The AI Daily Brief: Artificial Intelligence News and Analysis - 5 Reasons AI is a Bubble (And 5 It’s Not)

Starting point is 00:00:00 Today on the AI Daily Brief, five reasons AI is a bubble and five, it's not. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, robots and pencils, Notion, KPMG, and Superintelligent. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can get it on Apple's subscriptions. To learn more about sponsoring the show, or anything else about the show, speaking engagements, etc., go to AI Daily. Brief.A.I. One of the things that I'm thinking about for next year are extensions to this core show. Nothing is changing about this core show, but there is so much more to explore

Starting point is 00:00:46 out and around it that I'm exploring three different ways to expand the AIDB universe. The first is an enterprise edition that would basically take this show, repackage it, reorganize, and restructure it as learning materials and discussion and strategic material for enterprise teams. The second is an operator's cut, which would be additional supplemental material that was a little bit more practical and focused, stuff that would help you apply AI more directly, and then the third, relevant for this particular episode, is an investor's edition, which would be a supplement more focused on big market themes. I would love to know if any of these interest you. So if you would be so kind, please go to A.I.Dailybrief.aI. There's a three-question survey

Starting point is 00:01:26 there, and that would be ever so appreciative if you would fill it out. Lastly, today, we are talking about the big behemoth topic, is AI a bubble? And it got long and dominated the entire episode, So no headlines today. We'll be back with headlines tomorrow. And without any further ado, let's dive in. Welcome back to the AI Daily Brief. Today we are once again exploring a theme that has been with us since the beginning and will be with us for a long time to come, I think.

Starting point is 00:01:49 However, it has just gotten too loud, too unignorable. We have to dig in again because this is all anyone, at least in the mainstream media, is talking about right now. The question, of course, is AI Bubble. And we are going to talk about this latest report from the information in Oracle, which restarted this set of conversations. and look at a set of reasons why AI is or is not in a bubble right now. But just for a little bit of context, and to really reinforce the point that this has been with

Starting point is 00:02:13 us since the beginning, Chad CBT came out at the very end of November of 2022. And already by February 7th, people like Josh Brown of Ritzholtz Wealth Management were calling an AI bubble. It was loud enough that a few months later in September, Goldman Sachs had to come out and say that it wasn't a bubble. Despite the mega-cap tech stocks rising by 60% at that stage in, their analysts were convinced that there was still plenty of room to run. But then by December, we get articles like this one from Crunchbase. The AI bubble will burst. Here's how to limit your

Starting point is 00:02:44 exposure. This article was more focused on startups with random AI SaaS companies being valued at the same multiples as OpenAI or Anthropic. Now, of course, we know what has happened since then, at least from a big market perspective. With the small exception of the tariff tantrum earlier this year, it has been just up and to the right. And in 2025 in particular, the sheer size of everything surrounding AI has just gotten absolutely enormous. This has led over the last couple of months to a renewed discussion of the bubble conversation. We had a big burst in this topic in August, as we got the combined factors of initial disappointment with GPT5 and the renewed arguments that we were hitting a wall, widely overreported comments about Sam Altman saying there was a bubble,

Starting point is 00:03:26 and of course that now infamous MIT study, which I put in air quotes, that argued that 95% of AI pilots were failing, and which whipped around Wall Street with, incredible frenetic energy. Still, another interesting thing happened in early September when we got news of the $300 billion Oracle Open AI deal that sent Oracle stock soaring by 35% in the day. All of a sudden, people were seeing the financial consequences of missing out on this leg of the AI boom, and Bubble Talk quickly fell off the menu. In fact, Deutsche Bank published a report in late September that declared that the first bubble to burst was in fact discussion of the AI bubble. They found that the peak of the narrative was back on August 21st, with the number of web searches for AI bubble

Starting point is 00:04:06 falling by 85% over the following month. One of the things they pointed out is that, quote, identifying a bubble is almost impossible, not least because no one agrees exactly what it is. Typically, it's something like when asset prices rise significantly above intrinsic values, but they also don't agree what the correct intrinsic values are even after it bursts. What's more they point out, concern about a bubble may act as a pressure valve, lowering valuations and encouraging a whole new round of bargain hunting. And yet, despite this report coming out on September 30th, just a little more than a week old, it already feels out of date. Searches for AI bubble have tripled over the past two weeks as a wave of new news

Starting point is 00:04:42 reignited the narrative. On Monday, we got news of OpenAI's deal with AMD, which was the subject of yesterday's show, which based on its non-traditional structure, of OpenAI potentially owning 10% of AMD if it hits milestones, felt very bubbly to some. Then on Tuesday, the information published an expose on Oracle's financials. The piece was titled, Internal Oracle data show financial challenge of renting out Nvidia chips. They write, internal documents show the fast-growing cloud business has had razor-thin gross profit margins in the past year or so, lower than what many equity analysts have estimated. This could raise questions about whether the AI cloud expansion undertaken by Oracle and its rivals will affect profitability and sustain investors' expectations.

Starting point is 00:05:25 So the report states that in the three months that ended in August, Oracle generated around $900 million from renting out Nvidia powered AI compute. Gross profit was $125 million or 14%. Which, as the information points out, is lower than even many non-tech retail businesses. For some comparison, Walmart's gross margin was 25% in the last fiscal year.

Starting point is 00:05:44 And then on the other end of the spectrum, closer to Oracle's business, Microsoft's Azure Division currently operates at a 69% gross margin. Oracle stock actually dove 6.9% on the news, but recovered much of the drawdown by the end of the day. The narrative was absolutely,

Starting point is 00:05:59 catnip for headline writers, with FX leaders going with Oracle stock dives on weak cloud profits, AI hype meets tough reality. Still, some thought something felt off about the whole thing. Amit is investing posted on Twitter. This doesn't seem like a demand issue, aka Oracle not finding customers for renting their GPUs, but rather seems like a margin issue. It seems like customers are asking for a really good deal, or they would just leave to an Iran, Nebius, or Correve, and as a result, Oracle's margins on this business have not been as strong. Some people question the financial acumen in the article. Take him, a veteran financial reporter and author of the NVIDIA way posted, today I learned AI infrastructure biz has lower gross margins

Starting point is 00:06:38 than software, and margins are bad when GPUs are getting installed and not yet generating customer revenue. This is basically an argument that the information and then consequently Wall Street investors were turning a mole hill into a mountain by not understanding the natural life cycle of this particular type of product. Jensen Huang commented on something similar in an interview with Jim Kramer on Tuesday, stating, what Oracle does with our systems is not easy. We're talking about giant supercomputers. When you first ramp up a new technology,

Starting point is 00:07:03 there's every possibility that you might not make money in the beginning, but over the life of the systems, Oracle is going to be wonderfully profitable. In fact, differences of opinion on the depreciation schedule for AI chips is one of the big factors going into bubble analysis. Most firms are depreciating their chips over five or six years before they need replacement. Yet some of the loudest bears like Jim Chanos argue the depreciation schedule much shorter, with data centers needing to upgrade to the latest and greatest from

Starting point is 00:07:28 Nvidia every two or three years to remain competitive. JT of Laquoia Capital picked up on an interesting comment from the information article on this front. The article stated, One silver lining in Oracle's GPU business is the amount of revenue it is generating from older generations of Nvidia chips, such as the Ampere chips that came out in 2020. Those chips appear to be helping Oracle's margins, while newer versions of Invidia chips strain them. JT points out, hilariously, this is probably the most bulletproof.

Starting point is 00:07:55 data point on the actual versus theoretical useful life of invidia silicon I've seen anywhere, maybe ever. They're still printing it on ampere. In other words, while the margin story shows how difficult it is to make money initially off of the state of the art, it is real lived evidence that chips from five years ago are still profitable, which has huge implications for how we think about the longevity of the value of this infrastructure that's being installed. A huge argument from those who think we are in a bubble is that the infrastructure is going to go out of date even faster than people think, and that unlike railroad track from centuries past or fiber optic cable from decades past, these chips are going to be useless in two or three years. And this suggested at least

Starting point is 00:08:34 that life cycle might be a little bit longer than we thought. Now, the other big piece of news circulating on Tuesday that supercharged this bubble conversation once again was that XAI had raised $20 billion in an ongoing funding round. The fundraising is apparently a mixture of debt and equity and will be used to fund the expansion of XAI's Colossus 2 data center that's currently under construction in Memphis. The part that caught everyone's attention was that Invideo was investing $2 billion in the equity side of the round, a move that Bloomberg wrote, was a quote, strategy by the chipmaker that helps accelerate its customer's AI investments. Okay, so this brings us to the main thrust of this piece. Is this a bubble or not? Let's talk about five reasons this is a bubble and five reasons it's not.

Starting point is 00:09:14 I think, by the way, I'm probably going to end up at six or seven reasons in each case. And to be clear, as you can probably imagine, I am very much in the boom-not bubble camp, but I am going to to represent the reasons it is a bubble with as little snark as is manageable for me. By far, and without a shadow of a doubt, the number one reason that some people think this is a bubble is the notion of circular investment, with the X-A-I deal being the latest in a string of examples. You might have seen some version of this chart going around showing how interconnected all of these companies are, or maybe this one which shows the actual dollar amounts going between different companies. To take just example of that new NVIDIA-X-I deal,

Starting point is 00:09:51 Invidia will invest $2 billion into XAI, which will show up three months later as revenue on NVIDIA's balance sheet after XAI uses it to buy chips. OpenAIs deals with AMD and Oracle work similarly, with investment dollars and revenue getting passed between firms to boost everyone's bottom line. This is bringing up what are for some uncomfortable questions of vendor financing, and some think it's amplifying and overstating demand in the entire sector. Stanfield Capital, for example, wrote, None of these circular AI deals would be happening if there were genuine cash demand for the chips at list price. It's obvious that the economics of this industry don't work unless the chips

Starting point is 00:10:25 are hugely discounted, which means the chipmakers are hugely overvalued. All right, so circular investment, reason one that people think this is a bubble. Reason two is the risk that AI infrastructure will be overbuilt. Kip Devere, the CEO of Private Equity Group Ares Capital Management, told Bloomberg on Tuesday, if you look historically in areas like this over the past 20 or 30 years, typically when this much capital comes online, some of it at the end of the day has to be marginal. These trends tend to lead to overbuilds in certain places, so us being selective and measured in what we build is important. Now, at this stage, there are trillions of dollars worth of AI data center commitments over the next

Starting point is 00:10:59 five years. And what's fascinating is that while this has financial professionals, seeing ghosts of overbuilt telecom structure from the past, all of the hypers and the big foundation labs continue to claim that their greatest risk remains too little compute rather than too much. J.P. Morgan reported this week that AI companies are now the largest segment of the investment grade debt market with $1.2 trillion in commercial bonds issued. They've reached 14% of the market in total, overtaking U.S. banks for the first time. And although the numbers are getting big in absolute terms, the report was still positive, stating debt tied to AI companies is growing fast, but it

Starting point is 00:11:33 trades tight for good reasons. The report noted that AI companies tend to be cash rich, not highly levered and highly regulated, which makes them very solid investment-grade bonds. But for those who think this is a bubble, that of course doesn't speak to the fate of the industry if AI demand fails to keep up with the supply of data. Last month, Bain and Company forecast that $2 trillion of annual revenue would be required to fund AI compute by 2030. Their analysis found that AI-related revenue would fall short by $800 billion. So that is bubble argument two overbuilding. Bubble argument three is the echoes of dot-com. Many people feel like they've seen this movie before. It's important to note that most of the senior people currently on Wall Street had their seminal

Starting point is 00:12:12 experience during the dot-com bubble, making and losing their first fortune in the space of few years. To them, this bubble has lots of echoes, including overbuilt infrastructure and circular investment. During dot-com, millions of miles of fiber optic cable was laid to power high-speed internet, but as much as 90% of it laid dormant for years after the burst. Circular revenue was also a huge problem during dot-com, especially among the companies that were little more than a website and a ticker symbol. In addition to vendor financing of the build-out, you also had the circularity of what little revenue there was going on in the web space, where most of the revenue was from banner ads, which were largely bought by other dot-com companies,

Starting point is 00:12:47 essentially meaning that investment dollars float around the ecosystem adding revenue to each company in turn and massively inflating financials. OpenAI chairman Brett Taylor recently said, I think there's a lot of parallels to the internet bubble. It is both true that AI will transform the economy, and I think it will, like the internet,

Starting point is 00:13:02 create huge amounts of economic value in the future. I think we're also in a bubble and a lot of people will lose a lot of money. So bubble argument three echoes of dot com. Bubble argument four, stretched valuations. The Schiller price to earnings ratio, which is a standard metric to measure stock valuations, hit a high in September. The S&P 500 was valued at the highest level since, you guessed it, 2000.

Starting point is 00:13:24 Now, most analysts are careful to note that there's no reason theoretically that richly valued stocks can't stretch even further. Russ Mould, an investment director at A.J. Bell, said, the U.S. equity market looks expensive relative to its history pretty much any way you slice it. However, he added, valuation does not guarantee an imminent accident. Still, if you were looking for reasons a bubble might burst, incredibly high stock valuations is one of the core warning signs. On to argument five, part of the bubble logic is just the sheer size of what's happening, and the idea that this scale of activity simply isn't sustainable.

Starting point is 00:13:55 On Monday, the Financial Times published an op-ed from Rockefeller International Chair Ritchie Sharma entitled, America is now one big bet on AI. He claimed that AI investments have accounted for 40% of US GDP growth and 80% of the gains in US stock so far this year. Sharma argued that AI is increasingly viewed as a magic fix for anything wrong with the economy, backfiring tariffs, consumer debt defaults, and a deteriorating job market, AI productivity gains are the big bet to smooth everything over. Now, the view is more about the consequences of an AI bust rather than evidence of a bubble. The idea is that AI investment has become too

Starting point is 00:14:26 big to fail, but is also wildly speculative. For Sharma and many other bubble concerned, it is of course nonsensical that producing tokens to the exclusion of anything else could be a sustainable premise for an economy the size of the U.S. Let's throw in one more argument for the bubble, which we might call speaking it into existence. Remember, in many ways, bubbles are about narratives, and they unwind when results fail to live up to expectations, when there is, in other words, a narrative fracture or a narrative disconnect. At the moment, expectations are sky high. A.I. is viewed as a technology that has the potential to change the world, a narrative that has been only applicable a few times in the past century. However, because the bubble is built on narratives, sometimes it only takes

Starting point is 00:15:06 a few errant comments from leaders to make it burst. And those comments seem to be coming more frequently, Last week, while on a press tour of their Texas facility, Sam Altman said, Between the 10 years we've already been operating in the many decades ahead of us, there will be booms and busts. People will overinvest and lose money and underinvest and lose a lot of revenue. We'll make some dumb capital allocations. However, he assured the press, over the arc that we have to plan over, we are confident that this technology will drive a new wave of unprecedented economic growth. Altman has made a string of comments like this over recent months, and seems far less

Starting point is 00:15:36 disciplined, frankly, in his messaging than the veteran CEOs like Jensen Huang or Larry Ellison. At Monday's Dev Day, he acknowledged that stocks jumping when they were mentioned on stage was, quote, weird and something they're getting used to. Altman's bubble talk might not be enough to pop the bubble all on its own, but it is certainly contributing to market nerves at the moment. Small, nimble teams beat bloated consulting every time. Robots and pencils partners with organizations on intelligent, cloud-native systems powered by AI. They cover human needs, design AI solutions, and cut-through complexity to deliver meaningful impact without the layers of bureaucracy. As an AWS-certified partner, robots and pencils combines the reach of a large firm with the focus of a trusted partner. With teams across the U.S., Canada, Europe, and Latin America, clients gain local expertise and global scale.

Starting point is 00:16:22 As AI evolves, they ensure you keep peace with change. And that means faster results, measurable outcomes, and a partnership built to last. The right partner makes progress inevitable. Partner with robots and pencils at robots and pencils.com slash AI Daily Brief. chatbots are great, but they can only take you so far. I've recently been testing Notion's new AI agents, and they are a very different type of experience. These are agents that actually complete entire workflows for you in your style, and best of all, they work in a channel that you already know and love

Starting point is 00:16:53 because they are purpose-built Notion super users. Notion's new AI agents completely expands the range of what Notion can do. It can now build documents from your entire company's knowledge base, organize scattered information into organized reports, basically do tasks that used to take days and get them complete in minutes. These agents don't just help with work, they finish it. Getting started with building on Notion is easier than ever. Notion agents are now your very own super user to help you onboard in minutes.

Starting point is 00:17:18 Your AI teammates are ready to work. Try Notion AI for free at the link in our show notes. What if AI wasn't just a buzzword, but a business imperative? On You Can with AI, we take you inside the boardrooms and strategy sessions of the world's most forward-thinking enterprises. hosted by me, Nathania Wittamore, and powered by KPMG, this seven-part series delivers real-world insights from leaders who are scaling AI with purpose, from aligning culture and leadership to building trust, data readiness, and deploying AI agents.

Starting point is 00:17:48 Whether you're a C-suite executive, strategist, or innovator, this podcast is your front-row seat to the future of Enterprise AI. So go check it out at www.kpmG.org.us slash AI podcasts, or search you can with AI on Spotify, Apple Podcast, or wherever you get your podcasts. Today's episode is brought to you by my company, Super Intelligent. Look, guys, buying or building agents without a plan is how you end up in pilot purgatory. Super Intelligent is the agent planning platform that saves you from stalling out on AI.

Starting point is 00:18:20 We interview teams at scale, translate real work into prioritized agent opportunities, and deliver recommendations that you can execute on, what to build, what success looks like, how fast you'll get results, and even what platforms and tools you should consider. All customized for you. Instead of shopping for hype, you get to deploy with confidence. Visit B-Super.ai and book your AI planning demo today. Okay, so those are five, actually six arguments for why it's a bubble. Certainly, the ones that are at the very top of people's lists are the questions of circular

Starting point is 00:18:50 investment, which is related to the concern of overbuilding, and more recently, the Schiller price to earnings ratio and stretch valuations is really starting to weigh on people's minds as well. But let's move over now into the top five reasons that bubble talk is overblown. The first is, of course, that revenues in this case are real. You might have seen some version of this chart circulating on X or wherever you hang out on social media, comparing AI revenues to the dot-com bubble. It shows a chart demonstrating that Cisco valuations completely detached from earnings growth,

Starting point is 00:19:19 starting in about 1998. By comparison, Nvidia's stock price has been on an incredibly steep climb, but right alongside it has been an incredible streak of earnings growth. Rowan Paul shared this chart and said, this is not a bubble. Cisco was a valuation story, price inflated, while earnings lag, then the multiples deflated. Invidia is an earning story. Price climbs alongside surging earnings. Luxago recently posted a 90s-time magazine cover that asked is the boom over. They wrote, reminder that the dot-com bubble didn't top for another 18 months after the September 1998 cover.

Starting point is 00:19:51 And that was with companies like Pets.com doing 9 million in peak annual revenue. Invidia did 46 billion in sales last quarter. It is different this time. The same is true in private markets. Open AI's revenue growth forecasts have frequently been dismissed as a fantasy, but they've managed to outperform every year since the release of Chatchip-T. What's more, thanks to the AI coding boom, Anthropic has come into its own this year and is now growing even faster than Open AI. Long-tail startups are seeing the same thing.

Starting point is 00:20:19 Stripe's most recent report on startup revenue found that the top 100 AI companies were hitting a million in ARR in 11.5 months compared to 15 months for non-AIS startups. Now, of course, these companies are not profitable yet. This is revenue growth, not profit growth, but still revenue growth is significantly faster than previous startup booms. Keep in mind, OpenAI and Anthropics revenue is not based on advertising or strange structured deals. Close to $20 billion is now coming in from people to purchase a product for themselves

Starting point is 00:20:52 or their employees that did not exist three years ago. Full stop, we have never seen anything like that. The second argument for why AI Bubble Talk is overblown is low leverage. We heard about that $1.2 trillion in commercial debt tied to AI infrastructure, and anytime you get a number with a T, it starts to sound scary, but that debt is backed by very solid companies concentrated in meta and Oracle. At this stage, Google and Amazon seem to be funding their data center construction entirely off their own balance sheet, and Microsoft has a very conservative debt capital strategy.

Starting point is 00:21:24 And so far as Nvidia's circular investments go, a big part of the reason that they are offering vendor financing and equity for GPU swaps, is that they have an absolute boatload of cash. They can't move the needle by reinvesting into the business, so they need to take bets on the AI ecosystem to set up the next leg of growth. In a recent appearance on TBPN, Doug O'Loughlin, the president of semi-analysis wrote, none of the hypers are levered. Microsoft has net cash and has become more creditworthy than the U.S. government. And what's really crazy is that Microsoft has a five-bibs premium to the Treasury. The real issue is how much liquidity the private credit market can handle. They're sitting on an ungodly amount of capital and they have to deploy it.

Starting point is 00:22:02 The traditional wisdom is that bull markets don't die of old age. They're killed off, almost universally by a credit crunch. In other words, to bet on the bubble bursting right now is fundamentally about one or more of the hyperscalers running into acute debt problems rather than a simple loss of enthusiasm. Reason number three, why AI bubble talk is overblown. Demand is real and growing. At OpenAI's Dev Day, they said they were now serving around three quadrillion tokens a year. Yes, get used to needing to now have quadrillion in your common parlance and frame of reference. A group of 30 power users across startups and large enterprises have turned through more than a trillion tokens on their individual accounts.

Starting point is 00:22:40 Google's most recent figure showed a 100% increase in monthly tokens served between May and July this year. As of July, they were serving almost a quadrillion tokens a month, and that number is up 100x since May of last year. Point is, there is clearly a ton of demand for AI inference, and it's still growing at an incredibly rapid clip. If anything, in fact, the growth rate has been increasing. So while, yes, one of the big risks that people see is AI infrastructure being overbuilt,

Starting point is 00:23:07 when you look at the growth in token demand, it makes more sense why every single AI company seems willing to bet that underbuilding will actually be the larger problem. Reason number four, why the AI bubble talk is overblown is actually less about whether there's a bubble or not and more about what you do with it, we might pleasantly sum this up as F you I'm buying. Basically, one of the more recent counter narratives is that Wall Street simply can't afford to be bearish on AI anymore. Over the past few years, we've had repeated drawdowns in AI stocks, accompanied by some scary new narrative, the deep seek moment and last summer's too much spend to little benefit note from Goldman Sachs are two prime examples. Each time, retail traders have bought

Starting point is 00:23:43 the dip while Wall Street missed out, and you can feel the seething in some recent quotes. Speaking with Bloomberg on Tuesday, Michael O'Rourke, the chief market strategist at Jones Trading, said, the market is pricing these deals as if everyone who transacts with OpenAI will be a winner. Open AI is a negative cash flow company and has nothing to lose by signing these deals. Investors should be more discerning, but this is a by-first-ask-question's later environment. Others are simply acknowledging that nothing is anywhere near as compelling as AI investment. Wells Fargo chief equity strategist, Osang Kwan's week, outset of AI, I'm not really excited about anything. The same is clearly true in VC.

Starting point is 00:24:17 AI has been a hot sector as far back as 2019, but has now grown to represent 60% of every VC dollar. Oga's O, a self-styled contrarian investor, wrote, for reference, only 40% of the money went to internet companies in 1999. If those AI companies don't start generating real revenue soon enough, investors will start stepping back. And yet, there is no sign that investors have stepped back an inch. Aside from some sputtering at XAI, every venture round for these big ones is still upsized and oversubscribed, and valuations show no sign of plateauing. In short, across Wall Street and Menlo Park, investors cannot get enough exposure to AI. A fifth reason that AI bubble talk is overblown ties back to the information's reporting on

Starting point is 00:24:56 Oracle's financials and AI corporate accounting more generally. One of the more thoughtful bubble claims has been that GPUs are going to depreciate far more rapidly than previous types of infrastructure buildout and maybe even more rapidly than many companies expect. This was a big knock on Corweave when they went public as they were amortizing GPU depreciation across a six-year period, even long. longer than the industry standard five-year schedule. The logic goes that that Nvidia is releasing new GPU updates on a two-year cadence, and data centers will need to

Starting point is 00:25:23 serve the latest and greatest. That's why it's such big news that Oracle is still seeing fat profit margins from GPUs made in 2020. It suggests that the millions of H-100s currently deployed across the country could remain useful until close to the end of the decade. And while it might feel like a very technical accounting point, the difference between GPUs becoming worthless in two years compared to five years or more is worth hundreds of billions of dollars to the industry. Since we did a bonus for the AI bubble arguments, let's do a bonus for the not bubble as well. We'll call this one the watch pot doesn't boil. Bubbles typically don't burst when everyone is expecting them to.

Starting point is 00:25:57 Concerns about an AI bubble peaked in August and they look like they're ramping back up again. That's why we're doing this show. Historically, though, the moment you should be concerned is when your neighbor is mortgaging their house to buy the latest hot stock or crypto. Meanwhile, in our case, ahead of us, we still have an eventual OpenAI IPO, the commissioning of gigawatt data centers, and a ton of energy infrastructure to come online. Ryan Dietrich, the chief market strategist at Carson Group posted, the bull market turns three this Sunday. Just a reminder that the five previous bull markets going back the past 50 years that made it this far kept going. The shortest was five years, the average was eight years, and two made it to double digits. In a research note last

Starting point is 00:26:34 week, meanwhile, Bank of America chief strategist Michael Hartnett wrote, every bubble in history has been popped by central bank tightening, and there's absolutely no sign of tightening anytime soon. Now, one interesting rising narrative to keep an eye on is the idea that the AI bubble exists, but is good. Speaking at an event on Friday, Jeff Bezos commented, this is kind of an industrial bubble as opposed to financial bubbles. The banking bubble, the crisis in the banking system, that's just bad. That's like 2008.

Starting point is 00:27:00 Those bubble society wants to avoid. The ones that are industrial are not nearly as bad, they can even be good. Because when the dust settles and you see who are the winners, society benefits from those inventions. That's what's going to happen here too. This is real. The benefits to society from AI are going to be gigantic. So now, if we might for a moment, let me add a few thoughts that I have, as relates to this whole conversation.

Starting point is 00:27:22 As I mentioned, while I am in the boom-not bubble camp, I am not dismissive of all the points that the bubble people are making. The circular revenue conversation is important if I think it misses a few points. Watching price-to-earnings ratios as signs of exuberance. That's important. Having a sophisticated understanding of how fast these capital expenditures actually depreciate is important. But I think that there are some meta things that go into these calls of bubbles that are worth calling out as well. The first is a phenomenon that I want to call the big short generation, where everyone wants to be Cassandra. That movie came out and made the people who actually spotted the GFC before it

Starting point is 00:27:57 happened look like absolute superheroes, and there has been cachet ever since then in calling out exuberance. I think this is amplified by social media, which amplifies the historical fact that it's always been cooler to be skeptical than it is to be exuberant and optimistic. And while I certainly don't think that this explains the phenomenon on its own and would be wildly dismissive to individual investors who do believe this is a bubble to say it's all about this. I've lived for a long time creating media and have watched a lot of people call a lot of bubbles, both that came to fruition and that didn't. And the common thread is that people really, really like calling bubbles when their voice can get amplified for doing so. A second phenomenon I want to identify is something

Starting point is 00:28:36 that we might call the rearview fallacy. This is the idea that our sense of what's possible in the present and future is constrained by what we've seen in the past. And on the one hand, this is completely natural. We've only had our lived experience and the experience of history as the possibility set, so it's very hard to imagine a future that isn't constrained by that possibility set. However, the entire point of the economic system that we've designed is to be expansionary, is to unlock possibilities that were impossible before. That's also the mandate of science, the mandate of technology. And I think a lot of what you see, especially when it comes to comparisons to dot com, is basically just an inability or an unwillingness to see these massive numbers, these massive growth as real. Because we're talking about such enormous numbers, it feels like it must be bubbly.

Starting point is 00:29:24 This gets back to the quote we heard earlier about the fact that just because stocks are richly valued now doesn't mean they can't get more richly valued in the future. It is enormously difficult, in short, for us as humans, to imagine futures where the possibility set is bigger. and the faster those changes happen, the harder it is for us to wrap our heads around. And so I do think that a little bit of the bubble talk by how anchored to the past we naturally are. A third factor that's a little bit less undergraduate psychology class is that simply put, I think that most people who are calling this a bubble are radically underestimating both revenue and growth. I think that people see OpenAI's $12 billion, or the aggregate of that plus Anthropics 5, plus a bunch of other companies between $100 million and $1 billion,

Starting point is 00:30:04 and say, look at the gap between that $20,000. billion and the hundreds of billions or trillions being committed to growth. That, of course, however, doesn't take into account cloud revenue growth from the hyperscalers. And even when you've added that in, I think most analysis of AI revenue doesn't go to the next step and actually look at factors like the fact that meta continuously talks about how much better their ads are doing because of the implementation of AI. In other words, there is a lot of AI shadow revenue that's hard to spot that I think is underestimating where we are right now. Also, when it comes to growth, I think that people are just wildly underestimating what's possible and what's coming down the pipeline.

Starting point is 00:30:39 I talked earlier this week about the KPMG 2025 CEO outlook, which is a study of 1,350 CEOs of companies 500 billion in revenue or more. 83% of them anticipate spending between 10% and 40% of their budget on AI over the next 12 months. That is such an enormous amount of additional incremental money coming in that we have barely begun to account for as we think about the possibilities. Effectively, the skeptics are saying, look, for these numbers to make sense, AI would have to be the foundation for an entirely new economy. And my answer is, well, yeah, exactly. There is also this other detail, which goes way beyond the scope of an already too long show,

Starting point is 00:31:20 but we have not even scratched the surface on a next generation of AI, i.e. embodied AI. Figure is debuting its O3 robot in just a couple of days, and there is just about no one who has, is factoring into their considerations how much inference demand there is going to be from actual industrial robots coming online at mass scale, despite the fact that that too is just around the corner. The last part that I want to mention goes back to this Stanfield capital argument. Remember, he wrote, it's obvious that the economics of this industry don't work unless the chips are hugely discounted, which means the chipmakers are hugely overvalued. He said none of these circular AI deals would be happening if there were genuine cash demand for chips at list price. We already made the point

Starting point is 00:32:01 that part of why these circular deals are happening is that Nvidia has so much cash, they have to do something with it. But there's something bigger here. These deals and these non-traditional financings are not about artificially inflating demand. They are about cheating time. These deals are about betting on the future and paying for that future with resources for the future so you can act today to get to the future. Now, that does not mean that there aren't the seeds of potentially systematic failure in those types of dealmaking. That's not what I'm arguing at all. But when it comes to the motivation, it is just simply incorrect to say that these companies are somehow forced to make up these deals to artificially inflate demand.

Starting point is 00:32:40 These companies are trying to cheat time and move faster than the gravity and physics of markets would otherwise allow them to. Ultimately, though, we have to be humble and recognize that no one knows who's right about this. So what are things that are worth watching for over the next set of months or even years as this AI boom or bubble, depending on your perspective, continues to grow? What are the things, in other words, that would be clearer signs of trouble? The first and most obvious would be a true and unrecoverable loss of faith in the technology.

Starting point is 00:33:10 We've seen little miniature versions of this with MIT's 95% of AI pilot's fail report, Sam Altman's bubble talk, and other events like that. But if we get to the stage where enterprises are actively withdrawing their AI spend, pulling back from how invested in this category they are, if we get to the stage where CEOs are being rewarded for dismissing AI as a failed technology, That would be a huge indicator of trouble to come. Another thing to watch should be big failed catalysts. Imagine, for example, Open AI struggling to raise new funding,

Starting point is 00:33:38 or their stock dropping hard after an IPO. Those kinds of big visible signs that the market was refusing to put the next incremental dollar into AI investments. Another thing to watch for is infrastructure failures. The energy buildout is becoming a huge narrative in AI. And right now it seems as though data center construction is outpacing new energy coming online. AI being blamed for major blackouts.

Starting point is 00:33:59 would be a terrible look and could cause enough destabilization to really have a big market impact. There's also revenue growth. If I'm wrong and we start to see a tapering, if enterprises don't pour in money like it seems like they're going to, all of these investments start to look a lot more suspect. So by far the biggest factor, if you're just trying to look historically, the only thing that has ever truly popped a bubble is a credit crisis. As Bank of America's Michael Hartnett said, all bubbles end from central bank tightening and an inability to continue refinancing debt at a higher rate. The dot-com bubble, the housing bubble, the crypto bubble. They all popped after

Starting point is 00:34:34 interest rate hikes caused a credit crisis to rip through the sector. And it is absolutely the case that with these circular deals, a few key defaults could spread contagion. This is certainly the factor that the non-ideological folks on Wall Street who are trying to take a balance view of this are the most concerned with. Morgan Stanley wealth management CIO Lisa Shalett recently told Fortune, every morning the opening screen on my Bloomberg is what's going on with credit default swap spreads on Oracle debt. People start getting worried about Oracle's ability to pay. That's going to be an early indication to us that people are getting nervous. However, when asked when the bubble would pop, she said probably not in the next nine months, but possibly over the next 24. The short answer is,

Starting point is 00:35:13 of course, no one knows, but hopefully you now have a better sense of where I sit with this, and the arguments, frankly, for where everyone sits with it. As always, do your own research, or at least prompt deep research to do it for you, and make up your own mind. For now that's going to do for this quite long edition of the AI Daily Not So Brief. Until next time, peace.

The AI Daily Brief: Artificial Intelligence News and Analysis - 5 Reasons AI is a Bubble (And 5 It’s Not)

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.