some of our own opinions, or else, uh, what else are? What else are we doing here? That seems like fun, um, but the one of the, uh, one of the arguments for the fact that we are not in an AI bubble is that the kind of rationale, the the structural and economic rationale for AI deployment is is much deeper than previous bubbles.

L- I think the hyperbolic example would be like crypto, maybe, but the fact that AI is already being integrated into enterprise workflows, into even, you know, manufacturing and healthcare. Uh, it's not just kind of a technology that is looking for a application, uh, an interesting technology that's looking for an application, but it is actually being applied in across a variety of of industries. The the second piece of this would be kind of the tie of AI to a very long lead up of scientific, you know, research and and deep roots, right?

That have been going on since, um, you know, the sixties, seventies, eighties, you know, and and on, uh, and and had all of these things leading up to it, which gives it kind of roots in in kind of rigorous science and mathematics and and that sort of thing. The technology didn't kind of come out of nowhere, similar to kind of the revolution of electrification, right? People had actually been studying these topics, or at least thinking about them for centuries, right?

Thinking about, uh, these, these phenomena, even though maybe they weren't fully understood. And then kind of there were breakthroughs that that created this electrification of of the world, right?

It totally, um, you know, one of the things to your point right there that actually gives me a little bit of confidence, maybe that we're not in a classic bubble. Um, at least in the dot com context, is the fact that the fundamental underlying, uh, algorithmic technology that we're looking at here today in 2025 as we do. The show is actually about forty years old. Is is the the the basis being neural networks? And and it it, while we don't use that phrase as much as we used to anymore, um, you know, we we call everything AI these days.

But fundamentally, the AI that is, uh, powering everything that is of significant value of today is fundamentally neural networks. Uh, that have been, uh, enhanced and embellished and designed further, and, you know, next iteration, that kinda thing. And so we're building on a forty year history of this particular line of algorithmic technology. And so, you know that, that's a great point you raised there a 2nd ago. Um, that this is not, uh, fly by night, that there has been a, it, it, you know, the majority for me, you know, the majority of my lifetime.

Uh, this has been around for listener, just as a 2 s thing for listeners who may not have followed the show for years. Cause I know I've mentioned this before, but my parents, uh, were working on neural networks back in the, uh, in the early 90s. Um, and so like, and that's actually was my first exposure to this, uh, when I was in college, and so, um, this is not new stuff, uh, it's evolved, and I think, uh, the the biggest piece of it is you've had, you've had.

NVIDIA's come about able to make GPUs that could support the continuing evolution of the technology. W- It is thoroughly embedded in a bunch of industries, and some implement, like anything, some implementations are better than others. But yeah, great point you're making in terms of that. This is not, uh, a solution in search of a grounding, or in search of a a a market to use it.

Yeah, yeah, and I, I also tend to agree now. Of course, I'm biased on this show, and maybe my bias is not that surprising. I I think some of the valuations and the way people are treating in investment in this area is crazy. Not to say that you can't invest in prediction guard. Uh, uh, a, a, and I'll talk to you, but, uh. But I do think that generally, like, there have been many examples of craziness there.

At the same time, I think that that those crazy investments are partially founded. Maybe not in kind of the the earnings, or like a proven business model, but in a kind of deeper understanding that this technology is actually shifting how work is done and is fundamentally transformative for many industries. And that actually is going to happen, and so it's not, it's maybe speculative i in a certain way, but I think there are real kind of foundations to that speculation.

That, um, that I, I don't know, I would al- almost, uh, I would almost use the metaphor. It's kind of like when people go out and look for gold or or oil, right? The concept of gold or oil is known, and it's known that there is value if you get this material out of the out of the ground, right? But there's speculation and and risk in trying to figure out where that is here. Uh, it. It's not like you're d trying to discover a new precious metal or a new thing that's not known to anyone, right?

You know, this thing exists, it's a matter of of finding it, and certainly many people lose a lot of money in in that uh speculation here. It's it's similar there, there is a kind of known uh, or, or there i is at least a feeling and an intuition that there will be very transformative companies. That will be long lasting, and this technology will be long lasting and it will be impactful. Um, it's not that that that's maybe doubted, um, but the crazy valuations are, in some case, are driven by that.

Because you know, who knows going who's going to to survive this, this AI craziness, but but the technology, it seems, will be kind of pervasive and long lasting and transformative.

I think, so, I think, uh, I'll throw, I'm gonna throw a wild card into the into the mix here, uh, for a moment. And um, one of the, I think, the things that no one really knows where things are going for sure. And we sure talk about it a lot, is the fact that at this point you have a lot of um, of companies, especially some very large companies, such as Amazon, uh, who, uh, are doing massive layoffs, you know, and they're doing that on the notion, uh, in Amazon's case, 14,000 middle managers, um, and that's just one, that's just one organization, one very large organization, but one, um.

And this is happening in a lot of places. Is that, you know, we're definitely seeing the replacement efforts by companies to use technology to replace, uh, humans in that. And and this has been something we've talked about for years, you know, certainly coming and that would be happening. And you know, where would the balance be between a synergy between AI and humans, and a competition between AI and humans? And so we've had many conversations over the years about this.

But, um, you know, we're definitely at that point right now where, uh, a lot of companies are beginning to bet on AI technologies. Um, but it's also happening at a time when, as we talked about, some of those ROI on different, uh, efforts are not, are not yielding, you know, meaningful results. And so, aside from what happens with that, when you have, uh, unemployment rising from AI, uh, induced layoffs, um, that will affect the economy too.

So there's. It's not just whether or not the investment in these particular companies is, uh, is is wise or speculative. And, you know, based on their fundamentals, uh, and their earnings, but also, you know, h uh. As as we have groups of folks in the economy being laid off, um, and therefore their purchasing power is reduced, how does that play back in? I've seen a lot in the news about, like, all of this together, not only the ROI and and speculative nature or LA.

Or, you know, whether it's a bubble or not, going back to our our kind of, uh, original phraseology, but also whether or not this is going to affect workforces. So it's it is quite a complex thing. And when we look back on dot com, it seemed, uh, there were complexities there. But I think the the raw speculation of that era made the bubble. It was a little bit more of a black and white thing as you looked back on it, you know, historically.

Um, after we had lived through it and looked back and kinda said, Well, yeah, you know, I guess with 2020 hindsight, we can see that coming. As we've noted here, um, it kinda depends on who you are, uh, and how you're doing, and what you're claiming is your AI, and whether you're solving a real business problem. Uh, on whether or not you're in that bubble group or not in a bubble group. Uh, so a as we see the mixture, uh, pouring through the economy, it will be, uh, definitely interesting to see how this plays out, uh, in the in the weeks, months and years ahead.

Here,

Do you think that? Cause? We also talked recently on the show about almost the the both cognitive and emotional, you know, change and shift, or even manipulation that some of these these systems are doing, you know, um, across the population. If you look at it, there's people having, you know, romantic relationships with AI systems, or, you know, using these systems, maybe for therapeutic purposes, rather than their therapist. And, uh, cognitive load of work is changing because you're, you know, vibe coding and and all of these things.

So do you think that that sort of cognitive and emotional, almost like lifestyle shift, I is more impactful with this technology, or or with something like the dot com era and people kind of all all coming online?

you know, dot com era, uh, was, uh, and and sadly, I was well into adulthood, you know, as we hit that, you know, uh, you know. For those who don't realize that, I'm, I'm getting, uh, a little bit older than I like to imagine. But like, fundamentally, we went through the bust because of all the speculation, but eventually everything kind of, you know, we. We did realize what it was going at. It just wasn't on a a timeline and the and what you could achieve in that short of time, given the valuations, just wasn't real, but it was real in the long term.

And I think here what we're seeing is something a little bit different in that. Um, you weren't having relationships with your, with your ISP at the time, you know, it wasn't that kind of a relationship, uh, that you had with that wave of technological innovation, this one, it's, it's a little bit worrisome. Um, like, I, I don't believe in vibe coding being a great strategy personally. I I think that thinking of AI as a pair programming partner is a much sounder way of approaching it.

In terms of turning out, continuing to turn out very good software products, um, that you understand and that you can maintain over time, and that you have humans that that understand how their business is working. So I'm a little, uh, pure vibe coding, where someone who doesn't really know what they're doing is just asking the system and then they end up with something, you know? So it kinda depends on what you're doing with it. I see there's also been some research, and we may have an episode coming up on it, uh, that was done recently about, uh, the human dependence on AI, causing basically degradation.

Like it. W- They were measuring, uh, brain activity and and p, and, uh, the subjects that were in this, uh, study that were using, uh, their AI for everything were showing decreased brain capability. Um, over time. And so, like, it worries me that we're giving up some of what makes us so wonderfully human at the same time that maybe we're creating a strong dependence that we have in these ways that didn't exist in previous revolutions. So I think I think that there's a real risk here of, I think, how you, how you use AI capabilities today makes a difference on what your own personal human future is going to be.

And I very specifically, uh, choose how I use AI capabilities, uh, in a way that enables me versus, uh, kind of, uh, creates a crutch for me. So, uh, that's, that's kinda how I would answer. That's a little bit roundabout way of answering that. But I think the way you use AI has a lot to do with its long term effect on on your, your own personal life. In a as an individual,

Makes sense? Yeah, I think that's a that's a great way to look at it. Um, well, a as we close out here, Chris, what would you say? Are we in an AI bubble or not? What's your, what's your vote? Y- Yes or no?

I, I, I'm gonna say no. In the classic bubble analogy, I think, and and I, I came into this conversation not really knowing, uh, I think it's this, uh, us talking it through. So I would say no in the classic bubble context, like dot com bubble, but yes. In that, there might be, instead of one big bubble, there might be lots of little bubbles.

Ah, yeah, uh, fizzy, like our, uh, like our pib zero and and coke zero that we that we started talking about.

The fizz. Yeah, there you go, the fizzy economy, you heard it here 1st, folks.

The fizzy AI soup. On my end, I would tend to go with the the No. I, I'm. I definitely think that compared to some other technologies and cycles, this is already kind of at a level of utility and and permeating many, many, uh, enterprises and that sort of thing. And I do think that creates a trickle down of things that we will have to deal with and learn how to cope with, you know, workforce wise and emotionally and otherwise.

But yeah, I'll, I'll go with no as well. So so you heard it here, um, New York Times, you can quote us if you like. We are not in an AI bubble.

Cause Dan and Chris said some

I'm. I'm glad that, I'm glad that we put that one to rest, Chris.

Yeah, well, there we go. Solving world problems one episode at a time.

Yeah, yeah, well, um, I guess until next time, we can, we can solve the next world crisis in in the next episode. Chris, thanks for chatting.

Absolutely, talk to you next time.

All right, that's our show for this week. If you haven't checked out our website, head to practicalai. fm and be sure to connect with us on LinkedIn X or Bluesky. You'll see us posting insights related to the latest AI developments, and we would love for you to join the conversation. Thanks to our partner Prediction Guard for providing operational support for the show. Check them out at predictionguard. com. Also, thanks to Breakmaster Cylinder for the beats and to you for listening.

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