Transcription
I think we are going to see a supply glut. We spent half a trillion dollars to get one more sales force or two more sales forces run by some of the dampest, most annoying people alive. Jesus Christ. This is a sign they don't need the compute. And it's also a sign that perhaps they overbuilt. And if they overbuilt, I think it's fair to ask whether everyone else did, too. And also, this is the dot era all over again. If Meta sells compute to Anthropic, it's game over. We are at the end. We're in this weird situation where everyone wants them to reduce their cost. But if they reduce their cost, they reduce the need for AI compute, which means we've overbuilt the supply. But if they don't reduce their costs and they need all that compute supply, they need endless venture capital and debt, which will run out.
Hi and welcome to the tech report. I'm Isaac and joining me today is writer of Where's Your Edit and the host of the Better Offline podcast, Ed Zitran. Thanks for coming back on.
>> Thanks for having me.
>> Until now, the general assumption has been that the demand for memory and semiconductors far exceed supply. But this might no longer be the case as questions of an over supply of compute has kind of panicked investors after the first hyperscaler has started selling its surplus. Now, this is meta we're talking about. So, the obvious question first is, do they just not need the capacity because they're not popular enough to use it all?
>> Well, that's the thing with Meta. I don't know if anyone else has been counting, but I'm now at five different reorganizations of their AI department. They've come up with three or four different random they had Llama, their open-source one, which people liked, but it was open source and thus no one would pay for it. And so, they built I think they spent over hundred billion dollars on capex. Then they spent $14 billion on scale AI. Then they built the Muse Spark AI model which was immediately middle tier. So they spent all that money to not be the best. And now they are, and this is to be clear, this is an internal discussion at this point. They're talking about leasing out their compute to someone else. This is a sign they don't need the compute. And it's also a sign that perhaps they overbuilt. And if they overbuilt, I think it's fair to ask whether everyone else did too. Now bulls and the recently concussed will suggest that oh well this is actually a super smart play from Meta cuz it's a way of monetizing their capex when they haven't been. What it actually is is a tacit admission that they don't need it that they actually have no ideas that they never have had a real plan for this and even I think less than a month ago at the annual shareholder meeting Mark Zuckerberg said we think we have a use for the compute but if we don't we'll rent it out. So, it's just this is what a company does when they're out of ideas, just like Meta always has been. It also begs the question as to who's next and also when Meta will cut Capex because at this point, if they keep spending on Capex after saying this, what exactly is the plan? Are they going to become Coreweave 2? Are they just going to be the largest AI compute company? I don't really know what the thing is. The other problem Met has is that the majority of their compute is in older generations of GPUs, H100s and H200s. So, it's just they're going to become the largest oldest GPU provider. It's a mess. And I think the answer is well, there really never was a use for this compute in the beginning. And I think that we're going to the only reason that Amazon, Google, and Microsoft aren't doing the same thing aggressively like trying to find places for it is Anthropic and OpenAI take up the space. Which is why my prediction is is that if Meta sells compute to Anthropic, it's game over. We are at the end because that will just be a sign that the only people that will buy compute at scale are two bulbous unprofitable fail sons. I mean to your point, Meta is still on the books to spend I think between 125 145 billion this year.
>> Yeah.
>> And yeah, to your point, why if they're selling surplus?
>> Well, there's another question with that as well. They are they have a deal with Nebius for I think over $17 billion. They have a deal with Corey for over $30 billion. Are they going to resell that compute? What's the plan there? Because especially in I actually think in both of those cases, both of those companies took those contracts from Meta and used them to raise money to build the data centers for Meta that Meta might not need anymore.
>> Kind of a fair question to ask. What's going to happen there? And what about Hyperion? Their $30 billion data center in Louisiana. It's apparently meant to be the size of Manhattan. What are you going to do with that, Marky Mark? What's the plan? Cuz it's very clear that nothing is going on there. Alexander Wong is the head of whatever division runs AI for meta anymore. It's not really clear. He went on Twitter and he was because Mark Zuckerberg made the comments saying that the progress of agents has not been as fast as expected. Uh and Alexander Wong went out and he said, well actually Mark Zuckerberg was talking about the entire industry, not just Meta, which I love, by the way, cuz this already soured the mood quite a lot, this discussion. And Alexander was like, "Yeah, just to be clear, we don't we mean everyone. We don't just mean us. Just in case you were worried that it was just a me thing, it's a all of you thing, too." And so the bulls are furious, but they're all coming up with little ideas. I truly don't know why they're still spending capex. I don't know what the like what does I think, but I will be honest. I actually think this is a fair question for every hyperscaler. What is it you're getting by building more? Outside of just doing like running high-end welfare checks for anthropic and open AI, I'm not really sure what more capex is doing because we're what near we're over a trillion dollars now. Where are the outcomes? Like what's what has this done for Microsoft, Google, and Amazon outside of kind of pumping their own money back into their revenue? What? It's definitely not done anything for Meta other than that story from Reuters about an old man being led to his death by a Kylie Jenner. That's a real story. It's an insane crazy story. It's insane that that happened.
>> And I think I think that Meta is in the running to be the first to pull capex back. I've seen semi analysis said, "Oh, actually they're going to spend more." And it's like, why? Why? What is What is it with this industry? What is it with the AI industry that every time reality dawns, they're like, "No, we must be stupider now. We must we must escalate even further."
>> You say Meta might be the first one to pull capex. What we've also seen, if you count SpaceX, maybe not as a hyperscaler, but they have also sold surplus to Anthropic. Who do you think might be the next person to start selling surplus? And then where does that leave the the hundreds of billions of dollars of AI infrastructure that is still slated for construction?
>> I mean it's Meta. I think Meta if Meta ends up selling to Anthropic or OpenAI we really are at the end because remember I think that they have like 1 to 2 G of capacity. If they end up selling it to OpenAI and Anthropic that's them saying we don't have another big customer or there is not enough diverse demand to sell this to someone else. Microsoft, Google and Amazon, they don't have surplus capacity because anthropic and open AI take it all up.
>> We have already seen Coreweave their biggest customers are Microsoft for Open AI, Open AI for Open AI, Google for Open AI, Anthropic and Meta. Oh, and also Nvidia for themselves. And then there's Nebus, Microsoft for Open AI, Meta. I mean, it's the same thing every time. cipher mining, anthropic, iron, anthrop, sorry, an iron might have been anthropic as well. But that's the thing, it's always the same names because there's not really the demand outside of it. At this point, I think there's just a compelling question to us, which is why are we doing this? What is this for? Is it just is this industry existing to fuel anthropic and open AI? Because that's a problem as both of them are unprofitable. It's just it's feeding venture capital into hyperscalers or into into hyperscalers so they can feed it into Invidia and the Taiwanese companies that build their servers. Like what is and now SoftBank is apparently planning to build their own capacity which is equally bonkers. It's just I think we're going to see a supply glut. I think we're going to if Meta chooses to do this, if Meta chooses to rent to OpenAI and Anthropic, by the way, I think that that's to avoid a supply glut. That's to avoid the industry really reckoning with the fact there's too much supply. But I think that I don't know who else would have spare capacity. Elon Musk is already selling all of his. He already sold it to Anthropic and to Google. Google, I think, 900 million or something a year. It's unclear. And also when you line up the amount of GPUs that both Anthropic and Google are renting, they kind of like there's not enough in the there's they're using too many GPUs in both deals for both of them to do at the same time. I mean, is this industry capable of doing anything that isn't circular financing? Is this industry Meta is actually going to be the test of this? Cuz if Meta comes forward and they say we're going to do a standard inference operation where we're going to offer it to whoever wants to run open- source models or rent our models, we're going to do peacemeal contracts. Fine. Then that that's like that's a respectable is I don't think they'll have the demand, but it will be okay. We're going to have a real go up this. If they just sell it straight to OpenAI and Anthropic, that's because they know. It's because they know there's not actually going to be outside demand. It's just kind of a mess. I I think we're really going to look back on this era and say, why did we do any of this?
>> Even if we assume that all of the companies at play remain afloat somehow throughout all of this, how much over supply do you think there is going to be at at the end of this period?
>> I mean, it's remains to be seen how long it takes them to cut back capex cuz I think let's say 10 gawatt comes online in the next two years. I don't think it'll even be that much. Anthropic and Open AI I think I estimate take about three and a half gigawatts total which is the majority of available compute and the rest of it goes to the internal services Google Microsoft Amazon much more Google and Microsoft I think that there is probably about net outside of anthropic and open AAI maybe 500 megawatts to a gigawatt of capacity demand I think that that's it I don't think there's very much more I don't I don't I've looked around I've looked at lightning based all of these companies and I've tried to work out how much capacity they actually have and it's not that much and even then and the amounts of revenue they get are vanishingly small like I think lightning had 500 million annualized revenue which is got like 30 $40 million a month not that like that's a lot of money to you and me but for the amount of money the capacity cost it's kind of not that very much at all so I think as I said a few months ago the thing that's keeping their some sort of supply constraint is the fact that anthropic and open AI I take up everything and indeed the data centers has taken a while to come online. I think that ultimately what will bring this to a head will be someone dumping a bunch of capacity online like meta if they actually just dump it onto the market or alternatively stuff will come online and at that point people will say oh well now I can find a GPU for cheapest chips I can find one anywhere doesn't cost me anything. It will be what's going to be interesting is so there's two ways you buy GPU compute. You either buy an allocation for a year or two years or what have you. You buy like a hund few hundred few thousand or you buy spot prices. Whenever you see people talking about the price of GPUs going up or down, it's the spot price. The spot price is not indicative of the general availability. It's literally just what's available at that time based on who's who's got anything free. If those p if spot prices start to crash, however, that's a sign that there's just a ton of capacity available. The question is when do these bloody data centers get built? Because we truly don't know at this time. We like no one. It's really difficult to actually get an update on any data center project.
>> I know this is something we've covered quite extensively, but what happens if a hyperscaler does pull back on the aggressive a that capex spending on AI, especially given sort of how much debt there is involved in it? So I saw a fellow called uh Rich Gardovski I think it was a Goldman Delta analyst who said that the first hyperscaler to pull back on capex will be the will be rewarded once that happens all the others will choose to do it so they get rewarded they they have the brains of dogs the hyperscalers they they may have so much money but they have very kind of blunt thinking of oh market happy or market sad and I think I thought Meta was going be the last man standing. I actually think they could be the first. All it's going to take is one of them to do it for the others to cut back. And when they do so, it's not going to be we're cutting capex cuz AI isn't working. They're going to say era of efficiency. We're we're doing efficient AI. This is an attempt to make AI efficient. We're going to make sure our AI stuff works. We're being moderate with our costs to benefit shareholders. They'll bump share buybacks. like they'll do whatever they can to make it seem like a good thing, but I think the market will see through it because they're already even with this meta capacity story, Nebius, iron, core wave, all of them dumped. I mean, even applied digital, all of the exterior AI compute companies dumped on the markets. So, I think I think what is going to happen is someone one will do it and the rest will follow and the markets will reward them. But the thing I've been saying for years is okay, when AI is done, what's next? And there really isn't anything. So I think that I think it's going to be a case of Meta doing it then others following. But the question is who? It could be Microsoft, but Microsoft Sachin Nadella the CEO recently posted a thing about spending a billion dollars on forward deployed engineers. He has full AI psychosis. Could be Google, could be Amazon. I think Amazon is the candidate to at least do a little bit of cutting because they were planning $200 billion this year.
>> I think it really will be it it's going to be interesting to watch because they're an industry of cowards. They're cowards. They don't have any ideas. They just they're doing this because they have no other hyperrowth ideas. So they just they could stop it for equally thin reasons, for equally flimsy reasons after being so excited about AI. And also if they if Microsoft, Google and Amazon cut capex, that'll be very interesting as far as OpenAI and Anthropic go because as I've said before those two companies have never built any of their own infrastructure. None of neither of them have. I I estimate that it's cost about a quarter of a trillion dollars to build the hyperscala cap in hyperscala capex even to build out openai and anthropics just very basic infrastructure in the Alman versus Musk trial a Microsoft executive said they'd spent hundred billion dollars or more on their partnership they've only invested 13 billion so I think it's safe to say and that was well earlier in the year I think it's safe to say they spent $80 billion just on the infrastructure for Open AI. And that's before you consider that Amazon's built out stuff for Open AI. It's probably 2002 250 billion they've spent on this. So, OpenAI and Anthropic have never had to invest in infrastructure now that they'd have to. I don't think they can afford to. I don't know what they do. It's going to be a mess. And I think the sooner it happens, the better because the market has become so overheated over this stuff that I'm just not sure what to I'm not sure even what the purpose of investing further is. This isn't even a bearish take. This is just what are you do? Like why are we still doing this? The are these companies ever going to leave Pinocchio status?
So on a bit of a side note, the information reported that an open AI engineer had found a way to half inference costs and I just wanted to quickly ask what you know about that but then also the question it raises because if a major efficiency gain does happen, it may alleviate some of the pressures around sort of AI being subsidized even though half would still be not profitable or anywhere near.
>> Well, first of all, the information I I pay for the information for years. I really like them. This story was weird. It's very weird because I'm looking at it right now. It's um OpenAI engineers earlier this month told some colleagues that they figured out a way to more than half the cost of inference. But then it goes on to say when the engineers applied the new techniques to power chat GPT for visitors who didn't have a free or paid account. It's just like no they haven't haveved the cost of inference they have found a technique to have it in one situation. Maybe if open AAI had actually found this they would do a they do a blog. Sam Alman would make an annoying lowercase tweet about it. They when they talked about a jalapeno chip with Broadcom that may or may not reduce costs. They were they were playing saxophone out in Time Square. They not literally they were excited and they were talking about it. They would go on CNBC and say this. It wouldn't be what appears to, I'm guessing, be a Slack conversation which someone got sent. What I think this is is likely someone on Slack in OpenAI went, "Hey, Amaya found a way to half it. I tried this one thing. What do you think?" And that blew up. Even the AI boosters were like, "This is a nothing burger." when they are saying that you know it's nothing as here's the thing I don't think that open AI magically found a way to half inference I don't think that that happened I just I really don't because they would make a much bigger deal it would be a big deal but you're right if they actually did this it would mean they needed less compute which would lower their demands for compute this is the thing now we're in this weird situation where everyone wants them to reduce their cost but if they reduce their cost they reduce the need for AI compute, which means we've overbuilt the supply. But if they don't reduce their costs and they need all that compute supply, they need endless venture capital and debt, which will run out. And it appears that they're just going to linearly need more compute for the rest of time. Great. We've just got two unsustainable tracks going on. And now this growth of open-source models that's scary to them. And we can talk about Sonnet 5 if you want, but it's there there is just a certain degree here of there no one has a solution to any of these problems. We either have so much demand from two companies that means that we need to funnel them money forever or these companies will find efficiency gains which will mean they don't need as much compute which will mean that we've built way too much compute because the demand doesn't exist outside of them. Both of these situations are bad. Both of these situations end in tears. There is because if they reduce the cost of inference by half, they would still have to train which would still cost them way more than the money they make. Also, if they reduce the cost of free users by half, they still have the expensive users. I think that just thinking about what it could be, they could be serving free users inferior models. They could be serving them slower like just the actual compute. they could batch the requests or something so they come out slower. I'm sure there's a way that they've made it cheaper for free users by making it worse, but I severely doubt they've h haveved all inference costs. If they did, I'd love to hear, but again, it creates the problem that you discussed, which is, yeah, if they have their if they half their inference costs, they have the amount of compute they'd need, which would be bad for everyone. I don't think that that's what happened, though.
I want to talk about Nvidia for a second because they launched a new partnership program where they offer to lease or buy back GPUs from cloud providers in exchange for a percentage of their profits. But obviously that is to me anyway that sounds like a terrible deal for the cloud providers. But leaving that aside, it seems like the whole purpose of that that deal that partnership program is to reassure customers who are worried about the risk of a massive overupp problem. No. What what do you think?
>> I think it's something more evil than that. I think that by the way, at the end of this era, we need to make circular finance illegal. I just I think we need to end this because what Nvidia is doing is Nvidia is saying if you buy our GPUs, we will guarantee to rent them back. And he's specifically saying it to new Neocloud types. This should be illegal. I just really want to be clear. This is not real. And also this is what you do when real demand doesn't exist. And the bulls, the mold poisoned, whomever will say, "Well, actually, it's just Nvidia giving reassurances to customers and the demand exists. They call Professor X about it. Oh, oh, I've worked this out. I've got the solution." No, this is an act of desperation by Nvidia knowing that we don't have a functional SEC at the moment to say, "Hey, are you roundtpping?" Which roundt tripping is illegal. You're not meant to do it. Are you round tripping? But what they do is they do it at such small amounts it kind of goes. It's under the radar even though it's reported in the information. Nvidia is doing this because the the compute demand doesn't exist. Like it's that simple. It's not it's not a complex point. People want to make it complex. People want to turn it into this whole thing. Oh, it's just how supply works. It's like no, this is what you do when you know no one's going to rent these damn things. And you and I also think it has something to do with debt because corewave, Nebius, iron, all the neoclouds, the way that they raise money now is they take a contract from hyperscaler. So meta, let's say meta says we're going to pay Nebus 17 billion or what have you. They take that to the bank. They go, look, we have a big sexy cloud provide. We're going to provide the compute to these people with guaranteed money. And then the bank goes, oh well, they're going to have guaranteed money, so we'll give you the loan. Nvidia has done this already with Coree. They literally gave a contract. They agreed to buy back Corewee's supply so that they could raise money to build more G to buy more GPUs to put in the data center. Again, this should be illegal. This is really bad. This is the end run. This the fact that we are still doing this. If this was happening two years ago, which it was, it been happening since 2024. Project Osprey it was called with Core Weave and Nvidia, I would get it. I kind of got it in the early days. Sure. I can see I can see the argument. I don't love it. We're in the year of our lord 2026. It's it's been a while now. It's been a been a long while. We've had the we've had generative AI for a minute, Jensen. You shouldn't have to keep paying your customers to pay you. And also, this is the com era all over again. It's Lucent. It's Nortell. It's all the It's all the great We're doing again. It's we're doing all we're playing the hits because there is no there there is not the demand and the demand is not magically arriving. So these at some point this just the bottom falls out of this. At some point a bank is going to say hey Jensen love you baby. We love giving you money. However, I just don't believe that like I don't think that this is a stable relationship cuz remember Nvidia incredibly wealthy, incredibly profitable company with a ton of money. They have $26 billion over the next five or six years in cloud compute commitments as in to rent. They are spending $26 billion to rent back their own GPUs. Again, sign that there's not real demand. They also have made I think 70 or 80 billion worth of impossible to cancel commitments to TSMC. Nvidia in the event that I don't know what their cancellation terms are with their GPUs, but if their terms allow cancellations and people cancel, much like the dot bubble, then Nvidia could not afford their bills and could not afford to pay these deals like there is a way this unravels even for a very wealthy company like Nvidia. I'm not saying Nvidia dies or anything, though they are setting themselves up to make that not impossible. It's very, very, very, very unlikely. But this some of the upfront commitments they've made are genuinely bonkers. I think at some point the banks just get tired of issuing this debt cuz I think at some point these it's not the student loan business. It shouldn't be that every single loan is co-signed by someone's parents. you eventually want the the data to be able to pay you. It's just a very it's all very unstable and it drives me a little insane because you speak to leading journalists and analysts and such and they're still to this day going AI chips. It's all natural and good. We love it. If that was the case, why is everyone acting so weird? Why is everyone so shifty? Why is everyone like, "Yeah, you know, I'm I'm going to buy your GPUs from you. Great, but can you pay me to buy them from you?" That's not a real industry. None of this is. It's it's kayfabe. It's everyone pretending this is real in the hopes that it becomes real. It's like a like valley girl manifestation except done trillions of dollars at a time.
>> So, um completely threw me off with that.
>> Yeah. Sorry. Uh so yeah, if we do look at the the memory markets, Samsung and SKH Highix announced last week that they're planning to spend over $500 billion on expanding their memory memory fabrication capacity, which when you combine it with what we've been talking about meta and the general concern of over supply goes a long way to explaining why we did see those chunks taken out of memory memory makers that that you mentioned earlier. And do you think, maybe this is the gamer and me being a little too optimistic, do you think we could be going back to a time where memory is being sold maybe, maybe maybe not at the where it was before, being basically sold at or below cost, but a lot cheaper, not 700 times where it was last year.
>> So the memory, the thing with memory is it's a boom and bust industry. only 2 years ago, 3 years ago even, Micron and them were in real trouble because memory is classical memory. So DDR and all that, the stuff in your computer is not super high margin. High bandwidth RAM, so the kind that's actually on the GPUs themselves, extremely high margin, but they take up more space on the fabs when you actually build the RAM. I'm simplifying. Someone in the comments is going to say this is too simple. Shut up. Anyway, um but basically, so their fabs are being taken up more by these this very expensive RAM that's basically just going to Nvidia or it's going to other GPUs and AS6 then. So all of that's happening. So that's just taking up more room, leaving only a little bit of space for the regular RAM, which they can charge whatever they want for now because there's a supply shortage. It's going to take years to fix. I just I hate to say it, but when you when this era is done, hating the AI industry, you need to hate them way more than you already do, in my opinion. Because it's not just all of the horrible stealing and the all of the money they take and the lying and the misleading and the nonsensical economics. It's the fact that because of the demands of basically one industry and building data centers for basically two companies. Uh it's going to crank up the cost of RAM until 2028 minimum. And the problem is is that before this point SKH Micron they were saying we're not going to massively increase our capex. We're not going to overextend ourselves because memory is boom and bust. You get a big time you fill your boots you fill your coffers and then you say okay this is going to crash. No problem. Except now SKH Heinix is saying that they're going to remove the price caps on their long-term deals, meaning that they can just screw their partners all the live long day. I think you have to do a minimum agreement three years now versus one year. That again, not that scary. What is scary is this 500 billion investment.
>> The only way they can fund that is if there's continued business for their memory. If that if they make commitments that they can't fulfill, they are going to be in financial trouble again. Again, three years ago, all of them are in the same trouble because they massively over supplied because there was the postcoid thing where everyone wanted RAM and now no one wants RAM. This is going to be far more dangerous though because AI bubble bursts. The use of HB RAM is not it's not going we're not going to need all that VRAM anymore. we're not going to need quite as much, which means that they're just going to be sitting around with a bunch of RAM that has uses. There are other uses for high bandwidth RAM, but nowhere near as much. So, it's going to create this situation where they will have overextended themselves. Nvidia will have overextended themselves. Microsoft, Google, Amazon overextended. The whole tech industry is going to be cash poor for a while. I think the only way they fix that is by charging way more. I actually don't know. But what I do know is that these companies, these memory companies really think they're living high on the hog right now. And there's one argument to be made that they got kind of screwed in previous eras, but I think it's hard to I'm paraphrasing Steve Burke from Gamers Nex. It's hard to feel bad for a company like Micron when they're screwing gamers so badly and when they have 84 something% margins. Like they didn't have to do that. like they could have 70% margins which would be still great for memory but they're like no we have to and it's because everyone wants it so we're cranking it up and it's just it is an unhealthy way to run a business and perhaps we need the memory companies to have a more consistent business line which would mean in aggregate the prices raise a bit but what they're doing now is nakedly evil and it is completely caused by the AI industry it's caused by the demands of high bandwidth RAM and when the crash comes it's going to be so much just like just like I've been thing. It's going to be so much worse the longer this goes on because now the cost of pretty much every consumer electronic is going up. Even the cost of used consumer electronics. Go on eBay right now and look for a laptop and see how many of them are sold without RAM. It's truly disgusting actually. And it's in storage now with a nan solid state storage and nan storage and all that. It's just it's truly disgraceful. And I don't I don't know how they're going to spend500 billion dollars. I hope they don't begin construction too much because they're not gonna have the money to pay for it. Now to be clear, nothing's going to happen to Micron or Skhinx or Samsung, especially the last two. They're I think they're Shyballs, which is basically like quasationalized Korean companies. I think they will be fine. Nothing will happen to them, especially Samsung. Micron will be fine because the industry needs them. But it's it's frustrating because as always when this bursts the financial crisis that will follow will hit regular people. When the memory bubble bursts the cost won't come down. It will just be rough for everyone involved and ultimately the consumer will suffer. Again the AI industry I don't even think gets a hard enough time because they cause this. Every single person who inflated this bubble is to blame for the cost of RAM for the cost of storage for the cost of everything going up. The inflation caused by the AI industry is their fault and they should suffer for it. They won't. The rich people will be fine at the end of this. But we need to know who the enemy is and what they have done to us.
>> So just to kind of bring this full circle in your free newsletter, you kind of put it very succinctly that this sort of trillion dollar of hypers scale capex is essentially just feeding a massive semiconductor boom on the hopes that LLM's turn into something that they're not, something completely different.
>> Yeah. And currently the rate at which LLMs are improving is starting to plateau and open source is starting to kind of catch up. And we have talked about this in loose terms before but how much of a leap is needed to make the buildout make more sense even if we kind of do put aside this excess of compute.
>> They would have to actually do the things that they said LLMs would do. So, culturally, when we think of AI, we think of set it and forget it. And we think of autonomous intelligence. You know, AI. It's meant to be something where it just works. You don't think about it. I don't even think you'd prompt it. It would just do all this stuff in the background magically and it would just work. You wouldn't have to worry about hallucinations. So, you just have to solve the mathematically certain hallucination problem. By the way, when I say it's mathematically certain, that's from OpenAI's own research. So yeah, you just have to fix that, you know, just maths. Just fix maths. Just fix maths first. It would have to be the computer from Star Trek. It would have to just be like, I want this and it would pop out and it would be great. I want to clone Slack and it would have a Slack clone and it would work completely and it would be provisioned and it would be secure and it would be online. It would be on AWS. You would have all the CDN stuff set up. All of that would just have to happen. It would basically have to be a thing it's not. It would cause an immediate job apocalypse. This is like, but I am basically talking in fantasy terms. I may as well be talking about wyvens and dragons and such wizards because that is how realistic this is. And also, I don't know, that sounds like a completely different product to me, which suggests all the capex so far has been a waste. So, it would have to be a product so good that it did all the things they promised. And it would have to be so good and so revenue generating that it would make up for the fact that they basically wasted a trillion dollars getting there because it is a waste. Like if they somehow work this out, which I really don't believe they will, it will be because of something they've done from today onwards. It's not going to be anything to do with what they've done before. Large language models are not going to do that. And you can oink and squawk in the comments all you want about, oh, I've used it for coding. It's not good enough. It's just not good. It's not good enough. doesn't doesn't make any of this worthwhile. Sorry. For it to be worth it, it would have to be a product where they could get basically a hundred bucks a month from every human on Earth and they would have to pay. It would have to. And to be clear, that would mean a product more sticky and relevant than Spotify or Netflix. Like just they make 3040 billion a year. I think Netflix it would have to be like 10x that between two companies. And it would have to be consistent revenue because right now I think we're going to see we haven't had a report on new revenues from Anthropic in a minute. We haven't had a new ARR. Perhaps they'll have one more bump and then I don't know. But everyone's cutting back on that. Tesla is limiting people to 200 bucks a month in sorry 200 bucks a week of AI use. Everyone's cutting back. UBS had a study saying 60% of enterprises are doing some kind of token minimizing. This is a sign that their revenues are going to go down because they moved everyone to token based billing. They would have to get something that was real consistent recurring revenue, which would mean they would have to have lowered costs so much that the subscription model works because there's no there is no metered business on earth other than gasoline and electricity. That actually works like so they have to lower the cost to effectively nothing and make the end product so impossible to avoid and so useful that it would mean that everyone had to use it. And I'm just I'm what we're describing is the antithesis of LLMs. LLM's like, "Oh, the fuel it's insanely expensive. The output's extremely unreliable." When we say AI, we think of Commander Data from Star Trek. We think of this ultra intelligent, completely 100% reliable, cold, rational, completely functional thing. And with LLM, it's like, "All right, can you get it to do this?" Uh, kind of. But you need to prompt it, right? And if you use the wrong harness, it's not going to work. And yeah, you're going to have to make sure you have to check it doesn't do this. Cuz if it does, if it breaks this, well, then everything breaks. You in ideally when you do research using Netherlands, you have to know the subject matter completely so you can tell if it got something wrong. At which point it's like if you needed someone to be confidently wrong, you could just talk to anyone online. Literally anyone. You find someone in two seconds be like, "Yeah, yes, yeah, yeah. I think America was founded in 2001. I don't know, mate. I didn't really look recently. That is an LLM to me. No matter how much it gets right, it will always get something wrong. So yeah, the answer is for this to work out, they need something else. And that something else needs to be so overwhelmingly good that it needs to completely wipe out the past. It needs to just be like they need to cuz it's no longer sufficient for this to just become a regular business. Let's say best case scenario, OpenAI and Anthropic fudged together some profitability and they became Salesforce sized which is 40 50 60 billion of annual revenue and with like I don't know 50% gross margins. What that combined infrastructure cost I estimate along with their funding is about $540 billion. We spent half a trillion dollars to get one more sales force or two more sales forces run by some of the dampest, most annoying people alive. Jesus Christ. But that's the thing in that let's take that scenario for a ride for a second. Great. Microsoft, Google, Amazon. Wow. So, they've made they have two very large new clients and businesses that kind of work, but LLM still mess up in the way they do and people use it for coding. I guess it's still unexceptional and it's still not enough. They need trillions of dollars of revenue for AI. They need it to do many layers more. Microsoft just started a forward deployment engineer team to help organizations get the most out of AI. Guess what? That's what you do when it doesn't work. Why do if this is so magical, if this is so intelligent, if this is so autonomous, why do you need an army of McKenzie perverts to invade my business to make it functional? The answer is it isn't functional. LLMs are a con perpetuated by con artists. And I'm sick of I'm sick of them. I'm sick of the waste. I'm sick of the people who have dedicated themselves to this graveyard smash. I think it's insulting to humanity. It's driving the cost up of everything. And everyone involved should feel ashamed of themselves.
Well, on that note, Ed Zitron, thanks for taking the time.
>> Thanks for having me. If you enjoyed today's episode and you want to hear more of the tech report, please consider liking and subscribing. Also, you can get episodes of the Tech Report wherever you get your podcasts.