The Enshittifinancial Crisis: Part Four

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1:07Prices, they're still high, and the economy is all over the place. But 2026 is the year for you to get intentional and make real progress. That's right. Yeah, each week we break down what's happening with your money, the most important issues to focus on, and the small moves that make a big difference. Kick off the year with confidence. Listen to HowToMoney on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. Hello, hello, all my people. What's up? It's Questlove. Recently, I had the opportunity to sit down with the one and only A$AP Rocky. He reflects on his journey from Harlem roots to global icon status and discovering the hip-hop origin of his name.

1:45The ledge was on the TV. Rakim had the bucket-hat Kangol join on. I'm possibly like, that's Rakim. That's who you named after. I just was like, damn the f***ing f***ing swag. Swag. Listen to the Questlove show on the iHeartRadio app, Apple Podcasts, or wherever you get your podcast.

2:07Call Zone Media. Hello and welcome back to Better Offline. I'm your host, Ed Zitron.

2:22Better Offline. This is the last part of our four-part series about how the financial system and the financial markets are the last victims of the inshittification process. Over the past four episodes and a 20 ,000 or so word newsletter which this series is based on, I've explained how. And in this final episode, I'm going to explain how all this is going to fall apart and make it clear where I'm so fucking alarmed. Now, let's get back to those data centers. we've already got some signs of concern within the banking world around them and i'm kind of worried and so are they about their exposure in november the ft reported the deutsche bank which backed call weave multiple times and several data centers was exploring ways to hedge its exposure to the ai data centers after extending billions of dollars in debt including shorting a basket of ai related stocks or buying default protection on some of its debt using synthetic risk transfers which are when a bank sells the full or partial credit risk of a loan or loans to another bank while keeping the loans on their book, paying a monthly fee to investors.

3:26This is a simplification. Please don't be mad at me. In December, Fortune reported that Morgan Stanley, three times with CoreWeave, IPI Partners, Hyperion, SoftBank's Bridge Loan, was also considering synthetic risk transfers on loans to businesses involved in AI infrastructure. Wonder what those were for? Now, back in April, SMBC sold synthetic risk transfers tied to private debt BDCs, and while this predates the larger data center deals done by Blue Owl, who is a BDC themselves, SMBC has overseen multiple Blue Owl deals in the past. in december smbc closed another srt selling off risk from australian and asian project finance loans though i can't confirm in it if any of those were data center related now in december goldman sachs paused the planned mortgage bond sale for data center operator cyrus one with the intent to revive it in the first quarter of 2026 i've heard nothing from that since oracle's credit risk reaches 16 year high in the middle of december with credit default swaps basically betting that Oracle will default on its debt, which is unlikely yet no longer impossible, climbing to their highest price since the great financial crisis.

4:40While Morgan Stanley and Deutsche Bank's SRTs are yet to close, it's still notable that two of the largest players in data center financing feel the need to hedge their bets. So what exactly are they hedging against? Simple, that tenants won't arrive and debts won't get paid. I also believe that they're going to need bigger hedges because I don't think there's enough actual AI demand to meet the data centers being built, and I think most data center loans end up being underwater within the next two years. To be clear, this isn't a speculative chance, but rather one rung on the chain of pain that's been forged, and looks like it's ready to snap.

5:15Let's start by quoting my premium newsletter from December 5th. While many people talk about how circular the AI bubble may or may not be, the reality is that it's far more like a chain, a deeply vulnerable one held together by debt and venture capital. A company buys a GPU from NVIDIA, at which point nobody is making any profit anymore. These GPUs are purchased, for the most part, using debt provided by banks or financial institutions. While hyperscalers like Microsoft can and do fund GPUs using cash flow, even they have started to turn to debt. At that point, the company that bought the GPU sinks hundreds of millions of dollars, or even billions of dollars, to build out a data center, and once it turns on, provides compute to a model provider, such as OpenAI or Anthropic or even a smaller company, which then begins losing money selling access to those GPUs, or of course training models on them which only loses money.

6:05For example, both OpenAI and Anthropic lose billions of dollars and both rely on venture capital to fund their ability to continue paying for accessing those GPUs. At that point, OpenAI and Anthropic offer either subscriptions, which cost far more to offer than the revenue they provide, or API access to their models on a per million token basis. These rates are often subsidized too. AI startups pay to access those models to run their services, which end up costing more than the revenue that they make from offering them, which means they have to raise venture capital to continue paying to access those models.

6:38Outside of hyperscalers paying NVIDIA for GPUs out of cash flow, none of the AI industry is fueled by revenue. Every single part of the industry is fueled by a kind of subsidy, debt or equity as a result the ai bubble is really a stress test of the global venture capital private equity private credit institutional and banking system and its willingness to fund all of this forever because there isn't a single generative ai company that's got a path to profitability you see every little link in the chain of pain is necessary to understand things the inshittified stock market pumped not by actual cash flow or productivity by which i mean products that are selling Google, Microsoft, Amazon, Meta, they don't actually generate real revenue, definitely not profit from AI, but by signals read by analysts and investors trained over decades to push consumers to invest in the Magnificent Seven stocks.

7:31These stocks represent as much as 40 % of the value of the S &P 500, and their values, as I said, were pumped by analysts and the media misleading investors into believing that revenue growth for companies like Microsoft, Meta, Amazon, and Google have anything to do with AI versus the growth of their regular services. the other part in the chain is venture capital's liquidity crisis one peaking at a time when startups have become more capital intensive than any other point in history and the underlying value of their investments is only valuable as long as these companies stay alive and then of course the ballooning centralized data center debt bubble funded based on customer contracts or built for demand that does not exist funding massive data centers of gpus that immediately become commoditized as a result of this hysteria in really simple terms i believe that almost every reinvestment in a data center or AI startup may go to zero.

8:19Let me explain. If we assume that half of the$171.5 billion of data center debt is in GPUs, so$85 billion or so, that's about 3.2 gigawatts of data center capacity based on my model of NVIDIA's approximate split of sales between different AI GPUs from a premium piece from a few weeks ago. As a brief explainer, I made the model by taking NVIDIA's data center revenues, estimating how many of each GPU they sell, then dividing those revenues by those numbers and multiplying the result by the power output of the GPUs. In really simple terms, I worked out how many GPUs they sold and what the power to run them would be, and it'd be about 3.2 gigawatts.

8:56The likelihood of the majority of these projects being A, completed within the next year, and B, completed on budget is very, very small. Every delay increases the likelihood of default, as each of these projects is heavily debt-based. I also want to add, OpenAI claims, and I actually think they're bullshitting here, that they had two gigawatts of compute at the end of 2025. Two gigawatts. They are the only company with any real consumer exposure. They're the only ones with any number of real users other than Google, who has literally changed Google Assistant for Gemini. I don't think there's even like 500 megawatts of real demand outside of people training models or Elon Musk's CSAM generator.

9:38And that's a whole different story. Now, in general, the customers of these projects are either hyperscalers who are only doing AI because they have no other hyper-growth ideas and because Wall Street currently approves, or AI startups, all of whom are unprofitable. While there are potentially hedge funds or other small companies looking for private AI integrations, I think this is a very, very small market. On top of that, AI compute itself may not be profitable. And because, by my estimate, everybody has spent about$85 billion on filling data centers with the same GPUs, the aggregate price of renting out GPUs will decline.

10:12Already, the average price of renting out Blackwell GPUs has declined to an average of$4.45 an hour, according to Silicon data, and that's before the majority of Blackwell powered GPUs come online. Yet, the customer base shrinks from there because the majority of AI startups aren't actually renting GPUs. They build products on top of models built by OpenAI or Anthropic who have made it clear they're buying capacity from either hyperscalers or, in OpenAI's case, getting Oracle or CoreWeave to build it for them. Why? Because building your own model is incredibly capital-intensive, both on the compute and the data you have to get, and it's hard to tell if the results will be worth it.

10:50Now, let's assume, I don't actually believe it will, but let's try anyway, that all of that 3.2 gigawatts of capacity comes online. time how much of it how much actually how much compute does an ai company use like i said open ai ended 2025 with 2 gigawatts of capacity and they apparently have 900 million weekly active users i don't think there are any ai companies with even 10 of that user base but even if they were open ai spent 8.67 billion dollars on inference through the end of september who can afford to pay even 10 of that a year or five percent yet in reality open ai is likely more indicative of the overall compute spend of the entire AI industry.

11:29As I've said, most companies are powered not by their own GPU-driven models, but by renting them from model providers like OpenAI themselves. OpenAI and Anthropics spent a combined$11.33 billion in compute on Azure or AWS respectively through the first nine months of last year, and that's my own reporting by the way, and as the two largest consumers of AI compute, well, I'm a little worried. These things suggest two things. The market for AI compute is actually very, very small. If you assume that Anthropic spent the same amount on Google Cloud as it did in AWS, that'd be about a total of$5.32 billion.

12:05And that core weaves revenue, call it$5 billion, most of which was OpenAI via Microsoft or NVIDIA, there doesn't appear to be an AI compute market outside of servicing two companies. The other problem is the market for AI compute is not actually growing. In the last two years, no new major customers of AI compute have emerged. Every company that has signed a large compute deal has either been OpenAI, Anthropic, or Hyperscaler. Even if Cursor, an AI coding company, were to dump its entire$2.3 billion into funding AI compute, that would still not be very much. In fact, it would take sinking every single dollar of venture capital, over$200 billion, dollars every single year and then some funneled into ai compute just to produce the revenue to justify these deals existence in the space of a year microsoft azure made 75 billion dollars google cloud 43 billion dollars and amazon web services 100 billion dollars now that is just add those numbers together it's a little over 200 billion dollars and that's the three largest providers of any kind of compute not just ai compute most of that That is not AI compute.

13:14In fact, they barely make anything on that. They won't even talk about the AI revenues, probably because they're so stinky.

13:26What if mind control is real? If you could control the behavior of anybody around you, what kind of life would you have? Can you hypnotically persuade someone to buy a car? When you look at your car, you're going to become overwhelmed with such good feelings. Can you hypnotize someone into sleeping with you? I gave her some suggestions to be sexually aroused. Can you get someone to join your cult? NLP was used on me to access my subconscious. NLP, aka Neuro Linguistic Programming, is a blend of hypnosis, linguistics, and psychology. Fans say it's like finally getting a user manual for your brain.

14:02It's about engineering consciousness. Mind Games is the story of NLP. its crazy cast of disciples and the fake doctor who invented it at a new age commune and sold it to guys in suits. He stood trial for murder and got acquitted. The biggest mind game of all? NLP might actually work. This is wild. Listen to Mind Games on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. Hey, what's up y 'all? This is Questlove. Recently, I had the opportunity to sit down with A$AP Rocky ahead of his album release, Don't Be Dumb. He reflects on his journey from his Harlem roots to global icon status, discovering the hip-hop origin of his name.

14:44The ledge was on the TV. Rakim had the bucket hat Kangol during the last. Pops was like, that's Rakim, that's who you named after. I just was like, damn, that was f***ing. I swear. Rocky offers a window into not only a boundary-breaking artist, but as a man committed to fusing creative ideas, community, and remaining unapologetically himself. Have you ever gotten roasted for any of your outfits? For sure. Some people don't be getting the vision. Look, they can roast me, they can cook me, they can deep fry me, they can saute, whatever they want. It's nobody who can f*** with my fashion sense and my taste is impeccable.

15:21I'm just like, I impress myself a lot. It's an amazing conversation. one you definitely don't want to miss. So listen to the Questlove show on the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts. A new year doesn't mean erasing who you were. It means honoring what you've survived and choosing how you want to grow. It means giving ourselves permission to feel what we've been holding and knowing that it's okay to ask for help. I'm Mike Dallarocha, host of Sacred Lessons. This podcast is a space for men to talk openly about mental health, grief, relationships, and the patterns we inherit, but don't have to repeat.

16:05Here, we slow down. We listen. We learn how vulnerability becomes strength and how healing happens in community, not in isolation. If you're ready to let go of what no longer serves you and step into the year with clarity, compassion, and purpose, Sacred Lessons is your companion on your healing journey. Listen to Sacred Lessons with Mike DeLaRocca on America's number one podcast network, iHeart. Follow Sacred Lessons with Mike DeLaRocca and start listening on the free iHeart radio app today. Hey there, this is Dr. Jesse Mills, director of the men's clinic at UCLA Health and host of the Mailroom podcast.

16:45Each January, guys everywhere make the same resolutions. Get stronger, work harder, fix what's broken. But what if the real work isn't physical at all? To kick off the new year, I sat down with Dr. Steve Poulter, a psychologist with over 30 years experience helping men unpack shame, anxiety, and emotional pain they were never taught to name. In a powerful two-part conversation, we discuss why men aren't emotionally bulletproof, why shame hides in plain sight, and how real strength comes from listening to yourself and to others. Guys who are toxic, they're immature, or they've got something they just haven't resolved.

17:20Once that gets resolved, then there comes empathy, as in compassion. If you want this to be the year you stop powering through pain and start understanding what's underneath, listen to The Mailroom on the iHeartRadio app, Apple Podcasts, or wherever you get your favorite shows.

17:41Well, if you need more proof, if you still don't believe me, skip to page 18 of NVIDIA's most recent earnings. And I quote, multi-year cloud service agreement commitments as of october 26 2025 were 26 billion dollars which 1 billion dollars 6 billion dollars 6 billion dollars 5 billion dollars 4 billion dollars and 4 billion dollars will be paid in fiscal years 2026 fourth quarter 2027 2028 2029 2030 and 2031 and thereafter respectively now i know that was confusing but just to line that up that means in fiscal year 2027 which begins oh i would have to look that up uh yeah i'm literally doing this on the air i don't give a shit um so their fiscal year begins in february so basically 2027 uh begins this february 2026 so they're going to be spending six billion dollars on ai compute in 2027 this is a company that does not rent out compute if there's such incredible surging demand why is it why exactly is nvidia spending six billion fucking dollars a year in 2026 and 2027 on it nvidia doesn't need compute it just shut down its amazon web services compared to that it's called dgx cloud it looks far more like nvidia is propping up an industry with non-existent demand i'm afraid there is no secret amazon web services size spend waiting in the wings for the right moment to pounce there is no secret demand wave nor is there any capacity crunch that is holding back incredible swaths of revenue Oracle's$523 billion in remaining performance obligations are made up of OpenAI, Meta, and you'll never guess who, NVIDIA.

19:18Fucking NVIDIA. The AI bubble is just NVIDIA being handed money and then handing it to people. They're very profitable as well. They do great. Everyone else, not so much. For AI data center deals to make sense, most startups would have to start becoming direct users of AI compute, while also spending more on cloud compute services than they've ever spent. The largest consumers of AI compute are both unprofitable, unsustainable monstrosities dependent on venture capital. Eventually, reality will dawn on one or more of these banks. Projects will get delayed thanks to weather or budgetary issues or when customers walk away, as just happened to a data center at REIT called Fermi, and loan payments will start going unpaid.

20:00Elsewhere, AI startups will start asking for money again and again. And for a while, they'll keep raising until the valuations get too high or VC coffers get too low. You're probably going to say at this point that OpenAI or Anthropic might go public, which will infuse capital into the system. And I want to give you a preview of what that might look like, courtesy of AI Labs Minimax and Zipu, as reported by the information, which just filed to go public. I'm a little scared. These are the first real numbers about the AI public. I hope I'm not going to get embarrassed. Everybody's saying that behind the scenes, these companies are secretly great.

20:34Let's take a look. Oh my god! These numbers aren't great at all. These numbers are terrible. In the first half of 2025, Zipu had a net loss of$334 million on$27 million of revenue. Meanwhile, Minimax made$53.4 million in revenue in the first nine months of 2025 and burned$211 million to earn it. It's time to wake up. These are the real-life costs of running an AI company. OpenAI and Anthropic are going to be even worse than this. This is why nobody wants to take AI companies public. This is why nobody wants to talk about the actual costs of running AI. This is why nobody wants you to know the hourly cost of running a GPU and this is why OpenAI and Anthropic burn billions and billions of dollars.

21:21The margins fucking stink, every product is unprofitable, and none of these companies can afford their bills based on their actual cash flow. Generative AI is not a functional industry, and once the money works that out, everything burns. Though many AI data centers boast of having tenancy agreements, remember, these agreements are either with AI startups that will run out of money, who really shouldn't be renting GPUs by the way, or hyperscalers with legal teams numbering in the thousands. Every single deal that Microsoft, Amazon, Meta, Google, or NVIDIA signs is riddled without specifically hedging against this scenario.

21:57And there won't be a damn thing that anybody can do about it if hyperscalers decide to walk away. Before then, NVIDIA's bubble is likely to burst. As I discussed a few weeks ago, NVIDIA claims to have shipped 6 million Blackwell GPUs. And while it may be employing very dodgy maths, claiming that each GPU is actually two chips, Jensen, you're driving me insane. My modeling of its last three quarters suggest that NVIDIA shipped around 5.33 gigawatts worth of GPUs. And based on reading about every single data center deal I can find, it doesn't appear that many have been built and powered on, or even started building in many cases.

22:35Worse still, NVIDIA's diversified revenue is collapsing. In the first quarter of its fiscal year 2026, I'm sorry, you're just gonna have to ride with me on this one, two customers represented 16 % and 14 % in revenue. In the second quarter of fiscal year 26, two customers represented 23 % and 16%. And in the third quarter, four customers represented 22%, 15%, 13%, and 11 % of total revenue, with all of that money going towards GPUs or networking gear. In simpler terms, NVIDIA's revenue is no longer coming from a diverse swath of customers. In its first quarter fiscal year 2026, it had$30.84 billion of diversified revenue.

23:13That's from customers that do not number more than 10 % of its revenue. And in the second quarter, of FY26, that was$28.5 billion. Q3, it was$22.23 billion. In simpler terms, there are only a few companies that can buy GPUs, and other companies are no longer buying GPUs at the same rate. I doubt this number is going to increase. You see, NVIDIA GPUs are astronomically expensive, $4.5 million for a GB300 rack of 72B300 GPUs, for example, and filling data centers full of them requires debt unless you're a hyperscaler. Well, I can't say for sure. I believe NVIDIA's diversified revenue collapse is a sign that smaller data center projects are starting to have issues getting funded and or hyperscalers are pulling back on the GPU purchases from those Taiwanese companies I was mentioning.

24:02Now, let me look through the eyes of an AI booster for a second. Okay. Okay. Everything is blue and yellow as usual. Okay. One might say that these big customers are covering the loss of revenue, but the reality is that these big projects are run on debt issued by banks that are becoming increasingly worried about nobody paying them back. The mistake that every investor, commentator, analyst, and member of the media makes about NVIDIA is believing that its sales are an expression of demand for AI compute, when in reality, it's more of a statement about the availability of debt from banks and private credit.

24:32Similarly, the continued existence of AI startups is an expression of the desperation of venture capital, and the continuing flow of massive funding rounds is a sign that they see no other avenues for growth and that their startups can't wipe their own assholes. Eventually, data centers are going to go unbuilt and data center debt packages will begin to fall apart. Remember, Oracle's$38 billion data center deal is actually yet to close, much like Stargate New Mexico is yet to close and much like Stargate Michigan is yet to close. These deals, while seeming like they're trending positively, are all incredibly important to the future of the AI bubble and any failure will spook an already nervous market.

25:09Only one link in this chain of pain needs to break. Every single part of the AI bubble, this fucking charade is unprofitable, save for NVIDIA and the construction firms erecting future laser tag arenas full of negative margin GPUs. Tell me, what happens if the debt stops flowing to data centers? How will NVIDIA sell their so-called 20 million Blackwell and Virubin GPUs they're claiming they'll ship by the end of 2026. What happens if venture capitalists start running low on funds and can't keep feeding hundreds of millions of dollars to AI startups so that they can feed them directly to OpenAI or Anthropic?

25:47What happens to OpenAI and Anthropic and their already negative margin businesses when their customers can't pay them? What happens to Oracle or CoreWeave's work-in-progress data centers if OpenAI can't pay their bills? What happens to Anthropic's$21 billion of Broadcom orders or tens of billions of dollars of Google Cloud spend. And what if I'm right about everything I've said, not just in this series, but in the episodes and newsletters before it? In the last year, I estimate I've been asked the question, what if you're wrong over 25 times? Every single time the question comes with this undercurrent of venom, the suggestion that I'm being an asshole for daring to question the wondrous AI bubble.

26:27Every single person who's asked me this has been poorly read, both in terms of my work and the surrounding economics and technological possibilities of large language models, and believes they're defending technology, when in reality they're defending growth and the economy's growth at all costs mindset. In many cases, they are not excited about technology at all, but the prospects of being the first in line to lick an already sparkling boot. This has never, ever been about progress or productivity. If it was, we'd seen actual progress, or productivity boost or anything other than the frothiest debt, the frothiest venture capital markets, and the most annoying and incorrect headlines I've ever read in the news.