Are AI's Economics Unsustainable? — With Ed Zitron

Summary

Big Technology Podcast Summary: "Are AI's Economics Unsustainable? — With Ed Zitron"

Released on July 23, 2025

Introduction

In the latest episode of the Big Technology Podcast, host Alex Kantrowitz engages in a critical discussion with Ed Zitron, a prominent tech critic, about the financial viability of the artificial intelligence (AI) industry. Ed Zitron, known for his ownership of ezpr, hosting Better Offline, and authoring the Where's Your Ed At? newsletter, presents a sobering analysis of the economic underpinnings of major AI players, particularly OpenAI.

Financial Sustainability of AI Companies

Ed Zitron opens the conversation by highlighting the staggering financial losses incurred by OpenAI. He states, “[...] OpenAI will burn probably $12, $13 billion after revenue this year” (01:10). Zitron emphasizes that OpenAI lacks a clear path to profitability, questioning the feasibility of their projections to achieve profitability through Stargate, an enigmatic project he describes as “magical” (02:00). He contrasts this with other tech giants, pointing out that even Microsoft's AI revenue is modest compared to the industry's projected needs.

Zitron draws parallels to companies like Uber, which, despite significant losses, continue to operate based on their unique business models. However, he contends that the AI industry's financial model is fundamentally different and more precarious, citing massive capital expenditures and minimal revenue growth.

AI vs Traditional Search Engines

A significant portion of the discussion revolves around the potential of AI to replace traditional search engines like Google. Zitron argues that while ChatGPT and similar large language models (LLMs) demonstrate superior capabilities in understanding and inferring user intent, they struggle to scale into profitable search businesses. He notes, “[...] What you actually have to do is build a very different company because selling advertisements is fundamentally different from selling consumer ChatGPT subscriptions or enterprise services” (09:27). Zitron criticizes the inefficiency and high costs associated with transforming AI into a robust search platform, highlighting the lack of infrastructure ownership by OpenAI.

Funding and Investment Concerns

The conversation shifts to the complex funding landscape of AI companies. Zitron discusses the precarious relationship between OpenAI and major investors like Microsoft and SoftBank, revealing that OpenAI is heavily reliant on continuous capital infusion to sustain operations. He warns of a potential financial bubble, comparing the situation to the subprime mortgage crisis, where the lack of tangible assets and unsustainable financial practices could lead to widespread economic repercussions.

Zitron raises concerns about OpenAI's inability to generate substantial revenue despite aggressive marketing and high valuations. He states, “[...] That's their conversion rate. That's bad, man. It means that they can't work out and no one else can work out what the hell to sell this on” (58:16). This skepticism extends to the broader AI investment environment, where massive capital is poured into projects with dubious economic returns.

Alternative AI Use Cases

While critiquing the core business models, Zitron acknowledges some value in AI applications like coding assistants. He concedes, “[...] They are valuable in the sense that software engineering loves automating, they love shortcuts” (22:02). However, he remains doubtful about their scalability and reliability, citing issues like hallucinations in code generation that undermine trust and utility.

Furthermore, the episode touches on the controversial use case of AI companionship. Zitron expresses concern over individuals forming emotional attachments to AI, describing it as a symptomatic issue of a “decentralized society” lacking shared physical spaces for human interaction (43:33).

Media and Marketing Criticism

Zitron is openly critical of how media and tech leaders portray AI advancements. He accuses figures like Sam Altman and journalists like Kevin Roose of fostering unrealistic expectations without substantiating the actual technological progress. “[...] The idea that Tech Meme had Sam Altman's gentle singularity. We should be calling 911 and doing a welfare check on that man” (89:55). This, he argues, perpetuates public fear and misunderstanding, akin to previous tech bubbles like the Metaverse and crypto.

Conclusions and Outlook

Ed Zitron concludes with a bleak outlook on the AI industry's financial trajectory. He warns of unsustainable growth models, potential investor losses, and the broader economic impact of an AI bubble bursting. “[...] These numbers are alarming and I am shocked and actually kind of disgusted at some people in the media for not being more alarmed” (63:13). Zitron calls for greater transparency and critical analysis from both the media and tech companies to mitigate the risks posed by current AI economic practices.

Notable Quotes

• “OpenAI will burn probably $12, $13 billion after revenue this year. They also have no path to profitability.” — Ed Zitron (01:10)

• “The current combined revenue of all the generative AI companies is like, and that's including the big tech companies, is about $35, $40 billion dollars. It's insane, man. It's insane. And eventually this has to stop. It has. The growth is not there.” — Ed Zitron (03:45)

• “They've got all the king's horses and all the king's men. You have Google, you have Apple, you have Salesforce, you have ServiceNow. You have all these companies who could not talk about AI more if they tried. Where is the agent?” — Ed Zitron (15:10)

• “No one’s bloody done it. You have all the king's horses and all the king's men. You have Google, you have Apple, you have Salesforce, you have ServiceNow. You have all these companies who could not talk about AI more if they tried. Where is the agent?” — Ed Zitron (37:48)

• “These numbers are alarming and I am shocked and actually kind of disgusted at some people in the media for not being more alarmed.” — Ed Zitron (63:13)

Conclusion

This episode of the Big Technology Podcast provides a critical examination of the AI industry's financial health, highlighting significant concerns about sustainability, profitability, and the broader economic implications of current business models. Ed Zitron's insights serve as a counterbalance to the often unbridled optimism surrounding AI, urging stakeholders to adopt a more measured and financially prudent approach.

Transcript

[Big Technology Podcast Host]

Does the AI business have what it takes to survive? Our guest today says no. That's coming up right after this. Welcome to Big Technology Podcast, a show for cool headed and nuanced conversation of the tech world and beyond. We're joined today by Ed Zitron. He's the owner of ezpr, the host of Better Offline, and the author of the where's your Ed at? Newsletter. He's here to speak with us about his criticism of the AI business and why it may all soon collapse. Ed, great to see you. Welcome to the show.

[Ed Zitron]

Great to see you. Thank you for having me.

[Big Technology Podcast Host]

Okay, so we, we've had some very different varieties of critics on the show. We've had people who've said it's poisoning society. We've had people like Gary Marcus who've said that the progress is gone. We've had in various iterations, folks who've talked about how it can be used by bad actors to do things like enhance viruses. Soon we'll have someone who's gonna come on to talk about escape risk. But you are in a different category. You really think that the business of OpenAI and, and the AI industry is unsustainable? Yeah, this is something we talk about a lot on the show. I'm very familiar with your work and it's great to have you here to discuss it.

[Ed Zitron]

Yeah, it's just all very silly when you look at it. Right now we are sitting there. The most important company in AI is OpenAI. They will burn probably 12, $13 billion after revenue this year. That's based on projections. They also have no path to profitability. They don't have one. They claim 20. The information's reported a few times, like 20, 29, 20, 30. They're going to magically become profitable due to Stargate. Now how will that happen? Nobody actually knows. And Open AI will not tell us because OpenAI doesn't really discuss their revenues other than in really vague ways that go like, we have 3 billion business users. What's that about? When you look at the underlying finances, it's genuinely insane. And it's more insane outside of open AI. The information also reported the Microsoft will only make about $13 billion. Not profit, just revenue on AI this year. 10 billion of that is OpenAI's Azure Cloud spend. 3 billion is them selling Coppola. That's an insanely small amount, man. 3 billion is not a lot of money in the grand scheme of things. They do like 11, 19 billion dollars in profit a quarter and this is on 50, 70 billion dollars of capital expenditures. These numbers are terrible. There's an analyst, it's quoted by Laura Bratton at Yahoo Finance, who said that he only thinks that Amazon is going to make $5 billion in revenue again, not profit this year on AI, they are spending $105 billion in capital expenditures. This is an insane situation. And the fact that I am ever framed as radical or like a pessimist when I'm just doing very basic mathematics, it's kind of strange. I think it says something a lot about media in general, but also the tech industry in general. And people will say, oh, well, Uber lost a bunch of money. Give it the fuck up on that one. Uber lost a ton of money in 2020. They lost like $6.2 billion. I think their worst year on record was like an $8 billion loss. But they had a product and then they used it to fuck over labor forces like they used it to. They just dragged those numbers down. But nevertheless, fundamentally different business and also not a big company. Not. Uber is not the face of the savior of the tech industry because that's what generative AI needs to be now. It needs to be bigger than the smartphone market. It's about 450, 500 billion a year, bigger than the enterprise software market, about 250 billion. What the. The current combined revenue of all the generative AI companies is like, and that's including the big tech companies, is about 35, 40 billion dollars. It's insane, man. It's insane. And eventually this has to stop. It has. The growth is not there.

[Big Technology Podcast Host]

All right, so we're just going to talk through your arguments on this show, and I think that I will pressure test them and we'll just go through some of the objections and like we do. You know, I don't think listeners need to agree with everything that EDIS has to say, but I think I won't call you radical. I'm going to give you a fair hearing today, and we're going to go.

[Ed Zitron]

Through some of these strange, though, and I know that you're not characterizing it in this way necessarily, but the fact that the guy who is like, hey, this is losing billions of dollars and not making that much, I am the one getting the hearing. I know that that's not meant to be a negative characterization, but that my. My pointing at numbers that are out there that are ludicrous is strange and must be tested versus things like, oh, we'll have AGI in two or three years in the New York Times. It's obscene.

[Big Technology Podcast Host]

Well, we test all These.

[Ed Zitron]

And I know you do, but it's just in general.

[Big Technology Podcast Host]

Right.

[Ed Zitron]

It's very strange.

[Big Technology Podcast Host]

Okay, so maybe we'll talk a little bit about the general vibes around AI Absolutely. Later on, but let's just get right into where the value is here. So if this is going to all fall apart, it means that what's happened in AI has to be, I think, by definition, not valueless, but sort of there's a cap to however good it can get. You said in one of your shows, AI today is a $50 billion industry masquerading as a trillion dollar solution from a tech industry that's lost the plot.

[Ed Zitron]

Yes.

[Big Technology Podcast Host]

So let me just throw this out to you. I mean, it seems clear to me that I will be useful for search. You yourself have talked about how search is not a good product.

[Ed Zitron]

I don't agree with that fully, but I know, Keep going.

[Big Technology Podcast Host]

But let's say it's half as good as Google. Google is at a $2.14 trillion market cap. So let's say it just gets half there. Then it's already sizable business.

[Ed Zitron]

You're describing search as a product and search as a business. The largest and most successful search business is Google. Google makes over 100 billion on this a year. How do they do it? Well, it's simple. They own the search engine, they own the infrastructure, they own the advertiser, both the platform that sells the ads and the platform that buys the ads. These things are being mangled by antitrust. You ever notice how there's no other real competition? I think Bing makes like a billion, two billion a year.

[Big Technology Podcast Host]

Well, it's interesting because even in the antitrust hearings, because they're talking about now whether Google will be able to even pay Apple the 20 billion plus a year.

[Ed Zitron]

Yes.

[Big Technology Podcast Host]

One of the interesting details that has been overlooked in those hearings is that nobody, not Microsoft, not Perplexity or whoever it may be, can make money off of search in the way Google can.

[Ed Zitron]

And that to me suggests the. Fundamentally, there's a fundamental weakness in the business to grow to the size that go. Like perhaps the search market is actually a bit smaller. I don't know how much smaller. But you're describing two things, which is search as a product. And I do fully believe that if Google had tried to meaningfully innovate in search, other than ways to make money and ways to screw consumers, OpenAI would have been nowhere near as big, because most people do use it. Because the big thing is, is that OpenAI and generative AI large language models are really good at inferring meaning from a statement, really good's probably a push, but you can give it a vague question like, oh crap, what was that 1971 movie with like some gangsters in it? And. And it will have a much better time inferring the meaning than anything Google search has done in a while. That's a big reason. On top of that, people want answers. And Google has been hesitant, if not entirely resistant to giving answers until Chat GPT popped up and then went, crap. We've got to make a really shitty version of this. And it's still a shittier version of what OpenAI does with search, which I think is a shitty job unto itself because any search result that could be hallucinated is a dodgy one. And I think also Google has just given up any responsibility to their products and to any of their customers. I don't think people realize how much Google has had to do to make search that bigger business. Huge advertising. And I mean they bought. Was it doubleclick? Was it doubleclick way back when, like they bought the Rails for this a long time ago. And. And to your point, no one else has been able to copy it, despite there being multiple other companies that could other than Meta, who has created a competing advertising product. But that's what search has become. Search as a product is very different to search as a business. All told, OpenAI would have to build such significant sales teams, ad tech. They would have to be a very different company because selling advertisements is very different to selling consumer ChatGPT subscriptions or enterprise, I guess. But even then the information's reported recently that that's not going so good either. So we're in this weird situation where, yeah, you could say OpenAI could search GPT could be this. What happened to that branding, by the way? Remember when Search GPT was what it was going to be called? Now it's just chatgpt, but it's.

[Big Technology Podcast Host]

The branding fell away because you just search within ChatGPT.

[Ed Zitron]

I know, but it's like they make this big thing where they're going to compete with Google, but it's like what do you actually. And so sure, they could make a. They've already made a competitor to Google. I think a lot of their success has come from the fact that you can't search on Google search as well. Google search does not understand what you're asking it. Chat GPT often does kind of. Kind of sort of.

[Big Technology Podcast Host]

I think it does a great job with search in the. In certain use cases.

[Ed Zitron]

Yeah, it's.

[Big Technology Podcast Host]

It's replacing Google for me.

[Ed Zitron]

Yeah, and it has for many other people. But that's the thing that just means that Google search is bad. It doesn't necessarily mean chat GPT is good. And it's the inherent. One of the strengths of large language models is inferring meaning from what you're asking it. But making that into a search sized business is an entirely different thing and will cost them tens of billions of dollars. Like it's not something where even if they could do it. Humoring the idea, I don't think they will.

[Big Technology Podcast Host]

Let's talk the idea.

[Ed Zitron]

They would have to do tens of billions. Like Google owns thousands of miles of underground cable. They have content delivery systems all across the world. OpenAI doesn't own a damn thing of their own infrastructure even. This is the craziest thing that got reported recently. The Stargate entity does not exist.

[Big Technology Podcast Host]

Talk more about that.

[Ed Zitron]

It doesn't exist. They haven't formed it yet. Oracle said it on their earnings, it has not been formed yet. So Oracle is allegedly though Elon Musk claims this wasn't true. You know the classic truth guy, the guy who never lies. But he said that this isn't true. But Oracle is apparently buying, allegedly buying $40 billion worth of GPUs to put in the Abilene, Texas site for Stargate the first. I think it's 8 to 11 buildings. I forget now OpenAI who owns those buildings? Who knows. I think it's Crusoe. Crusoe just had to raise a 750 million dollar credit line as well to build it.

[Big Technology Podcast Host]

They're data center builders.

[Ed Zitron]

Yeah. And they're also, they've never done this before. They've never done HP so high performance computing before. It's also good. It's like when you look at the bits, it goes, oh, this is bad. Oracle has agreed to pay Crusoe, I think a billion dollars for 15 years. Like they've, they have contracted Crusoe to do the work. OpenAI According to the information hasn't even signed a contract for the compute in in Abilene. OpenAI has done a great job of getting other people to do the work for them. But if you think building a giant data center is hard, try building all of the ones you will need to make a modern search engine. Perhaps there are efficiency gains, perhaps there are ways of doing doing it differently, who knows. But it's not something where they can just go and now we're a search company as well. It's not that easy. And Sam Altman would love people to believe that. Notice he's not really talked about competing with search though recently. Not really heard much that a few months ago he had that story about ads within ChatGPT as well. Haven't heard any stories about the revenue from that either. That's the thing. Generally when companies are doing well, they tell you and they boast or they leak it surreptitiously in a very obvious way. None of the leaks coming out appear to be positive.

[Big Technology Podcast Host]

Now. Why do you think so? Let's just go to this core issue. Why do you think that generative AI Generative AI can't be a good replacement for search?

[Ed Zitron]

Because right now the unreal, the unreliability of search, Google search right now was already a problem. I think that the core technology of large language models could really help with inferring meaning in search. I think it could at some point be useful in that way. The problem is it's like replacing a bad thing with a slightly less bad thing. It's like, I guess you could do that. But I think that it's pretty evident that because nobody else has done it, including Chat, GPT, OpenAI, even that you can't really replace the business search. But we are getting mangled up in the technology because, yeah, I think large language models are really useful for the intake of information. I don't know about the presentation of information out the other end. I don't think that they're great for research. I don't think that they're great. I've used it for search and been like, this is a pain in the ass. This is not what I want. There's too much crap here. I have to sift through it. I can't trust any of this. So perhaps there are consumers who are just like, I can trust this. Bingo, bango, I'm done. Fine. If that's mediocre with. With piss, I don't know what you call it. So it's kind of like AIO reviews is kind of doing that. It's just such a mess because you can hear me kind of hesitating over the details because it's like, can you replace it as a product? Yes. Is it going to be good at it? No. Yes. It's. You like it as other people do because it understands what you're asking it way better than Google Search does. How has Google not copied that as well? That's the other thing.

[Big Technology Podcast Host]

They are in the process of copying it with.

[Ed Zitron]

AI modes are so crap and AI modes, it's.

[Big Technology Podcast Host]

I'm not saying that they're better than tea is better. I think that the real argument around Google is the models. The models perform quite well on the leaderboards, but you don't see that proficiency when it comes to actually building it into the products.

[Ed Zitron]

I don't think they even do it the same way. Because you ask a question to Chat GPT, it generates a result. With Google, it's like. Or it feels just like a disinterested uncle. He's reading the newspaper with a kid, like, knocking his knee. It's like, what do you want to. I think it's fucking. This here's a bunch of. Leave me alone. Because it's like, AI overviews do not do the same thing as how Chat GPT handles search. ChatGPT spits out an answer for better or for worse. AIOViews goes, all right, is I think the answer with some links, I don't know if they're good. Here's some other links. What do you do here? I don't know. I'm just here to show you ads. And that's why it's so hard to use. Goodbye or hello. Please stay on the page. I need money. It's just a really weird.

[Big Technology Podcast Host]

That is what.

[Ed Zitron]

It's so weird. It's just so strange that you've got these companies with trillion dollar market capitalizations who, who run services that look like a dog's dinner. It's just insane to me. And it's everywhere, right? Did you see the thing on Threads today?

[Big Technology Podcast Host]

Talk about it.

[Ed Zitron]

So Threads. There was. I don't exactly know what happened, but everyone's messages were coming up as the same thing. So you had a bunch of accounts saying, like, I don't know what's going on. It's the same thing again and again and again. Threads is terrible.

[Big Technology Podcast Host]

I agree with you on that front.

[Ed Zitron]

It's just. But that's the thing. I think the reason ChatGPT has been able to make any meaningful progress against search is not because of the proficiency of OpenAI. Pretty, pretty good. UX works clean. Pretty snappy. It's because everyone else has given up.

[Big Technology Podcast Host]

But isn't this how it's supposed to work? I mean, isn't it. No, let me talk it through. Like, isn't it supposed to be that some company gets the lead in something, then a challenger comes through, builds something slightly better, and then puts everybody on notice that if you don't improve, you're going to lose the lead?

[Ed Zitron]

Which is funny though, because you're right. That's how it's worked. I think that that era ended like 10, 15 years ago. I think that they kind of. We've not seen that kind of competition. And OpenAI is actually a great example because to compete with big tech, you need big tech to support you. So you might. OpenAI is a Microsoft subsidiary. That's what everyone needs to just accept right now. And what's happening in the news, which I imagine we'll talk in a bit. So there is no competition. There is an agreed upon substance that they all agreed to sniff and then they all sniff the substance and make money selling it. They all agree that AI is the thing they're doing now. So they're all going to compete in the same kind of soft, punchy way. You've got Amazon and Google backing anthropic, you've got Microsoft backing OpenAI. You have this weird thing where Google filed a suit to try and stop their exclusive deal to sell OpenAI's models, Microsoft's. No one's trying to make better search. I don't think even ChatGPT is trying to be better search. They're trying to sell a thing by claiming it's AI that does something they can't really specify. They're not sitting there going like, how is this a better search product? Because if it, if they wanted that, they would have, they would have built a deliberate search product that represented it as search rather than just an everything search. A search for thoughts which may or may not be correct. A better search. I don't even know what a better search platform is. But that was not what OpenAI started with. That's not where. I don't actually think that OpenAI had much of a product vision.

[Big Technology Podcast Host]

Oh, for sure not. I mean, they talked about how they released ChatGPT as a demo and have sort of iterated on that since.

[Ed Zitron]

But which is pretty much how like I was told by a reporter once that apparently Microsoft saw Chat GPT and the reason they bought all the GPUs was because they wanted it in Bing, that they wanted to do that in Bing. Hundreds of billions of dollars based on being like, what if Bing was better somehow?

[Big Technology Podcast Host]

And that didn't work.

[Ed Zitron]

It did not work.

[Big Technology Podcast Host]

But let's talk more about this because. So I think the thing that's nice about the searching through these bots is that they do, I think, like you've talked about, they give you, they understand your intent better. I think they are getting better at presenting information and they are getting better at linking information. Okay, so, so let's just say that this continues on a trajectory where it does, even if it's not the core intent, it replaces, it replaces a good chunk of search. I'll just make the business argument here and throw it out to you, which is that, yes, marketers really care a lot about the signal that they get from search or the fact that they can, you know, with some consistency, measure their media spend on Google and know if it's working or not. But ultimately, if people move from Google search to OpenAI or to some other LLM search, my anticipation is that the money won't go away. I think marketers have gotten, and advertisers have gotten used so used to spending online that they were. They'll be willing to spend even if they don't get the same signal. Like we saw.

[Ed Zitron]

When you say signal, what do you mean?

[Big Technology Podcast Host]

Like whether people are going and buying the products that they're advertising?

[Ed Zitron]

I just. So I'm clear, your argument is that they'll spend the money even if it doesn't work as well?

[Big Technology Podcast Host]

Yes.

[Ed Zitron]

When has that happened?

[Big Technology Podcast Host]

I mean, I think one example. I'm curious what you think about this is when Apple cut off Facebook's ability to measure whether people were buying after seeing their ads.

[Ed Zitron]

And then Facebook, that was the unilateral transparency thing. So it wasn't just focused on Facebook.

[Big Technology Podcast Host]

Right, Right. Absolutely right. Well, they, I mean, you could also argue that Apple wanted to build its own app install business, which they absolutely did.

[Ed Zitron]

Yeah, their own app.

[Big Technology Podcast Host]

So maybe it was not entirely focused on Facebook, but you'd have to argue that Facebook was a big motivation there. Advertisers are still spending a lot of money on Facebook, even if the signal is a little bit murkier than.

[Ed Zitron]

That's because. That's because Meta has effectively a monopoly on, on social networks, which are a different advertising platform. On top of this right now, OpenAI, I don't even believe has an ad network. I'm not sure your history. You know how multifaceted these things are. The infrastructure is not there. And the reason that Google makes so much money is because they built the infrastructure. And from what I know from the digital advertisers, I know they're. They will try stuff, but they'll try stuff. And if it doesn't work, they'll stick to what they know.

[Big Technology Podcast Host]

Correct.

[Ed Zitron]

Now, if OpenAI can get great CPM, great CPA, fantastic, they've proven themselves. Can they do that at the scale of Google? I don't think they can. And I don't, I don't know whether that. We don't know the exact cost. But we know they're burning billions if they're losing billions of dollars. It don't matter how good their ads is if the numbers don't add up. There's so much they have to spend as well the staff they would require. I really should have brought, I should have looked up the amount of advertising staff that, that Google has before this. But Jesus Christ, they don't have the people and they are still hiring and hiring and have to spend all of this money on salaries. They have to. I think there was a. One of their executives recently said that they have this incredible pressure to grow. Adding the pressure of building an ad network and then building the market for it. Because remember, you can't just say it's identical to search because it ain't right. These things aren't presented as results within a thing. They are presented as answers to a question. Theoretically. Theoretically, that could have a different reaction, a more sticky one. But has anyone fucking proved that yet? Perplexity hasn't. They wanted $50 a cpm bloody arrowvind gets head out of his arm. Just a pie in the sky right now. And I don't know that they have the time, I don't know that they have the time to do this. Nor do I think that they have the resources because they also have to do this and build data centers and build a chip with Broadcom. All the crap they promise for 2026 is bonkers though.

[Big Technology Podcast Host]

I think you're hitting on exactly what the problem is going to be. And we've talked about this on the show a bunch, which is that you can attract, I think they will attract a large chunk, whether it's OpenAI or Google through their AI mode which will evolve. I think we are going to see a lot of search funnel through these large language models eventually. But it's a different format, it's a different experience. It's very easy to mess up. It's not a slam dunk that it happens. Do I think that if they get their advertising money we'll probably follow probably.

[Ed Zitron]

If they get that.

[Big Technology Podcast Host]

But it's. It's an if. It's an if. And I think you're really spot on in pointing out that this won't be a slam dunk. So let's talk quickly about some other uses because you, you know, the promise here or the idea from these companies is that, you know, maybe you, like you said, they're not saying that they're a search engine. OpenAI isn't saying that. So maybe you do some search and you Build a search business. But then let's say your bot can also help people code better. So that's gotta be worth some economic value. So you can amalgamate. Well, yeah. Talk about your view on whether these code copilots are valuable in any way.

[Ed Zitron]

So they're valuable. They are valuable in the sense that software engineering loves automating, they love shortcuts. It's an industry that adores it. But I think that people misunderstand what a software engineer does. They don't just code. Sure, the junior level ones might and there will be some early stage people, but we don't know yet. And the numbers being parroted are nevertheless, as you said earlier, I think this is a 30 to $50 billion TAM total addressable market business. I think that the IDE market development environment, I think that's like a $13 billion one. Like there is a business there. Of course there is. It's. The code has problems and there's tons of studies about it that suggests that there's real issues with it. But I think that's probably the most lasting one. But just because a business exists and is viable in some sense doesn't mean that it adds up to a trillion dollar industry or even $100 billion industry. And indeed the. This is one of the most commoditized things. You've got a cursor came out of nowhere and everyone's like, wow, look, they're going to be sub. Was it 200 million ARR or something? It's like, great, That's a really solid public company SaaS business. No one should be doing backflips. It's changing the world. Is it? It's making developers faster. Is it? How is it doing it? Which developers? These questions, they really harsh the flow. So people don't tend to ask them too much. But one of the common misinterpretations of my work is, and I've definitely said it like a year ago said it's useless, there are use cases. It's just they're here. Like the industry is this big and everyone's acting like it's the biggest thing ever. And it's just. It's not like they want it to replace coders. It's actually not going to because of the hallucination problem, because of the probabilistic nature. There was this insane blog man that was on tech meme. Whereas God was like something about AI critics.

[Big Technology Podcast Host]

Oh yeah. And he used my AI Skeptic friends are all nuts.

[Ed Zitron]

Yeah, I ran that through a couple software engineers. Like Carl Brown over Internet of Bugs. And they just kind of fucking laughed at it because he was saying something and it was said, oh yeah, mediocre codes fine. Is it now? Is mediocre code fine. How do you think, like Karl Brown from Internet Bugs brought up a heartbleed that was like one thing that a bunch of software engineers missed for years in an open source product. Just because we, we as human beings can catch things doesn't mean we will. And just because it might be able to catch something wrong with your code doesn't mean it will either. But I trust a human over that more. If we're turning ourselves over to something we know to regularly get things wrong, I don't know how much infrastructure you can turn that over to, which is the only way you're getting to these massive revenue streams. Unless you can really rely on this. They've already got code automation things they hadn't before. Large language models. So yes, use cases. But how big are we really meant to believe that curse is going to make? 5 billion a year? Is that going to happen? Hey, is Cursor profitable? Is anyone asked whether Curse is profitable? You go and you see like a company like you dot com. Everyone's saying, wow, they got a valuation of a billion dollars, annualized revenue of like, I'm going to misquote this, it was like 12 million, $20 million. That's insanely small, man. This is crazy. It's just nonsensical almost. And everyone's saying that because we are here, we will be 70 miles in this direction in two years. It just confuses, I guess. It doesn't confuse me. I think people want it to be true.

[Big Technology Podcast Host]

Well, let's. That hits on the question of whether you think these models are done with getting better. Because there's like undeniable. There have been undeniable leaps from something like a GPT3 to a GPT4. And so I think you get an environment.

[Ed Zitron]

But when did GPT 4.0 come out?

[Big Technology Podcast Host]

Okay, let me just finish the question, then you can shoot it down. I would say that there is, you have an environment where you get the $12 million valuation funding or the $12 million in revenue and the billion dollar valuation where you have venture capitalists. I'm not going to stand on the table and defend venture capitalists, but where you have them say there is potential for this technology to, to get better. And therefore if this company continues to do what it's doing and the technology gets better, then maybe they can hit that market and they'll bet on 10 of them. And if one of them actually hits where they think the puck is going, excuse the sports metaphor, I get you. Then they'll be well rewarded for it. And so that's why I think you're seeing this environment. It's all predicated on the belief that these models will get better. So I am curious to hear your perspective on why you. Do you, do you factor that into your analysis or do you think it's kind of done?

[Ed Zitron]

I think the word better is where we need to start. Okay, what does better mean? This is actually a point made by Jim Cavallo at Goldman Sachs last year. It's like, oh yeah, these models get better. But what does better actually mean? We look at these benchmark tests which are built specifically because these models can't really do regular testing. You can't really give them human testing because they don't do, they don't do the things that they're meant to do. So better does not mean actually it might be Darren Acamoglu from MIT who said it was in the same Goldman report. But it's like, better does not mean more capabilities. It does not mean that these models now can do a new thing. Even reasoning what happened there. What I mean, it allowed some more, it helped with some coding things, sure, but. And there was some growth, but it's. To what end? What can we do now? What is the new thing? And I think that's the craziest thing. I don't, I don't know what I'm meant to be. I'm a. I love news crap. I knew I love gizmos and gadgets and all that shit. I. If there was a way that chat GPT could do something for me, I would make it do it just because I'm like, cool. This is why I love technology. I love doing things. What's new? What's new? And if the argument is, look, it's improved coding by xyz, awesome. Describe it in that term. Describe it in the terms of boring software as a service or cloud compute. Talk to. Talk about it like you talk about Docker. Talk about it like virtual engine. Talk about it like a technology that's a branch off. Don't talk about it like it's replacing everyone forever, always, because it isn't doing it. So I, by the way, you're completely right with the VCs. They're doing exactly what they've always done, which is make a bunch of bets, talk them up. See when you get in, like, see what happens because that's venture capital.

[Big Technology Podcast Host]

That's it.

[Ed Zitron]

That's the root of it. I'm not defending it either, but it's. They're not doing anything different. The problem is, is that we're in hysteria. We really are. We're in a hyster. I had someone tell me, a source tell me that there are. It's very rare that venture capitalists see the books, the actual accounts, and they almost never see the code base.

[Big Technology Podcast Host]

That's wild.

[Ed Zitron]

It's fucking crazy, man. And it only gets worse because as deals get more popular, it's like, you don't want to do it. I got five more assholes over here who will. So. Which is the mark of a classic bubble. So it's like nothing about what I'm writing or saying comes from a place where I'm like this, this is something that I've walked into and said, this sucks. I hate it. But. Because when Chat GPT came out, I dicked around with it for hours and hours trying to find out why everyone was so excited. So excited. Everyone was so excited. I'm like, okay, so it can generate crappy text. Like this is like, this is the most like 20, like 19 year old at college Aztecs. No wonder it can replace college students who aren't taught to write. It writes like them in the same kind of bland intro body conclusion way. Okay, not a business. But the actual use cases of this stuff have never emerged. They've never emerged. The reason that we keep hearing about agents but never about what agents can do is because the most common feature of agents is that they fail. There was a salesforce paper that came out fairly recently that said, I think that they just categorically break down on multi step processes. Like they only complete like 30 something percent of them. Multi step processes, by the way, referring to tasks in general, could you think of just one thing? But they failed at a remarkable amount of one step. 1.

[Big Technology Podcast Host]

But you're, you're answering the question about what happens when the models get better.

[Ed Zitron]

It's that they're not getting better.

[Big Technology Podcast Host]

But this is the.

[Ed Zitron]

Well, well, I think you're saying also when.

[Big Technology Podcast Host]

Look, let's go step by step, right? If the models get better, then they're able, they'll be able to handle these multi step processes in a way that they can't today because they are brittle.

[Ed Zitron]

If my grandmother had wheels, she'd be a bicycle.

[Big Technology Podcast Host]

Okay, I hear what you're saying, but like I said, let's circle back to the question I asked you at the beginning of this Conversation which is like you're pretty confident that there's no more improvement because I asked you about improvement and you said there's no such thing as improvement or we can't feel improvement. But now you're saying.

[Ed Zitron]

I'm saying improvement is over. Improvement is a. Is a metric that they have gamed with the benchmarks.

[Big Technology Podcast Host]

I'm not. So this is interesting with the benchmark side of things. Yeah, I really think that, like they're useful in some ways, but they're not the be all, end all. And it's weird to talk about and I'm sure you have a response to this. It's weird to talk about the vibes of the models, but like really is. But let's do it. I do think that you can with GPT3.03 from OpenAI. It's definitely the vibes are better than GPT4. It just feels like it's able to do more.

[Ed Zitron]

Tried O3 out the other day. I took a photo of a thing I had hung up and I said, how much space from the bottom of that photo of that picture, the poster to the floor. It took four minutes. It wrote multiple Python scripts to give me the wrong answer.

[Big Technology Podcast Host]

Well, this is why. I mean it is interesting that. And this is why I think people are talking about how they're going to be good at some things and not good at others.

[Ed Zitron]

Okay.

[Big Technology Podcast Host]

And so there'll be some, like capabilities where they're going to be quite effective and some like the one you.

[Ed Zitron]

And the thing is that's a reasonable position if that was how this industry had been sol.

[Big Technology Podcast Host]

But they're not selling it.

[Ed Zitron]

Yeah, exactly. If it was. No, I really want to say except.

[Big Technology Podcast Host]

Sundar Pichai is from Google talking about Jagged Intelligence.

[Ed Zitron]

But I think jack off intelligence. Fuck. I find that so disgusting. That man last year he lied about what agents can do. It was during IO. He said, oh yeah, you're going to have an agent that will be able to like do a full shoe return with the thing with your email. And they went and that was theoretical. What the. Why I can't go and lie to the bank. Why can he lie to the market? It's just I think though, getting back to the point because I think it's important says if they were selling this as. Yeah, this is kind of unreliable but interesting tech and we're expecting it to. There are some things it can't do. There's some things you shouldn't rely on it very clear about that. I wouldn't hate it if it was just like this is what I. Until you get to the stealing from everyone and horrible environmental stuff and then it gets even worse again. But putting that aside, if this was being sold as like an experimental branch or even just a industrial use of cloud compute, okay I would, I wouldn't judge them for that. I judge them for everything else. But they're not selling it this way. You've got Andy Jassy claiming, oh yeah, we're going to replace an indeterminate amount of people at an indeterminate time in some way or somehow, I'm not really sure how, but it's going to happen. And it's on the front page of fucking Tech Meme. It's insane. The idea that Tech Meme had Sam Altman's gentle singularity. We should be calling 911 and doing a welfare check on that man. That thing was fucking insane. If I said that they would check me for a concussion. Some of the things Sam Altman suggested that we'll have data centers that could build themselves. Just that's the thing that is the real distance because you've got what large language models can do. And as far as them getting better, better how they'll increase those percentages there is in very clear and Gary Marcus was just on talking about this. There's a very clear gap between what a large language model can do and what it needs to do to be reliable. And that gap I think is much larger than people realize. It's the classic problem with all AI with self driving cars even where it's like it's not the fact that it can't do some things well, it's that it can't reliably do anything. Self driving cars require someone watching them at all times just in case. You can't do that with chat. GPT is too many of people. So it's just this interesting industry wide cognitive dissonance I guess. It's insane when I talk about this stuff it makes me genuinely worried how many people have been taken by it.

[Big Technology Podcast Host]

You brought up this statement by Andy Jassy, by now it'll be a few weeks old about how he wants to replace. He wants to. Well, he wants to replace people with AI or believes that it will be a people replacement and I think that is. So I've talked, we talked about search and coding. I think the thing that's been unspoken so far is that when it comes to the valuations for a lot of these companies they're going to need to have to replace full time employees or at least the work that a full time employee does in order to be successful.

[Ed Zitron]

Agreed. And people either want completely autonomous or they want Jarvis. They want to be able to say I need you to look up, blah, blah, blah. Okay, give you an example. Manus, Is it Manus? Yeah, it should be maintenance. I asked Mainus to look up every article written about me in the last two years. It could be a list of links in the spreadsheet and I probably guess like 100 of them is what, what the actual number. 11 minutes later and like a ton of Python. These can love Python. It gives me 11 links, right. I tell it, you missed a few. Gives me another nine. After another 10 minutes I think it was is this, how close is this replacing? Who is this replacing? Because it's not even replacing offshoring, which I think is what companies really will plan to do. They just want to ship people overseas and get cheap labor. It's always been the case. Google loves it. People have talked to at Google, they're saying, yeah, they're just getting rid of people and replacing them. Contractors in India or in other countries in the global south as well. It's very strange what's happening. I think that I'm actually shocked that so many reporters are still saying agent with a straight face because what job is being replaced? Code is. No, sorry, it's not. You've got companies firing people and claiming AI. But notice that none of these big sexy Kevin Roose stories about replacing people actually include a single fucking person replaced. Now, Christopher Mims had a story in the Wall Street Journal about a year ago, a really good one, where it was artists, art directors and copy editors who had been replaced with AI. But the real story was they had been replaced with shittier versions of their product. Their process was not replaced, their job was not replaced. They were basically contractors rejected by idiot business idiots, as I call them. People that don't really understand the process of their work. And it's fucking tragic. But there are some jobs that will get replaced. Not as many as they're saying, by people who are assholes, who don't respect their customers, who want to do a shitty job and always will. And they would have found another way to do it. They would have gone on 99 designs, they would have gone on fiverr. They would have found cheap labor to do the labor that they don't respect. But there is right now, and I don't think there's going to be any replacement of labor at the scale that they're discussing. My evidence is nobody's bloody done it. You have all the king's horses and all the king's men. You have Google, you have Apple, you have Salesforce, you have ServiceNow. You have all these companies who could not talk about AI more if they tried. Where is the agent? Because if they did this, if they actually were doing the thing they're claiming, they'd be making tens of billions of dollars extra. They'd be making an absolute shit ton. The information reported a few months ago that Salesforce does not expect any growth from AI this year. That is absolutely bonkers for a company that's rebranded and I paraphrase here, as an agent first company, it feels like the most egregious lie I have ever seen told in business history. Just completely obscene and people are lapping it up and it's insane.

[Big Technology Podcast Host]

Well, I think with this software as a service companies, there's so much broken in SAS today that you can put AI in there potentially and like paper up some of the problems with like systems talking to each other and trying to synthesize information that you have in your systems to make sense of it because it's spread all over the place and takes hours to pull reports. So that's a possibility and maybe that's economically valid.

[Ed Zitron]

Your argument is that their systems are so poorly designed they can't put AI in them yet?

[Big Technology Podcast Host]

No, my, my argument is that speaking of broken products that AI fixes, they might be the most broken of all products.

[Ed Zitron]

Yeah.

[Big Technology Podcast Host]

With an opportunity for AI there.

[Ed Zitron]

Fully agree. And also if anyone was going to make money off of it though, one of the companies. It's not like a situation where one company is ahead of everyone else. OpenAI isn't ahead of everyone else other than scale. And I would argue they got that because literally every single media outlet has been talking about AI for three years. And when they talk about AI, they say chat GPT. It is the world's best marketing campaign ever. Sam Altman is a genius for that. And he's also like the business idiot whisperer. He can talk to guys that run companies that don't know how their companies work and just be like, yeah, we're going to replace everyone. It's going to take two minutes. It's going to be the best thing. Donald Trump sounds like Trump. Yeah, no, he really is like he list. He's like the soft spoken Trump. But he. It's just, it's so strange when I get kind of animated about it because when you start talking about it, I'm not even saying anything, I'm saying some objective statements. To be fair. But when you just say, like, they haven't done this yet, they haven't done this yet, there really isn't evidence they can do it. Like, really there isn't. They don't have. It's not like they have a whiz bang moment. Like you could. Waymo is imperfect, but you can get in a car in San Francisco and it will drive you around. And you could do that a few years ago in very controlled spaces. But we don't even have a controlled space where an agent's doing something really cool. And I think the closest they're going to get is like an agent that can do purchasing on a platform. And I think that that's just because they'll connect APIs to APIs. We're not. That doesn't feel terribly far away. But that's also not a trillion dollar industry.

[Big Technology Podcast Host]

Ed, are you, Are you potentially underrating the, the bureaucracy part of this and the fact that, like, big organizations, which this could help, they move slow. There's bureaucracy, there's approvals, there's owners of different groups. Like, it's tough for them to do anything. So maybe it's a people problem and not as much a technology problem. Maybe it is, as you would put it, a business idiot problem.

[Ed Zitron]

I would buy that if it was not everywhere and no one had done it. If it, if it was a few people were. I, I understand the argument. It's like if there were a few people that had done this and like, they'd done a ramshackle one, but it was kind of working, it's like, ooh, that would be cool. Would it? It's still like if someone was doing it in a smaller situation, I don't know, wouldn't open AI be doing it? Like, if just real blunt, Wouldn't Anthropic be doing it? Wario Amaday's out there saying, oh, yeah, we're going to replace, like, what, 10 to 20% unemployment, 50% of.

[Big Technology Podcast Host]

I don't think he said. Did he say unemployment? I know that he said 50% of.

[Ed Zitron]

White collar jobs, 10 to 20% unemployment as a result of this. If I'm wrong, I'm wrong. I apologize. But the 50% thing was on. Alison Morrow from CNN has the best piece.

[Big Technology Podcast Host]

Yeah, yeah, we actually read that on the show afterwards. She is very good.

[Ed Zitron]

Possibly the best living business journalist. She's absolutely fucking incredible. So the thing is, wouldn't OpenAI have these agents if they could do this? Wouldn't they be doing this? Indeed. Someone once made an argument to me online that I actually found quite compelling, which is why would you sell AGI if you made it? Why would. If you could make an agent, sure, you could sell it to everyone or you could just run an incredibly profitable business with like nobody. The one person billion dollar company Wario Amaday's been promising everyone next year. Next year. Oh, sorry, it's in 2026 with the chip from Broadcom. That's another thing with Stargate, of course, the Stargate in the uae. Also the device from Joni. I've. That's also coming. All of this is going to happen in what, six to 12 months. I can't wait for the future. But the thing is, where is. Where's the beef? Where's the thing? Where's the money even? But the money isn't there, the product isn't there. And anyone putting this to people who love AI quote unquote, where's the thing? Why are you actually excited about not what could it do? What does it do today that even makes you. And if the answer is wow, it's kind of like a living encyclopedia.

[Big Technology Podcast Host]

Okay, Can I give you a different answer to that?

[Ed Zitron]

Sure.

[Big Technology Podcast Host]

And this is again, this is. We've been talking a lot about use cases. I do want to spend a little time talking about the business of these companies, but I think it's worth bringing up one use case we haven't brought up yet which is companionship. That is the number one use case. I think surprisingly there's an HBR article that put pointed that out.

[Ed Zitron]

Was that a rank? I thought that that was just a list. I didn't know it was a ranking.

[Big Technology Podcast Host]

No, it was a ranking and it became number one.

[Ed Zitron]

And it's clear that is not a business.

[Big Technology Podcast Host]

It is clear. Well, people are becoming friends with these bots.

[Ed Zitron]

Sure.

[Big Technology Podcast Host]

They're paying for them.

[Ed Zitron]

Absolutely.

[Big Technology Podcast Host]

It seems and I'm not a big fan of the fact that people are replacing oh, I don't love friends with AI friends but they're doing it.

[Ed Zitron]

It's. Oh, it's a sign of something wrong. It is a. We are a decentralized society. We do not have the shared spaces where we would regularly meet people. Tons of people remote working, which is great. But non walkable cities means that people aren't meeting people regularly. Yeah, that is a use case. We don't know the scale of it. If I had to actually guess, I think the majority of people using Chat GPT are using it like Google Search. I'm deadly serious. I think that there is a growing amount of People using it. And I think it's a deeply unsafe technology. I also think that is one of the most easily commoditized businesses in the world.

[Big Technology Podcast Host]

I don't make AI friends or AI search.

[Ed Zitron]

I think. Well, kind of both. But really AI Companions feels like something that chat GPT again, because they are all over the place with all their use cases. It's something that they're getting because they are the biggest name said to everyone at all times. It's something that can be replaced by any number of other things. Hey, did you read the story about Meta and how you can have John Cena sext your child? Oh, man. You didn't. No, there was a story, Jeff.

[Big Technology Podcast Host]

I did read that.

[Ed Zitron]

Jeff Horwitz, the ghost, the goat himself, the Wall Street Journal, where you could have pedophile conversations with Meta's AI. So people are using Meta.

[Big Technology Podcast Host]

Wait, was it. Was it.

[Ed Zitron]

You could explicitly have it have. You could say you were underage and it would have a conversation with you. I think they've closed the gap now. It's a great story, incredible journalism by Jeff. But it's like, yeah, people are using this and people are likely using it in sick ways and it's disgusting. And hey, imagine if we'd have regulated tech. Imagine if we'd ever done that, if we had like an EPA for tech, if there was any restraints on these companies. But no, there aren't, because what. What if we didn't have growth forever. But nevertheless, it's a use case. But what does that use case prove exactly, other than this can do that and people are somewhat easily fooled.

[Big Technology Podcast Host]

It's the, the jet. The use case that Jeff Horowitz brings up in the Wall Street Journal is not one that I think is going.

[Ed Zitron]

To be no common companionship.

[Big Technology Podcast Host]

Companionship is.

[Ed Zitron]

Wait, you don't think that. That a teenage, A horny teenager would try and talk to.

[Big Technology Podcast Host]

I hope that. I hope that the build.

[Ed Zitron]

I hope I really. No, I genuinely mean this. I'm rooting for Meta and everyone to stop this. They need to. It's horrifying. But yeah, that's a use case. Is it a business? Is it not something that can be easy?

[Big Technology Podcast Host]

I would argue that if they get friendship right, it is a great business.

[Ed Zitron]

Because who is they in this case? And how big. How big could that be?

[Big Technology Podcast Host]

I think could be a big one. I mean, again, this is not. This is not the direction I'm rooting for the technology to go into. But if you have AI that replaces a friend for you or is your companion you Would easily. I mean, $20 a month, I think that would, that would be an easy subscription to charge.

[Ed Zitron]

But let's get into the business thing though, because I posted this earlier and I mentioned it earlier. For this to be as big it would need to be. Size of the software, is that because of the funding? Sorry, you say it's because of the investment in infrastructure. It would have to be bigger than smartphone markets at 4,5500 billion a year. Bigger than the enterprise software. We can take that side if we just focus on the consumer use cases for that to happen, this business would have to. For OpenAI. I think they've estimated they're going to estimate these wank. Just total nonsense. I think they've said like $126 billion of revenue a year by 2029 or something like that. And just to be clear, Netflix made about $39 billion in subscriptions last year and Spotify made $16 billion. So you're telling me that whatever this market is is going to be bigger than both of those doubled? Is that the plan? No, I'm not saying you. I'm just saying.

[Big Technology Podcast Host]

No, I want to answer this question because I'm the one that threw it out there. Look, I think that we are inevitably going to see some of the funding that's gone into this industry go to zero or very low. Without a doubt. Yeah, some maybe. I mean, if you take it in aggregate, we'll see if it pays off. Some will win, I think, but many will lose.

[Ed Zitron]

What does winning mean, though?

[Big Technology Podcast Host]

I mean, they'll get their investment back.

[Ed Zitron]

Oh, okay. Yeah, that worked out for scale. Or they'll scales investors.

[Big Technology Podcast Host]

Exactly. So there will be, there will be big, big exit. I think OpenAI will. Will IPO at a certain point.

[Ed Zitron]

I think that that is an astonishing leap of logic.

[Big Technology Podcast Host]

Well, because, okay, you're talking. You want to talk about the structure and the fact that they may never be able to even if they go public.

[Ed Zitron]

Do you think that they. These horrifying books are going to look good to the markets? There is nothing in the markets that looks like this dog. A company that burns 5 billion, that loses $5 billion by spending $9 billion.

[Big Technology Podcast Host]

I don't know. I mean, Coreweave is up like an insane amount since its IPO because people are interested in a story. So that's Core Weave.

[Ed Zitron]

That's cool. They don't lose anywhere near as much as OpenAI.

[Big Technology Podcast Host]

There are 81 core weave itself, which is literally just an infrastructure company that sort of RESELLS Nvidia chips. 81. Well, you. You tell me. $81 billion market cap. And since their IPO, they're up 325%.

[Ed Zitron]

Absolutely wild. So they have a very. By the way, most of which is owned by like Nvidia and Magnetar.

[Big Technology Podcast Host]

Right?

[Ed Zitron]

So Core Weave will probably raise another $10 billion by selling another share sale they can plug away for a few years. But what happens if the AI bubble bursts, if growth slows? Core Weave is a business heavily built on GPUs, on raising money based on. They. Here's an interesting question. Is it round tripping when Nvidia sells GPUs to a company that they own part of, that they own part of the stock in that they have a $1.3 billion project Osprey Cloud deal with? Is it round tripping if they sell them the GPUs that the Core Weave then takes the GPUs, raises money from institutional investors based on the value of those GPUs, and then uses that money to buy more GPUs from Nvidia? I don't know, maybe if we had a government to look into that. But fundamentally, Core Weave and OpenAI are even more insane businesses. Core Weave owns stuff. They have actual buildings now. I don't think that they're ever going to scale. And I do think that that dog will die and I will dance. Mostly because people. People think that stock valuations actually change anything. About my argument, which that. That article really drove me. I mean, mouth of madness.

[Big Technology Podcast Host]

The reason why I brought it up is you said, is the market gonna read the books about opening.

[Ed Zitron]

But.

[Big Technology Podcast Host]

Let me finish though, hold on. But I'm just saying that the market.

[Ed Zitron]

Can go with a story, but OpenAI has no assets. Really? They don't. They. Microsoft owns their IPO, their pre. Sorry, their IPO, their intellectual property. They own their. They. OpenAI owns no infrastructure. They have their staff, they have the research. Wait, Microsoft also has that. They have the exclusive right to sell. No, wait. Microsoft can also sell their models. They don't own Stargate. They don't own the GPUs within any of the servers. In fact, they don't even make enough. I refer to them as a banana republic because they require in exterior money to come in constantly. Because when you look at what OpenAI is, they don't own very much of anything. They own part of Core Weave. They had about $350 million worth of core Weave stock. That's. That's fun. By the way, open AIs deal with core Weave is pretty Much the only way that Core Weave can raise more money. So hope nothing happens with OpenAI. That's the thing. OpenAI is an asset light business with research and IP that's owned by another company. They don't have much to trade other their name. And their name is insanely strong. They really do. But as a company, they would have to, at ipo, expose themselves in a way that they never want to because they would have to say all of the material deficiencies within the company. They would have to list the genuine risks, and the risks would be every single thing I'm saying. They would say core. We've had to amend their S1 to add the counterparty credit risk from OpenAI. Because OpenAI, if they stop paying Cor Weave, Corweave, doesn't get a bunch of their revenue. OpenAI starts paying Core Weave in October 2025, just as Core Weave's second loan, DDTL2, starts requiring them to pay probably more than OpenAI will be paying them. This is the systemic risk.

[Big Technology Podcast Host]

I'm talking about 500 million user consumer.

[Ed Zitron]

Product that loses them money, that converts horribly.

[Big Technology Podcast Host]

All right, I want to talk about that. Let's take a break. And we'll be back talking a little bit more about the infrastructure costs of OpenAI and what ChatGPT is underneath the hood. We'll be back right after this. And we're back here on Big Technology Podcast with Ed Zitron. He is the host of the Better Offline podcast. You could also get his newsletter at. Where's your ED at? What's the.

[Ed Zitron]

Where's your ED at?

[Big Technology Podcast Host]

Where's your Ed? Great domain name. I know. So let's talk a little bit about the money that OpenAI loses. And so I've been listening to your podcast and whenever someone brings up this argument that they will learn how to deliver what they have today more efficiently, your next line is something like, I will squash you like a bug or I will compress you.

[Ed Zitron]

I would like a cube.

[Big Technology Podcast Host]

Cube in a car.

[Ed Zitron]

Yeah, yeah, exactly. That's. That's accurate.

[Big Technology Podcast Host]

So do that to me, Ed, because. Because, I mean, the stuff is without a doubt getting cheaper to run.

[Ed Zitron]

Why do you say without a doubt?

[Big Technology Podcast Host]

Because if you look at the. I mean, you could just look at the way that they're. Oh, shoot. Now you got. No, but that's. If you look at the. What the price that selling this stuff at.

[Ed Zitron]

That doesn't mean a goddamn.

[Big Technology Podcast Host]

But what about. Okay, so now let's. So here I am in the. In the trash compactor. But But I mean, if you think of. You don't think so. Do you deny that there's any algorithmic efficiency being had within these?

[Ed Zitron]

I'm sure they're trying, but the one public.

[Big Technology Podcast Host]

You think that this is sustainable? They had. They were selling so GPT4 open AIs. GPT4 was 3 cents per 1000 tokens.

[Ed Zitron]

Okay.

[Big Technology Podcast Host]

Prom tokens. O4 mini is. It's a. What is it? A dollar 10 per million tokens. It's much cheaper. Okay, so you think that they're just losing more money as opposed to becoming more efficient in the way.

[Ed Zitron]

Maybe there's some calculation where they're losing less money, but they're still losing money.

[Big Technology Podcast Host]

There have been. I'm going to get a little out of my depth here because I'm going to talk about model architecture, but there have been architectural innovations that have made it cheaper to run these models, like the mixture of experts.

[Ed Zitron]

When you say these models, which are you referring to?

[Big Technology Podcast Host]

I mean, you could talk about big foundational models.

[Ed Zitron]

Okay. But we're talking specifically about OpenAI's, so.

[Big Technology Podcast Host]

I think they do use. I mean, let's just talk about the mixture of experts model.

[Ed Zitron]

Right.

[Big Technology Podcast Host]

So instead of lighting up the whole model to get an answer, they will channel your query into the area where they think the model could answer. I mean the, the folks who built Deepseek, it seems like that was a big part of the way that they were able to make it cheap.

[Ed Zitron]

Right? Why do you think? Okay, I shouldn't really be answering the questions to your podcast with Deepseek. Isn't it weird that we didn't really see any efficiency gains discussed by a single one of the model companies? That none of them even seem to do the same thing other than Perplexity releasing like a 1776 version of R1 without the Tiananmen Square thing. Just one of the. Aravind's friend. He's like. He is so, so lame.

[Big Technology Podcast Host]

Okay, you brought this up a couple times. Just let it out about Perplexity. What do you like about them?

[Ed Zitron]

Well, first of all, they're an insanely badly run company. They. They did like 35 million they lost in. I forget exactly how much they lost, but they did refunds or discounts like $30 million. They're literally giving money away to make people use it. And even then they only have like 50 million users. I also think that as a CEO, Aravind just goes and says shit. That is just annoying. He just. He could be.

[Big Technology Podcast Host]

I'm surprised that you're saying that. You want him to behave better.

[Ed Zitron]

It's not. I want him to behave better. I wish he'd just be more direct about what perplexity can do, but every fucking few weeks he did this whole touchdown dance after the Google search trial and then nothing else. He's not. It doesn't feel like he's trying to create a compensation to Google. It feels like he's making a Silicon Valley hero story out of himself and it's boring and lame and it's a bad business. Give it up. Okay. That means. I don't mean like shut down the company, but he's good at raising money. I guess. But back to the. Back to the model thing and the efficiency thing. Yes, they are losing money because it just. Real easy one. They would be saying if they weren't. You think that Sam Altman, if they had managed to make this profitable, would not go out there and tell everyone? He absolutely would also. He'd be telling investors immediately. They're one of the great reports of the information. I quote them a lot because they're doing some of the best tech journalism out there. Which reporter it was might be Anisa Gardesi or Stephanie Palazzo? It's John Victor over there. He's excellent and he's gonna kill me. Corey Weinberg's done some excellent work on coif. There's also a new person there who, I'm forgetting who did.

[Big Technology Podcast Host]

Okay, that's a good number.

[Ed Zitron]

No, but like they've got like a really excellent team. But where was I? You would get leaks that say that they've gone profitable and that would be.

[Big Technology Podcast Host]

Well, I don't think they want to go profitable. They're just trying to. At least at the moment. Most startups at this stage don't want to be profitable.

[Ed Zitron]

OpenAI stage, I think so they're on like the equivalent of like series D or E. That's absolutely. When you go profitable.

[Big Technology Podcast Host]

Okay, so again, let me just.

[Ed Zitron]

And then they need to go public.

[Big Technology Podcast Host]

I'm going to bring up their side of it just for sake of the argument. I think what they're trying to do is get this technology in the hands of as many people as possible and they understand that it's a more capital intensive technology than most others and, and so therefore they're not profitable.

[Ed Zitron]

So that they. But I don't think there is a magic profit.

[Big Technology Podcast Host]

But no, that's, that's what I was going to bring up. I don't think there is a switch that they could flip today and be profitable and deliver the same quality of models. I think they just like Switch Chat Chat GPT to GPT4 and potentially be profitable.

[Ed Zitron]

Maybe they. Sam Altman has suggested that they would take away the model selector months ago. He likes to say stuff and then just they disappear. Gets the articles, nothing happens. Very good for Sammy. It's the thing is I think that what's happened is everyone thought about a year and a half ago that this was going to change. It was going to because there was that big jump from GPT3 to GPT4 to GPT4o there was the multimodal side. It was like a. Oh, this is really interesting. The voice mode was interesting. It's like, oh, I can extrapolate from here that we made this big ass leap. So in six months we're gonna be here and then six months after that. Except it's like in six months we're gonna be here and then maybe we're here in another six.

[Big Technology Podcast Host]

For listeners, Ed is doing the very.

[Ed Zitron]

Incremental, doing like a very small movement. So that's the thing, I think that they're all wrapped up in it. And yeah, open AI is absolutely trying to get as many users as possible. The problem is if you're losing money on each one and also their conversion rate. Here's my favorite open AI station. Well, more of a question I always ask, which is why do they not show monthly active users? They talk weekly. And the reason is because if you compared what their real monthly active users would be, 500 million weekly. So I'm going to guess 700 million monthly divided by the 15.5 million customers that pay for it. That's a dog's doo doo of a conversion rate. That is so bad.

[Big Technology Podcast Host]

So you're saying that they're giving the lower number that's more active because they don't want to make it seem like very few convert.

[Ed Zitron]

Don't want to. They don't want the conversion rate out there. They don't want people to say, oh, you have a conversion. I can't do math very well. Me and, me and Chat GPT share a problem.

[Big Technology Podcast Host]

It's yeah, just throw a number up.

[Ed Zitron]

No, but be very confident at 2%. Ish. Like a really. Yeah, bullshit conversion rate for the most notable company in the most notable industry with all the press and all the marketing. That's their conversion rate. That's bad, man. It means that they can't work out and no one else can work out what the hell to sell this on. Indeed. Sam Altman loves to say, oh yeah, I can't wait to See what you build with it, mate. What are you building with it? You're the fucking owner. And they want their API business. It sounds like also weirdly, Anthropic is doing better on API. They're selling more. A larger percentage of their business is API, but they still lost like $5.2 billion last year. It's completely insane, but it's. It's just so strange because you can have something this big that fails. You can have something this big. And when I say fail, I don't mean chat. GPT goes down and everything and all the people in the building get thrown out. It would be somewhat messier. And I can go into that at some point. But I think that we are in a moment of mass delusion where no one really wants to talk about these numbers, because when you talk about them, they're scary. And here's why. Okay. Magnificent Seven stocks make up about 35 of the US stock market. 19 of that is made up by Nvidia. Nvidia's revenue, I believe, is like high 80s based on GPU sales. Data center revenue and lost earnings from Nvidia was below analyst expectations. No one really wanted to write about that one because Nvidia is pretty much holding up the stock market on some level. It is. Every time Nvidia earnings come around, there is some story on, like, take in from Baron says, I love Nvidia. And then everyone else says, I hope that this is good. It really is like, I hope that this is good.

[Big Technology Podcast Host]

I think you're right about that.

[Ed Zitron]

And the reason Nvidia is making all the money is that everyone's agreeing to buy GPUs today. And so a couple weeks later from this, obviously Amazon said something that they're using the. Someone. It might have been anthropic. Forgive me if I'm wrong, but they're using 500,000 trainium GPUs their own. What happens if Trainium takes a meaningful chunk out of Amazon spend with Nvidia, that's a chunk of revenue gone. What happens if Microsoft's data center pullback means that they eventually finish? Because I'm assuming that they are retrofitting Blackwell chips into. Into their previous service. I would human that argument. Open AI is if Abilene, Texas goes well, which I don't know if it will for that's $40 billion of revenue once for Nvidia, we are basically saying that Nvidia will continue growing because it's not like Nvidia could just keep doing this. Well, the market requires growth forever. Nvidia. We are saying that within the next year or two, Nvidia will be making a hundred and or more billion dollars in GPU sales. And the year after year that it will be 120, 150 a quarter. That's. I'm the crazy one for suggesting that's bad.

[Big Technology Podcast Host]

Well, I think that this is all.

[Ed Zitron]

Dependent on one thing. The continued purchase of GPUs for generative AI. What happens if that's not the case? What happens if. I don't know, there's. Say the efficiency gains are there. Say that happens. Say that Google there's. They mentioned that one H100. Can one run one of their Gemini models, I forget which. What if that is how they scale, wouldn't that mean they need less GPUs? So put aside all of the gains and the growth, Nvidia is just holding everyone up. And the capital expenditures from the rest of the Magnificent Seven is holding Nvidia up. What happens? What happens? What happens? The market goes tits up. Do you think the market will go? Yeah, well, they're not buying the GPUs and Nvidia is doing badly. But we still love AI. Fuck no. They're going to say, what did we spend all this money on? I'm going under the bed, I'm going to find the pornography you've been looking at. You're all in trouble because people don't like tech right now. People are pissed at the tech industry and this is all vibes, man. Because when you look at the numbers, numbers are bad. So yeah, my long and short of it is the reason I am alarmist about this is these numbers are alarming and I am shocked and actually kind of disgusted at some people in the media for not being more alarmed. Because if things progress in the way, and I really think it will in this way, people's pensions, retirements are going to be so much lies on this. Retail investors make up a large chunk of the buying for Nvidia as well. Recently as well. It's so worrying. And the growth from AI isn't there either. These companies are not making shit, tons of money. Microsoft 2/4 straight said they would tell you their ARR for AI. They think it was one quarter. They said 10 billion ARR, which is month times 12. Next quarter they said 13 billion next quarter. They just didn't bring it up. Probably because the growth rates flat. What are we doing, man?

[Big Technology Podcast Host]

I think that there's. That you're right that a lot of this trade is predicated on scale working and that is a lot that is a risk because, I mean, what we're hearing from the tech companies is that they're getting diminishing returns from scale and like, in terms of making these models bigger, building up the GPU clusters, training them with more data. Like it's not as data as well. That's true, that's true. And I think maybe that's why you see the scale acquisition from AT Meta.

[Ed Zitron]

Insane.

[Big Technology Podcast Host]

Yes.

[Ed Zitron]

Because it's from one of the like, top of the market bullshit. $14 billion for Alexander Wang, a labor abuser at scale. I mean, lower case s there. And on top of that, basically cutting off the fuel supply for multiple companies for training data at a time. They're running out.

[Big Technology Podcast Host]

Well, it's interesting because a lot of those companies are. They're cutting it off on their own.

[Ed Zitron]

But yeah, you're right, OpenAI was moving away.

[Big Technology Podcast Host]

You're right.

[Ed Zitron]

But Google was their biggest customer and they pulled away.

[Big Technology Podcast Host]

But I think just going back to this scaling thing, everybody is now admitting that there are diminishing returns from making these models bigger. And I think we're really going to hit a point where they're going to say, do I need. If I'm, you know, okay, I'm just buying this month, you know, billions and billions more Nvidia chips to make my model a little bit better, do I need to be doing that? Like, just to go back to a conversation that I had a couple of weeks ago or now a month plus, with Sergey Brin, where he said he thinks that the improvement is going to largely be algorithmic, meaning these models, meaning not by adding more GPUs and data, by like actually changing the algorithms inside these models to make them better.

[Ed Zitron]

Right.

[Big Technology Podcast Host]

Things like reasoning. Okay, I'm just saying that, like right now, within. Anyway, let's just talk about it. Right now, within these tech companies, there is a consideration that maybe scale scaling up these models isn't what's going to get them there. And then there is that risk to Nvidia.

[Ed Zitron]

And.

[Big Technology Podcast Host]

And if that goes down, then it could be a problem.

[Ed Zitron]

It will go down. Like, that's the thing. At some point, putting aside my feelings about AI, at some point there will not be enough space. There will not be enough space for these GPUs. There will be not enough space on the earth to fill with them. There will eventually not be a need to. Are you saying that micro. Because the assumption here that this keeps going is that Nvidia either comes up with a completely. Like the Rubin, for example. Are we meant to believe that Everyone who's just getting Blackwell when Ruben comes out is gonna go, yep, I definitely need that. Is that. That is the gamble. And it's just, it's kind of scary because whether or not AI succeeds because also the growth isn't there. The software sales aren't there. Even if they made the software sales profitable tomorrow, the actual revenue is really piss poor. Like, it's not that much. Even if OpenAI was profitable, okay, they're the biggest AI company. Cool. Are they going to 100 billion a year? Bullshit. No. And also if they made it profitable, someone else would and they would get price fucked. It's just, it's such a brittle industry. There's never been anything of this scale this bad within tech. You can say the fiber boom. But no, you didn't have every single software company selling a fiber solution. You did every consumer. Because you didn't have apps back then in the same way, but you didn't have Notepad and Microsoft Word trying to sell you fiber. Or saying the new glory of fiber is here partly because of the site. We lived in the time, but it's like, this is bonkers.

[Big Technology Podcast Host]

The argument that the Nvidia's would make it would be that eventually AI use is going to be so intense that you'll actually need more GPUs to fulfill that demand.

[Ed Zitron]

Fascinating. What I. Jensen Huang, I give him credit. He's got great leather jackets. Sounds like horrible to work with, but.

[Big Technology Podcast Host]

Why do you think horrible to work with?

[Ed Zitron]

The reports like, there have been multiple, multiple reports of it. Like, he's an aggressive CEO. It's probably worse. It's probably better. But he's an aggressive fucking CEO and he humiliated someone at ces. It was someone at CES Sound guy and called him out by name in front of everyone. Disgusting. You have, you have a bazillion dollars. You should be, you should be happy to be there. But he'll never be happy. Once some more GPUs. It's. It's frustrating though. I understand. But also, what's Jensen Huang meant to do is go up on stage, be like, yeah, we're, we're gonna. People are eventually not gonna buy these. I should let you know as the. No, he's not gonna say that. He's gonna say, yeah, well, there will always be. He's done it before, he'll do it again. That's. The Nvidia will be fine long term. They're actually positioned because they make real things. And Jensen Huang is a pretty good CEO. They have actual innovation there. They have tons of different layers to the company the actual value creation. They have the monopoly on the consumer graphics market. They do make good stuff. There's a lot of problems with their consumer hardware right now. Sorry consumer graphics hardware right now there's where basically they've killed the mid market it that sucks but still a business that sells things and owns things the rest of them right now I think it's more likely at some point they go why are we doing this? This is so annoying. This is so annoying. It's so costly. I think Sachin at Della is also really tired of Sam Altman. From everything I've heard based on by which I mean Red I'm not like it's sourced with them. I wish I'll fly on the wall in those Everything that's being reported Journal's done some really good reporting on this has basically said that that relationship is frayed because I think Sam Altman thought he had more power than he does. And Redmond you're against the ultra monopolist. You're against like the OG the Michael Jordan of monopolies like they beat the antitrust claims with Ms. DOS and Windows. You I know what we're going to talk about this at some point but the conversation that some of the conversation the story about the whole threat of antitrust from OpenAI.

[Big Technology Podcast Host]

I'll just. Just bring it up now. Now that you brought it up.

[Ed Zitron]

Yeah. So it's just been on my mind ever since I read the story. So right now OpenAI in this wonky thing is trying to convert part of itself into a for profit entity with control from the non profit board which Sam Altman's still on but whatever part of that conversion requires Microsoft to say okay. And Microsoft says okay well we'll convert in exactly the way right now 49 of shares and we'll continue having your IP and up until you get AGI which is no. And we also get to sell your models exclusively and we have all your research too. Sounds great to us. And Sam Altman said no actually you should get 33 you shouldn't be able to have access to our IP after a certain point. Also the Windsurf acquisition, I don't know if that's ever going to happen because Microsoft is according to the journalist Berber Gin over there apparently the Windsurf acquisition has become a major problem because OpenAI is saying well we can't give you the IP from them. You compete with them with Copilot. And Microsoft says actually our contract says you have to. And the line in the article Solaris, it's like Microsoft gave the blessing for the Windsurf acquisition under the current terms. It's just like, yeah, of course they did. And the thing is, OpenAI has allegedly hinted at, by which I mean leaked to the Journal, I assume, I don't, I don't have any interior knowledge there that they were considering an antitrust action against Microsoft for some reason. People sign away their First Amendment rights and NDAs all the time. Like they, people make contracts to give away their rights all the time. It's not anti competitive because you don't like a contract. Also, even if they filed it today, good luck seeing that shit in front of a judge for three years. You don't have that kind of time. The fact that they're saying that suggests that things are desperate because understandably Microsoft said, oh, also OpenAI wants to reduce Microsoft's revenue share. It's like I put it in a monologue I recorded today is like being in a hostage situation, putting a gun to your own head and saying, if you don't give me what I want, I'll give you the hostages and kill myself. Because it is, it's like Microsoft. The only reason Microsoft would agree to these terms is because of reputational damage because Sam Altman believes he is the most popular, well liked, special boy in the world. And I think he believes that Microsoft would just roll over. And Microsoft said why, why should we bother? We don't have to do that. And sure they could work it out. There's every chance that Microsoft just goes oh fuck it, I don't care. But also why would they, why would they, why would they do that? What possible value indeed. Now it would be a reputational harm to Microsoft. It would suggest that Microsoft can't negotiate. And then the information had another story today where it went so a couple weeks ago where it was saying that OpenAI has been undercutting Microsoft in deals, selling their models and undercutting their enterprise.

[Big Technology Podcast Host]

Subscription deals and just making a deal with Google.

[Ed Zitron]

By the way, the Google well, oh my God, are you talking about the Google Compute deal? This is my favorite deal ever signed. Okay, here is how the Google deal works. OpenAI is contracting Google for cloud compute. Google is contracting Core Wave to serve that compute. Why would OpenAI not just hire Core Wave? Well, I'm, I assume Google needs to add some revenue even if they're probably just losing. It's the most strange situation I've ever heard. Just, I feel like we need more tech analysts who just look at the absurdity of all this because it is absurd. But no. So within this situation you've got OpenAI competing with Microsoft to sell their own models and undercutting them. Microsoft provides all their infrastructure. Sure Microsoft probably fears some anti competitive action if they start taking measures against OpenAI. But Microsoft never. I don't think that Microsoft has to provide them the discounted like a quarter of the price as your costs which they at least as recently as last year are providing them. I don't think Microsoft has to give them any of the things they have to. OpenAI signed a dog shit deal, a really bad deal that made sense at the time because I assume that they thought this would do something different than it did. Now they're in a price war and what OpenAI is doing, the undercutting thing, that's a Michael Jordan. Sorry, Michael Jordan. The Michael Jordan of monopolies I should say. That's a Microsoft move. A Microsoft move. Just go, I'm just going to lower the prices until you die. You can't do that when you lose billions of dollars a year, dickhead. You've got. Microsoft does that because they have the ability to just go. We will pay ourselves using our monopoly over business software. We will use it over our monopoly over Azure and one of the three companies that really makes meaningful cloud revenue. Like that's the thing. Microsoft can Bankroll that crap. OpenAI can't. And on top of that, if OpenAI does an antitrust action, think I mentioned it earlier, 2,000 people in Microsoft's legal department. 2,000 people. You got a small arm. You got more people working legal at Microsoft than work at OpenAI. All told, it's just brazen. And I think that, I think it could. There is a chance. I'm not saying it's for sure but Microsoft could kill OpenAI because they need to. By the end of the year OpenAI must convert to a for profit entity or SoftBank does not have to give them more than $20 billion total. SoftBank's already given them $10 billion. Another problem. Not that, just that this is a small one. I'm sure this is easily going to be solved. SoftBank to give OpenAI that money and to buy Ampere for I think 6 billion or something, they had to get a 1 year 15 billion dollar convert convertible bridge loan even and they had to go to 21 banks.

[Big Technology Podcast Host]

21 hurt their credit rating.

[Ed Zitron]

Yeah, I think that there, there was a threat, like there was a story was there was a consideration of hurting their credit rating. I don't think it's happened yet. And on top of that, SoftBank does not have the money to do the Next, the next $30 billion. They don't have it. They would have to raise more money. Now another story that went out where it was saying that now they're going to the Sauds and they're going to Reliance. I think in India it's like you don't go and do the Sauds unless things are not looking good and SoftBank is. So if they raise another $30 billion, SoftBank will only be providing 20 billion of that. So 10 billion will be syndicated. So OpenAI on top of SoftBank having to do all of this gump to make this happen, to have find money that they don't have, they will have to raise $10 billion, one of the largest private rounds of all time. And if they succeed, they will have to do it again and again and again and again and again because OpenAI will be, according to their own projections, burning money until 2029, 2030 when Stargate, which will somehow exist, which will also require another $19 billion from SoftBank that they don't have. Once that happens, they will go profitable somehow. It's just really strange that this is considered a like an outlier position versus arguably one of the least stable financial situations in history and perhaps not tantamount to the subprime mortgage crisis because that was so, that was so clearly like when you saw the fundament of it. I don't think that if this. I am not an expert in mortgage security, so forgive me, but I can't imagine it would have happened in the same way if it happened today, just because there was more access to information. But in that case we just had millions of consumers with loans they couldn't pay off that was bigger and would have more widespread damage because there are people losing their houses and then it the economy. I don't think this is going to be super far off when it happens because of the MAG7 problem in Nvidia. And what's holding it up is one company that burns billions of dollars, their sugar daddy out in Japan, run by Masayoshi Son, who is well known for losing money and making really bad investments. By the way, another question. All the reporters talking about the $3 billion a year in agents that SoftBank was going to buy. Where's the fucking reporting on that? Absolutely egregious. Almost as egregious as people claiming OpenAI had closed a 40 billion dollar round. They didn't do that. They ain't got the money. No one's got the money. Why is OpenAI raising money for a round that they claim was. It's just. It frustrates me because people will get hurt.

[Big Technology Podcast Host]

So let me. What is the best argument against the claims that you're making? Have you heard one?

[Ed Zitron]

Honestly, I would love to. It very much is if a frog had wings, it could fly. It's like, if they get better, sure. If they manage to make this much, much cheaper and they end up working out a thing that could sell really well, sure.

[Big Technology Podcast Host]

Can I ask you. You run a PR firm. That's your core business.

[Ed Zitron]

What do you mean?

[Big Technology Podcast Host]

That's what brings in the most revenue with easy pr?

[Ed Zitron]

No, it's. I mean, it's spread across the businesses.

[Big Technology Podcast Host]

Wait, okay.

[Ed Zitron]

As in, like.

[Big Technology Podcast Host]

As in like media and a pr.

[Ed Zitron]

Yeah.

[Big Technology Podcast Host]

I mean, how do you, as someone who owns a PR firm, decide that? This is. I'm just curious. This is not like.

[Ed Zitron]

A lot of my business is working with journalists to pitch clients to them.

[Big Technology Podcast Host]

Right.

[Ed Zitron]

And I stay away from AI stuff. Like, I don't work with. I worked with a consumer TV company. I didn't write about anything like that for obvious reasons. The thing is, a lot of my business is talking to journalists. Journalists want to be presented stuff that matters to them, that comes from a person who's considered and read their work. The fact is, I consider and read their work all the time. It's what I've done for, like, 10, 15 years. I've been doing this business. Like, it's the same thing, except I started writing and, yeah, I fairly well demonstrated that I understand what I'm talking about in the writing. I do. And I also firewall that very precisely.

[Big Technology Podcast Host]

So it hasn't hurt the PR firm, then?

[Ed Zitron]

No.

[Big Technology Podcast Host]

Okay.

[Ed Zitron]

No. And in fact, the client. Clients kind of like it. Like, they do it. They appreciate the fact that I can elucidate that I understand business. And it's one of those things where. Yeah, it is. At some point, the media stuff will probably take it over, but I'm just. I'm having a great time doing all of it. But on top of that, when it comes to doing pr, doing media relations so much, what PR people don't have is basic knowledge. And I do pride myself on knowing what I'm talking about, and it helps, and it's great. And also, there are strict firewalls. CES is a great example. So I had a client at CES at the time, I would pitch them for the show, pitch a journalist to come on my show beforehand before I pitch them the client. Because I didn't want any possible situation where they thought for even a second, even though I don't think they'd think this, that them saying no to my client.

[Big Technology Podcast Host]

Right.

[Ed Zitron]

Anything to do with the show and it. And there were. There were people that said no to stuff who came on the show, and it was fine. Who gives a. Like. It's like they. They are separate entities, and my clients are very respectful of that as well.

[Big Technology Podcast Host]

Can we just take a moment of levity? Because the way I first found out about what you do was when speaking of ces, I think you told, like, a bunch of people that you would meet them at updog. They would say, what's up, dog? And you would say, nothing much. You.

[Ed Zitron]

Oh, that was so much fun. They were so pissed. They were.

[Big Technology Podcast Host]

So you got them good.

[Ed Zitron]

You pants someone, they get. No, that was great as well.

[Big Technology Podcast Host]

So what happened there?

[Ed Zitron]

So what it was was I was. I had. Was heading back to England. I think it was a few days before I headed back, and I was getting spammed, and it's like, I'm not. I went to CES because I think I had a blog at some point that got me in the media system. They screenlight you automatically. So I said, okay, I'm just gonna respond to these people who have not got. And none of these people are considered who I was for a second, because they just spam me. So I respond with like, can you send me more info on Up Dog? And they'd be like, what's up, dog? I'm like, nothing much. What's up with you? Most of them didn't respond. Some responded, I can't believe you do this. I can't. This is so unprofessional. One of my favorite tweets at me was like, oh, making fun of your Pierce? You're a real douchebag. I have that tweet somewhere. It's so funny because it's like, look, if someone got me like that, I'd be like, oh. Like, it's like yesterday, I said to my dear friend Casey Kagawa, I said to him, yeah, I've hit this number of paying subs. He said, you'll never eat all those. And I got so pissed at him because it was such a good dunk, because he was suggesting I was talking about sub sandwiches. Not a great joke, but he got me good. If you get done with a funny joke in a professional scenario, you should enjoy the fact that you're not having to talk about business for a second. I don't judge anyone who failed for that. You're a PR person emailing a bazillion people. Laugh with me. We're all having a good time. Or you should be. Apparently a major agency that was sent a company wide email saying warning Ed Zitron, which is really funny.

[Big Technology Podcast Host]

And that was your screen name for a while.

[Ed Zitron]

It was, it was, was it good callback, real OG fan? I. No, it's. Yeah, that was really, it was really funny. I meant no harm with it. And I think anyone who took it see anyone who took offense to that go outside.

[Big Technology Podcast Host]

Let me ask you this to end. I mean we have listeners here, I think, that believe in the power of AI, are working in it, are implementing it, are building it, and some that are concerned about it, worried about it, and really are curious about the business side of things. And sometimes those people overlap. You've built a sizable audience among people who are really concerned about this. And I think that every time we do a show about like the downsides of AI, people grab onto it. I mean even with the Gary Marcus show, like there are people that will like go in the comments on YouTube months afterwards and be like, this helped me like sort of have come down from all the AI based fear yesterday. So what do you think? Why do you think people are so concerned about this technology and why do you think the criticism of it resonates the way that it does?

[Ed Zitron]

I think there's a few things. I think one is the most obvious, which is I think anyone would be afraid of someone taking their job. I think it's a natural thing of the thing I have, someone might take it. And when you have the entire media and most public companies saying, I can't wait to replace humans, you would mean nothing to me. Yeah, that's scary. People. When you have Ezra Klein and Kevin Roos saying, AGI is just around the corner, baby, and it's going to change everything. Notice that they never say how. That's very scary. And this is not saying people are stupid or uninformed. The average person does not have my very special stupid mind where I'm like, I must learn all the numbers. And most people don't have the time to sit down. They have jobs, they have families, they have things to do, more fun things, I imagine. So they see the news and they get scared. And then I think there's a layer deeper where tons of people realize that something is being, they're being told a lie, that they go and use chat GPT and they go, okay, this search is better, my friend. Talks to it like a therapist, which is worrying. But they keep describing. They referring to big companies. Sam Altman as the next big thing. The power of AI. But when a regular person looks at it, they go, this isn't, this isn't what they're saying. But everywhere saying it is. And their bosses are saying AIs and everything. And I think that people feel this cognitive dissonance and they feel it profoundly. It's the same way they felt about the Metaverse. It's the same way they felt about crypto, AR VR, all of these things. But none, none of those were this pungent. And you've really just seen companies so horny for the idea of replacing people. They're so excited there. Shouldn't you as a CEO? Unless you care more about your shareholders and growth, which is. Andy Jassy's an NBA. As are all of them. I think, I think all of the motherland. Mark Zuckerberg have MBAs now all the major big tech CEOs. I don't know if Jensen does. Anyway, wait, let's.

[Big Technology Podcast Host]

Let's get this right.

[Ed Zitron]

So I think Tim Cook does Sachin Adela, Sundar Pichai, he worked at McKinsey.

[Big Technology Podcast Host]

Okay.

[Ed Zitron]

Andy Jassy, I even think the guy replaced Andy Jesse at AWS as an NBA. Okay. Pretty sure I'm correct on those. If I'm. If I'm wrong, score me. But people realize that there's a disconnection by from what's being told and yet they are very clearly seeing how lascivious people are around the idea of replacing them. So they have this dual offense of you haven't even built the future yet, but you're doing the touchdown dance and you're so proud of the fact you replaced me. You're so excited to replace a real person. Mark Zuckerberg wants you to have fake friends. Sam Altman wants you to have fake coders. And then they see that the outputs are kind of shit. They see that it doesn't really replace people. It replaces an aspect of labor and a small aspect of labor in exactly the same way that bad bosses mistreat their employees, do not value their labor. I had this thing I wrote called the era of the Business. Idiot did a three part episode on it. And my principal thing is I believe throughout most power structures there are people that do not understand work, that do not want to do work and exist as a kind of ultra middle manager. I think Sam Altman is their antichrist. Which sounds dramatic, but hear me out. Sam Altman is the single Most gifted business idiot whisperer of all time. He convinced. Look at what he's done. I think he's reprehensible. A real scumbag. But I cannot. I cannot ignore the work he's doing. Just. He convinced fucking Oracle to do all these chips. He convinced Masayoshi Son, Sachin Adela. Of course he's confident that he can con Microsoft. I think he's wrong because he's done it before. He convinced everybody that Generative AI was the future without really proving it. Someone else did that work for him. Someone else built Chat GPT. How many of the people who built GPT are still there? Ilya Suitscaver Respect to the guy for just doing his own scam. Mirror Marathi, same deal. I get Stephen Levy piece being like, yeah, they're gonna build an AI thing. And I was like, oh my God. Oh my God. And then on top of all of this, you have this about AGI, the most fictional of all fictional concepts. I. I've said this a few times. It's like having a bunch of billionaires saying they're going to hunt and capture Santa Claus. It we are closer to the Ninja Turtles. I'm deadly serious. I've talked to biologists. That's about as firm as Sam Altman can get with AGI too. Because that's the thing. You have all these people hearing that there's going to be this conscious computer and they're fucking scared of that. Of course they are. Even though it's a complete lie. Even though it's a falsehood. Because Kevin Roose said was at a dinner party with some other credulous people.

[Big Technology Podcast Host]

You don't like Kevin Roose?

[Ed Zitron]

I think Kevin Roose was very good at his job and he has now gone anti remote work pro Metaverse. Pro nft. The pudgy penguins. Colin was disgusting.

[Big Technology Podcast Host]

What was that?

[Ed Zitron]

He joined a penguin NFT club. That was the article. There was the healing one as well.

[Big Technology Podcast Host]

I will say, and I think it's important to note, unlike crypto, Metaverse AI feels different to me.

[Ed Zitron]

It is different.

[Big Technology Podcast Host]

It is. It seems far more useful.

[Ed Zitron]

There are more products, there are more actual. I will. I indeed. When this bubble started, I pushed back on. People said, it's just like crypto. It's just like Metaverse. Because there was a thing here, right? Was it as big as people said? No. But the egregious lie with the metaverse was like, We've made a VR space. This is worth 100 bazillion dollars now. But with Rus, he did an article At Helium, a crypto company. And then Matt Bender, I believe, over at Mashable. You got outplayed by Mashable, man. Actually, Bender's amazing. Tons of great people. That's Celia, I think. Anyway, with Ruse, he did this story where he was like, yeah, Helium works with Lime and Salesforce. Turns out they didn't. Turns out they didn't. Matt Bender went and asked and they went. They went, no, we didn't. Kevin Roose added by saying skeptics have suggested or critics have suggested that this wasn't the case. It's like, motherfucker, come on. I don't like Kevin Roose because he has this amazing power. He has this huge audience, and he chooses to support the powerful. He did a story about AI, An AI welfare guy. An AI welfare guy being added to Anthropic. Just a Ninja Turtles expert. It's. We will find the ooze. The ooze is here by talking about.

[Big Technology Podcast Host]

I thought that was an interesting story.

[Ed Zitron]

I thought it was fucking stupid because it didn't discuss the welfare of AI if you discuss the welfare of AGI. If we have a conscious computer. You are describing a slave. If this thing has consciousness, you now have issues of personage.

[Big Technology Podcast Host]

Are you open to the idea that it could be.

[Ed Zitron]

I think it could be possible in 30, 50? I think we are.

[Big Technology Podcast Host]

You're just now saying you're open to this idea?

[Ed Zitron]

I'm open to the idea in the same way that I'm open to the idea of Teenage Mutant Ninja Turtles in the sense that if we got the use that could do it AGI. We do not have evidence. It's possible. We don't understand how humans think. How the fuck are we meant to create it in a computer? But say we do, and this is the dirty part of the conversation. No one wants to have say this succeed. Are you saying that this conscious being that Microsoft owns, by the way, Microsoft owns this conscious being with intelligence and consciousness and a personality. Are you saying we wouldn't let that free because what you were describing there would be a slave?

[Big Technology Podcast Host]

Yeah. It should not be the goal.

[Ed Zitron]

And. No, but that's what they're thinking now. They could say, oh, we'll do it, but we'll make it so its consciousness just focuses on doing whatever Salesforce wants. Still a slave.

[Big Technology Podcast Host]

Right.

[Ed Zitron]

This is the thing. If Kevin. I genuinely would have respected Kevin had he done that thing and then had a really, like, agonized discussion, which is genuinely interesting, saying, what would be the ethical ramifications of owning a conscious thing? Fascinating.

[Big Technology Podcast Host]

But doesn't that story that the. That the. The labs are thinking about this kick off that conversation? Like, I don't think that you can expect.

[Ed Zitron]

I'm Wario Am A day.

[Big Technology Podcast Host]

Okay.

[Ed Zitron]

I have decided that.

[Big Technology Podcast Host]

Okay.

[Ed Zitron]

I'm never calling him his real name. Yeah.

[Big Technology Podcast Host]

All right.

[Ed Zitron]

Dario. I'm sorry. Dario. I am. I am him. I am trying to work out reasons for. For people to invest in me in the future. I think probably give. Let's call it a million dollars salary, probably a couple mil more in stock. I'll make a new guy. A new guy will come in and his thing will be AI Welfare. What does that mean? What if it's life? We can do a Google Doc back and forth. Karen, how's Empires of AI does an excellent job of discussing how many of these people fart in a glass and sniff it because they have jobs there where they just sound kind of, what if this happens? What if this happens? It's a marketing spend and it worked. It worked on a guy who it's worked on before. Kevin Roose did an article recently about a company claiming that they were going to replace workers. You know, what they hadn't done, even created the environment they do it in. Kevin can do good journalism. He's done really good. That's the young money he did. It's great. Like, there is actual things. Casey Newton's the same way. Like, they're good journalists. They could do good journalism. They could even do. If they were optimists, they could engage in actual optimism. There'd be interesting thing. The welfare story is a great example, man. Having a conversation in the Times about what's considered human or not. Where. Where have they not been doing that elsewhere anyway? It's just. It's this frustrating thing where the. Ultimately, the people that suffer will be the people who depend on the markets for their pensions, the people. The markets do eventually affect the workforce. And on top of this, the other thing is that we've got major people in the media hot and heavy over the idea of replacing people. Hot and heavy. They're excited. I think that's disgraceful. On top of it, who are you fighting for? Who are you writing for? It isn't clear.

[Big Technology Podcast Host]

All right. I think you and I will. Will disagree on Kevin Roose and on some other things. But I am. I am glad that we've had this discussion. Me too. I. I don't agree with everything you've said. I think it was good that we had a conversation where we, you know, brought some of this out there, tested it, and I think the one thing I'll say is I leave open the space that you're right.

[Ed Zitron]

Yeah.

[Big Technology Podcast Host]

And that's and I think that that is why I think you have a very interesting perspective on this, and I think that's why it was important for us to have this conversation.

[Ed Zitron]

I'm really happy to be. And we've talked a good about this.

[Big Technology Podcast Host]

We have.

[Ed Zitron]

And like, like, I'm really excited to be here. Thank you for having me.

[Big Technology Podcast Host]

Definitely. Well, thank you for coming, folks. If you're interested in the podcast, it's better offline. The newsletter is where's your ED at? And it's also the still alive and kicking EZPR ezpr.com All right, everybody. Thank you, Ed.

[Ed Zitron]

Thank you.

[Big Technology Podcast Host]

Thank you for watching or listening. And we'll see you next time on Big Technology Podcast.