Are we in an AI bubble?

Dan and Chris unpack whether today’s surge in AI deployment across enterprise workflows, manufacturing, healthcare, and scientific research signals a lasting transformation or an overhyped bubble. Drawing parallels to the dot-com era, they explore how technology integration is reshaping industries, affecting jobs, and even influencing human cognition, ultimately asking: is this a bubble, or just a fizzy new phase of innovation? Featuring: Chris Benson – Website https://chrisbenson.com/, LinkedIn https://www.linkedin.com/in/chrisbenson, Bluesky https://bsky.app/profile/chrisbenson.bsky.social, GitHub https://github.com/chrisbenson, X https://x.com/chrisbensonDaniel Whitenack – Website https://www.datadan.io/, GitHub https://github.com/dwhitena, X https://x.com/dwhitenaLinks: Powell says that, unlike the dotcom boom, AI spending isn’t a bubble: ‘I won’t go into particular names, but they actually have earnings’ https://fortune.com/2025/10/29/powell-says-ai-is-not-a-bubble-unlike-dot-com-federal-reserve-interest-rates/?queryly=related_articleSponsors: Outshift by Cisco - The open source collective building the Internet of Agents. Backed by Outshift by Cisco, AGNTCY gives developers the tools to build and deploy multi-agent software at scale. Identity, communication protocols, and modular workflows—all in one global collaboration layer. Start building at AGNTCY.org http://agntcy.org/. Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U. S. eCommerce. Start your one-dollar trial at shopify.com/practicalai http://shopify.com/practicalaiFabi.ai http://fabi.ai/ - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.ai http://fabi.ai/Upcoming Events: Join us at the Midwest AI Summit https://midwestaisummit.com/ on November 13 in Indianapolis to hear world-class speakers share how they’ve scaled AI solutions. Don’t miss the AI Engineering Lounge, where you can sit down with experts for hands-on guidance. Reserve your spot today! Register for upcoming webinars here https://practicalai.fm/webinars!

• 0:03Speaker 00

  Welcome to the Practical AI Podcast, where we break down the real-world applications of artificial intelligence and how it's shaping the way we live, work, and create. Our goal is to help make AI technology practical, productive, and accessible to everyone. Whether you're a developer, business leader, or just curious about the tech behind the buzz, you're in the right place. Be sure to connect with us on LinkedIn, X, or Blue Sky to stay up to date with episode drops, behind-the-scenes content, and AI insights. You can learn more at practicalai.fm. Now, onto the show.

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• 2:17Speaker 02

  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 things that are being discussed in the community. Hopefully, we learn along the way and our listeners learn along the way 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?

• 2:54Speaker 03

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

• 3:02Speaker 02

  We both, we both needed a sugary but not sugary caffeinated drink. I think you've got a Pib0, I've got a Coke Zero.

• 3:12Speaker 03

  There you go.

• 3:13Speaker 02

  It's been a long day of work, and now we get to talk about some, some fun things. Hopefully, we won't pop the AI bubble today, but certainly-

• 3:25Speaker 03

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

• 3:29Speaker 02

  Yeah, exactly. It's interesting, Chris. 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, this other stuff, which I think a couple of these things that I saw connected. And Chris, a little while ago, we kind of did a, the 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 we

• 4:09Speaker 02

  can just talk through some of those. Certainly, there is a debate going on. And 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 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- Maybe just the general concept of bubble. We're not talking about bubble gum, but.

• 4:45Speaker 03

  Yeah, I mean, the general notion of a bubble, you know, is it's really a financial concept where the valuation of an organization 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, you know, if you were talking, for instance, about the dot com bubble, and for those of you who may not have, depending on if you're in the younger skew of our audience, around 2000 ish, and that there was all this internet craze and

• 5:25Speaker 03

  rage and hype, not dissimilar from the hype we've been seeing in recent years over AI. And a lot of companies came about and 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 by the market with absolutely nothing coming out of them of value. And so, there's a point where the market kind of realizes that and corrects. And, and the giant dot com, you know, facade came falling down and kind of led into a recessionary period around the globe.

• 6:08Speaker 03

  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, 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?

• 6:30Speaker 02

  Maybe so, yeah. And, and I think there is, you know, genuine concern because previous bubbles that have burst have actually caused real harm. As you mentioned, whether that's economic kind of recession, certainly it distorts.

• 6:49Speaker 02

  The way people invest, or maybe what they invest into, which kind of has an effect potentially on retirement, or 401ks, there's a reduction in trust in certain types of organizations, or financial institutions, or technology companies, that sort of thing. And it could be companies, it could be assets. Like, a lot of times, people talk about crypto as an asset that, or I remember not too long ago, talking to tons of people about NFTs, right? And this really chaotic time with NFTs. And there's a lot of people that lost a lot of money in that. Indeed.

• 7:34Speaker 02

  So it is a valid concern. And I think the question that's on people's mind is, are we in an AI bubble? And one of the interesting articles that I saw this week, Chris, was that Powell, the Federal Reserve Chair, Jerome Powell, in the US, for those that aren't listening from the US, that's the Federal Reserve Chair Jerome Powell, often can kind of, anything that's said about the economy by whoever's in this position is taken with

• 8:18Speaker 02

  a lot of weight, because, well, Chris, you may have comments on this, but I'm not an economist. But generally, it is a sign of at least an intelligent opinion on things, where there's a lot that's gone on, or a direction that the Federal Reserve wants people to think.

• 8:39Speaker 03

  So the two second background without going off on 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 thus slow down or speed up the economy to either tackle an underperforming economy

• 9:24Speaker 03

  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. And he is certainly an expert in a lot of ways. I think that there are some other considerations in there, but it's definitely a powerful statement coming from that particular individual.

• 9:52Speaker 02

  Yeah, yeah. The title of the article in Fortune, which we'll link, is Powell Says That Unlike The Dot-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 talking about. I'm assuming it's some of these larger names that would be whatever OpenAI, Anthropic, Cohere, whatever the ones are that people would think of. I imagine some of those are, quote, "the names." But he says they sort of actually have earnings. The other interesting

• 10:34Speaker 02

  piece that I saw, Chris, which is maybe on the other side of this argument, and we can talk maybe after this about 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 is reporting that Nvidia is now worth $5 trillion.

• 10:55Speaker 02

  Dollars as it and this is the quote from the article as it consolidates power in AI boom. 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 political angle to this article, but the general idea with the article is that this $5 trillion valuation maybe is, is part of an AI boom. So yeah, that's certainly interesting.

• 11:29Speaker 03

  It is. 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 large cloud service providers that are offering a collection of AI services probably, you know, round out some of those names. One of the things, 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 Mr. Powell noted that some of these organizations have earnings and we are seeing, you know, that reflected in AI related stocks that are just dominating

• 12:14Speaker 03

  S and P 500 returns to the, to the degree of about 75% of those returns, 80% of earnings growth and 90% 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, that, that he did not say, and speaking as someone who has nowhere near the economic expertise of Mr. Powell, but did, did have some university studies in economics, that, you know, those, those numbers are concentrated

• 12:58Speaker 03

  in a tiny fraction of companies overall. And so my question-

• 13:05Speaker 03

  That I would ask is for for some of those giant companies that are that are making huge earnings from many, many, many thousands of customers spending huge amounts of money on AI growth. We have also talked about the fact that there is there's also in the media quite a bit of questioning of ROI on a lot of those AI investments at various companies. And so, you know, if you're the cloud provider making bukus of money, 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,

• 13:46Speaker 03

  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. Maybe it's not just a universal bubble, but it depends on who you're talking to to some degree.

• 13:59Speaker 02

  Yeah, and I guess that's where maybe this is murky is the some people might define bubble differently. I think that that 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 of years of these crazy valuations where essentially there is an unproven revenue model. So I'm looking at at one source here that's that's saying over 50% of VC funding in in Q2 of this year 2025 went into AI companies.

• 14:43Speaker 02

  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 valuation. So 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 15, 20, 25x, 30x for, you know, plus for an AI company

• 15:26Speaker 02

  where other companies, kind of your normal run-of-the-mill SaaS company in tech that's raising is definitely not raising at those multiples right now. So that would be, I guess, the argument or an argument for that affirmative is these kind of speculation and valuation that's maybe reminiscent of that dot com era.

• 15:51Speaker 03

  Yeah. By the way, another term, just to connect kind of that financial world with, you know, what we're talking about in terms of observations is those of you who invest, some of you may have heard the notion of a beta, which is essentially 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 that that valuation is not so extravagant. And so I guess, and that's another way of looking at this, is if you're

• 16:32Speaker 03

  looking at a company's, you know, portfolio analysis, you know, that some analyst is doing, and there might be a beta number attached, if you're, 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. And so, you know, that's another sign, well, you know, is there some bubble? Maybe. Is it as bad in terms of the sheer speculation of the dot com era? Maybe not, you know, that's one metric by which we can evaluate.

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• 19:34Speaker 02

  Yeah, Chris, I think you were starting to get into maybe something we've alluded to, which is the other side, the negative side of saying, no, we're not in a bubble, corresponding to this first argument of the speculative investing, which is that, you know, maybe the earnings or the kind of business fundamentals or the scale is, you know, the diversification is a bit stronger in this particular time than in the dot com time. So, you know, on the one side, Jerome Powell is talking about, talking about real earnings, right, which is maybe different from some of the dot com era.

• 20:17Speaker 02

  On the other side, there is, there does seem to be a diversified set of, of 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 on top of AI. We've talked a lot on this show about how the service providers, the large consultancies are, are doing quite well in the, in the AI space. And, and those things are things that are already scaling, whether that's chips

• 20:59Speaker 02

  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, the magnitude of the investment relative to kind of the GDP is still relatively low compared to other kind of, if you want to think back to actual, you know, other transformative revolutions like railroads or electrification.

• 21:31Speaker 02

  And that sort of thing. So this this kind of counter argument 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.

• 21:51Speaker 03

  I think 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 going to find that there's a selection of companies that absolutely fit that 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, are very little. And that the business model is is still quite questionable, 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 kind of comes back to something I mentioned at the beginning of the call of

• 22:33Speaker 03

  like, you know, the the bubblesque nature if we're if we're if we're in that kind of dot com internet period as an, you know, like, as our contextual reference, that it doesn't quite fit that. And it's it seems to be very much in like, how you're engaged and what your, you know, what your ideas, do you have customers, are you providing services, and thus have earnings that that support that versus the ones that are not. And I think, you know, we've spent so much time on the show over the years, really trying to cut through the hype cycle. Sometimes, quite literally, you know, we'll get the it will get the current year published hype cycle and start talking about some of that.

• 23:16Speaker 03

  And I think if you're deeply engaged, 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. I had a conversation earlier today with someone who was that person and was kind of asking about some. Stuff and I was kind of doing a little bit of mentoring, maybe. Uh, 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,

• 24:02Speaker 03

  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.

• 24:10Speaker 02

  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,

• 24:54Speaker 02

  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 going to come out of the AI world are going to be. I, I, you know, we've talked about this on the show.

• 25:39Speaker 02

  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.

• 26:04Speaker 02

  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 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 confusion, which maybe is not, I guess in thinking about it, it's not, it is similar to that dot com era because it's like everything related to

• 26:49Speaker 02

  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.

• 26:57Speaker 03

  Yeah, I mean, even then, people were buying hardware 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 feeding the purchase frenzy during that. And I think that is a similarity we have to today, where you have a small group of companies that are providing a lot of capability and stuff. I think, you know, when it comes to the others, you know, in that, like, you just identified, just, you know, with the AI label being so marketable and yet having almost no meaning

• 27:38Speaker 03

  because of the immense diversity of possibilities that you could apply AI labeling to. It really comes down to solving business problems that are real business problems as opposed to trying to put an AI thing out there, you know? And I think, I know that you and I, in our roles hosting the podcast here, we get pitched by a lot of companies, a lot. And so we see a lot of different, you know, positions.

• 28:14Speaker 03

  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 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 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 way of doing these evaluations. I wonder, you know, how the general population who is not 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 and marketing effort. You know, how do they, how do they tell the difference, you know?

• 28:59Speaker 03

  I, I think, I think that has a lot to do with, with bubbles as well as 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.

• 29:14Speaker 02

  Yeah, just, just anecdotally, it kind of has gone, I, I remember, I don't know if you had the similar experience, Chris, but 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 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,

• 29:54Speaker 02

  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, 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, as I was

• 30:36Speaker 02

  walking through the Indianapolis airport, there were multiple billboards and banners that I saw that all had some AI slant related to a product or service. So it's pervasive now and it is kind of the soup that, that we, that we live in.

• 30:55Speaker 03

  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 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 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 they are, they are suddenly, uh, I, I mentioned that conversation I had earlier today and

• 31:40Speaker 03

  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, 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. So times are changing quickly.

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• 33:34Speaker 02

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

• 34:18Speaker 02

  But the fact that AI is already being integrated into enterprise workflows, into even manufacturing and healthcare. It's not just kind of a technology that is looking for a application, an interesting technology that's looking for an application, but it is actually being applied and across a variety of industries. The second piece of this would be kind of the tie of AI to a very long lead-up of scientific research and deep roots, right? That have been going on since the 60s, 70s, 80s, and on.

• 35:03Speaker 02

  And had all of these things leading up to it, which...

• 35:08Speaker 02

  Gives it kind of roots in in kind of rigorous science and mathematics 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 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?

• 35:43Speaker 03

  Totally. 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, at least in the dot com context, is the fact that the fundamental underlying algorithmic technology that we're looking at here today in 2025, as we do the show, is actually about 40 years old, is is the the basis being neural networks. And while we don't use that phrase as much as we used to anymore, you know, we we call everything AI these days. But

• 36:21Speaker 03

  fundamentally, the AI that is powering everything that is of significant value of today is fundamentally neural networks that have been enhanced and embellished and designed further and, you know, next iteration, that kind of thing. And so we're building on a 40 year history of this particular line of algorithmic technology. And so, you know, that that's a great point you raised there a second ago, that this is not a fly by night, that there has been a, you know, the majority, for me, you know, the majority of my lifetime, this has been around. For listeners, just as a two second thing, for listeners who may not have followed the show for years, because I know I've mentioned this before,

• 37:05Speaker 03

  but my parents were working on neural networks back in the in the early 90s. And so, like, and that's actually was my first exposure to this when I was in college. And so, this is not new stuff. It's evolved. And I think the the biggest piece of it is you've had you've had Nvidia's come about, able to make GPUs that can support the continuing evolution of the technology. It is thoroughly embedded in a bunch of industries. And some like anything, some implementations are better than others. But yeah, great point you're making in terms of that this is not a solution in search of a grounding

• 37:48Speaker 03

  or in search of a market to use it.

• 37:51Speaker 02

  Yeah, yeah. And 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 investment in this area is crazy. Not to say that you can't invest in prediction guard. And I'll talk to you, but, 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,

• 38:32Speaker 02

  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 in a certain way, but I think there are real kind of foundations to that speculation that, that, I don't know. I would almost, I would almost use the metaphor. It's kind of like when people go out and look for gold or, or oil, right?

• 39:14Speaker 02

  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. It's not like you're 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 finding it. And certainly, many people lose a lot of money in that speculation. Here, it's similar. There is a kind of known or there is at least a feeling and an intuition that there will be very transformative companies that will be long lasting

• 39:58Speaker 02

  and this technology will be long lasting and it will be impactful. It's not that that's maybe doubted. But the crazy valuations are in some case are driven by that because, you know, who knows who's going to survive this AI craziness? But the technology, it seems, will be kind of pervasive and long lasting and transformative.

• 40:24Speaker 03

  I think so. I think I'll throw, I'm going to throw a wild card into the into the mix here for a moment. And 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 companies, especially some very large companies such as Amazon, who are doing massive layoffs, you know? And they're doing that on the notion, in Amazon's case, 14,000 middle managers. And that's just one, that's just one organization, one very large organization, but one. And this is happening in a lot of places.

• 41:06Speaker 03

  Is that, you know, we're definitely seeing the replacement efforts by companies to use technology to replace humans in that. 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, you know, we're definitely at that point right now where a lot of companies are beginning to bet. On AI technologies, but it's also happening at a time when, as we talked about,

• 41:45Speaker 03

  some of those ROIs on different efforts are not yielding, you know, meaningful results. And so aside from what happens with that, when you have unemployment rising from AI-induced layoffs, that will affect the economy too. So it's not just whether or not the investment in these particular companies is wise or speculative and, you know, based on their fundamentals and their earnings, but also, you know, as we have groups of folks in the economy being laid off, and therefore their purchasing power is reduced, how does that play back in?

• 42:28Speaker 03

  I've seen a lot in the news about like all of this together, not only the ROI and speculative nature or whether it's a bubble or not, going back to our kind of original phraseology, but also whether or not this is going to affect workplaces. So it is quite a complex thing. And when we look back on dot com, it seemed, there were complexities there, but I think 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, after we had lived through it and looked back and kind of said, well, yeah, you know, I guess with 2020 hindsight, we can see that coming. As we've noted here, it kind of depends on who you are and how you're

• 43:12Speaker 03

  doing and what you're claiming is your AI and whether you're solving a real business problem on whether or not you're in that bubble group or not in a bubble group. So as we see the mixture pouring through the economy, it will be definitely interesting to see how this plays out in the weeks, months and years ahead here.

• 43:33Speaker 02

  Do you think that, because we also talked recently on the show about almost the both cognitive and emotional

• 43:43Speaker 02

  You know, change and shift or even manipulation that some of these these systems are doing, you know, 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 cognitive load of work is changing because you're, you know, vibe coding and all of these things. So do you think that that sort of cognitive and emotional, almost like lifestyle shift is more impactful with this technology or with something like the dot com era and people

• 44:28Speaker 02

  kind of all coming online?

• 44:30Speaker 03

  You know, dot com era was, and sadly, I was well into adulthood, you know, as we hit that, you know, you know, for those who don't realize that I'm getting 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 did realize what it was going at. It just wasn't on 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 you weren't having relationships with your with your ISP at the time, you know, it wasn't

• 45:13Speaker 03

  that kind of a relationship that you had with that wave of technological innovation. This one, it's a little bit worrisome. Like, I don't believe in vibe coding being a great strategy personally. 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 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 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 kind of depends. Depends on what you're doing with it. I see there's also been some research and we may have

• 45:58Speaker 03

  an episode coming up on it that was done recently about the human dependence on AI causing basically degradation, like they were measuring brain activity and the subjects that were in this study that were using their AI for everything were showing decreased brain capability 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

• 46:37Speaker 03

  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 choose how I use AI capabilities in a way that enables me versus kind of creates a crutch for me. So that's, that's kind of 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 and a, as an individual.

• 47:15Speaker 02

  Makes sense. Yeah, I think that's a, that's a great way to look at it. Well, 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? Yes or no?

• 47:26Speaker 03

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

• 47:47Speaker 02

  Yeah, a fizzy like our like our PIB zero and Coke zero that we that we started talking about.

• 47:54Speaker 03

  The fizzy, yeah, there you go. The fizzy economy. You heard it here first, folks.

• 47:58Speaker 02

  The fizzy AI soup. On my end, I would tend to go with the the no. I I definitely think that compared to some other technologies and cycles, this is already kind of at a level of utility and permeating many, many 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 go with no as well. So so you heard it here. New York Times, you can quote us if you like. We are not in an AI bubble.

• 48:38Speaker 03

  Because Dan and Chris said so.

• 48:39Speaker 02

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

• 48:42Speaker 03

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

• 48:46Speaker 02

  Well, I guess until next time, we can we can solve the next world crisis in in the next episode. Chris, thanks for chatting.

• 48:54Speaker 03

  Absolutely. Talk to you next time.

• 49:03Speaker 00

  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 Blue Sky. 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. That's all for now, but you'll hear from us again next week.