Speaker 1: A media Hello, and welcome to Better Offline. I'm your
Speaker 1: host ed zich Tron. What as ever, please check the
Speaker 1: episode notes for links to the things that I'm talking
Speaker 1: about now. Frequent listeners know that I'm immensely skeptical of
Speaker 1: generative AI, both as a technology but also as a business.
Speaker 1: It's expensive, it's unreliable, it doesn't actually do that much,
Speaker 1: and the real world use cases range from kind of
Speaker 1: helpful to unhelpful to not really useful in any way,
Speaker 1: shape or form, and definitely not useful enough to justify
Speaker 1: hundreds of billions of dollars in spending. And I know
Speaker 1: somebody is gonna email and say, but ed, my mate's
Speaker 1: granny's uncle's dog uses chat GBT to brainstorm or something
Speaker 1: else equally flimsy. And I really need you to put
Speaker 1: all of this in context. Open AI loses five billion
Speaker 1: dollars a year, and basically every big tech company is
Speaker 1: blown past their emissions targets, with few signs that they'll
Speaker 1: ever bother to try and meet them again, all in
Speaker 1: pursuit of the piddliest or most convoluted use cases in history.
Speaker 1: It's a goddamn fast and that's why generative AI is
Speaker 1: such a regular topic on this show. I feel like
Speaker 1: the tech industry is experiencing a kind of collective madness,
Speaker 1: a delusion that's seeing companies like Microsoft and Google, but
Speaker 1: both their companies and our planet on a technology that
Speaker 1: continually fails to deliver on well anything I want to
Speaker 1: say here, And I actually wrote down this supposedly massive potential,
Speaker 1: but what was the potential? Ever? Can anyone actually tell
Speaker 1: me what this was meant to do? Other than agi? Anyway,
Speaker 1: Eventually I see this all falling apart, and I think
Speaker 1: there's going to be a clamorous event when everything does
Speaker 1: actually unravel. I return so often to Generative AI because
Speaker 1: I truly fear the damage that this confrontation will cause,
Speaker 1: and I'm concerned about the damage that's happening right now.
Speaker 1: If I'm honest, And while my tone's off in acerbic
Speaker 1: and I don't think you'd have it an any other way,
Speaker 1: I don't really take much joy in watching these things burn. Sure,
Speaker 1: I admit it's pretty funny thinking about satching a Delea
Speaker 1: getting fired or sunded up a shy getting fired, or
Speaker 1: both of them looking stupid, But it's not the same
Speaker 1: thing Miglee's kind of tempered. When I stop and think
Speaker 1: about what all of this means or will mean, I
Speaker 1: should say, for the companies trying to get funding right now,
Speaker 1: or for the companies that will try and raise money
Speaker 1: after the bubble bursts, and for the tech workers that
Speaker 1: will get laid off, either because Microsoft and Google want
Speaker 1: to put more money into data centers and GPUs, or
Speaker 1: because their generative AI bets have gone tits up and
Speaker 1: they need to save money some other way. And so
Speaker 1: I hope you'll forgive me for a somewhat more somber
Speaker 1: tone to this episode. I want to again make a
Speaker 1: clear headed analysis of where we are today and where
Speaker 1: I think we're going. And the reason I'm retreading this
Speaker 1: path is because over the last month or so, we've
Speaker 1: seen some really really alarming signs about the accelerating crisis
Speaker 1: in generative AI, whispers that the party will soon come
Speaker 1: to a halt. Now, you may remember a few episodes
Speaker 1: back that I started talking about pale horses of the
Speaker 1: AI apocalypse, signs that things were falling apart, like layoffs
Speaker 1: at AI companies, price increases or decreases, internal discord at
Speaker 1: these big AI companies, speciously impressive yet kind of flimsy
Speaker 1: product announcements and so on and so forth. Since then,
Speaker 1: I've kind of been proven right several times. Multiple pale
Speaker 1: horses have emerged. There was a big, stupid magic trick
Speaker 1: to impress investors in the form of open aised rush
Speaker 1: launch of its one and that model, by the way,
Speaker 1: was code named Strawberry. Rumored pricing increases which hat GBT
Speaker 1: in the future. Now they're looking at forty four dollars
Speaker 1: a month by twenty thirty, and they're looking at potentially
Speaker 1: thousands for models in the future, and then layoffs at
Speaker 1: Scale AI, which is one of the biggest players in
Speaker 1: AI training data, if not the biggest. And these are
Speaker 1: all signs that things are beginning to fall apart. And
Speaker 1: I think it's important to explain how precarious things are
Speaker 1: right now despite all of the money stashing around, and
Speaker 1: how dangerous the power of magical thinking really is. I
Speaker 1: want to express my concerns about the fragility of this
Speaker 1: movement and the obsessiveness and directionless that brought us here,
Speaker 1: and I want us all to kind of do better now.
Speaker 1: Don't mean you the listener, but if you remember the
Speaker 1: media that's written something vague about AI and you've kind
Speaker 1: of carried water for Sam Mortman. It is time to stop.
Speaker 1: It was already time to stop some time Aguary, I
Speaker 1: should just be clear, but now really is the time
Speaker 1: to stop. But this week's a two parter, and I'll
Speaker 1: be explaining things well in two parts. Obviously. First of all,
Speaker 1: we're going to talk about open ai, the most recent
Speaker 1: funding round, and how bad their business is and exactly
Speaker 1: how worried you should be about them now. The second
Speaker 1: part is going to be about something I'm calling the
Speaker 1: subprime AI crisis, where I see a growing bubble of
Speaker 1: companies integrating generative AI at prices well heavily subsidized by
Speaker 1: big tech and heavily discounted by companies like open ai
Speaker 1: and Anthropic. Should either of these companies get desperate or
Speaker 1: I don't know, actually want to make more money than
Speaker 1: they spend, they're inevitably going to have to raise the
Speaker 1: prices to match their actual costs, which will likely make
Speaker 1: the existence of many AI startups completely untenable. You know,
Speaker 1: kind of like when the teaser interest rates on subprime
Speaker 1: mortgages that expired during the Financial crisis, and people suddenly
Speaker 1: started losing their houses. In any case, these are going
Speaker 1: to be meaningful, yeah, kind of brutal episodes, in part
Speaker 1: because while it's enjoyable to watch big tech burn or
Speaker 1: get embarrassed, there's a real human cost, like I said,
Speaker 1: and the damage to our environment is already being done
Speaker 1: and might not even stop when Generative AI does. And
Speaker 1: whether Microsoft and Google and the other big generative AI
Speaker 1: backers slowly wind down their positions or cannibalize their companies
Speaker 1: to keep open AI and Anthropic alive, I'm convinced that
Speaker 1: the end result is still going to be the same.
Speaker 1: I fear tens of thousands of people will lose their
Speaker 1: jobs and much of the tech industry will suffer as
Speaker 1: they realize that the only thing that can grow forever
Speaker 1: is a cancer. I'm going to paint you oblique picture
Speaker 1: not just for the big AI players, but for tech
Speaker 1: more widely, and for the people to work at these companies,
Speaker 1: and tell you why I think the conclusion to this
Speaker 1: sordid saga, as brutal and damaging as it will be,
Speaker 1: is coming sooner than you think. Let's begin, as have
Speaker 1: explained in agonizing detail in the past in my newsletter
Speaker 1: Open AI will have to continue to raise more money
Speaker 1: than any startup has ever raised in history, in perpetuity
Speaker 1: just to survive. They're going to burn five billion dollars
Speaker 1: this year, and yes, that's after they make their revenue
Speaker 1: and costs are only set to increase over the next
Speaker 1: few years they develop bigger models. Their business as it
Speaker 1: stands is completely untenable, and I'm going to explain why
Speaker 1: in a bit. Nevertheless, that's why open Ai, the ostensible
Speaker 1: nonprofit that may soon become a for profit who bloody
Speaker 1: knows at this point, raise the funding round at evaluation
Speaker 1: of one hundred and fifty seven billion dollars, bringing in
Speaker 1: a reported six point six billion dollars in cash, along
Speaker 1: with opening a four billion dollar revolving credit line from
Speaker 1: banks like JP morgan See and a bunch of others
Speaker 1: that should know better after the acquisition of Twitter. Investors
Speaker 1: in the funding ground included Josh Kushner's Thrive Capital in
Speaker 1: Video and of course Microsoft, who were somehow undeterred by
Speaker 1: the abrupt exiffs open ai cto mirror Marati days before
Speaker 1: the round closed. Also joining the frame was soft Bank,
Speaker 1: the Japanese investment company with a drag record of making
Speaker 1: some of the worst bets in history, and they dumped
Speaker 1: five hundred million dollars into open Ai, and that alone
Speaker 1: should start getting people a little worried. You see, soft
Speaker 1: Bank's founder, Masayoshi Son is what we in the business
Speaker 1: call the dumbass. I realized this is a very broad
Speaker 1: brush to paint somebody with. But let me explain. Soft
Speaker 1: Bank's vision fund dumped sixteen billion dollars into we Work,
Speaker 1: which by the end of last year, by the way,
Speaker 1: was worth forty four million dollars, and nearly a billion
Speaker 1: dollars into wire Card, which turned out to be an
Speaker 1: elaborate fraud. With its leadership. Are the facing criminal charges
Speaker 1: or becoming fugitives from justice in Russia. Soft Bank has
Speaker 1: become effective synonymous with burning cash on terrible bets and
Speaker 1: lost over thirty two billion dollars in the last three years.
Speaker 1: The problem that open Ai faces is that they need
Speaker 1: an absolute shit ton of money, and generally the only
Speaker 1: companies that need that much are the ones that may
Speaker 1: not have a sustainable business model. Open Ai demanded a
Speaker 1: minimum investment of two hundred and fifty million dollars from investors,
Speaker 1: and while regular American vcs might have that much, and
Speaker 1: indeed had in the case of Costler and Kochume Management,
Speaker 1: there aren't enough of them to fill out a six
Speaker 1: point six billion dollar funding round. And because open Ai
Speaker 1: needed that much, not wanted needed, their only real choices
Speaker 1: were to go to Masayoshi Son, who's a man who
Speaker 1: put tons of money into stupid things and believes he
Speaker 1: was put on this earth to make digital superintelligence and
Speaker 1: I have a link to that. By the way. It's insane,
Speaker 1: all I mean. There's also another choice, you know, the
Speaker 1: far dodgier investors in the Middle East m mg X,
Speaker 1: one hundred billion dollar investment fund backed by the United
Speaker 1: Arab Emirates to invest primarily in AI and semiconductor companies.
Speaker 1: This should also be a big warning sign that things
Speaker 1: are going poorly, because absolutely nobody raises from the UAE
Speaker 1: of the SuDS because they want to. They're the place
Speaker 1: you go if you need a lot of money and
Speaker 1: you're not confident anybody else is going to give it
Speaker 1: to you. Other aspects of this deal are also a
Speaker 1: bit worrying, one of them being that one of the
Speaker 1: founding partners of MGX is the Sovereign Wealth Fund of
Speaker 1: Abu Dhabi, which brought in around five hundred million dollars
Speaker 1: into Anthropic in twenty twenty three. Kind of a conflict
Speaker 1: of interest. Do you think any of these people actually
Speaker 1: goddamn care though they're all working to the same rot economy.
Speaker 1: Nonsense fucking Anyway, as I mentioned previously, open Ai now
Speaker 1: has access to that four billion dollars in debt from
Speaker 1: banks in that revolving credit facility too, and that's also
Speaker 1: not brilliant for a company that just burns cash. I
Speaker 1: don't know what the interest rate on it is, but
Speaker 1: I can't imagine it's great. Generally, revolving credit lines are
Speaker 1: worse interest rates, So that's great, I guess. But open
Speaker 1: ai is desperate. Fundraising comes down to one one thing,
Speaker 1: one really obvious thing. They need so much money. They
Speaker 1: needed like ten billion dollars here, and they kind of
Speaker 1: got it in this wonky way. But they need that
Speaker 1: money to survive because, like I said, they lost five
Speaker 1: billion in twenty twenty four, and that figure is likely
Speaker 1: to increase as more complex models demand more compute and
Speaker 1: more training. Data and Anthropic CEO Dario ama Day predicted
Speaker 1: that future models may cost as much as one hundred
Speaker 1: billion dollars to train and open ai. By the way,
Speaker 1: they may have just raised the biggest round in history.
Speaker 1: They're going to have to raise another round again soon.
Speaker 1: And I'll explain why. While open ai succeeded here, it
Speaker 1: was only after a fairly arduous process where they'd already
Speaker 1: tried to raise a hundred billion dollar valuation earlier in
Speaker 1: the year, and that specifically turned off investors because of
Speaker 1: the huge price tag. And there's this, by the way,
Speaker 1: to quote the information, there's a growing concern over the
Speaker 1: overvaluation of generative AI companies. Oh you fucking think do
Speaker 1: you think that there's a concern here? Well, after this podcast,
Speaker 1: you're going to be really, really concerned. I guarantee anyway
Speaker 1: to get the round done, open ai committed to converting
Speaker 1: itself from a nonprofit to a for profit entity. Failure
Speaker 1: to do so within two years will see their funding
Speaker 1: converted into debt, which by the way, will be the
Speaker 1: kiss of death for a company that only ever loses money.
Speaker 1: The deal, per Reuter's, also includes provisions that would allow
Speaker 1: investors to adjust the valuation or claw back their investment
Speaker 1: should the transition from nonprofit to for profit fail. And
Speaker 1: I mean this is worrying because I don't think there's
Speaker 1: any historical precedence of a company, a nonprofit at least,
Speaker 1: that had this much money then converted. And what complicates
Speaker 1: that as well is converting a business of this scale
Speaker 1: from a nonprofit to a for profit. Well, it involves
Speaker 1: transferring assets, and because any assets previously donated to the
Speaker 1: public benefit, as Alexander Reed, partner at Baker Holsteller, is
Speaker 1: quote as saying The Wall Street Journal cannot be converted
Speaker 1: into a private benefit without compensating the public for the loss.
Speaker 1: Every asset, which includes things like patterns and other intellectual property,
Speaker 1: would have to be paid for. Well, it's hard to
Speaker 1: say for certain, it's likely this deal and the process
Speaker 1: of untangling open ai from its nonprofit beginnings is really
Speaker 1: only going to add to open AI's cash problem. And
Speaker 1: it's not like that was a good problem to deal
Speaker 1: with in the beginning. And now I will do a
Speaker 1: thorough review and analysis of open ai because I want
Speaker 1: you to see exactly how stupid things have become in
Speaker 1: the tech industry and how ridiculous all of this writing
Speaker 1: this boiled my blood, by the way, because when you
Speaker 1: see how lossy this company is, when you really ingest
Speaker 1: how bad open ai is and how stupid it is
Speaker 1: that we've let this happen, and we meaning the tech industry.
Speaker 1: You then will think on your own lives and be like, wow,
Speaker 1: you think I could pay my rent like late, or
Speaker 1: like ask a company to pay my rent because my
Speaker 1: job involves me just burning piles of cash. No, you
Speaker 1: wouldn't be able to lose money for a business. You
Speaker 1: and I we have to operate normally, not sam Oltman,
Speaker 1: though sam Oltman doesn't have to be normal. Sam Altman,
Speaker 1: like all of the gilded assholes of the tech industry,
Speaker 1: is allowed to live in this fantasy land based on
Speaker 1: marketing high Now, before we go into it, though, I'd
Speaker 1: like to enjoy one of the following lovingly crafted advertisements
Speaker 1: that in no way seem out of place from anything
Speaker 1: I'm saying. And we're back, So to put it bluntly,
Speaker 1: open ai is an absolute dog of a company. On
Speaker 1: September twenty seventh, The New York Times reported that open
Speaker 1: ai would lose five billion dollars in twenty twenty four,
Speaker 1: a number which the Information had estimated back in July,
Speaker 1: and the open Ai expected to raise the price of
Speaker 1: chat GPT plus its premium product to twenty two dollars
Speaker 1: a month by the end of twenty twenty four and
Speaker 1: are remarkable forty four dollars a month by twenty thirty. Interestingly,
Speaker 1: and worryingly, the Times also confirmed another hypothesis of mine
Speaker 1: that and I quote fundraising material also signaled that open
Speaker 1: ai would need to continue to raise money over the
Speaker 1: next year because its expenses grew in tandem with the
Speaker 1: number of people using its products. In simpler terms, open
Speaker 1: ai may have raised six point five or six point
Speaker 1: six billion in funding literally a week ago, but they
Speaker 1: need to raise more, probably the same amount or more
Speaker 1: I'm going to say, within the next six months. And
Speaker 1: The Times also reports that open ai is making internal
Speaker 1: revenue estimates I would describe as this is a technical term,
Speaker 1: absolutely fucking ridiculous. Open aiy's monthly revenue hit three hundred
Speaker 1: million dollars in August, and the company expects to make
Speaker 1: three point seven billion dollars this year. The company will,
Speaker 1: as mentioned, loose five billion dollars anyway, and I'm going
Speaker 1: to keep minding you of that. Yeah. Open ai says
Speaker 1: that it expects to make eleven point six billion dollars
Speaker 1: in twenty twenty five and an astonishing one hundred billion
Speaker 1: dollars by twenty twenty nine, a statement that is so
Speaker 1: egregious that I'm surprised it's not some kind of financial
Speaker 1: crime to say it. For some context, by the way,
Speaker 1: Microsoft makes about two hundred and fifty billion dollars a year,
Speaker 1: Google about three hundred billion dollars a year, and Apple
Speaker 1: about four hundred billion dollars a year. So yeah, I
Speaker 1: guess by twenty thirty that's how big open ai. Well
Speaker 1: you've well, you fucking talk. It drives me insane. And also,
Speaker 1: by the way, all of those companies make more money
Speaker 1: than they spend. Open ai, on the other hand, spends
Speaker 1: two dollars and thirty five cents to make one dollar.
Speaker 1: If you remember one thing from this podcast, it's that
Speaker 1: every dollar they make they have to spend two dollars
Speaker 1: and thirty five cents to get. It drives me insane. People,
Speaker 1: we don't have to live in these conditions. How do
Speaker 1: I do this? How do I get to burn money?
Speaker 1: What the no? Seriously, open ai loses money on every
Speaker 1: single transaction, every single time that somebody uses chet, GPT
Speaker 1: or plus or connects one of their models, and while
Speaker 1: it might make money selling premium subscriptions, I severely doubt
Speaker 1: those subscriptions are turning a profit and they I really
Speaker 1: do think losing money even on their power users. And
Speaker 1: as I'll get into the next episode, I believe there's
Speaker 1: also a SUBPRIMEI crisis brewing because open ai is API
Speaker 1: services which let people integrate their models into products, are
Speaker 1: currently priced to attract customers in scale, and increasing these
Speaker 1: prices to match the actual cost will likely make this
Speaker 1: product unsustainable for many businesses currently relying on these discount
Speaker 1: of rates, and that's if they have any usage. But
Speaker 1: I'll also get to that later. Now, if you anything
Speaker 1: like me, you have somebody who's told you that open
Speaker 1: ai is a growth business and that it will just
Speaker 1: turn the knob to make it self profitable, much like
Speaker 1: Amazon Web Services, which is Amazon's cloud computing product, did
Speaker 1: years ago. Now, I just want to be clear. If
Speaker 1: you're listening and you think that you're just wrong, you're
Speaker 1: just completely wrong. You live in a fancyland. Wake the
Speaker 1: fuck up. I'm sick and tired of hearing this crap.
Speaker 1: Open ai is nothing like Amazon Web Services. First of all,
Speaker 1: open ai owns none of its infrastructure as everything everything
Speaker 1: is run on Microsoft's as Your Cloud. Secondly, Microsoft, also
Speaker 1: as part of an open ai funding around from twenty nineteen,
Speaker 1: has full access to all of open AI's pre agi research,
Speaker 1: which is all of it, by the way, and full
Speaker 1: license to sell and integrate all of their technology. They
Speaker 1: have complete free reign over open aiy's intellectual property. Thirdly,
Speaker 1: Amazon Web Services did not immediately start with a deficit
Speaker 1: so great that it required raising more money than's ever
Speaker 1: been raised in the history of tech. Where still open
Speaker 1: AI's technology doesn't get cheaper as it scales. In fact,
Speaker 1: it does the opposite. This is not like other businesses.
Speaker 1: You want to compare this to stop saying this to people.
Speaker 1: It's ridiculous. And I know why people say this, and
Speaker 1: I am ranting, and you just have to forgive me.
Speaker 1: I know that people don't want to believe that this
Speaker 1: much money can be wrong. It can be. It is
Speaker 1: currently being wrong. You are watching and listening to it
Speaker 1: being wrong. This is not like Google Cloud. It is
Speaker 1: not like the early days of the Internet. It is
Speaker 1: not like Amazon Web Services. It's nothing like them at all.
Speaker 1: There is no historical example like this, not even Uber
Speaker 1: Uber at least had a business model. In the worst
Speaker 1: year of its life, Uber lost I think six point
Speaker 1: six billion dollars or something like that. So about one
Speaker 1: point six billion dollars in open ai lost in twenty
Speaker 1: twenty four. Right, you want to know what year that was?
Speaker 1: Twenty twenty the year when people couldn't go outside, and
Speaker 1: there are many years after they probably should have stayed indoors. Two,
Speaker 1: But that's a different podcast. The point I'm making is,
Speaker 1: if you've got a comfortable little thing in your soul
Speaker 1: that's saying this is just like things I've seen before,
Speaker 1: they'll turn it around. They absolutely And now I'm going
Speaker 1: to break down exactly how untenable open ai is with
Speaker 1: a few statements for starters. Open ai is trying to
Speaker 1: hit eleven point six billion dollars of revenue by the
Speaker 1: end of twenty twenty five, and to do that it
Speaker 1: will have to triple its revenue and its current cost
Speaker 1: of revenue, so two thirty five to make a dollar,
Speaker 1: open ai will spend twenty seven billion dollars to hit
Speaker 1: eleven point six billion dollars, even if open ai somehow
Speaker 1: harves their costs, and by the way, in the next
Speaker 1: year they're going to be building a brand new model,
Speaker 1: which will cost them an absolute shit ton of money.
Speaker 1: They will still lose two billion dollars in twenty twenty
Speaker 1: five to hit these revenues. However, I must be clear,
Speaker 1: these costs are going up. They need this company to
Speaker 1: grow by three hundred percent and the only way they're
Speaker 1: going to do that is by making a new model.
Speaker 1: And the only thing that's really growing at this company
Speaker 1: is they're free users, and those free users lose the
Speaker 1: money every single time they use it. And even if
Speaker 1: they added a two dollars price increase to chat GPT
Speaker 1: plus and a similar price on their business plans like
Speaker 1: teams and enterprise, these things aren't really going to significantly
Speaker 1: move the needle without also adding a bunch of growth
Speaker 1: on top. An open Aiy's latest GPT four model it
Speaker 1: cost them one hundred million dollars to train, and more
Speaker 1: complex models like the Orian one they're allegedly coming up
Speaker 1: with and I imagine oh one which will get to
Speaker 1: next episode, well, they're going to cost them an absolute
Speaker 1: shit ter more to build. And also, by the way,
Speaker 1: the information estimated back in July the open AI's training
Speaker 1: costs would be about three billion dollars in twenty twenty four.
Speaker 1: The costs are not coming down. People. Now here's another problem.
Speaker 1: Buzzy tech companies need exciting things to get investors in,
Speaker 1: customers jazzed and opening eye. Well, they haven't really had
Speaker 1: anything exciting or truly important since the launch of GPT
Speaker 1: three point five, and even their latest reasoning model, like
Speaker 1: I said, I'll get to it next episode, it's not
Speaker 1: been particularly impressive. That model, by the way, is much
Speaker 1: more expensive to run and uses something called chain of
Speaker 1: thought reasoning, which I'll get into. But nevertheless, it takes
Speaker 1: more power to run because they're doing way more calculations
Speaker 1: and they didn't even have a use case when they
Speaker 1: announced it. What is going on with this company? But
Speaker 1: putting that aside, open AI's products are also becoming increasingly commoditized,
Speaker 1: with Google, Meta, Amazon, and even Microsoft building their own
Speaker 1: large language models and other models to compete. Where still
Speaker 1: these models are using effectively identical training data, which they're
Speaker 1: also running out of, which makes their outputs and by extension,
Speaker 1: the technology itself kind of similar. But most worrying of all,
Speaker 1: and I'm really going to drum on this one later.
Speaker 1: Open AI's cloud business, So the one where they connect
Speaker 1: their models to other businesses and then the businesses sell
Speaker 1: products to customers using those models technology. It's small, It's
Speaker 1: really small. It's small to the point that it suggests
Speaker 1: there's a fundamental weakness in the generative AI industry. It's
Speaker 1: extremely worrying that the biggest player in the game, oh
Speaker 1: only makes a billion dollars less than thirty percent of
Speaker 1: its revenue from selling access to its supposedly innovative technology.
Speaker 1: And fundamentally, I can't really find any compelling evidence that
Speaker 1: suggests that open ai is going to be able to
Speaker 1: sustain this growth. In fact, I really can't find any
Speaker 1: historical comparison for this company. And I also feel like
Speaker 1: open AI's growth is already stumbling. But if you don't
Speaker 1: want to stumble through life bereft of joy or growth
Speaker 1: or happiness, I really recommend you buy one of the
Speaker 1: following things. And if you can't buy it, download it.
Speaker 1: If you can't download it, go into a shop and
Speaker 1: demand that they start stocking it. And if they'll just
Speaker 1: give it to you, demand that you can give them money.
Speaker 1: Listen to the advertisers. All right, we're back, So for
Speaker 1: the next part of this episode, I'm going to begin
Speaker 1: to exactly how open ai makes money, which is going
Speaker 1: to require me to lay out its various businesses and products,
Speaker 1: and it's going to have a lot of numbers. Trust me,
Speaker 1: it's worth it, because this shit is insane. So, according
Speaker 1: to the New York Times, open ai expects chat GPT
Speaker 1: to make about two point seven billion dollars in revenue
Speaker 1: in twenty twenty four, with an additional billion dollars in
Speaker 1: revenue coming from other businesses using open AI's technology. Roughly
Speaker 1: seventy three percent, or two point seven billion dollars of
Speaker 1: open AI's revenue comes from selling premium versions of chat
Speaker 1: jupt called plus Teams and Enterprise. Chat Jupt Plus is
Speaker 1: marketed to individuals for twenty bucks a month, offering faster
Speaker 1: response times, priority, access to new features, and capability is
Speaker 1: not found in the free product, like image generation, which
Speaker 1: you can get in so many different other places. Importantly,
Speaker 1: open ai can use anything you'd do as training data
Speaker 1: unless you explicitly opt out. Open Ai also sells access
Speaker 1: to a team's product, which costs twenty five dollars a
Speaker 1: user a month if pay annually, so three hundred bucks
Speaker 1: a year per user and thirty dollars a user a month.
Speaker 1: If paid monthly from this point on, your date is
Speaker 1: excluded from that used to train open AI's models. By deform.
Speaker 1: Open ai sells enterprise subscriptions that include an expanded context
Speaker 1: window for longer prompts, meaning you can give more detailed instructions,
Speaker 1: admin controls, and enhance support an ongoing account management. It
Speaker 1: isn't clear how much this costs, but I found a
Speaker 1: Reddit thread from a year ago that suggests it's about
Speaker 1: sixty dollars a user a month, with a minimum of
Speaker 1: one hundred and fifty seats on an annual contract. I
Speaker 1: also believe open ai offers discounts for customers who buy
Speaker 1: in bulk very standard software as a service business model.
Speaker 1: A further billion dollars, or twenty seven percent of open
Speaker 1: AI's revenue comes from open ai licensing its models and
Speaker 1: services via its API. One thing you notice when you
Speaker 1: look at this price page is that there's this huge
Speaker 1: variety of models and APIs available, and that there's massive
Speaker 1: amounts of variation in pricing too. I look into these
Speaker 1: in depth in my newsletter, which by the way, is
Speaker 1: called open ai is a bad business and it's worth
Speaker 1: reading if you want to know, if not, just for
Speaker 1: the fact that the pricing in its various services is
Speaker 1: also super messy, but you don't need to know that
Speaker 1: right now. Open Ai also makes about two hundred million
Speaker 1: a year selling access to its models through its Microsoft
Speaker 1: according to Bloomberg, where open Ai takes a twenty percent
Speaker 1: cut of all revenue, and by the way, that's not
Speaker 1: on top of the billion. This means that open ai
Speaker 1: only makes about eight hundred million dollars a year by
Speaker 1: selling access to its API. That two hundred million is
Speaker 1: on top I want to add, how worrying this is
Speaker 1: both open Ai and the larger generative AI market. If
Speaker 1: open Ai, the most prominent name in all of generative ai,
Speaker 1: is only making a billion dollars a year from selling
Speaker 1: the shovels for the gold rush, what does that say
Speaker 1: about the growth trajectory for this company all the actual
Speaker 1: usage of generative AI products. That's the question for later
Speaker 1: in the show. The first let's talk dollars. So as
Speaker 1: it stands, open Ai makes the majority, like I said,
Speaker 1: more than seventy percent of its revenue from selling access
Speaker 1: to premium versions of chat GPT. A few weeks ago,
Speaker 1: the Information Report that chat gpt plus had more than
Speaker 1: ten million paying subscribers, and that it had one million
Speaker 1: more than we're paying for higher priced plans for business teams.
Speaker 1: As I've laid out previously, this means that open ai
Speaker 1: is making about two hundred dollars million dollars a month
Speaker 1: from consumer subscribers. But business teams is a very vague.
Speaker 1: It isn't obvious what it means. It could mean the
Speaker 1: team plan, it could mean the enterprise plan, and you
Speaker 1: may think, well ed, couldn't you be horribly wrong? Couldn't
Speaker 1: it be that they're actually ripping' they they got a
Speaker 1: million enterprise subscribers. Wouldn't that be good? Wrong? Oh? The
Speaker 1: New York Times has my back here. Based on their reporting,
Speaker 1: we can actually get a little more specific. Chat gpt
Speaker 1: plus is ten million customers, making open Ai around two
Speaker 1: point four billion dollars a year. As ten million users
Speaker 1: spending about twenty bucks a month, which equates two hundred million,
Speaker 1: might apply by twelve two point four billion dollars. Dad
Speaker 1: I swear I was listening in Mathson Times. This means,
Speaker 1: by the way, that business users make up about three
Speaker 1: hundred million dollars a year in revenue. Of twenty five
Speaker 1: million dollars a month, which isn't really great. While ten
Speaker 1: million paying customers might seem like a lot. Chat GPT
Speaker 1: is effectively to generative AI what Google is to search.
Speaker 1: Ten million people paying for this kind of table stakes,
Speaker 1: and the idea that this company can triple that number
Speaker 1: in a year is absolutely ridiculous. Open ai has been
Speaker 1: covered by effectively every media outlet in the world. It's
Speaker 1: mentioned in almost every single conversation about AI, even when
Speaker 1: it's not about generative AAI, and has the backing and
Speaker 1: marketing push of Microsoft and pretty much the entirety of
Speaker 1: Silicon Valley. Chat GPT has over two hundred million weekly users,
Speaker 1: and The New York Times reports that open ai has
Speaker 1: and I quote, three hundred and fifty million people using
Speaker 1: their services each month as of joom though it's unclear
Speaker 1: if that includes those using the API. I would guess
Speaker 1: that's chat GPT users collectively. This means that open ai,
Speaker 1: the most popular company in the industry, in the most
Speaker 1: prevalent industry in the industry, talked about to everyone and everywhere,
Speaker 1: can only convert about three percent of its free users
Speaker 1: into paying customers. Now, by the way, Eager listeners may go, well,
Speaker 1: three twenty percent conversion, that's not bad, right, right, wrong. Generally,
Speaker 1: free products don't cost this much to run. Chat GPT
Speaker 1: itself is extremely expensive. Whether it's free or whether it's premium,
Speaker 1: it's the same thing. So yeah, those three hundred and
Speaker 1: fifty million people, they're more of like a parasite than anything.
Speaker 1: The ninety seven percent who won't give them the credit card.
Speaker 1: It's not great. And I think that lack of conversion
Speaker 1: might be because chat GPT and chat GPT Plus are
Speaker 1: really similar products. Chat GPT Plus that you use the
Speaker 1: product more often and have access to numer models, but
Speaker 1: there's no obvious new thing you can do. As a result,
Speaker 1: you can't really upsell to plus unless you found someone
Speaker 1: who's already worked out the use case for themselves. And
Speaker 1: open Ai remains piss poor at actually marketing this product,
Speaker 1: mostly because of the limitations of what a large language
Speaker 1: model can do. As a result, most people diddling with
Speaker 1: chat GBT will get what they need to out the
Speaker 1: free version. I'd also argue that those willing to pay
Speaker 1: for a Plus subscription are more likely to use the
Speaker 1: platform way way more than free users, and because every
Speaker 1: prompt on chat, GBT loses the company money. It's reasonable
Speaker 1: to believe that paying users would be far more of
Speaker 1: a burden on the system. While there's a chance to
Speaker 1: open an eye, could have a chunk of users that
Speaker 1: aren't particularly active. One cannot run a business based on
Speaker 1: selling stuff you hope that people won't use. And no, no,
Speaker 1: it's nothing like a gym or insurance. Stop it. When
Speaker 1: I wrote the newsletter and I said that, I got
Speaker 1: so many people who thought they were the cleverest people
Speaker 1: at all school. Oh, it's like a gym. It's like, sure,
Speaker 1: it's not the same. Stop it. You're not clever. No
Speaker 1: one's impressed, And I should be clear. There's also a
Speaker 1: reason why enterprise customers are generally more desirable than private individuals.
Speaker 1: As with any other consumer centric subscription product, regular customers
Speaker 1: are far more likely to cut their spending when they
Speaker 1: don't feel like they're getting value from the product, or
Speaker 1: when the household budget demands it, or there's economic problems.
Speaker 1: Just look at Netflix. They were the biggest name while
Speaker 1: they still are the biggest name in streaming, and they
Speaker 1: lost a million customers in twenty twenty two because of
Speaker 1: the cost of living crisis. These are real things that
Speaker 1: will happen to open ai if they're not already happening.
Speaker 1: Chat GPT plus is likely for many people, kind of
Speaker 1: a lifestyle product, and the problem is that when people
Speaker 1: lose their jobs, or inflation hikes happen, or cheaper things
Speaker 1: come along that do much the same thing, these products
Speaker 1: are the first to get slashed from the budget. And
Speaker 1: that's before any arbitrary or silly or desperate price increase
Speaker 1: is done by a company that isn't the good business. Honestly,
Speaker 1: it's kind of remarkable that open ai found ten million
Speaker 1: people to actually pay for chat gpt, But how do
Speaker 1: you grow that to twenty million or forty million people.
Speaker 1: I think they need like thirty million by the end
Speaker 1: of twenty twenty five. How does that happen? Very worrying anyway.
Speaker 1: At present, open ai makes about two hundred and twenty
Speaker 1: five million dollars a month. That's two point seven billion
Speaker 1: a year. By selling these premium subscriptions. To hit eleven
Speaker 1: point six billion dollars in twenty twenty five, open ai
Speaker 1: would have to increase revenue from chat GPT customers by
Speaker 1: three hundred and ten percent. If we consider and forgive me.
Speaker 1: I'm going to do some maths at you. The current
Speaker 1: ratio of plus subscriptions, the teams and enterprise subscriptions that
Speaker 1: eighty eight point eight nine percent is GPT plus versus
Speaker 1: the business ones at eleven point eleven percent. Open Ai
Speaker 1: would need to find eighteen point two nine million paying users,
Speaker 1: and that's at the new price point of twenty two
Speaker 1: bucks a month, while also retaining every single one of
Speaker 1: the current subscribers to Chat GPT plus, who would also
Speaker 1: need to renew at the same price point to hit
Speaker 1: seven point four billion dollars or about six hundred and
Speaker 1: sixteen million dollars a month. It would also have to
Speaker 1: make an additional nine hundred and thirty three million dollars
Speaker 1: in revenue from its business or enterprice clients, which again
Speaker 1: would require open Ai to more than triple their users
Speaker 1: and retain the current ones to triple these users. To
Speaker 1: actually do this, Chat GPT has to meaningfully change, It
Speaker 1: has to do so soon, or disclose multiple meaningful, powerful
Speaker 1: use cases that are so impressive that eighteen million new
Speaker 1: people agreed to give them twenty two dollars a month.
Speaker 1: That's an incredible, and I would say insane goal and
Speaker 1: one that I do not think this company is capable
Speaker 1: of achieving. It would require making chat GPT something far
Speaker 1: more compelling than it already is, in ways that I
Speaker 1: can't even imagine. Just as the company lost multiple members
Speaker 1: of its senior leadership team, it doesn't look good. There
Speaker 1: needs to be a meaningful change. Now. I know I've
Speaker 1: already given you a lot of worrying things about open
Speaker 1: aiye about their very top heavy, subscription driven business, Why
Speaker 1: it isn't going to grow, why they need to grow
Speaker 1: it to grow faster than any one's ever grown, why
Speaker 1: they need to stop losing so much money. But there's
Speaker 1: something else to be worried about. There's something even flimsier
Speaker 1: about this business, and it's actually something that's disastrous. It's disastrous.
Speaker 1: I'm serious. It is simply disastrous. How little of open
Speaker 1: AI's revenue comes from providing other companies that means to
Speaker 1: integrate generative AI into their systems. It is astonishingly bad.
Speaker 1: I cannot be clear enough here. Before I wrote this script,
Speaker 1: before I wrote the newsletter that led to it, I believed,
Speaker 1: in my heart of hearts that how OpenAI made their
Speaker 1: money was from providing access to their models. That makes sense, right,
Speaker 1: because this company's talked about everywhere. Their technology is meant
Speaker 1: to be innovative. Everyone's meant to use it, right, that
Speaker 1: makes sense. Surely most of their money would come from
Speaker 1: people getting in on the revolution and then integrating the
Speaker 1: revolution into their products, and then people using the revolutionary thing. Right. Wrong.
Speaker 1: First of all, if open ai only makes a billion
Speaker 1: dollars a year selling API access and thus let you
Speaker 1: integrate the models into your products, it suggests that even
Speaker 1: the biggest company in generative ai cannot find enough customers
Speaker 1: to make its business viable. Secondly, it's yes, there's a
Speaker 1: remarkably small amount of demand for GENERATIVEAI integrations. Or consider
Speaker 1: another way that the companies connecting to open ai aren't
Speaker 1: really making it very much money at all. If the
Speaker 1: GENERATIVEAI revolution were really here, surely open ai, the household
Speaker 1: name in large language models, would be rolling in cash
Speaker 1: from their ABI business, not leaving it at less than
Speaker 1: thirty percent of their and your revenue. This isn't the case.
Speaker 1: It's so strange. So at the twenty twenty four open
Speaker 1: Ai Dev Day event, it's developer conference, which took place
Speaker 1: in October, first, the company said that over three million
Speaker 1: developers are building apps using open AI's infrastructure. That works
Speaker 1: out to about three hundred and thirty three dollars a developer,
Speaker 1: and that's far less money than other companies which make
Speaker 1: money by providing a service through their API actually make. Twilio,
Speaker 1: a company that makes its money sending SMS, messages and
Speaker 1: push notifications for companies, over the past quarter, made about
Speaker 1: a billion dollars in revenue. That's what OpenAI made from
Speaker 1: renting out its models and APIs over the past year.
Speaker 1: Twilio also made roughly four billion dollars over the last
Speaker 1: four quarters, which is more than open AI's projected revenue
Speaker 1: for the entirety of twenty twenty four. As I mentioned before,
Speaker 1: open ai makes two hundred million dollars of its one
Speaker 1: billion dollar revenue from Microsoft reselling its models a twenty
Speaker 1: percent cut. That suggests that Microsoft two is making about
Speaker 1: a billion dollars from open aised models. So in the
Speaker 1: event that open ai and Microsoft are making about a
Speaker 1: billion dollars in annualized revenue by providing access to open
Speaker 1: AI's models. Again, these are estimates based on current growth trajectories.
Speaker 1: It suggests that there's only two billion dollars in annual
Speaker 1: revenue coming from both of these companies combined, and that's
Speaker 1: without wait is open ai making less money from open
Speaker 1: AI's models than Microsoft is. Oh my god, this business
Speaker 1: is a stinker. And this also suggests that generative AI
Speaker 1: as a technology doesn't have a product market fit. According
Speaker 1: to a survey by Andrews and Hory It's a VC
Speaker 1: earlier in the year and I quote, the twenty twenty
Speaker 1: three market share of closed source models was estimated at
Speaker 1: eighty to ninety percent, with the majority of that share
Speaker 1: going to open ai and open source ones would include
Speaker 1: things like metas Lama model, which is kind of open source.
Speaker 1: That's a whole other thing anyway. Another survey from IoT
Speaker 1: Analytics published late last year suggested that the number might
Speaker 1: look a little different, with thirty nine percent of the
Speaker 1: market share going to open Ai and thirty percent going
Speaker 1: to Microsoft. Assuming that the latter numbers are true or
Speaker 1: even close to true, this suggests that the generative AI
Speaker 1: market is really small. If open Ai, which dominates with
Speaker 1: I'd wager about thirty percent of the market, is only
Speaker 1: making a billion dollars a year from selling access to
Speaker 1: its models at this stage. In this massive hype bubble.
Speaker 1: There might not even be ten billion dollars of annual
Speaker 1: revenue from companies integrating generative AI into their products. That's tiny,
Speaker 1: and this should be where all the money is. If
Speaker 1: this stuff is the future of everything, why is the
Speaker 1: revenue stream so painfully weak. Open ai is making so
Speaker 1: little selling access to their models, and it suggests that
Speaker 1: despite this hype cycle, there either is an interest in
Speaker 1: integrating these products from developers, or when these integrations are
Speaker 1: actually in there, consumers aren't really into them or using them. Remember,
Speaker 1: these products are charged on usage, and so it's possible
Speaker 1: for generative AI to be integrated into a service but
Speaker 1: not actually drive much revenue for open Ai as a
Speaker 1: result of users not really caring. While chat gpt as
Speaker 1: brand recognition, companies integrating open AI's models into their products
Speaker 1: are far more indicative of the long term health of
Speaker 1: both the company and the industry itself. Because if open
Speaker 1: ai can't convince people to integrate and use this shit,
Speaker 1: do you think others are succeeding? I mean, think about it.
Speaker 1: Where have you seen some weird chatbot up here in
Speaker 1: your life? Where have you seen an LM poked into
Speaker 1: something you use? Have you been like, oh good, I
Speaker 1: can't wait, or have you just kind of tried to
Speaker 1: ignore it. Maybe you've interfaced with it. It sucks. There
Speaker 1: are some decent products, like there are email clients that
Speaker 1: summarize emails Microsoft teams Apparently people really like the summarization.
Speaker 1: But we are meant to be describing the future here.
Speaker 1: We're meant to be describing something exciting and sexy. Not huh.
Speaker 1: This summarized the meeting for me interesting. But looking at
Speaker 1: these numbers, it's hard to imagine how open ai will
Speaker 1: more than triple revenue in the next fifteen months to
Speaker 1: hit eleven point six billion dollars in sales. Furthermore, at
Speaker 1: its current burn ray, open ai is currently spending, like
Speaker 1: I said, two dollars and thirty five cents to make
Speaker 1: a buck, meaning that eleven point six billion dollars in
Speaker 1: revenue could cost as much as twenty seven billion dollars
Speaker 1: to actually make. And as I previously mentioned, what costs
Speaker 1: could foreseeably come down, All signs point to them increasing.
Speaker 1: GPT four costs one hundred million dollars to train, and
Speaker 1: more complex future models will cost hundreds of millions or
Speaker 1: billions to train, as I mentioned the Information said that
Speaker 1: training costs were would look like three billion dollars in
Speaker 1: twenty twenty four, and I think it's fair to assume
Speaker 1: that the new models are just as costly, if not
Speaker 1: more so. Ye there's something deliciously ironic about all of
Speaker 1: this that, despite a clear lack of user interest in
Speaker 1: generative AI, open Ahi's global marketing push has succeeded in
Speaker 1: making lots of people intrigued enough to try a completely
Speaker 1: free service that only loses the money. While it's usually
Speaker 1: great news that a product has three hundred or more
Speaker 1: million free users, every book time somebody uses a service
Speaker 1: like chet GPT, it loses the company money. And in
Speaker 1: the case of chet GPT, good lord, they must be
Speaker 1: losing so much. The Information estimated in July the open
Speaker 1: Ai will spend around four billion dollars in server costs
Speaker 1: in twenty twenty four to run chat GPT and host
Speaker 1: other companies running their services using GPT in its other models,
Speaker 1: effectively meaning that every dollar of revenue is immediately eaten
Speaker 1: by the costs of acquiring it, and that's before your
Speaker 1: factor in more than fifteen hundred people, as many as
Speaker 1: seventeen hundred people now work at open Ai, which is
Speaker 1: another one point five billion dollars or more in costs,
Speaker 1: and other costs, by the way, are on top of that,
Speaker 1: they've got real estate taxes, stock grunts. This is all
Speaker 1: very bad and while open ay could potentially reduce costs,
Speaker 1: they've shown no proof that they can. And they tried once,
Speaker 1: well at least one got out, the so called iraqis
Speaker 1: model from last year that they tried to show that
Speaker 1: was meant to be more efficient if failed to launch.
Speaker 1: That's not a good sign, is it. But there's one
Speaker 1: more problem. There's still more problems, and this one, well,
Speaker 1: this one was caused by their fundraising. You see, they
Speaker 1: just raised six point five six point six billion dollars
Speaker 1: in capital one hundred and fifty seven billion dollar valuation.
Speaker 1: This means that all future rounds have to be at
Speaker 1: that valuation or higher. A lower valuation, which is called
Speaker 1: the down round, would make current investors quite pissy and
Speaker 1: send a very loud signal to the market that the
Speaker 1: company is having trouble because nobody thinks they're worth what
Speaker 1: they used to be, which in turn would overwhelmingly suggest
Speaker 1: open AI's only way to survive is to raise its
Speaker 1: next valuation at a two hundred billion dollar valuation and
Speaker 1: require yet another giant raise. I would say at least
Speaker 1: ten billion. For context, the biggest IPO valuation in US
Speaker 1: corporate history was Alababa, which debuted on the NASC with
Speaker 1: a market cap of nearly one hundred and seventy billion dollars.
Speaker 1: That figure is more than double the runner up Facebook,
Speaker 1: which had a value of eighty one billion dollars. And
Speaker 1: I want to give you some history on that one too.
Speaker 1: Facebook's initial OPO was really bad because people were concerned
Speaker 1: about mobile users and not monetizing them. Well, they won
Speaker 1: that one, but the market's pulverized Facebook for that. Do
Speaker 1: you think that they're going to be Oh yeah, so
Speaker 1: your company loses five or more billion dollars a year
Speaker 1: and you have no path of the profitability. Yes, put
Speaker 1: you up on a Nasdaq sounds perfect. Fuck that. No,
Speaker 1: they're not going to do that. How is this company
Speaker 1: going to do? How is this company going to IPO?
Speaker 1: And yet there's more problems too. I don't know how
Speaker 1: openay is meant to convert itself from its weird nonprofit
Speaker 1: structure into a for profit company. I don't know if
Speaker 1: it's possible, it won't be easy. And what's crazier is
Speaker 1: and there's so many little things like this in this
Speaker 1: story where you're like, people are going to look back
Speaker 1: on this and think, Wow, we were goddamn stupid. At
Speaker 1: least I hope they did. But open ai has two
Speaker 1: years from close to convert from a nonprofit to a
Speaker 1: for profit or their funding will convert into debt. I
Speaker 1: think it's six to nine percent interest. Hey, this isn't good. Also,
Speaker 1: at some point open ai is going to have to
Speaker 1: work out a way to go public, like I said,
Speaker 1: because otherwise, why did people invest? Why did people bother?
Speaker 1: They could do future secondary sales, And at some point,
Speaker 1: if that's all they're going to be able to do
Speaker 1: in secondary sales referring to selling private stock to another individual, well,
Speaker 1: I mean at that point it's a Ponzi scheme. You're
Speaker 1: just pulling in money to hand out money to other people. Eventually,
Speaker 1: it's not good these This company has no past to profitability.
Speaker 1: It doesn't have one. And regardless of what happens with
Speaker 1: everything I'm mentioning, they still need to raise more funds.
Speaker 1: Chat GPT's free version is an actual poison on open
Speaker 1: AI's system. It's a marketing channel that burns billions of
Speaker 1: dollars to introduce people to a product that only ten
Speaker 1: million people will actually pay for. And open AI's future
Speaker 1: depends largely on its ability to continue convincing people to
Speaker 1: use it. So how does this continue? How does open
Speaker 1: ai survive? I don't think it can. Open ai is
Speaker 1: a disaster in the making, and behind it, it's a nastier,
Speaker 1: shittier disaster, a lack of fundamental strength in the generative
Speaker 1: AI market writ Large. If open ai can only make
Speaker 1: a billion dollars as the leader in this market, and
Speaker 1: really only eight hundred million because the other two hundred
Speaker 1: million comes from Microsoft, it suggests that there's not really
Speaker 1: developer or user interest in generative AI products writ Large.
Speaker 1: Perhaps it's the hallucination problem, where it authoritatively states something
Speaker 1: that isn't true. Well, maybe it's just that generative AI
Speaker 1: isn't something that produces interesting interactions with a user. While
Speaker 1: you could argue that somebody could work out a really
Speaker 1: cool product, it's time to ask why Amazon, Google, Meta,
Speaker 1: open Ai, Apple and Microsoft have failed to make one
Speaker 1: one in the last two years? Where is it? Where's
Speaker 1: the killer app? And no, it's not early days. Shut up.
Speaker 1: More money than anything has ever raised has gone into
Speaker 1: these companies. More attention has gone into these companies than
Speaker 1: any other hyperscalar movement ever, even the metaverse. Where's the product? Man?
Speaker 1: Where is it? And while this bubble can continue coasting
Speaker 1: for a little while longer, nothing about the open ai
Speaker 1: story looks good. This company's lost. They're bleeding money with
Speaker 1: every single interaction with the customer, and they're flogging serve
Speaker 1: software that's the best kind of useful and worst actively
Speaker 1: harmful to the environment. Unless something significantly changes, like a
Speaker 1: massive scientific breakthrough in energy or compute efficiency, I just
Speaker 1: don't see how open ai makes it two more years.
Speaker 1: And worse still, if my hypothesis about the wider market
Speaker 1: is true, there might just not be a viable business
Speaker 1: in make and selling large language models. While Meta and
Speaker 1: open Ai might be able to claim hundreds of millions
Speaker 1: of users on these services, I don't see any evidence
Speaker 1: that these people will make them any money, and in fact,
Speaker 1: I only see evidence they'll lose it. And if I'm right,
Speaker 1: we're watching vcs in companies like Microsoft burn tens of
Speaker 1: billions of dollars to power the next generation of products
Speaker 1: and nobody really gives a shit about And in the
Speaker 1: next episode, I'm going to go into the much bigger problem,
Speaker 1: the subprime AI crisis, where everyone building on these platforms
Speaker 1: is inevitably going to get rug pulled when Open AI
Speaker 1: and Anthropic and other companies raise their prices, because if
Speaker 1: they don't raise their prices, how are they going to
Speaker 1: be able to afford to keep going. I don't bloody no,
Speaker 1: but we'll get into it next episode. Thank you for
Speaker 1: listening to Better Offline. The editor and composer of the
Speaker 1: Better Offline theme song is Matosowski. You can check out
Speaker 1: more of his music and audio projects Matttersolski dot com,
Speaker 1: M A T T O s O W s Ki
Speaker 1: dot com. You can email me at easy at Better
Speaker 1: offline dot com or visit Better Offline dot com to
Speaker 1: find more podcast links and of course my newsletter. I
Speaker 1: also really recommend you go to chat dot Where's youreaed
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Speaker 1: so much for listening.
Speaker 2: Better Offline is a production of Cool Zone Media. For
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