Speaker 1: Media. Hello and welcome back to Better Offline. I'm your
Speaker 1: host ed ZiT Try. This is the last part of
Speaker 1: our four part series about how the financial system and
Speaker 1: the financial markets are the last victims of the inshitification process.
Speaker 1: Over the past four episodes, in a twenty thousand or
Speaker 1: so word newsletter which this series is based on, I've
Speaker 1: explained how and in this final episode, I'm going to
Speaker 1: explain how all this was going to fall apart and
Speaker 1: make it clear where I'm so fucking alarmed. Now let's
Speaker 1: get back to those data centers. We've already got some
Speaker 1: signs of concern within the banking world around them, and
Speaker 1: I'm kind of worried, and so are they about their exposure.
Speaker 1: In November, the ft reported the Deutsche Bank, which back
Speaker 1: cor we've multiple times and several data centers, was the
Speaker 1: exploring ways the hedge it's exposure to the AI data
Speaker 1: centers after extending billions of dollars in debt, including shortening
Speaker 1: a basket of AI related stocks or buying default protection
Speaker 1: on some of its debt using synthetic risk transfers, which
Speaker 1: are when a bank sells the full or partial credit
Speaker 1: risk of a loan or loans to another bank or
Speaker 1: keeping the loans on their book paying a monthly fee
Speaker 1: to investors. This is a simplification. Please don't be mad
Speaker 1: at me. In December, Fortune reported the Morgan Stanley three
Speaker 1: times with core Weave IPI partners, Hyperions, Soft Banks Bridge
Speaker 1: Loan was also considering synthetic risk transfers on loans to
Speaker 1: businesses involved in AI infrastructure. One of what those were
Speaker 1: for now. Back in April, SMBC sold synthetic risk transfers.
Speaker 1: Back in April, SMBC sold synthetic risk transfers tied to
Speaker 1: private debt BDCs. And while this predates the larger data
Speaker 1: center deals done by Blue Al, who is a BDC themselves,
Speaker 1: smbc's oversee multiple blue ol deals in the past. In December,
Speaker 1: s MBC closed another SRT selling off risk from Australian
Speaker 1: and Asian project finance loans, though we can't confirm if
Speaker 1: any of those were data center related now. In December,
Speaker 1: Goldman Sachs pause the planned mortgage bond sale for data
Speaker 1: Center Operate A Cyrus one, with the intent to revive
Speaker 1: it in the first quarter of twenty twenty six. I
Speaker 1: have heard nothing from that since Oracle's credit risk reaches
Speaker 1: sixteen year high in the middle of December, with credit
Speaker 1: default swaps basically betting the Oracle will default on its debt,
Speaker 1: which is unlikely yet no longer impossible, climbing to their
Speaker 1: highest price since the Great Financial Crisis. While Morgan Stanley
Speaker 1: and Deutsche Banks SRTs are yet to close, it's still
Speaker 1: notable that two of the largest players in data center
Speaker 1: financing feel the need to hedge their bets. So what
Speaker 1: exactly are they hedging against? Simple that tenants won't arrive
Speaker 1: and debts won't get paid. I also believe that they're
Speaker 1: going to need bigger hedges because I don't think there's
Speaker 1: enough actual AI demand to meet the data center's being built,
Speaker 1: and I think most data center loans up being underwater
Speaker 1: within the next two years. To be clear, this isn't
Speaker 1: a speculative chance, but rather one wrong on the chain
Speaker 1: of pain that's been forged and looks like it's ready
Speaker 1: to snap. Let's start by quoting my Premium newsletter from
Speaker 1: December fifth. While many people talk about how circular the
Speaker 1: AI bubble may or may not be, the reality is
Speaker 1: that it's far more like a chain, a deeply vulnerable
Speaker 1: one held together by debt and venture capital. A company
Speaker 1: buys a GPU from Nvidia, at which point nobody is
Speaker 1: making any profit anymore. These GPUs are purchased for the
Speaker 1: most part using debt provided by banks or financial institutions,
Speaker 1: while hyperscalers like Microsoft can and do fund GPUs using
Speaker 1: cash flow even they have started to turn to debt.
Speaker 1: At that point, the company that bought the GPUs six
Speaker 1: hundreds of millions of dollars or even billions of dollars
Speaker 1: to build out a data center, and once it turns on,
Speaker 1: provides compute to a model provider such as open ai Oranthropic,
Speaker 1: or even a smaller company, which then begins losing money
Speaker 1: selling access to those GPUs, or of course training models
Speaker 1: on them, which only loses money eat sample. Both open
Speaker 1: ai and Anthropic loose billions of dollars, and both rely
Speaker 1: on venture capital to fund their ability to continue paying
Speaker 1: for accessing those GPUs. At that point, open ai and
Speaker 1: Anthropic offer either subscriptions, which cost far more to offer
Speaker 1: than the revenue they provide, or API access to their
Speaker 1: models on a per million token basis. These rates are
Speaker 1: often subsidized too. AI startups pay to access those models
Speaker 1: to run their services, which end up costing more than
Speaker 1: the revenue that they make from offering them, which means
Speaker 1: they have to raise venture capital to continue paying to
Speaker 1: access those models. Outside of hyperscalers paying in video for
Speaker 1: GPUs out of cash flow, None of the AI industry
Speaker 1: is fueled by revenue. Every single part of the industry
Speaker 1: is fueled by a kind of subsidy, debt, or equity.
Speaker 1: As a result, the AI bubble is really a stress
Speaker 1: test of the global venture capital, private equity, private credit,
Speaker 1: institutional and banking system and its willingness to fund all
Speaker 1: of this forever. Because there isn't a single generative AI
Speaker 1: company that's got a path to profit stability. You see,
Speaker 1: every little link in the chain of pain is necessary
Speaker 1: to understand things. The intitified stock market pumped not by
Speaker 1: actual cash flow or productivity, by which I mean products
Speaker 1: that are selling Google, Microsoft, Amazon matter they don't actually
Speaker 1: generate real revenue and definitely not profit from AI, but
Speaker 1: by signals read by analysts and investors trained over decades
Speaker 1: the push consumers to invest in the Magnificent seven stocks.
Speaker 1: These stocks represent as much as forty percent of the
Speaker 1: value of the S and P five hundred and their values,
Speaker 1: as I said, were pumped by analysts and the media,
Speaker 1: misleading investors into believing that revenue growth for companies like Microsoft, Meta, Amazon,
Speaker 1: and Google have anything to do with AI versus the
Speaker 1: growth of their regular services. The other part in the
Speaker 1: chain is venture capital's liquidity crisis, one peaking at a
Speaker 1: time when startups have become more capital intensive than any
Speaker 1: other point in history, and the underlying value of their
Speaker 1: investments is only valuable as long as these companies stay alive.
Speaker 1: And then, of course, the ballooning centralized data center debt
Speaker 1: bubble funded based on customer contracts, will built for demand
Speaker 1: that does not exist, finding massive data centers of GPUs
Speaker 1: that immediately become commoditized as a result of this hysteria.
Speaker 1: In really simple terms, I believe that almost every investment
Speaker 1: in a data center AI startup may go to zero.
Speaker 1: Let me explain if we assume that half of the
Speaker 1: one hundred and seventy one point five billion dollars of
Speaker 1: data center debt is in GPUs, so eighty five billion
Speaker 1: or so, that's about three point two gigawats of data
Speaker 1: set capacity. Based on my model of in Videa's approximate
Speaker 1: split of sales between different aigpus from a premium priest
Speaker 1: from a few weeks ago. As a brief explainer, I
Speaker 1: made the model by taking in videos data center revenues,
Speaker 1: estimating how many of each GPU they sell, and dividing
Speaker 1: those revenues by those numbers, and markeplying the result by
Speaker 1: the power output of the GPUs. In really simple terms,
Speaker 1: I worked out how many GPUs they sold them what
Speaker 1: the power to run them would be. There'd be about
Speaker 1: three point two gigawts. The likelihood of the majority of
Speaker 1: these products being a completed within the next year and
Speaker 1: b completed on budget is very very small. Every delay
Speaker 1: increases the likelihood off, as each of these projects is
Speaker 1: heavily debt based. I also want to add open Ai claims,
Speaker 1: and I actually think they're bullshitting here that they had
Speaker 1: two gigawatts of compute at the end of twenty twenty five,
Speaker 1: two gigawatts. They are the only company with any real
Speaker 1: consumer exposure. They're the only ones with any number of
Speaker 1: real users other than Google, who has literally changed Google
Speaker 1: a system for Gemini. I don't think there's even like
Speaker 1: five hundred megawatts of real demand outside of people training
Speaker 1: models or Elon Musk's s SAM Generator, and that's a
Speaker 1: whole different story now. In general, the customers of these
Speaker 1: projects are either hyperscalers who are only doing AI because
Speaker 1: they have no other hyper growth ideas and because Wall
Speaker 1: Street currently approves, or AI startups, all of whom are unprofitable.
Speaker 1: While there are potentially hedge funds or other small companies
Speaker 1: looking for private AI integrations. I think this is a
Speaker 1: very very small market. On top of that, AI compute
Speaker 1: itself may not be profitable. And because by my estima,
Speaker 1: everybody is spent about eighty five billion dollars on filling
Speaker 1: data centers with the same GPUs, the aggregate price of
Speaker 1: renting out GPUs will decline. Already, the average price of
Speaker 1: renting out Blackwell GPUs is declined to an average of
Speaker 1: four dollars and forty five cents an hour according to
Speaker 1: Silicon Data, and that's before the majority of black Well
Speaker 1: powered GPUs come online. Yeah, the customer base shrinks from
Speaker 1: there because the majority of AI startups aren't actually renting GPUs.
Speaker 1: They build products on top of models built by Open
Speaker 1: Ai or Anthropic, who have made it clear they're buying
Speaker 1: capacity from either hyperscalers, or, in open AI's case, getting
Speaker 1: Oracle or core Weave to build it for them. Why
Speaker 1: Because building your own model is incredibly capital intensive, both
Speaker 1: on the compute and the data you have to get,
Speaker 1: and it's hard to tell if the results will be
Speaker 1: worth it. Now, let's assume I don't actually believe it will,
Speaker 1: but let's try anyway that all of that three point
Speaker 1: two gigawatsop capacity comes online? How much of it? How much? Actually?
Speaker 1: How much compute does an AI company use? Like I said,
Speaker 1: open Ai ended twenty twenty five to two gig what's
Speaker 1: of capacity? And they apparently have nine hundred million weekly
Speaker 1: active users. I don't think there are any AI companies
Speaker 1: with even ten percent of that user base. But even
Speaker 1: if they were, open ai spent eight point six seven
Speaker 1: billion dollars on inference through the end of September. Who
Speaker 1: can afford to pay even ten percent of that a
Speaker 1: year or five percent? Yeah? In reality, open Ai is
Speaker 1: likely more indicative of the overall compute spend of the
Speaker 1: entire AI industry. As I've said, most companies are powered
Speaker 1: not by their own GPU driven models, but by renting
Speaker 1: them from model providers like open Ai. Themselves. Open Ai
Speaker 1: and and Thropic Spenter combined eleven point three to three
Speaker 1: billion dollars in compute on Zoro AWS, respectively through the
Speaker 1: first nine months of last year. And that's my own reporting,
Speaker 1: by the way, and as the two largest consumers of
Speaker 1: AI compute, Well, I'm a little worried. These things suggest
Speaker 1: two things. The market for AI compute is actually very
Speaker 1: very small. If you assume that Anthropics spent the same
Speaker 1: amount on Google Cloud as it did in AWS, that'd
Speaker 1: be about a total of five point three two billion dollars,
Speaker 1: and that Core Weaves revenue called it five billion dollars,
Speaker 1: most of which was open Ai via Microsoft or in video.
Speaker 1: That doesn't appear to be an AI compute market outside
Speaker 1: of servicing two companies. The other problem is the market
Speaker 1: for AI compute is not actually growing. In the last
Speaker 1: two years, no new major customers of AI compute have emerged.
Speaker 1: Every company that assigned a large compute deal has either
Speaker 1: been open Ai, Anthropic or a hyperscaler. Even if Cursor
Speaker 1: and AI Coding Company were to dump its entire two
Speaker 1: point three billion dollars into funding AI compute, that would
Speaker 1: still not be very much. In fact, it would take
Speaker 1: sinking every single dollar of venture capital over two hundred
Speaker 1: billion dollars every single year, and then some funneled into
Speaker 1: AI compute just to produce the revenue to justify these
Speaker 1: deals existence. In the space of a year, Microsoft Zure
Speaker 1: made seventy five billion dollars, Google Cloud forty three billion dollars,
Speaker 1: and Amazon Web Services one hundred billion dollars. Now that
Speaker 1: is just add those numbers together, it's a little over
Speaker 1: two hundred billion dollars, and that's the three largest providers
Speaker 1: of any kind of compute, not just AI compute. Most
Speaker 1: of that is not AI compute. In fact, they barely
Speaker 1: make anything on that. They won't even talk about. The
Speaker 1: AI revenue is probably because they're so stinky. Well, if
Speaker 1: you need more proof, If you still don't believe me,
Speaker 1: skip to page eighteen of Nvidia's most recent earnings and
Speaker 1: I quote multi year cloud service agreement commitments as of
Speaker 1: October twenty six, twenty twenty five, were twenty six billion dollars,
Speaker 1: for which one billion dollars, six billion dollars, six billion dollars,
Speaker 1: five billion dollars, four billion dollars, and four billion dollars
Speaker 1: will we paid in fiscal years twenty twenty six, fourth quarter,
Speaker 1: twenty twenty seven, twenty twenty eight, twenty twenty nine, twenty
Speaker 1: thirty and twenty thirty one and thereafter respectively. Now I
Speaker 1: know that was confusing, but just to line that up,
Speaker 1: that means in fiscal year twenty twenty seven, which begins Oh,
Speaker 1: I would have to look that up. Yeah, I'm literally
Speaker 1: doing this on the air, and I'm gonna shit. So
Speaker 1: their fiscal year begins in February, So basically twenty twenty
Speaker 1: seven begins this February twenty twenty six. So they're going
Speaker 1: to be spending six billion dollars on AI compute in
Speaker 1: twenty twenty seven. This is a company that does not
Speaker 1: rent out compute. If there's such incredible surging demand, why
Speaker 1: is it? Why exactly is in Vidia spending six billion
Speaker 1: fucking dollars a year in twenty twenty six and twenty
Speaker 1: twenty seven on it. In Vidia doesn't need compute, it
Speaker 1: just shut down. It's Amazon Web Services. Compared to those
Speaker 1: it's called DJX cloud. It looks far more like in
Speaker 1: video is propping up an industry with non existent demand.
Speaker 1: I'm afraid there is no secret Amazon Web Services size
Speaker 1: spend waiting in the wings for the right moment to pounce.
Speaker 1: There is no secret demand wave, nor is there any
Speaker 1: capacity crunch that is holding back incredible swarths of revenue oracles.
Speaker 1: Five hundred and twenty three billion dollars in remaining performance
Speaker 1: obligations are made up of OpenAI meta and you'll never
Speaker 1: guess who in video fucking in VideA. The AI bubble
Speaker 1: is just in Vidia being handed money and then handing
Speaker 1: it to people. They're very profitable as well. They do
Speaker 1: grame everyone else not so much. For AI data center
Speaker 1: deals to make sense, most startups would have to start
Speaker 1: becoming direct users of AI compute while also spending more
Speaker 1: on cloud compute services than they've ever spent. The largest
Speaker 1: consumers of AI compute are both unprofitable unsustainable monstrosities dependent
Speaker 1: on venture capital. Eventually, reality will dawn on one or
Speaker 1: more of these banks. Projects will get delayed thanks to
Speaker 1: weather or budgetary issues, or when customers walk away, as
Speaker 1: just happened to a data center ariit called FERMI, and
Speaker 1: loan payments will start going unpaid elsewhere. AI startups will
Speaker 1: start asking for money again and again, and for a
Speaker 1: while they'll keep raising until the evaluations get too high,
Speaker 1: or VC coffers get too low. You're probably going to
Speaker 1: say at this point that Open AI or Anthropic might
Speaker 1: go public, which will infuse capital into the system, and
Speaker 1: I want to give you a preview of what that
Speaker 1: might look like. Courtesy of AI Labs, Minimax, and Zipu,
Speaker 1: as reported by the Information which just filed to go Bubblica.
Speaker 1: I'm a little scared of These are the first real
Speaker 1: numbers about the AI BUBBLA. Hope, I'm not going to
Speaker 1: get embarrassed. Everybody's saying that behind the scenes these companies
Speaker 1: are secretly great. Let's take a look. Oh my god,
Speaker 1: these numbers aren't great at all. These numbers are terrible.
Speaker 1: In the first half of this of twenty twenty five,
Speaker 1: Zipu had a net loss of three hundred and thirty
Speaker 1: four million dollars on twenty seven million dollars of revenue. Meanwhile,
Speaker 1: Minimax made fifty three point four million dollars in revenue
Speaker 1: in the first nine months of twenty twenty five and
Speaker 1: bun two hundred and eleven million dollars to earn it.
Speaker 1: It's time to wake up. These are the real life
Speaker 1: costs of running an AI company, Open Ai and Anthropic
Speaker 1: are going to be even worse than this. This is
Speaker 1: why nobody wants to take AI company's public This is
Speaker 1: why nobody wants to talk about the actual costs of
Speaker 1: running AI. This is why nobody wants you to know
Speaker 1: the hourly cost of running a GPU, And this is
Speaker 1: why open Ai and Anthropic burn billions and billions of dollars.
Speaker 1: The margins fucking stink. Every product is unprofitable and none
Speaker 1: of these companies can afford their bills based on their
Speaker 1: actual cash flow. Generative AI is not a functional industry,
Speaker 1: and once the money works that out, everything burns. Though
Speaker 1: many AI data centers boast of having tendency agreements, remember
Speaker 1: these agreements are either with AI startups that will run
Speaker 1: out of money who really shouldn't be renting GPUs by
Speaker 1: the way, or hyperscalers with legal teams numbering in the thousands.
Speaker 1: Every single deal that Microsoft, Amazon, Meta, Googler, and Video
Speaker 1: signs is riddled withouts specifically hedging against this scenario, and
Speaker 1: there won't be a damn thing that anybody can do
Speaker 1: about it. If Hyperscalers decide to walk away before then,
Speaker 1: in Video's bubble is likely to burst. As I discussed
Speaker 1: a few weeks ago, and Vidia claims to have shipped
Speaker 1: six million Blackwell GPUs, and while it may be employing
Speaker 1: very dodgy maths claiming that each GPU is actually to
Speaker 1: chips Jensen Jensen, I've been saying. My modeling of its
Speaker 1: last three quarters suggests that in videos shipped around five
Speaker 1: point three to three gigawatts worth of GPUs, and based
Speaker 1: on reading about every single data center deal I can find,
Speaker 1: it doesn't appear that many have been built and powered on,
Speaker 1: or even started building in many cases. Worse still, in
Speaker 1: Video's diversified revenue is collapsing. In the first quarter of
Speaker 1: its fiscal year twenty twenty six, I'm sorry, you're just
Speaker 1: going to have to ride with me on this one,
Speaker 1: two customers represented sixteen percent and fourteen percent in revenue.
Speaker 1: In the second quarter of fiscal year twenty six, two
Speaker 1: customers represented twenty three percent and sixteen percent, and in
Speaker 1: the third quarter, four customers represented twenty two percent, fifteen percent,
Speaker 1: thirteen percent, and eleven percent of total revenue, with all
Speaker 1: of that money going towards GPUs or networking gear. In
Speaker 1: simpler terms, in Vidia's revenue is no longer coming from
Speaker 1: a diverse swarth of customers. In its first quarter fiscal
Speaker 1: year twenty twenty six, it had thirty point eight four
Speaker 1: billion dollars of diversified revenue. That's from a customer that
Speaker 1: from customers that do not number more than ten percent
Speaker 1: of its revenue, and in the second quarter of FY
Speaker 1: twenty six that was twenty eight point five billion Q three.
Speaker 1: It's twenty two point twenty three billion. In simpler terms,
Speaker 1: there are only a few companies that can buy GPUs,
Speaker 1: and other companies are no longer buying GPUs at the
Speaker 1: same rate. I doubt this number is going to increase.
Speaker 1: You see in video, GPUs are astronomically expensive four point
Speaker 1: five million dollars for a GB three hundred radc of
Speaker 1: seventy two B three hundred GPUs, for example, and feeling
Speaker 1: data centers full of them requires debt unless you're a hyperscaler. Well,
Speaker 1: I can't say for sure. I believe in videos, diversified
Speaker 1: revenue collapses a sign that smaller data center projects are
Speaker 1: starting to have issues getting funded and or hyperscalers are
Speaker 1: pulling back on the GPU purchases from those Taiwanese companies.
Speaker 1: I was mentioning, Now, let me look through the eyes
Speaker 1: of an AI boosted for a second. Okay, okay, everything
Speaker 1: is blue and yellow as usual. Okay. One might say
Speaker 1: that these big customers are covering the loss of revenue,
Speaker 1: but the reality is that these big projects are run
Speaker 1: on debt issued by banks are becoming increasingly worried about
Speaker 1: nobody paying them back. The mistake that every investor, commentator, analyst,
Speaker 1: and member of the media makes about Nvidia is believing
Speaker 1: that its sales are an expression of demand for AI compume,
Speaker 1: when in reality it's more of a statement about the
Speaker 1: availability of debt from banks in private credit. Similarly, the
Speaker 1: continued existence of AI startups is an expression of the
Speaker 1: desperation of venture capital and the continuing flow of massive
Speaker 1: funding rounds as assigned that they see no other revenues
Speaker 1: for growth and that their startups can't wipe their own assholes. Eventually,
Speaker 1: data centers are going to go unbuilt and data center
Speaker 1: debt packages will begin to fall apart. Remember, Oracle's thirty
Speaker 1: eight billion dollar data center deal is actually yet to close,
Speaker 1: much like Stargate New Mexico is yet to close, and
Speaker 1: much like Stargate Michigan is yet to close. These deals
Speaker 1: while seeming like they're trending positively, are all incredibly important
Speaker 1: to the future of the AI bubble, and any failure
Speaker 1: will spooken already notice mark them only one link in
Speaker 1: this chain of pain needs to break every single part
Speaker 1: of the AI bubble. This fucking charade is unprofitable save
Speaker 1: for in Video and the construction firms erecting future laser
Speaker 1: tag arenas full of negative margin GPUs tell me what
Speaker 1: happens if the debt stops flowing data centers? How will
Speaker 1: in Vidia sell their so called twenty million Blackwell and
Speaker 1: veried Ruben GPUs their claiming they'll ship by the end
Speaker 1: of twenty twenty six. What happens if venture capitalists start
Speaker 1: running low on funds and can't keep feeding hundreds of
Speaker 1: millions of dollars to AI startups so that they can
Speaker 1: feed them directly to open Ai or Anthropic. What happens
Speaker 1: to open Ai and Anthropic and they're already negative margin
Speaker 1: businesses when their customers can't pay them. What happens to
Speaker 1: Oracle or core weaves, work in progress data centers if
Speaker 1: open ai can't pay their bills? What happens to Anthropics?
Speaker 1: Twenty one billion dollars of Broadcom orders or tens of
Speaker 1: billions of dollars of Google cloud spend. And what if
Speaker 1: I'm right about everything I've said, not just in this series,
Speaker 1: but in the episodes and newsletters before him. In the
Speaker 1: last year, I estimate I've been asked the question what
Speaker 1: if You're wrong? Over twenty five times. Every single time
Speaker 1: the question comes with this undercurrent venom, the suggestion that
Speaker 1: I'm being an asshole for daring to question the wondrous
Speaker 1: AI bubble. Every single person who's asked me this has
Speaker 1: been poorly read, both in terms of my work and
Speaker 1: the surrounding economics and technological possibilities of large language models
Speaker 1: and believes they're defending technology, when in reality they're defending
Speaker 1: growth in the rock economy's growth at all cost mindset.
Speaker 1: In many cases, they are not excited about technology at all,
Speaker 1: but the prospects of being the first in line to
Speaker 1: lick an already sparkling boot. This has never ever been
Speaker 1: about progress or productivity. If it was, we'd seen actual
Speaker 1: progress or productivity boosts. So anything other than the frothiest debt,
Speaker 1: the frothiest venture capital markets, and the most annoying and
Speaker 1: incorrect headlines I've ever read in the news. Large language
Speaker 1: models do not create novel concepts. They are inconsistent and unreliable,
Speaker 1: and even the things that people like them for, like
Speaker 1: coding very wildly thanks to the dramatic very tents of
Speaker 1: a giant probability machine l alams, are not good enough
Speaker 1: for people to pay regular software prices at any scale,
Speaker 1: and the consequences of this will be that every single
Speaker 1: dollar spent on GPUs has been for exactly one point
Speaker 1: manipulating the value of stocks by making hyperscalers look good
Speaker 1: so that they can keep pretending that they create anything.
Speaker 1: AI does not have the business returns and may indeed
Speaker 1: have negative gross margins across the board. It is inconsistent, ugly, unreliable,
Speaker 1: expensive and environmentally ruinous, pissing off a large chunk of consumers,
Speaker 1: and underwhelming most of the rest, other than those convinced
Speaker 1: they're smart for using it, or those who have resigned
Speaker 1: to giving up at the site of a confidence game
Speaker 1: sold by a tech industry that stopped making products primarily
Speaker 1: focused on solving the problems of consumers or businesses a
Speaker 1: long time ago. You may say I'm wrong because Google, Microsoft,
Speaker 1: Meta and Amazon continue to have healthy net revenues and
Speaker 1: revenue growth. And as I've previously said, these companies are
Speaker 1: not sharing AI revenues, and their existing businesses are still
Speaker 1: growing due to the massive monopolies they've built. And I
Speaker 1: want to plead to the AI boosters and bullish analysts alike,
Speaker 1: you are being had. Sacha Adela, Sam Altman, Dario Amade,
Speaker 1: Jensen Huang, Mark Zuckerberg, Larry Ellison, saffracats, Elon Musk, Klay mcguk,
Speaker 1: Mike Cecilia, Mike truell Aravincerivenus, all of them are laughing
Speaker 1: at you behind your back because they know that you're
Speaker 1: never going to ask the obvious questions that would defeat
Speaker 1: my arguments, and know that you will never ever push
Speaker 1: back on them. They know the truth, they just don't
Speaker 1: want to tell you because you don't care to argue.
Speaker 1: The inceritification of the share has the downstream effect of
Speaker 1: an intitification of the media and the Wall Street analysts
Speaker 1: writ large analysts media. These companies own you, they own
Speaker 1: your asses. They treat you with disdain and condescension because
Speaker 1: they know you'll let them. They know that no Cell
Speaker 1: side analysts will ever ask them when will you be profitable?
Speaker 1: Or how much you spending? Or if you do ask,
Speaker 1: they know you will experience temporary amnesia and forget whatever
Speaker 1: answer they give, because these are the incentives of an
Speaker 1: inshitified stock market, where stocks are not extrapolations of shareholder
Speaker 1: value but chips in a fucking casino where the house
Speaker 1: always wins and changes the rules every three months. These
Speaker 1: companies have changed the meaning of the word stock to
Speaker 1: mean whatever the market will reward, and when you allow
Speaker 1: companies to start dictating the terms of what will be rewarded.
Speaker 1: As neoliberalism, Freedman, Reagan, Nixon, NAFTA, and every other fucked
Speaker 1: up growth focused policy has orienting everything exclusively around growth,
Speaker 1: companies eventually cut off any powers that may curtail any
Speaker 1: reevaluation of the fundamental terms of capitalism and the incentives
Speaker 1: with him focusing on growth at all costs thinking naturally encourages, enables,
Speaker 1: and empowers grifters, because all they ever have to promise
Speaker 1: is more more users, more debt, more venture, more features,
Speaker 1: more everything forever. From Adam Becker by it Today, the
Speaker 1: very institutions that are meant to hold companies accountable. Analysts
Speaker 1: and the media are far more desperate to trade scoops
Speaker 1: for interviews, to pull punches, to find ways to explain
Speaker 1: why a company is right, rather than understand what the
Speaker 1: company is doing. And this is something pushed not by
Speaker 1: writers but by editors that want to make sure they
Speaker 1: stay on the right side of the largest companies. And goddamn,
Speaker 1: do I know a few stories there that one day
Speaker 1: I might even tell. And if I'm right, open AI's
Speaker 1: death will kill off most, if not all, AI startups
Speaker 1: Anthropic included. Every investor that invested in AI will take
Speaker 1: massive losses. Every startup that builds on the back of
Speaker 1: their models will see their companies fold if it hasn't
Speaker 1: already done so to the massive costs an upcoming price
Speaker 1: increase we've already seen signs of with priority processing with
Speaker 1: both Anthropic and open Ai in the middle of last year.
Speaker 1: The majority of GPU based data centers, which really have
Speaker 1: no other revenue stream, will be left inert, likely powered down,
Speaker 1: waiting for the day that someone works it all out,
Speaker 1: which they won't because literally everybody has these things now,
Speaker 1: and I truly believe they've tried everything. And I'm gonna
Speaker 1: hear from someone that says us, just like the Duck combo,
Speaker 1: they're fiber optic cable. We had so much fiber optic
Speaker 1: cable and then we put internet in them. This is
Speaker 1: not GPUs are not fiber optic cable. They're not I
Speaker 1: just did a premium piece on this. I'm probably going
Speaker 1: to have to do an episode on it. But they
Speaker 1: are not the same fucking thing. And people that keep
Speaker 1: saying this are flippant about the damage that's going to
Speaker 1: be caused and just flat out wrong. I really do
Speaker 1: challenge you to actually read history before you make any
Speaker 1: fucking statements like that. This is not for the people
Speaker 1: who are saying this just because they haven't looked and
Speaker 1: they just assumed that the world wouldn't be stupid. I
Speaker 1: don't think many people saying that or off that camp.
Speaker 1: I think they are people that come up with comfortable
Speaker 1: reasons to validate bad behavior. And I must be clear,
Speaker 1: I'm watching I'm watching everyone. I'm watching how everyone handles this,
Speaker 1: and I'm going to be watching extra hard on the
Speaker 1: way down because anybody who has been a booster that
Speaker 1: tries to change their target and tries to change their
Speaker 1: direction without a direct acceptance and real contrition about their role.
Speaker 1: I have taken such detailed notes, but I will add something.
Speaker 1: I don't hate on AI because I'm a hater. I
Speaker 1: hate on it because it fucking sucks. And what I'm
Speaker 1: worried about happening seems to be happening. The tech industry
Speaker 1: has run out of hypergrowth ideas, and in its desperation,
Speaker 1: hitched itself to the least profitable hardware and software in history.
Speaker 1: Then spent three straight years lying about what was possible
Speaker 1: to the media, alice, and shareholders. And they were allowed
Speaker 1: to lie because everybody lapped it the fuck up. They
Speaker 1: didn't need to worry about convincing Anybodyncers, editors, analysts, and
Speaker 1: investors were already drafting reasons why they were so excited
Speaker 1: about something they didn't really understand or believe in, other
Speaker 1: than the fact it promised more. This is what happens
Speaker 1: when you make everything about growth. Everybody becomes stupid, ready
Speaker 1: to be conned, ready to hear what the next big
Speaker 1: growth thing is because asking nasty questions gets your fucking fired.
Speaker 1: And what's left is a tech industry that doesn't build
Speaker 1: technology but growth focused startups. Look at silicon value. Do
Speaker 1: you see these fucking people ever building a new kind
Speaker 1: of computer? Do you believe these men are fit to
Speaker 1: even imagine a future? These men care about the status quo.
Speaker 1: They want to always have more software to sell in
Speaker 1: what or ways to increase advertising revenue so that the
Speaker 1: stock number goes up, so they receive more money in
Speaker 1: the form of stock compensation. They are concerned with neither
Speaker 1: actual business value on this exchange of value or societal value.
Speaker 1: Their existence is only in shareholder value, which is how
Speaker 1: they are incentivized by their board of directors. And right
Speaker 1: now they're in shitifying being a shareholder. But really, if
Speaker 1: you're still defending AI, does it matter to any of
Speaker 1: you that this software fucking sucks? If you think it's good,
Speaker 1: you don't know much about software. Sure, your coding tool
Speaker 1: is useful in whatever way it can fart out and
Speaker 1: language simula or whatever. Oh, it can do some of
Speaker 1: the easy coding things. I'm sorry, I'm sorry, man, I
Speaker 1: can't get excited about that. We're hundreds of billions of
Speaker 1: dollars in the hole. I need something more than that.
Speaker 1: I need so much more than that. And if I'm honest,
Speaker 1: the problem with large language models, it's not good software.
Speaker 1: It doesn't respond precisely at any point to a user
Speaker 1: or a programmers intent. That's bad software. And I don't
Speaker 1: care that you've heard developers really like it, because that
Speaker 1: doesn't fix the underlying economic and social poison in AI.
Speaker 1: I don't care that it's sort of replaced search for you.
Speaker 1: I don't care if you know a team of engineers
Speaker 1: that use it. Every single AI app is subsidized. Its
Speaker 1: price is fake. You are being laid to, and none
Speaker 1: of this is real. I also, and this is a
Speaker 1: side a little bit of a side quest, I think
Speaker 1: AI psychosis is so much bigger than people think. I
Speaker 1: feel like I might have mentioned this on the recent monologue,
Speaker 1: but it's just it's really bothering me. I think there
Speaker 1: is something that happens when you play with these things
Speaker 1: and you make them work, versus just being like, oh,
Speaker 1: they don't work. I think what happens is it convinces
Speaker 1: you you're smart, when what you really are is being
Speaker 1: a slave to the software yourself. You are being tricked.
Speaker 1: You are being convinced that the software is doing something
Speaker 1: because you are bonking it on the head until it
Speaker 1: does something you need it to. Really, none of this
Speaker 1: is real, none of it. I'm so scared. I'm so
Speaker 1: scared because on one hand, I kind of look like
Speaker 1: I'm about to be proven right in a way that's
Speaker 1: going to be good for business, I guess. But being
Speaker 1: right here means watching something really calamitous and when the
Speaker 1: collapse happens. Do not let a single person that waved
Speaker 1: off the economics have a moment's piece. Do not let
Speaker 1: anybody who sat in front of Dario Amadey or Sam
Speaker 1: Ortman such as I don't know on a New York
Speaker 1: Times podcast and squealed with delight at whatever vacuous talking
Speaker 1: points they burped out. Forget that they didn't push them,
Speaker 1: They didn't ask the hard questions. They didn't worry or
Speaker 1: wonder or feel any concerns for investors of the general public.
Speaker 1: They only cared about getting rock hard listening to whatever
Speaker 1: bullshit the latest large Language model asshole has to say.
Speaker 1: Do not let a single analyst that called AI skeptics, loodites,
Speaker 1: Daniel Newman futuream group, or equate them to flat earthers
Speaker 1: hear the end of it. Do not let anybody who
Speaker 1: claimed that we lost control of AI or that it
Speaker 1: blackmailed developers go without their complimentary fell for it again, badge,
Speaker 1: because no, these systems didn't blackmail anyone, they were literally
Speaker 1: being prompted to do it. You fell for it, and
Speaker 1: you will You'll No one is ever going to hear
Speaker 1: the end of this from me, And when it happens,
Speaker 1: I promise I won't be too insufferable, but I will
Speaker 1: be calling for accountability for anybody who boosted AI twenty
Speaker 1: twenty seven, who sat in front of Sam Ortman of
Speaker 1: Dariyama Day and once again refused to ask real questions
Speaker 1: or allowed bullshit answers, And for anyone anyone who collected
Speaker 1: anything resembling detailed notes about me or any other AI
Speaker 1: skeptic threatening independent reporters because I didn't clap for Daddy's
Speaker 1: venture capital. Bullshit is insufferable, poisonous, and will never ever
Speaker 1: be forgotten. And if you think I'm talking about you,
Speaker 1: I probably am. And I have a question. Why didn't
Speaker 1: you approach the AI companies with as much skepticism as
Speaker 1: you did the skeptics. Why were you so concerned about
Speaker 1: minor details when you could have cared about the major
Speaker 1: details that will very likely fuck our markets up lead
Speaker 1: to an apocalyptic state of venture capital and startups, and genuinely,
Speaker 1: I don't even know if a recession will be it.
Speaker 1: I also genuinely promise you if I'm wrong, I'll happily
Speaker 1: explain how and why, and I'll do so at length
Speaker 1: to I'll have links, I'll have citations, I'll do podcast episodes.
Speaker 1: I will make a good faith effort to explain every
Speaker 1: single failing because my concern is the truth and I
Speaker 1: would love everybody else to follow suit. Do you think
Speaker 1: any AI booster will have the same courtesy? Do you
Speaker 1: think they care about the truth or do they want
Speaker 1: their fish biscuit from Sam Ormon or Jensen Joan. It's
Speaker 1: absolutely pathetic, and as we enter into twenty twenty six,
Speaker 1: I'm going to fucking floor it with this stuff. I've
Speaker 1: taught myself a great deal about numbers in the last year.
Speaker 1: I've really got a good head for reading these ten cues,
Speaker 1: and there's already stuff I'm seeing that is spelling the
Speaker 1: end that I'm yet to talk about. This has been
Speaker 1: a long episode, and it's been a long four parter.
Speaker 1: I really hope you've enjoyed it, because I've loved reading it.
Speaker 1: More to come next week I'll be joined by mister
Speaker 1: Matt Rosoff, wonderful editor in chief over at the Register.
Speaker 1: We're going to talk about the dot com bubble. Just folks,
Speaker 1: hit me up on the round app, slub me on Goop.
Speaker 1: Thank you for listening to Better Offline. The editor and
Speaker 1: composer of the Better Offline theme song is Matasowski. You
Speaker 1: can check out more of his music and audio projects
Speaker 1: at Matasowski dot com, M A T T O S
Speaker 1: O W s ki dot com. You can email me
Speaker 1: at easy at Better Offline dot com or visit Better
Speaker 1: Offline dot com to find more podcast links and of
Speaker 1: course my newsletter. I also really recommend you go to
Speaker 1: chat dot Where's Youreed dot at to visit the discord,
Speaker 1: and go to our slash Better Offline to check out
Speaker 1: our reddit. Thank you so much for listening. Better Offline
Speaker 1: is a production of cool Zone Media. For more from
Speaker 1: cool Zone Media, visit our website cool Zonemedia dot com,
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Speaker 1: or wherever you get your podcasts.