Better Offline - OpenAI Is Not A Real Company

Episode Date: February 26, 2025

In this episode (the first of a two-parter), Ed Zitron walks you through how OpenAI isn’t a real company, but a venture-backed welfare recipient that spent $9 billion to lose $5 billion in 2024 with little product-market fit and a stagnant API business that suggests that there’s little adoption of generative AI. --- LINKS: https://www.tinyurl.com/betterofflinelinks Newsletter: https://www.wheresyoured.at/ Reddit: https://www.reddit.com/r/BetterOffline/  Discord: chat.wheresyoured.at Ed's Socials: https://twitter.com/edzitron https://www.instagram.com/edzitron https://bsky.app/profile/edzitron.com https://www.threads.net/@edzitronSee omnystudio.com/listener for privacy information.

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Either way, the podcast's Superhuman documented it all, embedded in the games and with the athletes for a full year. Within probably 10 days, I'd put on 10 pounds. I was having trouble stopping the muscle growth. Listen to Superhuman on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts. Orzo Media. Soul of an angel, body of a devil, chosen by God and perfected by science. better offline and I'm your host Ed Citron. Now, we're working on my newsletter last week. I was chatting with my friend,

friend of the show, Casey Kagawa, about generative AI and we kept coming back to one thought, where's the money? Where is it? No, really, where is the money? Where is the money that this supposedly revolutionary world-changing industry is making? And of course, we'll make in the future. And the answer's simple.

After hours of hours of grinding through earnings, of grinding through media articles, of grinding through all sorts of things, I just don't believe it really exists. It's real, but it's small. Generative AI lacks the basic unit economics, product market fit, or market penetration associated with any meaningful software boom, and outside of open AI, the industry may be pathetically hopelessly small, all while providing few meaningful business returns and constantly losing money. I'm going to be pretty straightforward with everything I say in this two-parter, because the numbers and the facts

and my hypothesis are pretty fucking damning of both the generative AI industry and its associated boosters. You're going to get this episode, then there's going to be a monologue about something else or something related. I really haven't got to it yet. And then a second part, which I'm recording immediately after this one, a little behind the curtain there for you. Anyway, in reporting this analysis, I've done everything I can to try and push back against my own work, and I've saw evidence to counter the things that I've seen, like the revenue and the business models of these companies. Yet, in doing so, I've only become more convinced of the flimsyness of generative AI and the associated industry and the likelihood of this bubble bursting

in a way that kneecaps tech valuations for a prolonged period, or worse, hits the major stock market. Now, I really had originally written a far more jocular and outraged and pissy script, but while I was writing it, I realized I really had to be blunt, because what I'm describing is a systemic failure. Venture Capital has propped up OpenA.I. and Anthropic, two companies that have burned a combined $10.5 billion in 2024, and that number is set to double or more in 2025. The tech media has allowed Sam Altman to twist them to validate completely fictional ideas as a means of propping up this unprofitable, environmentally destructive software company, and big tech has become so disconnected from reality that it is incapable of seeing how little

actual returns there are in generative AI. And they're failing, by the way. As I'll walk you through in these episodes, the generative AI industry is very small. with the consumer market of the entire American Generative AI industry outside of ChatGPT, barely cracking 100 million monthly active users, which puts them below a lot of free-to-play games that you get on your iPhone. Hyper-scalers have already spent hundreds of billions of dollars in capital expenditures for an AI industry that has the combined monthly active users of a free-to-play mobile game.

I really must repeat myself. It's insane. But unlike most mobile games, generative AI doesn't really make any much. money. And for those of you wondering if selling access to AI models is the solution, it's important to know that OpenAI, the market leader in Generative AI, made less than a billion dollars on API calls in 2024. And that's when people plug their models in for those of you who don't understand. So it's the difference between you know, load up the ChatGPT app or someone has an AI, a generative AI like ChatGPT plugged into it. Now Microsoft pays OpenAI a revenue share of 20% on them selling OpenAI's models, so $200 million.

So, this means that Microsoft likely only makes a billion dollars in revenue from API calls themselves. This is a pathetic amount of money and suggests there really isn't significant demand at all, or they're not charging enough. Neither of these are great. And honestly, I'm sick and tired of hearing people prop up this fucking industry. In these episodes, I will explain as calmly as possible how the generative AI industry barely exists outside of OpenAI. And honestly, in writing this, I've become completely disgusted at Silicon Valley at the waste. Why is nobody talking about the revenues? Why is nobody sharing real user numbers other than OpenAI? Well, I believe it's because there isn't that much money, and there certainly aren't that many users.

Nobody is making a profit from this other than consultants, and that's because this is a hype-driven movement. What you see on TV and in the newspaper is not the advent of a revolutionary piece of technology. It's a cynical marketing campaign for one company, Open AI. I need you to understand how precarious this all is. So much money has been wasted propping up an industry that only burns money that does not have mass market appeal. ChatGPT is not significant enough or useful enough or meaningful enough to justify spending $9 billion to lose $5 billion. And yes, those are the raw economics of OpenAI. Now you may say, well, Uber lost a lot of money, didn't it, Edward?

Guess what? Uber lost about $6.2 billion in one year, and that was in 2020 when they couldn't run their bloody service. Uber is a very different company. I will gladly, if you email me, I will explain this to you, but Uber is not a comparison. There is no comparison to what Open AI is doing, what Anthropic is doing. I sound crazed as ever, but you're going to understand why when I'm done. I am deeply worried about this industry, and I need you to know why. But in this first episode, I'm going to focus on one specific thing, and that's the capitalist delusion known as Open AI, a company that encompasses almost all of the traffic, funding, and attention in generative

AI. And I believe they die without a constant flow of venture capital and hyperscale welfare. And I actually don't know why I said I believe that. They will. They cannot survive without that money. But okay, let's take a second. Let's talk about Open AI's unit economics. Putting aside the hype, the Blaster, Open AI, as with all generative AI model developers, loses money on every single prompt and output. Its products do not scale like traditional software, in that the more users it gets, the more expensive its services are to run, because its models are so compute-intensive. For example, chat GPT having 400 million weekly active users is not the same thing as a traditional

app like Instagram or Facebook having that many users, or indeed Uber. The cost of serving a regular user of an app like Instagram is, significantly smaller because these are effectively websites with connecting APIs, images, videos and user interactions. These platforms aren't innately compute heavy and so you don't need to have the same level of infrastructure to support the same amount of people. Conversely, generative AI requires expensive to buy and expensive to run and expensive to maintain graphics processing units, GPUs, both for inference and training the models themselves. These GPUs must be run at full tilt for both inference and training, which shortens their lifespan.

also consuming ungodly amounts of energy. And by the way, inference is just the thing that happens when you tell chat GPT something. It infers the meaning of the prompt. And the training is what they do when they throw all the training data to make the model smart. Not really, though. And by the way, surrounding the GPU in there isn't like the GPUs just kind of hang out. There's the rest of a computer, which is usually highly speced and incredibly difficult to cool and thus very, very expensive.

These generative AI models also require endless amounts of training data and supplies of that training data have been running out for a long time. While synthetic data might bridge some of the gap, there are likely diminishing returns due to the sheer amount of data necessary to make a large lag in which model even larger, as much as more than four times the size of the internet. This is insane. There is not enough data, and it already kind of sucks,

and it's not getting better. These companies also must spend hundreds of millions of dollars on salaries to attract and retain AI talent, as much as $1.5 billion a year in Open AI's case, and that's before stock-based compensation. In 2016, Microsoft claimed that top AI talent could cost as much as an NFL quarterback to hire, and that sum has likely only increased since then, given the generative AI frenzy, and the fact they're overpaying quarterbacks. As an aside, one analyst told the Wall Street Journal that companies running generative AI models could,

and I quote, be utilising half their capital expenditures because all of these things could break down. that's really bad. These costs are not a burden on OpenAI or Anthropic, but they absolutely are on Microsoft, Google and Amazon. The shit's crazy. Anyway, as a result of the costs of running these services, a free user of ChatGPT is a cost burden on Open AI, as is every single free customer of Google's Gemini,

Anthropics Claude, perplexity, or any other generative AI company. Said costs are also so severe that even paying customers lose these companies' money. Even the most successful company in the business appears to have no way to stop burning capital. And as I'll explain, there's only really one real company in the industry, OpenAI. And Open AI is not a real business. But let's start with a really, really important fact.

If you forget everything I say, I want you to remember this. Open AI spent $9 billion to make just under $4 billion in 2024, and the entirety of their revenue, that's about $4 billion, is spent on compute, $2 billion to run models and $3 billion to train them. That is completely and utterly fucking insane. That is bonkers. That is crazy. That is completely nuts.

This is not a real company. It is insane. We're allowing this. Everyone should be screaming this at everyone. We live in an alternate reality where this is acceptable. There has been no precedent for this, not Amazon Web Services, not Uber, not anyone. No one has done this. And it's sickening and wasteful that we continue to.

And in the past, I've repeatedly said the Open AI lost $5 billion after revenue. Now, that is true, by the way. That is completely true. They made money and they lost money, but ended up losing $5 billion either. Either way. However, I really just, I can't in good conscience suggest that OpenAI only spent $5 billion. It's time to be honest about these numbers. While it's fair to say that their net losses are $5 billion, they spent $9 billion to lose $5 billion. Another podcast from some SNL late-night comedy guide, not quite. Unhumor me with Robert Smygel and friends, me and hilarious guests from Jim Gaffigan to Bob Odenkirk to David Letterman help make you funnier.

This week, my guest, SNL's Mikey Day and headwriter, Streeter Seidel, help an a cappella band with their between songs banter. There's the worst singer in the group. The worst? Yeah. Me. Is there anything to the idea that because you're from Harvard, you only got in because your parents made a huge donation.

The group. The yarn herds, right? That's the name. The Harvard Yard. They're open. Do you have a name suggestion? We're open. Since you guys are middle aged, one erection.

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say it's unleashing human potential. Either way, the podcast, Superhuman, documented it all, embedded in the games and with the athletes for a full year. Within probably 10 days, I'd put on 10 pounds. I was having trouble stopping the muscle growth. Listen to Superhuman on the I-Hard Radio app, Apple Podcasts, or wherever you get your podcasts. A win is a win.

A win is a win. Yep, that's me. Cliver Taylor the 4th. You might have seen the skits. the reactions, my journey from basketball to college football, or my career in sports media. Well, somewhere along the way, this platform became bigger than I ever imagined. And now I'm bringing all of that excitement to my brand new podcast, The Clifford Show. This is a place for raw, unfiltered conversations with some of your favorite athletes,

creators, and voices that not only deserve to be heard, but celebrated. One week, I'll take you behind the scenes of the biggest moments in sports and entertainment, and the next we'll talk about life, mental health, purpose, and even music. The Clifford Show isn't just a podcast. It's a space for honest conversations, stories that don't always get told, and for people who are chasing something bigger. So, if you've ever supported me or you're just chasing down a dream, this is right where you need to be. Listen to The Clifford show on the IHeart Radio app, Apple Podcasts, or wherever you get your podcast. And for more behind the scenes, follow at Clifford and at TikTok Podcast Network on TikTok. Let's really get down into the nitty-gritty of these numbers.

So as discussed previously, according to the reporting by the information, OpenAI's revenue was likely somewhere in the region of $4 billion in 2024. Their burn rate, according to the information, was $5 billion after revenue in 2024, excluding stock-based compensation, which OpenAI, like other startups, uses as a means of compensation on top of cash. Nevertheless, the more it gives away, the less it has for capital raises, and these are technically costs, though they're not real money, unless there's a liquidity event, but you don't need to worry about that. To put this in blunt terms, based on reporting by the information, and I'm repeating myself here, but I really need you to remember this, running OpenAI costs $9 billion in 2024. The cost of the computer to trick the compute, to train models alone, $3 billion, obliterates the entirety of their subscription revenue, which is about $3 billion, by the way. And the compute from running models, $2 billion, takes the rest and then some. They actually end up losing an extra billion on top of that. Sam Altman's net worth is a billion dollars, by the way. Casey Gagawa has now used this as the Altman index, so it's like you've lost one Sam Altman. That's a billion dollars. But just to be clear, it doesn't just cost more to run Open AI than they make. It costs them a billion dollars more than the entirety of their revenue to run the software they sell before any other costs. Why are we not more concerned about this company? Now, something else to know is that. that OpenAI also spends an alarming amount of money on salaries, over $700 million in

2024 before you consider that compensation from stock, a number that will also have to increase because OpenAI is growing, which means hiring as many people as possible, and they're paying through the nose for them. But let's talk about how OpenAI makes money. OpenAI sells access to its models via its API and selling premium subscriptions to ChatGPT. The majority of its revenue over 70% comes from subscriptions to premium versions of ChatGPT. The information also reported that OpenAI now has 15.5 million paying customers, though it's unclear what level of the service they're paying for, or how sticky these customers are, as in how luckily they are to stick around,

or the cost of acquiring these customers, or really any other metric to tell them, tell us how valuable these customers are to the bottom line. Nevertheless, OpenAI loses money on every single paying customer, just like it's free users. Increasing paid subscribers to OpenAI services somehow increases OpenAI's burn rate. is not a real company. Now, the New York Times reports that OpenAI projects it will make $11.6 billion in 2025, and assuming that Open AI burns at the same rate it did in 2024, spending $2.25 to make $1, open AI is on course to burn over $26 billion in 2025 for a loss of $14.4 billion. Who knows

what their actual costs will be? Now, you've probably heard about SoftBank coming in. SoftBank's going to feed the money, and SoftBank said they're going to spend money on this, that, and the other. That round has not closed yet. Masayoshi's son, a complete fucking idiot who's lost $30 odd billion for SoftBank, the Japanese mega conglomerate, he's dedicating billions of dollars of revenue to buying OpenAI services. Unless this is a straight-up trade where he's just sending money before the services come in, I don't know if it happens. And I'm going to get into things like agents later, but the information reported that OpenAI expects

to make $3 billion in revenue from agents. By the end of this episode, you're going to realize how fucking stupid that sounds. We'll get there later. It's also important to note that OpenAI's costs are partially subsidized by its relationship with Microsoft, which provides cloud compute credits for its Azure cloud service. Not super technical, it's just when they host people's software and files and such, and the compute to run these models. And they also offer this a steep, steep discount to Open AI.

Or put another way, it's like OpenAI got paid with air miles, but the airline lowered the redemption cost to booking a flight with those. air miles, allowing it to take more flights than any other person with the equivalent amount of points. Until recently, OpenAI exclusively used Microsoft Azure services to train, host, and run its models, but recent changes to its deal means that OpenAI is now working with Oracle to build out further data centers to train, host, and run its models. It's unclear whether this partnership will work in the same way as the Microsoft deal, with OpenAI provided credits and discounts like before.

If not, OpenAI's operating costs will only go up. Per previous reporting from the information, OpenAI pays just over 25% of the cost of Azure's GPU compute as part of their deal with Microsoft. And that's about $1.30 per GPU per hour versus the regular Azure cost of $3.40 to $4 an hour. I know that this sounds really technical, but in very short, they're getting a sweet deal from Microsoft and if anything happens to that, they're completely fucked. They're fucked anyway. They don't have, they're burning billions of dollars.

It's insane. But let's talk about user numbers. OpenAI has quite a few. They recently announced that they have 400 million weekly active users. Now, weekly active users is a wanky number and a very strange one for a company like this. OpenAI may pretend to be a consumer company, but the majority of their revenue comes from monthly subscriptions, making them kind of a cloud software company. Classically, cloud software companies report monthly active users.

That way you can, I don't know, compare one number, which is the amount of active users you have, with the paid users you have, and then say, oh, that's a good business. That's a good business right there, man. Guess what? OpenAI isn't given their monthly active users. Don't worry, I might have estimated it. When I asked OpenAI to define what a weekly active user was, it responded by pointing me to a tweet by Chief Operating Officer Brad Lightcap that said ChatGPT recently crossed 400 million weekly active users.

We feel very fortunate to serve 5% of the world every week. What a fucking liar. It's extremely questionable that OpenAI refuses to define this core metric, by the way, and without a definition, in my opinion, there is no way to assume anything other than OpenAI is actively gaming its numbers. Now, there's likely two reasons they focus on weekly active users. One, as described, these numbers are easy to game. You can choose any seven-day period. And also, the majority of OpenAI's revenue comes from paid subscriptions to chat GPT.

And that latter point is crucial because it suggests OpenAI is not doing anywhere near as well as it seems, based on the very basic metrics used to measure the success of a software product. The information reported on January 31st, the OpenAI, like I mentioned, had 15, $1.5 million monthly paying subscribers, and they added in this piece that this was less than a 5% conversion rate of OpenAI's weekly active users. A statement that's kind of like dividing the number 52 but a letter A. This is not an honest or reasonable way to evaluate the success of chat GPT's still unprofitable software business, because the actual metric, like I mentioned, would have been to defied paying subscribers by monthly active users, or the other way around, I guess, a number that would be

considerably higher than 400 million. And the reason they don't want to do that, by the way, is because you would divide them and see that they have a piss poor conversion rate. Good conversion rate is way higher than 5%, by the way. And DES is definitely lower. But don't worry, I'm a sneaky little shit, so I went and looked some stuff up and I talked to some people. Based on data from the market intelligence firm sensor tower, OpenAI's chat GPT app on Android and iOS is estimated to have more than 339 million monthly active users, and based on traffic data for market intelligence company similar web, chat gpt.com had 246 million unique monthly visitors, and these were in January 2025. There's likely some crossover with people using both the mobile and web interfaces,

though how big that group is, is kind of hard to tell and remains uncertain. Though every single person that visits chatgpte.com might not become a user, it's safe to assume that chat GPT's monthly active users are somewhere in the region of 500 to 600 million. That's good, right? Its actual users are higher than officially claimed, right? That's good? No, it's bad. First of all, each user that uses chat GPT for free is a drain on the company, whether they're free or not, honestly. But either way, their free ones definitely are. It would also suggest that the real conversion rate is somewhere in the neighborhood of 2.583% from free to paid users on chat GPT, which is astonishingly bad. And it's a fact that's made worse by the fact that every single user, regardless of whether

they pay or not loses them money. Either way. And while it's quite common for Silicon Valley companies to play fast and lose with metrics, this particular one is, well, it's deeply concerning, and I hypothesize that Open AI is choosing to go with weekly versus monthly active users in an intentional attempt to avoid people calculating the conversion rate of its subscription products. As I will continue to repeat, these subscription products lose the company money every single time. Now, let's talk product strategy, shall we, because I don't think Open AI really has one. Open AI makes most of its money from subscriptions, approximately $3 billion in 2024 and the rest on API access to its models, approximately a billion.

As a result, OpenAI has chosen to monetize ChatGBT and its associated products in an all-you-can-eat software subscription model or otherwise make money by other people productizing it. And just to be clear, in both of these scenarios, OpenAI loses money on every transaction. OpenAI's products are not fundamentally differentiated or interesting enough to be sold separately. It has failed, as with the rest of the generative AI industry, to meaningfully productize its models due to the massive training and operational costs, and a lack of any meaningful killer app use cases for large language models. The only product that OpenAI has succeeded in scaling to the mass market is the free version

of ChatGBTGT, which loses the company money with every single prompt and output. This scale isn't a result of any kind of product market fit, by the way. It's entirely media-driven, with reporters making ChatGPT synonymous with artificial intelligence, a thing they regularly write about without thinking. As a result, I do not believe that the Generative AI industry is real. It's not a real industry, which I will define as one with multiple competitive companies with sustainable or otherwise growing revenue streams and meaningful products with actual market penetration. And I feel this way because this market is entirely subsidized by a combination of venture capital and hyperscaler cloud credits,

and, well, real money, I guess. ChatGPT is popular because it's the only well-known product, one that's mentioned in basically every article on AI. If this were a real industry, other competitors would also be mentioned all the time. They would have similar scale, especially those run by hyperscalers, but as I'll get to later, data suggests that Open AI is the only company with any significant user base in the entire generative AI industry, and it's still wildly unprofitable and unsustainable. Open AI's models have also been entirely commoditized. Even its reasoning model, 01, has been commoditized by both Deepseek's R1 model and perplexities, agonizingly named R11776 model, both of which have similar outcomes at a much-disciplatized. discounted price to OpenAIs 01, though it's unclear and unlikely, in my opinion, that these models are profitable anyway. Open AI as a company, well, they're just piss poor at product. It's been two

years and chat GPT mostly does the same thing, still costs more to run than it makes, and ultimately does the same thing as every other LLM chat bot from every other company. The fact that nobody has managed to make a mass market product by connecting Open AI's models also suggests that the use cases just aren't there. Furthermore, the fact that API access is such a small part of its revenue suggests that the market for actually implementing large language models is relatively small. If the biggest player in the space only made a billion dollars in selling access to its models unprofitably, and that amount is the minority of its revenue, there may not actually be a real industry here. And I must be clear, if there was user demand, this would be where it was in the APIs.

it would be doing gangbusters because people wouldn't be able to help themselves. They'd just be all over this generative AI shit. But they're not. Another podcast from some SNL late-night comedy guy, not quite. Unhumor me with Robert Smygel and friends. Me and hilarious guests from Jim Gaffigan to Bob Odenkirk to David Letterman, help make you funnier. This week, my guest, SNL's Mikey Day and head writer Streeter Seidel,

help an a cappella band with their between songs banter. There's that more singer in the group. The worst? Yeah. Me. Is there anything to the idea that because you're from Harvard, you only got in because your parents made a huge donation. The group.

The yard herds, right? That's the name. The Harvard yard, but they're open. Do you have a name suggestion? We're open. Since you guys are middle aged, one erection. Listen to humor me with Robert Smigel and Friends on the I-Heart Radio app, Apple Podcasts, or wherever you get your podcast.

me, I need some jokes to make me seem funny. Run a business and not thinking about podcasting, think again. More Americans listen to podcasts than ads supported streaming music from Spotify and Pandora. And as the number one podcaster, IHearts twice as large as the next two combined. So whatever your customers listen to, they'll hear your message. Plus, only IHeart can extend your message to audiences across broadcast radio. Think podcasting can help your business. Think IHeart.

streaming, radio, and podcasting. Let us show you at iHeartadvertising.com. That's iHeartadvertising.com. Imagine an Olympics where doping is not only legal but encouraged. It's the enhanced games. Some call it grotesque. Others say it's unleashing human potential. Either way, the podcast's Superhuman documented it all,

embedded in the games and with the athletes for a full year. Within probably 10 days, I'd put on 10 pounds. I was having trouble stopping them. I'm not so great. Listen to Superhuman on the I Heart Radio app, Apple Podcasts, or wherever you get your podcasts. A win is a win. A win is a win.

I don't care what you're saying. Yep, that's me, Clifford Taylor the 4th. You might have seen the skits, the reactions, my journey from basketball to college football, or my career in sports media. Well, somewhere along the way, this platform became bigger than I ever imagined. And now I'm bringing all of that excitement

to my brand new podcast, The Clifford Show. This is a place for raw, unfiltered conversations with some of your favorite athletes, creators, and voices that not only deserve to be heard, but celebrated. One week, I'll take you behind the scenes of the biggest moments in sports and entertainment, and the next we'll talk about life, mental health, purpose, and even music. The Clifford Show isn't just a podcast, it's a space for honest conversations, stories that don't always get told, and for people who are chasing something bigger. So, if you've ever supported me, or you're just chasing down a dream, this is right where

you need to be. Listen to the Clifford show on the IHeart Radio app, Apple Podcasts, or wherever you get your podcast. And for more behind the scenes, follow at Clifford and at TikTok Podcast Network on TikTok. Now, I want to address one counterpoint. Some might argue that OpenAI has a new series of products that could open up new revenue streams, such as operator, its agent product and deep research, their research product. And I'm so fucking tired of hearing about agents. Whenever you hear someone say agent, really look at what they're saying, because they want you to think, autonomous bit of software. What they're actually talking about is either a chatbot or, well, the dog shit the OpenAI and Anthropic have warmed up, which will get too shortly. But first, let's talk costs. Both of these products are very compute-intensive. Operator uses OpenAI's computer-using agent, the CUA, which combines OpenAIs models with virtual machines that take distinct actions on web pages in this extremely unreliable and costly way where they take screenshots as they scroll down. And it just doesn't fucking work. I had a whole thing. thing about Casey Newton writing about this. It was just so bad. Like, Casey Newton, please go outside

challenge. Just go outside, Casey. Stop with the compute. You don't know what you talked about. But failures with these. And remember, these models, pretty much all of them are inconsistent. And the more in-depth the thing you ask them to do, the more likely there's going to be a problem with it. So think about it like this. Failures from something you've asked them to do will either increase the amount of attempts you make to get the thing you want or make users not use it at all. Not a really great idea. Now let's talk deep research. They use a version of OpenAI's O3 reasoning model,

which is a model so expensive because it spends more time to generate a response based on the model reconsidering and evaluating steps as it goes, that Open AI will no longer launch O3 as a standalone model. And that's really a good thing when you see a company be like, yeah, you can't touch it, it's too expensive. In short, these products are extremely expensive to run, and this means that any time their outputs aren't perfect,

which is to say a lot of the time, there's a high likelihood that they'll be triggered again, which will in turn spend more compute. But let's talk about the product market fair, because this is really important. To use operator or deep research currently requires you to pay $200 a month for OpenAI's ChatGPT Pro,

a $200 a month subscription, which Sam Altman recently revealed still loses the money because people are using it more than expected, and that is a quote. Furthermore, even on ChatGPT Pro, deep research is currently limited to 100 queries per month, adding that it is very compute intensive and slow.

Though Altman has promised the chat GPT Plus and free users will eventually get access to a few deep research queries a month, well, that's not good for their cash burn. That's actually bad for the cash burn. I'm not sure it's going to make them, I'm not really sure how that turns into money anywhere. But let's talk about Operator. Operator is this agent product where you're meant to be able to be like, hey, look, go and look something up for me, and it only works like 30% at the time, and it takes

it's just very bad. As I covered in my newsletter a few weeks ago, this product, and it claims to control your computer and does not appear to be able to do so consistently, it's not even ready for the prime time, and I don't think it has a market. The way they're selling this is that you'll be able to make it do distinct tasks on the computer, but even Casey Newton and his article was like, yeah, it only works sometimes, and the things it works on are like searching trip advisor. Imagine this, if you will.

What if, for the cost of boiling a lake and throwing an entire zoo into the lake and boiling the animals inside it, you could sometimes be able to search TripAdvisor in two minutes versus 10, like five seconds. The future is so cool. I love living in it. But let's talk about deep research for a second. It's already being commoditized. Perplexity AI and XAI have launched their own versions immediately. And deep research itself is not a good product. As I covered in my newsletter last week, the quality of the writing that you receive from deep research is really piss poor. And it's rivaled only by the appalling quality of its citations, which include forum posts and search engine optimized content instead of actual news sources. These reports are

neither deep nor well research can cost open AI a great deal of money to deliver. And just to give you a primal deep research is meant to be, you meant to be able to type something in and it does like a 3,000 word report. It's gobbledy gook. It's nonsense. It's bullshit. I really, if you, you should go and look up, go to my newsletter, where's your ed.org, not at. It's the, it's the, It's the piece before the ones that's going to come out when these episodes come out. I forget the name exactly. You need to go and look at how shit deep research is. It's incredible that this money-losing juggernaut piece of shit thinks that this is a real product,

and it's insulting to the intelligence of readers that people like Casey Newton claimed it was good. But now we've established that both of these products are expensive, commoditized, and don't work very well. Let's talk about how they make money. Or don't. Both operate and deep research, like I told you, currently require you to pay $200 a month to a company that loses money all the time that also loses money on the $200 a month. Neither product is sold in its own, and while they may drive revenue to the ChatGPT Pro product, as said before, said product loses open AI money.

These products are also compute-intensive and have questionable outputs, making each prompt very likely to create another follow-up prompt. And the problem is you're asking something that doesn't know anything that probabilistically generates answers to research something. So as a result, the research isn't going to be any good. It's not like it's going to research it and go, hey, what would be a good source? It's going to say, what matches the patterns?

What matches all the patterns that are being trained on? Eh, that's fine. Who gives a shit? It's like having the world's worst intern, except the intern gets a concussion every 10 minutes. But in summary, both operator and deep research are expensive products to maintain, are sold through an expensive $200 a month subscription

that, like every other service provided by OpenAI, loses the company money, and due to the low quality of their outputs and actions are likely to increase user engagement to try and get the desired output, incurring further costs for OpenAI. Well, you know, like Ed, you say, Ed, you're just being a hater, right? Just being a hater. Things don't look great today, but this early days, it isn't early days.

But still, Ed, it's early days. Things don't look great today. What about the future prospects for OpenAI? Things can't be that bad, can they? Yeah, yeah, they can. A week or two ago, Sam Altman announced the updated roadmap for GPT, 4.5 and GPT5. Now these are their next generation

models that have been hyping up for the best part of a year. Except GPT4.5 didn't exist before. It was always GPD5. Now, GPT4.5 will be OpenAI's last chain of thought model, referring to the core functionality of its reasoning models where it checks the work as it goes and really it uses a model to ask another model whether the model's

doing the right thing. Can they both hallucinate? Yes. GPT5 will be, and I quote Sam Altman, a system that integrates a lot of open AIs technology, including 03. What the fuck are you talking about? Orkman also vaguely suggests that paid subscribers will be able to run GPT5 at a higher level of intelligence, which likely refers to being able to ask the models to spend more time computing an answer. He also suggests that GPT5, and I quote, will incorporate voice,

canvas, search, deep research, and more. Fucking bedbath and beyond, motherfucker? Come on! My man, your company spent $9 billion to lose $5 billion. Why is anyone taking this Seriously, this is ridiculous. But both of these statements, all of these statements, honestly, vary from vague to meaningless. But I hypothesize the following. GPT4.5 will be an upgraded version of GPT40, OpenAI's foundation model you're probably using right now,

and it's codenamed Orion. GPT5, which used to be codenamed Orion, could literally be anything. But one thing that Altman mentioned in the tweet is that OpenAI's model offerings have got too complicated. They'd be doing away with the ability to pick what model you use. gussying this up and he's claiming it's unified intelligence. This fucking guy. If I said this shit to a doctor, they'd institutionalise me. They'd say you sound like a lunatic. But anyway, as a result of doing away with the model picker, which is literally the thing you click and you choose GPD 40 or GBT40 or like the O1 reasoning things, I think they're going to attempt to moderate cost by picking what

model will work best for a prompt. A process, it will automate. And if there's one thing I've noticed with Open AI, they're not very good at automating anything. So I expect this to be bad. And I believe that Altman announcing these things is a very bad omen for open AI, because Orion has been in the works for more than 20 months and was meant to be released at the end of 2024, but it was delayed due to multiple training runs that resulted in, to quote the Wall Street Journal, software that fell short of the results researchers were hoping for. As an aside, the Wall Street Journal refers to Orion as GPT-5, this was from several months back, but based on the copy in Altman's comments, I believe Orion refers to a foundation model,

which is one to replace the core GPD, one that powers chat GPT. Open AI now appears to be calling a hodgepodge of different mediocre models, something called GPT5. It's almost as if Altman's making this up as he goes along. Now, the journal further adds that as of December, Orion performed better than OpenAI's current offerings but hadn't advanced enough to justify the enormous costs

of keeping the new model running. With each six-month-long training run, no matter how well it works, costing over $500 million. Open AI also, like every generative AI company, is running out of high-quality training data, the data necessary to make its models smarter based on the benchmarks, specifically made up to make LLM seem smart. And I should note that being smarter means completing tests, not new functionality or new things that it can do.

Sam Altman deputizing Orion from GPT5 to GPT4.5 suggests that Open AI has hit a war with making its new model, requiring him to lower expectations for a model OpenAI Japan president Tagau Nagasaki had suggested would, and I quote, aim for 100 times more computational volume than GPT4, which some took to mean 100 times more powerful when it actually means it will take way more computation to train or run inference on it. I guess he was right. Now, if Sam Altman, who is a man who loves to lie, is trying to reduce expectations for a product, I think we should all be really, really worried. Now, large language models, which are trained by feeding them massive amounts of training data

and then reinforcing their understanding through further training runs, are hitting the point of diminishing returns. In simple terms, to quote, friend of the show, Max Zeff of TechCrunch, everyone now seems to be admitting you can't just use more compute and more training data with pre-training large language models and expect them to turn into some all-knowing digital god. Max is a fucking legend. Open AI's real advantage, other than the fact it's captured the entire tech media, has been its relationship with Microsoft because access to large amounts of compute and capital

allowed it to corner the market for making the biggest, most hugest large language model. Now that it's pretty obvious this isn't going to keep working, OpenAI is scrambling, especially now Deepseekers' commoditized reasoning models, and prove that you can build LLMs without the latest GPUs. It's unclear what the functionality of GPT4.5 or GPT5 will be. Does the market care about an even more powerful large language model

if said power doesn't do anything new or lead to a new product? Does the market care if Unified intelligence just means stapling together various models to produce more outputs that kind of look and sound the same? As it stands, Open AI has effectively no moat beyond its industrial capacity to train large language models and its presence in the media. Open AI can have as many users as it wants, but it doesn't matter because it loses billions of dollars and appears to be continuing to follow the money losing large language model paradigm, guaranteeing. or lose billions of dollars more if they're allowed to. This is the biggest player in the generative AI industry,

both the market leader and the recipient of almost every single dollar of revenue that this industry generates. They have received more funding and more attention than any startup in the last few years, and as a result, their abject failure to become a sustainable company with products that truly matter is a terrible sign for Silicon Valley and an embarrassment to the tech media. In the next episode, I'm going to be honest, I have far darker news. Based on my reporting, I believe that the generative AI industry, outside of Open AI, is incredibly small, with little-to-no-no-consumer adoption and pathetic amounts of revenue compared to the hundreds of billions of dollars sunk into supporting it. This is an entire hype cycle fueled by venture capital and big tech hubris, with little real adoption and little hope for a turnaround.

Enjoyed tomorrow's monologue, and then the final part on Friday. Thank you for listening to Better Offline. The editor and composer of the Better Offline theme song is Matt Rosowski. You can check out more of his music and audio projects at Matersowski.com. M-A-T-T-O-S-O-S-K-I.com. You can email me at E-Z at Better Offline.com or visit Better Offline.com to find more podcast links and, of course, my newsletter. I also really recommend you go to chat. Where's Your Ed? at to visit the Discord and go to R-S-Better-O-L-Line to check out our Reddit. Thank you so much for listening.

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