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Circular Financing: Does Nvidia's $110B Bet Echo the Telecom Bubble?

249 points by miltava 1y ago

alephnerd 1y ago
Glad to see Tom's blog on HN - as usual a great write up. A number of us have been chatting about this for several months now, and the take is fairly sober. Meta commentary but I've grown weary of how commentary by actual domain experts in our industry are underrepresented and underdiscussed on HN in favor of emotionally charged takes.
- dvt 1y ago
  > actual domain experts Calling a VC a "domain expert" is like calling an alcoholic a "libation engineer." VC blogs are, in the best case, mildly informative, and in the worst, borderline fraudulent (the Sequoia SBF piece being a recent example, but there are hundreds). The incentives are, even in a true "domain expert" case (think: doctors, engineers, economists), often opaque. But when it comes to VCs, this gets ratcheted up by an order of magnitude.
  - alephnerd 1y ago
    Tom has had a fairly solid track record at Redpoint and now Theory in Data, Enterprise SaaS, and AI/ML. And it's not like we see many posts by engineers, doctors, or economists on HN either - most posts are listicles about the "culture" of technology, an increased amount of political articles growing increasingly tenuously related to the tech industry, and a portion of actually interesting technical content.
  - hodgesrm 1y ago
    Martin Casado is a counter-example. His writings on technology starting with his phd thesis are very informative. [0] He’s the real thing as are many others. [0] http://yuba.stanford.edu/~casado/mcthesis.pdf http://yuba.stanford.edu/~casado/mcthesis.pdf
- deleted 1y ago
  [deleted]
redwood 1y ago
TLDR: Lucent was committing various forms of accounting fraud and had an unhealthy cash flow position, and had their primary customers on economically dangerous ground. Nvidia meanwhile appears to be above board, has strong cash flow, and has extremely strong dominant customers (eg customers that could reduce spending but can survive a downturn). Therefore there's no clear takeaway: similarities but also differences. Risk and a lot of debt as well as hyperscalers insulating themselves from some of that risk... but at the same time as lot more cash to burn.
dangus 1y ago
I think we are at the PS3/Xbox 360 phase of AI. By that I mean, those were the last consoles where performance improvements delivered truly new experiences, where the hardware mattered. Today, any game you make for a modern system is a game you could have made for the PS3/Xbox 360 or perhaps something slightly more powerful. Certainly there have been experiences that use new capabilities that you can’t literally put on those consoles, but they aren’t really “more” in the same way that a PS2 offered “more” than the PlayStation. I think in that sense, there will be some kind of bubble. All the companies that thought that AI would eventually get good enough to suit their use case will eventually be disappointed and quit their investment. The use cases where AI makes sense will stick around. It’s kind of like how we used to have pipe dreams of certain kinds of gameplay experiences that never materialized. With our new hardware power we thought that maybe we could someday play games with endless universes of rich content. But now that we are there, we see games like Starfield prove that dream to be something of a farce.
- ben_w 1y ago
  > By that I mean, those were the last consoles where performance improvements delivered truly new experiences, where the hardware mattered. I hope that's where we are, because that means my experience will still be valuable and vibe coding remains limited to "only" tickets that take a human about half a day, or a day if you're lucky. Given the cost needed for improvements, it's certainly not implausible… …but it's also not a sure thing. I tried "Cursor" for the first time last week, and just like I've been experiencing every few months since InstructGPT was demonstrated, it blew my mind. My game metaphor is 3D graphics in the 90s: every new release feels amazing*, such a huge improvement over the previous release, but behind the hype and awe there was enough missing for us to keep that cycle going for a dozen rounds. * we used to call stuff like this "photorealistic": https://www.reddit.com/r/gaming/comments/ktyr1/unreal_yes_this_is_an_actual_pc_game_screenshot/ https://www.reddit.com/r/gaming/comments/ktyr1/unreal_yes_th...
- jcranmer 1y ago
  > By that I mean, those were the last consoles where performance improvements delivered truly new experiences, where the hardware mattered. The PS3 is the last console to have actual specialized hardware. After the PS3, everything is just regular ol' CPU and regular ol' GPU running in a custom form factor (and a stripped-down OS on top of it); before then, with the exception of the Xbox, everything had customized coprocessors that are different from regular consumer GPUs.
davedx 1y ago
Some great insights with some less interesting in there. I didn’t know about the SPVs, that’s sketchy and now I wanna know how much of that is going on. The MIT study that gets pulled out for every critical discussion of AI was an eye roll for me. But very solid analysis of the quants. How much of a threat is custom silicon to Nvidia remains an open question to me. I kinda think, by now, we can say they’re similar but different enough to coexist in the competitive compute landscape?
- alephnerd 1y ago
  > How much of a threat is custom silicon to Nvidia remains an open question to me Nvidia has also begun trying to enter the custom silicon sector as well, but it's still largely dominated by Broadcom, Marvell, and Renesas.
monkeydust 1y ago
Where can you track GPU utilization rates? Assuming private data but curious if not.
spaceballbat 1y ago
Looking at the last chapter of the essay, there was a lot of illegal activity by lucent in the runup to the collapse. Today, We won’t know the list of shady practices until the bubble bursts. I doubt Tom could legally speculate, he’d likely be sued into oblivion if he even hinted at malfeasance by these trillion dollar companies.
hackthemack 1y ago
I worked at a mom and pop ISP in the 90s. Lucent did seem at the forefront of internet equipment at the time. We used Portmaster 3s to handle dial up connections. We also looked into very early wireless technology from Lucent. Something I wanted to mention, only somewhat tanget. The Telecommunications Act of 1996 forced telecommunication companies to lease out their infrastructure. It massively reduced the prices an ISP had to pay to get T1, because, suddenly, there was competition. I think a T1 went from 1800 a month in 1996, to around 600 a month in 1999. It was a long time ago, so my memory is hazy. But, wouldn't you know it, the Telecommunication companies sued the FCC and the Telecommunications Act was gutted in 2003 https://en.wikipedia.org/wiki/Competitive_local_exchange_carrier#Important_FCC_rulings https://en.wikipedia.org/wiki/Competitive_local_exchange_car...
- awongh 1y ago
  You're implying only 4 years of regulation was enough to shift the balance of power between telecoms and smaller ISPs." If it's true that this regulation was what helped jumpstart the internet it's an interesting counterpoint to the apocalyptic predictions of people when these regulations are undone. (net neutrality comes to mind as well) I've never heard anyone claim before that just having these laws on the books for a small period of time is "enough".
  - watwut 1y ago
    > 've never heard anyone claim before that just having these laws on the books for a small period of time is "enough". Why would it be enough? This legislation prevents monopolies from abusing position, therefore we will repeal it the moment it turns out to be useful? Yeah, it takes time to consolidate power again, that does not mean the legislation is not good.
    - awongh 1y ago
      > Why would it be enough? It worked out just fine? Are you saying that post-2003 internet access should have had more regulation to allow open access? I've never heard anyone complain about that before- is there a specific issue that could have been fixed?
narmiouh 1y ago
I think the fundamental issue is the uncertainty of achieving AGI with baked in fundamentals of reasoning. Almost 90% of topline investments appear to be geared around achieving that in the next 2-5 years. If that doesn’t come to pass soon enough, investors will loose interest. Interest has been maintained by continuous growth in benchmark results. Perhaps this pattern can continue for another 6-12 months before fatigue sets in, there are no new math olympiads to claim a gold medal on… Whats next is to show real results, in true software development, cancer research, robotics. I am highly doubtful the current model architecture will get there.
- cl42 1y ago
  Not sure why you're getting downvoted. If you speak with AI researchers, they all seem reasonable in their expectations. ... but I work with non-technical business people across industries and their expectations are NOT reasonable. They expect ChatGPT to do their entire job for $20/month and hire, plan, budget accordingly. 12 months later, when things don't work out, their response to AI goes to the other end of the spectrum -- anger, avoidance, suspicion of new products, etc. Enough failures and you have slowing revenue growth. I think if companies see lower revenue growth (not even drops!), investors will get very very nervous and we can see a drop in valuations, share prices, etc.
  - Cheer2171 1y ago
    > their expectations are NOT reasonable. They expect ChatGPT to do their entire job for $20/month and hire, plan, budget accordingly. This is entirely on the AI companies and their boosters. Sam Altman literally says gpt 5 is "like having a team of PhD-level experts in your pocket." All the commercials sell this fantasy.
    - watwut 1y ago
      I would blame the business people for being so gullible too.
      - 1y ago
xbmcuser 1y ago
With all the major players like Amzn, Msft and Alphabet going for their own custom chips and restrictions on selling to China it will be interesting to see how Nvidia does. I personally would prefer China to get to parity on node size and get competitive with nvidia. As that is the only way I see the world not being taken over by the tech oligarchy.
- JCM9 1y ago
  The custom chips don’t seem to be gaining traction at scale. On paper the specs look good but the ecosystem isn’t there. The bubble popping and flooding the market with CUDA GPUs means it will make even less sense to switch.
pgspaintbrush 1y ago
Are these companies developing InfiniBand-class interconnects to pair with their custom chips? Without equivalent fabric, they can’t replace NVIDIA GPUs for large-scale training.
- whp_wessel 1y ago
  recent Huang podcast went into this, making the point that custom chips won't be competitive to Nvidia's as they are now making specialised chips instead of just 'gpu's'. https://open.spotify.com/episode/2ieRvuJxrpTh2V626siZYQ?si=24e05045bfaa41f6 https://open.spotify.com/episode/2ieRvuJxrpTh2V626siZYQ?si=2...
  - pgspaintbrush 1y ago
    Thank you for the pointer!
pragmatic 1y ago
At a "telecom of telecom" we (they) were still lighting up dark fiber 15 years later (2015) when mobile data for cell carriers finally created enough demand. Hard to fathom the amount of overbuild. The only difference is fiber optic lines remained useful the whole time. Will these cards have the same longevity? (I have no idea just sharing anecdata)
- hyghjiyhu 1y ago
  I think the chips themselves won't have longevity, but the r&d gone into them is useful. Question is whether the value of that can be captured.
  - adventured 1y ago
    Depends on which companies we're talking about. Nvidia's annualized operating income is so high right now that it'll be capturing more value (op income) in the next four quarters (~$120 billion) than its R&D expenditures have cost over its 32 year history combined. For Nvidia the return has long since been achieved. As the AI spending bubble gives out, Nvidia's profit growth will slow dramatically (single digits), and slamming into a wall (as Cisco did during the telecom bubble; leading up to the telecom crash, Cisco was producing rather insane quarter over quarter growth rates).
- pragmatic 1y ago
  In 2005 telecom was a cash cow because of long distance charges and if your mechanical phone switch was paid off you were printing money (regulations guaranteed revenue) This didn't last that much longer and many places were trying to diversify into managed services (data dog for companues on Orem network and server equipment,etc) which they call "unregulated" revenue. Add written an things business, irrational exuberance can kill you.
- Zigurd 1y ago
  New fiber isn't significantly more power efficient. The other side of the coin is that backhoes haven't become more efficient since the fiber was buried.
mg 1y ago
Fiber networks were using less than 0.002% of available capacity, with potential for 60,000x speed increases. It was just too early. I doubt we will see unused GPU capacity. As soon as we can prompt "Think about the codebase over night. Try different ways to refactor it. Tomorrow, show me your best solution." we will want as much GPU time at the current rate as possible. If a minute of GPU usage is currently $0.10, a night of GPU usage is 8 * 60 * 0.1 = $48. Which might very well be worth it for an improved codebase. Or a better design of a car. Or a better book cover. Or a better business plan.
- cantor_S_drug 1y ago
  With improvements on the algorithm side and new techniques, even older hardware will become useful.
  - Zigurd 1y ago
    I get what you're saying and the reasoning behind it, but older hardware has never been useful where power consumption is part of determining usefulness.
  - chatmasta 1y ago
    This is the biggest threat to the GPU economy – software breakthroughs that enable inference on commodity CPU hardware or specialized ASIC boards that hyperscalers can fabricate themselves. Google has a stockpile of TPUs that seem fairly effective, although it’s hard to tell for certain because they don’t make it easy to rent them.
    - xadhominemx 1y ago
      More efficient inference = more reasoning token. Hyperscaler ASICs are closing the gap at the hardware/system level, yes.
    - Zigurd 1y ago
      I don't think we will need to wait for anything as unpredictable as a breakthrough. Optimizing inference for the most clearly defined tasks, which are also the tasks where value is most readily quantified, like coding, is underway now.
ivape 1y ago
One of the things before AI in the market was that capital had limited growth opportunities. Tech, which was basically a universe of scaled out crud apps, was where capital would keep going back into. AI is a lot more useful than hyper scaled up crud apps. Comparing this to the past is really overfitting imho. The only argument against accumulating GPUs is that they get old and stop working. Not that it sucks, not that it’s not worth it. As in, the argument against it is actually in the spirit of “I wish we could keep the thing longer”. Does that sound like there’s no demand for this thing? The AI thesis requires getting on board with what Jenson has been saying: 1) We have a new way to do things 2) The old ways have been utterly outclassed 3) If a device has any semblance of compute power, it will need to be enhanced, updated, or wholesale replaced with an AI variant. There is no middle ground to this thesis. There is no “and we’ll use AI here and here, but not here, therefore we predictably know what is to come”. Get used to the unreal. Your web apps could truly one day be generated frame by frame by a video model. Really. The amount of compute we’ll need will be staggering.
- pessimizer 1y ago
  > Your web apps could truly one day be generated frame by frame by a video model. Really. The amount of compute we’ll need will be staggering. We've technically been able to play board games by entering our moves into our telephones, sending them to a CPU to be combined, then printing out a new board on paper to conform to the new board state. We do not do this because it would be stupid. We can not depend on people starting to do this saving the paper, printer, and ink industries. Some things are not done because they are worthless.
  - ivape 1y ago
    You know that N people can now point a webcam onto their boards and have a multi modal LLM understand everyone’s board state now, right? Literally zero programming involved, you just have to point a camera at the damn thing and maybe write some glue code. If you’re a board game player then you are more than capable of imagining possibilities well beyond this.
    - 1y ago
stephc_int13 1y ago
Knowing history of past bubbles is only mildly informative. The dotcom bubble was different than the railroads bubble etc. The only thing to keep in mind is that all of this is about business and ROI. Given the colossal investments, even if the companies finances are healthy and not fraudulent, the economic returns have to be unprecedented or there will be a crash. They are all chasing a golden goose.
- delusional 1y ago
  > only mildly informative I agree, but would like to maybe build out that theory. When we start talking about the mechanisms of the past we end up over-constricting the possibility space. There were a ton of different ways the dotcom bubble COULD have played out, and only one way it did. If we view the way it did as the only way it possibly could have, we'll almost certainly miss the way the next bubble will play out.
- Printerisreal 1y ago
  This time they have fiat money and government on their side. so that is also different.
  - candiddevmike 1y ago
    It just means we're all going to be hurt by the collapse, not just investors. In line with socialized loses, privatized profits.
    - Printerisreal 1y ago
      That is also true :)
- Mistletoe 1y ago
  I’m concerned that the accounting differences mentioned between Lucent and Nvidia, Microsoft, OpenAI, Google just mean we have gotten much better at lying and misrepresenting things as true. Then the bubble pops and you get the real numbers and we are all like “yep it was the same thing all over again”.
cl42 1y ago
Great points. I am bullish on AI but also wary of accounting practices. Tom says Nvidia's financials are different from Lucent's but that doesn't mean we shouldn't be wary. The Economist has a great discussion on depreciation assumptions having a huge impact on how the finances of the cloud vendors are perceived[1]. Revenue recognition and expectations around Oracle could also be what bursts the bubble. Coreweave or Oracle could be the weak point, even if Nvidia is not. [1] https://www.economist.com/business/2025/09/18/the-4trn-accounting-puzzle-at-the-heart-of-the-ai-cloud https://www.economist.com/business/2025/09/18/the-4trn-accou...
Theodores 1y ago
This reminds me of SGI at the peak of the dot-com bubble. SGI (Silicon Graphics) made the 3D hardware that many companies relied on for their own businesses, in the days before Windows NT and Nvidia came of age. Alias|Wavefront and Discreet were two companies where their product cycles were very tied in the SGI product cycles, with SGI having some ownership, whether it be wholly owned or spun out (as SGI collapsed). I can't find the reporting from the time, but it seemed to me that the SGI share price was propped up by product launches from the likes of Alias|Wavefront or Discreet. Equally, the 3D software houses seemed to have share prices propped up by SGI product launches. There was also the small matter of insider trading. If you knew the latest SGI boxes were lemons then you could place your bets of the 3D software houses accordingly. Eventually Autodesk, Computer Associates and others eventually owned all the software, or, at least, the user bases. Once upon a time these companies were on the stock market and worth billions, but then they became just another bullet point in the Autodesk footer. My prediction is that a lot of AI is like that, a classic bubble, and, when the show moves on, all of these AI products will get shoehorned into the three companies that will survive, with competition law meaning that it will be three rather than two eventual winners. Equally, much like what happened with SGI, Nvidia will eventually come a cropper due to the evaluations due to today's hype and hubris not delivering.
digitcatphd 1y ago
The biggest issue with Nvidia is their revenue is not recurring but the market is treating their stock as it were, which is correlated with all semi stocks, with a one-time massive CAPEX investment lasting 1-2 years. Simple as this - as to why its just not possible for this to continue.
- cyanydeez 1y ago
  TSLA is the same. Tge market is basically a new rich persons bank, abstracted by loans and lines of credit. Obviously its a bubble but thats meaningless for anyone but the richest to manage. The rest of us are just ants.
- xadhominemx 1y ago
  NVDA stock does not trade at a huge multiple. Only 25x EPS despite very rapid top line growth and a dominant position at the eve of possibly the most important technology transition in the history of humankind. The market is (and has been) pricing in a slowdown.
  - swexbe 1y ago
    What are you talking about? It's trading at 55x EPS and 41x forward EPS.
    - xadhominemx 1y ago
      Consensus EPS for FY27 (~CY26) is $6.40. Buy side is higher!
      - deleted 1y ago
        [deleted]
      - foobarqux 1y ago
        That's 30x for earnings that will be known Jan 2027 (1 year and 3 months away). It's 40x earnings for Jan 2026 (3 months away). For reference Enron was 40x earnings for current year forward estimates early in the year of the crash.
JCM9 1y ago
The smartest finance folks I know say that this “irrational exuberance” works until it doesn’t. Meaning nobody really thinks it’s sustainable, but companies and VCs chasing the AI hype bubble have backed themselves into a corner where the only way to stop the bubble from bursting is to keep inflating the bubble. The fate of the bubble will be decided by Wall Street not tech folks in the valley. Wall Street is already positioning itself for the burst and there’s lots of finance types ready to call party over and trigger the chaos that lets them make bank on the bubble’s implosion. These finance types (family offices, small secret investment funds) eat clueless VCs throwing cash on the fire for lunch… and they’re salivating at what’s ahead. It’s a “Big Short” once in 20-30 years type opportunity.
- delusional 1y ago
  > have backed themselves into a corner where the only way to stop the bubble from bursting is to keep inflating the bubble. They are not in any corner. They rightly believe that they won't be allowed to fail. There's zero cost to inflating the bubble. If they tank a loss, it's not their money and they'll go on to somewhere else. If they get lucky (maybe skillful?) they get out of the bubble before anyone else, but get to ride it all the way to the top. The only way they lose is if they sit by and do nothing. The upside is huge, and the downside is non-existent.
- bwfan123 1y ago
  oracle's announcement of a 300b purchase commitment from openai followed soon by a 100B investment into openai. The pace and size of these announcements is reaching a fever-pitch which seems like an attempt to keep the music playing.
- ProjectArcturis 1y ago
  >These finance types (family offices, small secret investment funds) eat clueless VCs throwing cash on the fire for lunch… and they’re salivating at what’s ahead. It’s a “Big Short” once in 20-30 years type opportunity. No - it's very hard to successfully bet against anything in finance, and VCs and non-public investments are particularly hard. When you go long, you simply buy something and hold it until you decide to sell. If you short, you have to worry about borrowing shares, paying short fees, and having unlimited risk. How would you even begin to bet against OpenAI specifically? The closest proxy I can think of is shorting NVDA. There's also nobody whose job it is to make big one-time shorts. Like you said, it's a once in 20-30 years opportunity, so no one builds a hedge fund dedicated to sitting around for decades waiting for that opportunity. There will certainly be exceptions, and maybe they'll make a Big Short 2 about the scrappy underdogs who saw the opening and timed it perfectly. But the vast majority of Wall Street desperately wants the party to continue.
rossdavidh 1y ago
"This time it's different"
ekjhgkejhgk 1y ago
In reference 14 we read > However, what’s become clear is that OpenAI plans to pay for Nvidia’s graphics processing units (GPUs) through lease arrangements, rather than upfront purchases I wish someone here could explain it to a dummy like me. Nvidia tells OpenAI: heres some GPUs, can you pay for them over 5 years. How is this an "investment" by Nvidia? That reference keeps calling this an investment, but what they describe is a lease agreement. Why do they call it an investment? What am I missing?
- sbuttgereit 1y ago
  That Nvidia has to front the costs of the product at the beginning and arguably the risk that the allocation of assets end up not being paid off (bankruptcy, etc.) By carrying those costs early and the associated risk, Nvidia expects a return on that. If the risk is realized they'll lose but otherwise they'll gain. That has all the hallmarks of an investment.
  - ekjhgkejhgk 1y ago
    Thanks for your reply, but: NVidia could protect itself against OpenAI bankrupcy by adding a clause to the lease saying that if OpenAI goes bankrupt, Nvidia gets its GPUs back. So the risk would only be that the lease would be aborted sooner than expected.
    - tome 1y ago
      > So the risk would only be that the lease would be aborted sooner than expected. That is, in fact, the risk.
      - ekjhgkejhgk 1y ago
        But Im saying something different than the person I was responding to. They said that the risk was due to company going bankrupt and therefore Nvidia losing its "investment" - read: the GPUs that it leased. Whereas Im saying that the risk is due to company going bankrupt, Nvidia getting its GPUs back, but now they have too many at hand than they can usefully deploy/sell. The two are risks triggered by the same event, but the former is about 1 order of magnitude greater than the latter. The former is lost capital, the latter is lost opportunity - read: return on the capital.
MASNeo 1y ago
I wonder if the buying customers of Nvidia are going to find the self’s left with the overcapacity. Certainly people are waking up to LLM challenges and as budgets focus more on useful applications, smaller language models, how much of that demand will remain. Also, depreciation schedules beyond useful life of an asset may not be fraud but I’d call it a bit too creative for my liking. Time will tell.
nextworddev 1y ago
This article is pretty confusing, doesn't really have a thesis, just listing some stats. Maybe that's the intent.
- foundart 1y ago
  I had the same response. Certainly it suggests that “this time is different” without saying it in a quotable fashion. The metrics it provides seem useful. What are the metrics it is missing?
  - nextworddev 1y ago
    The thing that this doesn't get is that 10bn a year is basically 70%+ of yearly R&D and inference budget of OpenAI.. so this Nvidia deal is actually great (for OpenAI) in terms of protecting its cashflow
rglullis 1y ago
The one thing I don't understand is this assumption that demand for GPUs for training is going to keep growing at the rate they grew so far. I get the demand for new applications, which require inference, but nowadays with so many good (if not close to SOTA) models available for free and the ability to run them on consumer hardware (apple M4 or AMD Max APUs), is there any demand for applications that justify a crazy amount of investment in GPUs?
- porridgeraisin 1y ago
  Inference will be cheapest when run in a shared cloud environment, simply due to the LLMs roofline. Thus, most B2B use cases are likely to be datacenter based, like AWS today. Of course, cern is still going to use their FPGA hyper-optimized for their specific trigger model for the LHC, and apple is gojng to use a specialized low power ASIC running a quantized model for hello Siri, but I meant the majority usecase.
  - rglullis 1y ago
    I do not buy this premise. I think it will end up being cheaper to simply run the LLMs directly on the user device. I think that there are plenty of competitors in the "LLMs with open weights" space to essentially make the models a commodity, so all that is left is the compute cost and there is no way that someone will be running a datacenter in a way that is cheaper than "the computer that I already have running on my desk".
    - lelanthran 1y ago
      I nake your point every time this comes up[1] but its absolutely surprising how few business people, most of whom have some credibility in the form of qualifications or experience, actually recognise a value chain when they see it. ========== [1] https://rundata.co.za/blog/index.html?the-ai-value-chain https://rundata.co.za/blog/index.html?the-ai-value-chain
- bix6 1y ago
  Isn’t the whole point of the arms race that the more GPUs you have the closer you get to AGI? Which is the supposed goal here.
ekjhgkejhgk 1y ago
Related https://capitalgains.thediff.co/p/vendor-financing https://capitalgains.thediff.co/p/vendor-financing
yalogin 1y ago
The telecom bubble built infrastructure for something that didn’t exist, they built anticipating the need for high didn’t come in time. The gpu bubble is different. Nvidia is actually selling gpus in spades. So it’s not comparable to the telecom bubble. Now the question remains how many more gpus can they sell? That depends on the kind of services that are built and how their adoption takes off. So now is it a bubble or just frothy at the top? There is definitely going to be a pull back and some adjustment, but I cannot say how bad it is
mooreds 1y ago
Good analysis. But the answer is, "kinda"? There are similarities, but the AI buildout is worse in some ways (more concentration, GPU backed debt) and better in others (capacity is being used, vendors actually have cash flow). The conclusion: > Unlike the telecom bubble, where demand was speculative & customers burned cash , this merry-go-round has paying riders. Seems a little short sighted to me. IMO, there is a definite echo, but we are in the mid-late stage, not the end stage. It's simply not fair to compare Lucent at the end of a bubble with Nvidia in the middle, and that is what the author did. If you haven't listened to the referenced interview between Thompson and Kedrosky, I'd do so: https://www.theringer.com/podcasts/plain-english-with-derek-thompson/2025/09/23/this-is-how-the-ai-bubble-could-burst https://www.theringer.com/podcasts/plain-english-with-derek-...
nickdothutton 1y ago
I was there in the middle of the dotcom crash and the telecoms crash which was much worse. Fiber does not rust, and while there was vast overcapacity, not all of it was lit, or indeed worth lighting. 10 years after, thanks to DWDM there were 8 strand cables where only 2 strands were lit, albeit with many more wavelengths than envisaged before. Even though demand had grown. How much is a 10 year old GPU worth? Where is the “dwdm but for GPUs?”. There truly are interesting times and we have the benefit of being in them.
- keeda 1y ago
  Just so I understand correctly, you mean that with DWDM 2 strands of cables were equivalent to 8 since DWDM as a multiplexing technology increased the capacity of each fiber, right? > How much is a 10 year old GPU worth? Where is the “dwdm but for GPUs?”. From other sources cited in TFA it seems GPUs won't last 3 years, let alone 10! But I think we know what the "DWDM for GPUs" is -- it's the processing efficiency gains that we've seen over the last few years which keeps driving the per-token prices sharply down.
  - nickdothutton 1y ago
    I'm not sure where DWDM is currently, but we quickly went from 1 colour to 512 colours per strand. I expect and hope for increases in GPU performance, some via process shrink, some via wafer size/yield, and some...perhaps... by software efficiencies (most interesting to me). Maybe volumes will increase too, further driving down the price for essentially the same parts. However I don't see how these gains (if they happen) can "get us to 512".
dehrmann 1y ago
> Evidence from Google architects shows GPUs at 60-70% utilization survive 1-2 years , with 3 years maximum. Really?! I'm not used to chips having such a short lifespan.
- metadat 1y ago
  This sounds like major FUD unless the data is public.
  - bigyabai 1y ago
    Feels like a teensy tiny conflict of interest, coming from GCP. Additionally - GPUs have multiple components. Which parts are at 60-70% load, the SM unit or the memory controller? If you're throttling the GPU but not the memory, it makes perfect sense why you're burning the damn card out...
cameldrv 1y ago
There was a similar circular effect in the dot com boom around ads. VCs poured money into startups, which put the money into ads on Yahoo and other properties. Yahoo was getting huge revenue from the ads, which pumped up the stock price. The rising price and revenue, and hence stock price of Yahoo pumped up the market for other dot coms, as it proved you could make money on the Internet, so the market for dot com IPOs was strong. That drew more VC money. More VC money meant more ads.
sails 1y ago
> Nvidia’s vendor financing becomes exposure to customers building competitive alternatives. This is surely the most important line in the piece? In what world would this much demand not lead to alternatives emerging? (Assuming the upside, yes if the demand is not there in two years then yes it’s all going to burn)
mwkaufma 1y ago
Distinguishing that in-hindsight Lucent was committing accounting fraud and present firms aren't is a load-bearing assumption here; for all we know the big players in the AI bubble just haven't been outed yet.
- brazukadev 1y ago
  They are infringing copyright in all ways possible, if AI fail they will also have to pay this bill. It'll be the reparations after they lose the war.

249 points by miltava 1y ago

Glad to see Tom's blog on HN - as usual a great write up. A number of us have been chatting about this for several months now, and the take is fairly sober. Meta commentary but I've grown weary of how commentary by actual domain experts in our industry are underrepresented and underdiscussed on HN in favor of emotionally charged takes.

dvt 1y ago
> actual domain experts Calling a VC a "domain expert" is like calling an alcoholic a "libation engineer." VC blogs are, in the best case, mildly informative, and in the worst, borderline fraudulent (the Sequoia SBF piece being a recent example, but there are hundreds). The incentives are, even in a true "domain expert" case (think: doctors, engineers, economists), often opaque. But when it comes to VCs, this gets ratcheted up by an order of magnitude.
- alephnerd 1y ago
  Tom has had a fairly solid track record at Redpoint and now Theory in Data, Enterprise SaaS, and AI/ML. And it's not like we see many posts by engineers, doctors, or economists on HN either - most posts are listicles about the "culture" of technology, an increased amount of political articles growing increasingly tenuously related to the tech industry, and a portion of actually interesting technical content.
- hodgesrm 1y ago
  Martin Casado is a counter-example. His writings on technology starting with his phd thesis are very informative. [0] He’s the real thing as are many others. [0] http://yuba.stanford.edu/~casado/mcthesis.pdf http://yuba.stanford.edu/~casado/mcthesis.pdf
deleted 1y ago
[deleted]

redwood 1y ago

TLDR: Lucent was committing various forms of accounting fraud and had an unhealthy cash flow position, and had their primary customers on economically dangerous ground. Nvidia meanwhile appears to be above board, has strong cash flow, and has extremely strong dominant customers (eg customers that could reduce spending but can survive a downturn). Therefore there's no clear takeaway: similarities but also differences. Risk and a lot of debt as well as hyperscalers insulating themselves from some of that risk... but at the same time as lot more cash to burn.

dangus 1y ago

I think we are at the PS3/Xbox 360 phase of AI. By that I mean, those were the last consoles where performance improvements delivered truly new experiences, where the hardware mattered. Today, any game you make for a modern system is a game you could have made for the PS3/Xbox 360 or perhaps something slightly more powerful. Certainly there have been experiences that use new capabilities that you can’t literally put on those consoles, but they aren’t really “more” in the same way that a PS2 offered “more” than the PlayStation. I think in that sense, there will be some kind of bubble. All the companies that thought that AI would eventually get good enough to suit their use case will eventually be disappointed and quit their investment. The use cases where AI makes sense will stick around. It’s kind of like how we used to have pipe dreams of certain kinds of gameplay experiences that never materialized. With our new hardware power we thought that maybe we could someday play games with endless universes of rich content. But now that we are there, we see games like Starfield prove that dream to be something of a farce.

ben_w 1y ago
> By that I mean, those were the last consoles where performance improvements delivered truly new experiences, where the hardware mattered. I hope that's where we are, because that means my experience will still be valuable and vibe coding remains limited to "only" tickets that take a human about half a day, or a day if you're lucky. Given the cost needed for improvements, it's certainly not implausible… …but it's also not a sure thing. I tried "Cursor" for the first time last week, and just like I've been experiencing every few months since InstructGPT was demonstrated, it blew my mind. My game metaphor is 3D graphics in the 90s: every new release feels amazing*, such a huge improvement over the previous release, but behind the hype and awe there was enough missing for us to keep that cycle going for a dozen rounds. * we used to call stuff like this "photorealistic": https://www.reddit.com/r/gaming/comments/ktyr1/unreal_yes_this_is_an_actual_pc_game_screenshot/ https://www.reddit.com/r/gaming/comments/ktyr1/unreal_yes_th...
jcranmer 1y ago
> By that I mean, those were the last consoles where performance improvements delivered truly new experiences, where the hardware mattered. The PS3 is the last console to have actual specialized hardware. After the PS3, everything is just regular ol' CPU and regular ol' GPU running in a custom form factor (and a stripped-down OS on top of it); before then, with the exception of the Xbox, everything had customized coprocessors that are different from regular consumer GPUs.

davedx 1y ago

Some great insights with some less interesting in there. I didn’t know about the SPVs, that’s sketchy and now I wanna know how much of that is going on. The MIT study that gets pulled out for every critical discussion of AI was an eye roll for me. But very solid analysis of the quants. How much of a threat is custom silicon to Nvidia remains an open question to me. I kinda think, by now, we can say they’re similar but different enough to coexist in the competitive compute landscape?

alephnerd 1y ago
> How much of a threat is custom silicon to Nvidia remains an open question to me Nvidia has also begun trying to enter the custom silicon sector as well, but it's still largely dominated by Broadcom, Marvell, and Renesas.

monkeydust 1y ago

Where can you track GPU utilization rates? Assuming private data but curious if not.

spaceballbat 1y ago

Looking at the last chapter of the essay, there was a lot of illegal activity by lucent in the runup to the collapse. Today, We won’t know the list of shady practices until the bubble bursts. I doubt Tom could legally speculate, he’d likely be sued into oblivion if he even hinted at malfeasance by these trillion dollar companies.

hackthemack 1y ago

I worked at a mom and pop ISP in the 90s. Lucent did seem at the forefront of internet equipment at the time. We used Portmaster 3s to handle dial up connections. We also looked into very early wireless technology from Lucent. Something I wanted to mention, only somewhat tanget. The Telecommunications Act of 1996 forced telecommunication companies to lease out their infrastructure. It massively reduced the prices an ISP had to pay to get T1, because, suddenly, there was competition. I think a T1 went from 1800 a month in 1996, to around 600 a month in 1999. It was a long time ago, so my memory is hazy. But, wouldn't you know it, the Telecommunication companies sued the FCC and the Telecommunications Act was gutted in 2003 https://en.wikipedia.org/wiki/Competitive_local_exchange_carrier#Important_FCC_rulings https://en.wikipedia.org/wiki/Competitive_local_exchange_car...

awongh 1y ago
You're implying only 4 years of regulation was enough to shift the balance of power between telecoms and smaller ISPs." If it's true that this regulation was what helped jumpstart the internet it's an interesting counterpoint to the apocalyptic predictions of people when these regulations are undone. (net neutrality comes to mind as well) I've never heard anyone claim before that just having these laws on the books for a small period of time is "enough".
- watwut 1y ago
  > 've never heard anyone claim before that just having these laws on the books for a small period of time is "enough". Why would it be enough? This legislation prevents monopolies from abusing position, therefore we will repeal it the moment it turns out to be useful? Yeah, it takes time to consolidate power again, that does not mean the legislation is not good.
  - awongh 1y ago
    > Why would it be enough? It worked out just fine? Are you saying that post-2003 internet access should have had more regulation to allow open access? I've never heard anyone complain about that before- is there a specific issue that could have been fixed?

narmiouh 1y ago

I think the fundamental issue is the uncertainty of achieving AGI with baked in fundamentals of reasoning. Almost 90% of topline investments appear to be geared around achieving that in the next 2-5 years. If that doesn’t come to pass soon enough, investors will loose interest. Interest has been maintained by continuous growth in benchmark results. Perhaps this pattern can continue for another 6-12 months before fatigue sets in, there are no new math olympiads to claim a gold medal on… Whats next is to show real results, in true software development, cancer research, robotics. I am highly doubtful the current model architecture will get there.

cl42 1y ago
Not sure why you're getting downvoted. If you speak with AI researchers, they all seem reasonable in their expectations. ... but I work with non-technical business people across industries and their expectations are NOT reasonable. They expect ChatGPT to do their entire job for $20/month and hire, plan, budget accordingly. 12 months later, when things don't work out, their response to AI goes to the other end of the spectrum -- anger, avoidance, suspicion of new products, etc. Enough failures and you have slowing revenue growth. I think if companies see lower revenue growth (not even drops!), investors will get very very nervous and we can see a drop in valuations, share prices, etc.
- Cheer2171 1y ago
  > their expectations are NOT reasonable. They expect ChatGPT to do their entire job for $20/month and hire, plan, budget accordingly. This is entirely on the AI companies and their boosters. Sam Altman literally says gpt 5 is "like having a team of PhD-level experts in your pocket." All the commercials sell this fantasy.
  - watwut 1y ago
    I would blame the business people for being so gullible too.
    - 1y ago

xbmcuser 1y ago

With all the major players like Amzn, Msft and Alphabet going for their own custom chips and restrictions on selling to China it will be interesting to see how Nvidia does. I personally would prefer China to get to parity on node size and get competitive with nvidia. As that is the only way I see the world not being taken over by the tech oligarchy.

JCM9 1y ago
The custom chips don’t seem to be gaining traction at scale. On paper the specs look good but the ecosystem isn’t there. The bubble popping and flooding the market with CUDA GPUs means it will make even less sense to switch.

pgspaintbrush 1y ago

Are these companies developing InfiniBand-class interconnects to pair with their custom chips? Without equivalent fabric, they can’t replace NVIDIA GPUs for large-scale training.

whp_wessel 1y ago
recent Huang podcast went into this, making the point that custom chips won't be competitive to Nvidia's as they are now making specialised chips instead of just 'gpu's'. https://open.spotify.com/episode/2ieRvuJxrpTh2V626siZYQ?si=24e05045bfaa41f6 https://open.spotify.com/episode/2ieRvuJxrpTh2V626siZYQ?si=2...
- pgspaintbrush 1y ago
  Thank you for the pointer!

pragmatic 1y ago

At a "telecom of telecom" we (they) were still lighting up dark fiber 15 years later (2015) when mobile data for cell carriers finally created enough demand. Hard to fathom the amount of overbuild. The only difference is fiber optic lines remained useful the whole time. Will these cards have the same longevity? (I have no idea just sharing anecdata)

hyghjiyhu 1y ago
I think the chips themselves won't have longevity, but the r&d gone into them is useful. Question is whether the value of that can be captured.
- adventured 1y ago
  Depends on which companies we're talking about. Nvidia's annualized operating income is so high right now that it'll be capturing more value (op income) in the next four quarters (~$120 billion) than its R&D expenditures have cost over its 32 year history combined. For Nvidia the return has long since been achieved. As the AI spending bubble gives out, Nvidia's profit growth will slow dramatically (single digits), and slamming into a wall (as Cisco did during the telecom bubble; leading up to the telecom crash, Cisco was producing rather insane quarter over quarter growth rates).
pragmatic 1y ago
In 2005 telecom was a cash cow because of long distance charges and if your mechanical phone switch was paid off you were printing money (regulations guaranteed revenue) This didn't last that much longer and many places were trying to diversify into managed services (data dog for companues on Orem network and server equipment,etc) which they call "unregulated" revenue. Add written an things business, irrational exuberance can kill you.
Zigurd 1y ago
New fiber isn't significantly more power efficient. The other side of the coin is that backhoes haven't become more efficient since the fiber was buried.

mg 1y ago

Fiber networks were using less than 0.002% of available capacity, with potential for 60,000x speed increases. It was just too early. I doubt we will see unused GPU capacity. As soon as we can prompt "Think about the codebase over night. Try different ways to refactor it. Tomorrow, show me your best solution." we will want as much GPU time at the current rate as possible. If a minute of GPU usage is currently $0.10, a night of GPU usage is 8 * 60 * 0.1 = $48. Which might very well be worth it for an improved codebase. Or a better design of a car. Or a better book cover. Or a better business plan.

cantor_S_drug 1y ago
With improvements on the algorithm side and new techniques, even older hardware will become useful.
- Zigurd 1y ago
  I get what you're saying and the reasoning behind it, but older hardware has never been useful where power consumption is part of determining usefulness.
- chatmasta 1y ago
  This is the biggest threat to the GPU economy – software breakthroughs that enable inference on commodity CPU hardware or specialized ASIC boards that hyperscalers can fabricate themselves. Google has a stockpile of TPUs that seem fairly effective, although it’s hard to tell for certain because they don’t make it easy to rent them.
  - xadhominemx 1y ago
    More efficient inference = more reasoning token. Hyperscaler ASICs are closing the gap at the hardware/system level, yes.
  - Zigurd 1y ago
    I don't think we will need to wait for anything as unpredictable as a breakthrough. Optimizing inference for the most clearly defined tasks, which are also the tasks where value is most readily quantified, like coding, is underway now.

ivape 1y ago

One of the things before AI in the market was that capital had limited growth opportunities. Tech, which was basically a universe of scaled out crud apps, was where capital would keep going back into. AI is a lot more useful than hyper scaled up crud apps. Comparing this to the past is really overfitting imho. The only argument against accumulating GPUs is that they get old and stop working. Not that it sucks, not that it’s not worth it. As in, the argument against it is actually in the spirit of “I wish we could keep the thing longer”. Does that sound like there’s no demand for this thing? The AI thesis requires getting on board with what Jenson has been saying: 1) We have a new way to do things 2) The old ways have been utterly outclassed 3) If a device has any semblance of compute power, it will need to be enhanced, updated, or wholesale replaced with an AI variant. There is no middle ground to this thesis. There is no “and we’ll use AI here and here, but not here, therefore we predictably know what is to come”. Get used to the unreal. Your web apps could truly one day be generated frame by frame by a video model. Really. The amount of compute we’ll need will be staggering.

pessimizer 1y ago
> Your web apps could truly one day be generated frame by frame by a video model. Really. The amount of compute we’ll need will be staggering. We've technically been able to play board games by entering our moves into our telephones, sending them to a CPU to be combined, then printing out a new board on paper to conform to the new board state. We do not do this because it would be stupid. We can not depend on people starting to do this saving the paper, printer, and ink industries. Some things are not done because they are worthless.
- ivape 1y ago
  You know that N people can now point a webcam onto their boards and have a multi modal LLM understand everyone’s board state now, right? Literally zero programming involved, you just have to point a camera at the damn thing and maybe write some glue code. If you’re a board game player then you are more than capable of imagining possibilities well beyond this.
  - 1y ago

stephc_int13 1y ago

Knowing history of past bubbles is only mildly informative. The dotcom bubble was different than the railroads bubble etc. The only thing to keep in mind is that all of this is about business and ROI. Given the colossal investments, even if the companies finances are healthy and not fraudulent, the economic returns have to be unprecedented or there will be a crash. They are all chasing a golden goose.

delusional 1y ago
> only mildly informative I agree, but would like to maybe build out that theory. When we start talking about the mechanisms of the past we end up over-constricting the possibility space. There were a ton of different ways the dotcom bubble COULD have played out, and only one way it did. If we view the way it did as the only way it possibly could have, we'll almost certainly miss the way the next bubble will play out.
Printerisreal 1y ago
This time they have fiat money and government on their side. so that is also different.
- candiddevmike 1y ago
  It just means we're all going to be hurt by the collapse, not just investors. In line with socialized loses, privatized profits.
  - Printerisreal 1y ago
    That is also true :)
Mistletoe 1y ago
I’m concerned that the accounting differences mentioned between Lucent and Nvidia, Microsoft, OpenAI, Google just mean we have gotten much better at lying and misrepresenting things as true. Then the bubble pops and you get the real numbers and we are all like “yep it was the same thing all over again”.

cl42 1y ago

Great points. I am bullish on AI but also wary of accounting practices. Tom says Nvidia's financials are different from Lucent's but that doesn't mean we shouldn't be wary. The Economist has a great discussion on depreciation assumptions having a huge impact on how the finances of the cloud vendors are perceived[1]. Revenue recognition and expectations around Oracle could also be what bursts the bubble. Coreweave or Oracle could be the weak point, even if Nvidia is not. [1] https://www.economist.com/business/2025/09/18/the-4trn-accounting-puzzle-at-the-heart-of-the-ai-cloud https://www.economist.com/business/2025/09/18/the-4trn-accou...

Theodores 1y ago

This reminds me of SGI at the peak of the dot-com bubble. SGI (Silicon Graphics) made the 3D hardware that many companies relied on for their own businesses, in the days before Windows NT and Nvidia came of age. Alias|Wavefront and Discreet were two companies where their product cycles were very tied in the SGI product cycles, with SGI having some ownership, whether it be wholly owned or spun out (as SGI collapsed). I can't find the reporting from the time, but it seemed to me that the SGI share price was propped up by product launches from the likes of Alias|Wavefront or Discreet. Equally, the 3D software houses seemed to have share prices propped up by SGI product launches. There was also the small matter of insider trading. If you knew the latest SGI boxes were lemons then you could place your bets of the 3D software houses accordingly. Eventually Autodesk, Computer Associates and others eventually owned all the software, or, at least, the user bases. Once upon a time these companies were on the stock market and worth billions, but then they became just another bullet point in the Autodesk footer. My prediction is that a lot of AI is like that, a classic bubble, and, when the show moves on, all of these AI products will get shoehorned into the three companies that will survive, with competition law meaning that it will be three rather than two eventual winners. Equally, much like what happened with SGI, Nvidia will eventually come a cropper due to the evaluations due to today's hype and hubris not delivering.

digitcatphd 1y ago

The biggest issue with Nvidia is their revenue is not recurring but the market is treating their stock as it were, which is correlated with all semi stocks, with a one-time massive CAPEX investment lasting 1-2 years. Simple as this - as to why its just not possible for this to continue.

cyanydeez 1y ago
TSLA is the same. Tge market is basically a new rich persons bank, abstracted by loans and lines of credit. Obviously its a bubble but thats meaningless for anyone but the richest to manage. The rest of us are just ants.
xadhominemx 1y ago
NVDA stock does not trade at a huge multiple. Only 25x EPS despite very rapid top line growth and a dominant position at the eve of possibly the most important technology transition in the history of humankind. The market is (and has been) pricing in a slowdown.
- swexbe 1y ago
  What are you talking about? It's trading at 55x EPS and 41x forward EPS.
  - xadhominemx 1y ago
    Consensus EPS for FY27 (~CY26) is $6.40. Buy side is higher!
    - deleted 1y ago
      [deleted]
    - foobarqux 1y ago
      That's 30x for earnings that will be known Jan 2027 (1 year and 3 months away). It's 40x earnings for Jan 2026 (3 months away). For reference Enron was 40x earnings for current year forward estimates early in the year of the crash.

JCM9 1y ago

The smartest finance folks I know say that this “irrational exuberance” works until it doesn’t. Meaning nobody really thinks it’s sustainable, but companies and VCs chasing the AI hype bubble have backed themselves into a corner where the only way to stop the bubble from bursting is to keep inflating the bubble. The fate of the bubble will be decided by Wall Street not tech folks in the valley. Wall Street is already positioning itself for the burst and there’s lots of finance types ready to call party over and trigger the chaos that lets them make bank on the bubble’s implosion. These finance types (family offices, small secret investment funds) eat clueless VCs throwing cash on the fire for lunch… and they’re salivating at what’s ahead. It’s a “Big Short” once in 20-30 years type opportunity.

delusional 1y ago
> have backed themselves into a corner where the only way to stop the bubble from bursting is to keep inflating the bubble. They are not in any corner. They rightly believe that they won't be allowed to fail. There's zero cost to inflating the bubble. If they tank a loss, it's not their money and they'll go on to somewhere else. If they get lucky (maybe skillful?) they get out of the bubble before anyone else, but get to ride it all the way to the top. The only way they lose is if they sit by and do nothing. The upside is huge, and the downside is non-existent.
bwfan123 1y ago
oracle's announcement of a 300b purchase commitment from openai followed soon by a 100B investment into openai. The pace and size of these announcements is reaching a fever-pitch which seems like an attempt to keep the music playing.
ProjectArcturis 1y ago
>These finance types (family offices, small secret investment funds) eat clueless VCs throwing cash on the fire for lunch… and they’re salivating at what’s ahead. It’s a “Big Short” once in 20-30 years type opportunity. No - it's very hard to successfully bet against anything in finance, and VCs and non-public investments are particularly hard. When you go long, you simply buy something and hold it until you decide to sell. If you short, you have to worry about borrowing shares, paying short fees, and having unlimited risk. How would you even begin to bet against OpenAI specifically? The closest proxy I can think of is shorting NVDA. There's also nobody whose job it is to make big one-time shorts. Like you said, it's a once in 20-30 years opportunity, so no one builds a hedge fund dedicated to sitting around for decades waiting for that opportunity. There will certainly be exceptions, and maybe they'll make a Big Short 2 about the scrappy underdogs who saw the opening and timed it perfectly. But the vast majority of Wall Street desperately wants the party to continue.

rossdavidh 1y ago

"This time it's different"

ekjhgkejhgk 1y ago

In reference 14 we read > However, what’s become clear is that OpenAI plans to pay for Nvidia’s graphics processing units (GPUs) through lease arrangements, rather than upfront purchases I wish someone here could explain it to a dummy like me. Nvidia tells OpenAI: heres some GPUs, can you pay for them over 5 years. How is this an "investment" by Nvidia? That reference keeps calling this an investment, but what they describe is a lease agreement. Why do they call it an investment? What am I missing?

sbuttgereit 1y ago
That Nvidia has to front the costs of the product at the beginning and arguably the risk that the allocation of assets end up not being paid off (bankruptcy, etc.) By carrying those costs early and the associated risk, Nvidia expects a return on that. If the risk is realized they'll lose but otherwise they'll gain. That has all the hallmarks of an investment.
- ekjhgkejhgk 1y ago
  Thanks for your reply, but: NVidia could protect itself against OpenAI bankrupcy by adding a clause to the lease saying that if OpenAI goes bankrupt, Nvidia gets its GPUs back. So the risk would only be that the lease would be aborted sooner than expected.
  - tome 1y ago
    > So the risk would only be that the lease would be aborted sooner than expected. That is, in fact, the risk.
    - ekjhgkejhgk 1y ago
      But Im saying something different than the person I was responding to. They said that the risk was due to company going bankrupt and therefore Nvidia losing its "investment" - read: the GPUs that it leased. Whereas Im saying that the risk is due to company going bankrupt, Nvidia getting its GPUs back, but now they have too many at hand than they can usefully deploy/sell. The two are risks triggered by the same event, but the former is about 1 order of magnitude greater than the latter. The former is lost capital, the latter is lost opportunity - read: return on the capital.

MASNeo 1y ago

I wonder if the buying customers of Nvidia are going to find the self’s left with the overcapacity. Certainly people are waking up to LLM challenges and as budgets focus more on useful applications, smaller language models, how much of that demand will remain. Also, depreciation schedules beyond useful life of an asset may not be fraud but I’d call it a bit too creative for my liking. Time will tell.

nextworddev 1y ago

This article is pretty confusing, doesn't really have a thesis, just listing some stats. Maybe that's the intent.

foundart 1y ago
I had the same response. Certainly it suggests that “this time is different” without saying it in a quotable fashion. The metrics it provides seem useful. What are the metrics it is missing?
- nextworddev 1y ago
  The thing that this doesn't get is that 10bn a year is basically 70%+ of yearly R&D and inference budget of OpenAI.. so this Nvidia deal is actually great (for OpenAI) in terms of protecting its cashflow

rglullis 1y ago

The one thing I don't understand is this assumption that demand for GPUs for training is going to keep growing at the rate they grew so far. I get the demand for new applications, which require inference, but nowadays with so many good (if not close to SOTA) models available for free and the ability to run them on consumer hardware (apple M4 or AMD Max APUs), is there any demand for applications that justify a crazy amount of investment in GPUs?

porridgeraisin 1y ago
Inference will be cheapest when run in a shared cloud environment, simply due to the LLMs roofline. Thus, most B2B use cases are likely to be datacenter based, like AWS today. Of course, cern is still going to use their FPGA hyper-optimized for their specific trigger model for the LHC, and apple is gojng to use a specialized low power ASIC running a quantized model for hello Siri, but I meant the majority usecase.
- rglullis 1y ago
  I do not buy this premise. I think it will end up being cheaper to simply run the LLMs directly on the user device. I think that there are plenty of competitors in the "LLMs with open weights" space to essentially make the models a commodity, so all that is left is the compute cost and there is no way that someone will be running a datacenter in a way that is cheaper than "the computer that I already have running on my desk".
  - lelanthran 1y ago
    I nake your point every time this comes up[1] but its absolutely surprising how few business people, most of whom have some credibility in the form of qualifications or experience, actually recognise a value chain when they see it. ========== [1] https://rundata.co.za/blog/index.html?the-ai-value-chain https://rundata.co.za/blog/index.html?the-ai-value-chain
bix6 1y ago
Isn’t the whole point of the arms race that the more GPUs you have the closer you get to AGI? Which is the supposed goal here.

ekjhgkejhgk 1y ago

Related https://capitalgains.thediff.co/p/vendor-financing https://capitalgains.thediff.co/p/vendor-financing

yalogin 1y ago

The telecom bubble built infrastructure for something that didn’t exist, they built anticipating the need for high didn’t come in time. The gpu bubble is different. Nvidia is actually selling gpus in spades. So it’s not comparable to the telecom bubble. Now the question remains how many more gpus can they sell? That depends on the kind of services that are built and how their adoption takes off. So now is it a bubble or just frothy at the top? There is definitely going to be a pull back and some adjustment, but I cannot say how bad it is

mooreds 1y ago

Good analysis. But the answer is, "kinda"? There are similarities, but the AI buildout is worse in some ways (more concentration, GPU backed debt) and better in others (capacity is being used, vendors actually have cash flow). The conclusion: > Unlike the telecom bubble, where demand was speculative & customers burned cash , this merry-go-round has paying riders. Seems a little short sighted to me. IMO, there is a definite echo, but we are in the mid-late stage, not the end stage. It's simply not fair to compare Lucent at the end of a bubble with Nvidia in the middle, and that is what the author did. If you haven't listened to the referenced interview between Thompson and Kedrosky, I'd do so: https://www.theringer.com/podcasts/plain-english-with-derek-thompson/2025/09/23/this-is-how-the-ai-bubble-could-burst https://www.theringer.com/podcasts/plain-english-with-derek-...

nickdothutton 1y ago

I was there in the middle of the dotcom crash and the telecoms crash which was much worse. Fiber does not rust, and while there was vast overcapacity, not all of it was lit, or indeed worth lighting. 10 years after, thanks to DWDM there were 8 strand cables where only 2 strands were lit, albeit with many more wavelengths than envisaged before. Even though demand had grown. How much is a 10 year old GPU worth? Where is the “dwdm but for GPUs?”. There truly are interesting times and we have the benefit of being in them.

keeda 1y ago
Just so I understand correctly, you mean that with DWDM 2 strands of cables were equivalent to 8 since DWDM as a multiplexing technology increased the capacity of each fiber, right? > How much is a 10 year old GPU worth? Where is the “dwdm but for GPUs?”. From other sources cited in TFA it seems GPUs won't last 3 years, let alone 10! But I think we know what the "DWDM for GPUs" is -- it's the processing efficiency gains that we've seen over the last few years which keeps driving the per-token prices sharply down.
- nickdothutton 1y ago
  I'm not sure where DWDM is currently, but we quickly went from 1 colour to 512 colours per strand. I expect and hope for increases in GPU performance, some via process shrink, some via wafer size/yield, and some...perhaps... by software efficiencies (most interesting to me). Maybe volumes will increase too, further driving down the price for essentially the same parts. However I don't see how these gains (if they happen) can "get us to 512".

dehrmann 1y ago

> Evidence from Google architects shows GPUs at 60-70% utilization survive 1-2 years , with 3 years maximum. Really?! I'm not used to chips having such a short lifespan.

metadat 1y ago
This sounds like major FUD unless the data is public.
- bigyabai 1y ago
  Feels like a teensy tiny conflict of interest, coming from GCP. Additionally - GPUs have multiple components. Which parts are at 60-70% load, the SM unit or the memory controller? If you're throttling the GPU but not the memory, it makes perfect sense why you're burning the damn card out...

cameldrv 1y ago

There was a similar circular effect in the dot com boom around ads. VCs poured money into startups, which put the money into ads on Yahoo and other properties. Yahoo was getting huge revenue from the ads, which pumped up the stock price. The rising price and revenue, and hence stock price of Yahoo pumped up the market for other dot coms, as it proved you could make money on the Internet, so the market for dot com IPOs was strong. That drew more VC money. More VC money meant more ads.

sails 1y ago

> Nvidia’s vendor financing becomes exposure to customers building competitive alternatives. This is surely the most important line in the piece? In what world would this much demand not lead to alternatives emerging? (Assuming the upside, yes if the demand is not there in two years then yes it’s all going to burn)

mwkaufma 1y ago

Distinguishing that in-hindsight Lucent was committing accounting fraud and present firms aren't is a load-bearing assumption here; for all we know the big players in the AI bubble just haven't been outed yet.

brazukadev 1y ago
They are infringing copyright in all ways possible, if AI fail they will also have to pay this bill. It'll be the reparations after they lose the war.