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This article goes more into the technical analysis of the stock rather than the underlying business fundamentals that would lead to a stock dump. My 30k ft vie

This article goes more into the technical analysis of the stock rather than the underlying business fundamentals that would lead to a stock dump. My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. Right now Nvidia is flying high because datacenters are breaking ground everywhere but eventually that will come to an end as the supply of compute goes up. The counterargument to this is that the "economic lifespan" of an Nvidia GPU is 1-3 years depending on where it's used so there's a case to be made that Nvidia will always have customers coming back for the latest and greatest chips. The problem I have with this argument is that it's simply unsustainable to be spending that much every 2-3 years and we're already seeing this as Google and others are extending their depreciation of GPU's to something like 5-7 years.

KeplerBoy 9mo ago
Also there's no way Nvidia's market share isn't shrinking. Especially in inference.
- blackoil 9mo ago
  But will the whole pie grow or shrink?
- gpapilion 9mo ago
  The large api/token providers, and large consumers are all investing in their own hardware. So, they are in an interesting position where the market is growing, and NVIDIA is taking the lion's share of enterprise, but is shrinking at the hyperscaler side (google is a good example as they shift more and more compute to TPU). So, they have a shrinking market share, but its not super visible.
  - zozbot234 9mo ago
    > The large api/token providers, and large consumers are all investing in their own hardware. Which is absolutely the right move when your latest datacenter's power bill is literally measured in gigawatts. Power-efficient training/inference hardware simply does not look like a GPU at a hardware design level (though admittedly, it looks even less like an ordinary CPU), it's more like something that should run dog slow wrt. max design frequency but then more than make up for that with extreme throughput per watt/low energy expense per elementary operation. The whole sector of "neuromorphic" hardware design has long shown the broad feasibility of this (and TPUs are already a partial step in that direction), so it looks like this should be an obvious response to current trends in power and cooling demands for big AI workloads.
- dogma1138 9mo ago
  Market share can shrink but if the TAM is growing you can still grow.
jwoods19 9mo ago
“In a gold rush, sell shovels”… Well, at some point in the gold rush everyone already has their shovels and pickaxes.
- krupan 9mo ago
  Or people start to realize that the expected gold isn't really there and so stop buying shovels
  - deleted 9mo ago
    [deleted]
- gopher_space 9mo ago
  The version I heard growing up was "In a gold rush, sell eggs."
  - FergusArgyll 9mo ago
    Selling jeans is the one that actually worked
clownpenis_fart 9mo ago
[dead]
baxtr 9mo ago
I no AI fanboy at all. I think it there won’t be AGI anytime soon. However, it’s beyond my comprehension how anyone would think that we will see a decline in demand growth for compute. AI will conquer the world like software or the smartphone did. It’ll get implemented everywhere, more people will use it. We’re super early in the penetration so far.
- marricks 9mo ago
  > I no AI fanboy at all. While thinking computers will replace human brains soon is rabid fanaticism this statement... > AI will conquer the world like software or the smartphone did. Also displays a healthy amount of fanaticism.
  - jwoods19 9mo ago
    Even suggesting that computers will replace human brains brings up a moral and ethical question. If the computer is just as smart as a person, then we need to potentially consider that the computer has rights. As far as AI conquering the world. It needs a "killer app". I don't think we'll really see that until AR glasses that happen to include AI. If it can have context about your day, take action on your behalf, and have the same battery life as a smartphone...
  - xenospn 9mo ago
    I don’t see this as fanaticism at all. No one could predict a billion people mindlessly scrolling tiktok in 2007. This is going to happen again, only 10x. Faster and more addictive, with content generated on the fly to be so addictive, you won’t be able to look away.
    - Yossarrian22 9mo ago
      Vine was around then
- Ekaros 9mo ago
  At this point computation is in essence commodity. And commodities have demand cycles. If other economic factors slowdown or companies go out of business they stop using compute or start less new products that use compute. Thus it is entirely realistic to me that demand for compute might go down. Or that we are just now over provisioning compute in short or medium term.
mnky9800n 9mo ago
I really don't understand the argument that nvidia GPUs only work for 1-3 years. I am currently using A100s and H100s every day. Those aren't exactly new anymore.
- iancmceachern 9mo ago
  They're no longer energy competitive. I.e. the amount of power per compute exceeds what is available now. It's like if your taxi company bought taxis that were more fuel efficient every year.
  - bob1029 9mo ago
    Margins are typically not so razor thin that you cannot operate with technology from one generation ago. 15 vs 17 mpg is going to add up over time, but for a taxi company it's probably not a lethal situation to be in.
    - deleted 9mo ago
      [deleted]
    - iancmceachern 9mo ago
      Tell that to the airline industry
      - bob1029 9mo ago
        I don't think the airline industry is a great example from an IT perspective, but I agree with regard to the aircraft.
      - hibikir 9mo ago
        And yet they aren't running planes and engines all from 2023 or beyond: See the MD-11 that crashed in Louisville: Nobody has made a new MD-11 in over 20 years. Planes move to less competitive routes, change carriers, and eventually might even stop carrying people and switch to cargo, but the plane itself doesn't get to have zero value when the new one comes out. An airline will want to replace their planes, but a new plane isn't fully amortized in a year or three: It still has value for quite a while
nospice 9mo ago
> My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. Their stock trajectory started with one boom (cryptocurrencies) and then seamlessly progressed to another (AI). You're basically looking at a decade of "number goes up". So yeah, it will probably come down eventually (or the inflation will catch up), but it's a poor argument for betting against them right now. Meanwhile, the investors who were "wrong" anticipating a cryptocurrency revolution and who bought NVDA have not much to complain about today.
- munk-a 9mo ago
  That's the rub - it's clearly overvalued and will readjust... the question is when. If you can figure out when precisely then you've won the lottery, for everyone else it's a game of chicken where for "a while" money that you put into it will have a good return. Everyone would love if that lasted forever so there is a strong momentum preventing that market correction.
  - jama211 9mo ago
    It was overvalued when crypto was happening too, but another boom took its place. Of course, lightening rarely strikes twice and all that, but it proves overvalued doesn’t mean the price is guaranteed to go down it seems. Predicting the future is hard.
    - sidrag22 9mo ago
      if there was anything i was going to bet against between 2019 and now, it was nvidia... and wow it feels wild how much in the opposite direction it went. I do wonder what people would think the reasoning would be for them to increase in value this much back then, prolly would just assume crypto related still.
      - jama211 9mo ago
        It’s not impossible they could’ve seen AI investment coming but it would’ve been very hard
AnotherGoodName 9mo ago
I'll also point out there were insane takes a few years ago before nVidia's run up based on similar technical analysis and very limited scope fundamental analysis. Technical analysis fails completely when there's an underlying shift that moves the line. You can't look at the past and say "nvidia is clearly overvalued at $10 because it was $3 for years earlier" when they suddenly and repeatedly 10x earnings over many quarters. I couldn't get through to the idiots on reddit.com/r/stocks about this when there was non-stop negativity on nvidia based on technical analysis and very narrow scoped fundamental analysis. They showed a 12x gain in quarterly earnings at the time but the PE (which looks on past quarters only) was 260x due to this sudden change in earnings and pretty much all of reddit couldn't get past this. I did well on this yet there were endless posts of "Nvidia is the easiest short ever" when it was ~$40 pre-split.
lairv 9mo ago
NVIDIA stock tanked in 2025 when people learned that Google used TPUs to train Gemini, which everyone in the community knows since at least 2021. So I think it's very likely that NVIDIA stock could crash for non-rationale reasons edit: 2025* not 2024
- readthenotes1 9mo ago
  It also tanked to ~$90 when Trump announced tariffs on all goods for Taiwan except semiconductors. I don't know if that's non-rational, or if people can't be expected to read the second sentence of an announcement before panicking.
  - Loudergood 9mo ago
    The market is full of people trying to anticipate how other people are going to react and exploit that by getting there first. There's a layer aimed at forecasting what that layer is going to do as well. It's guesswork all the way down.
    - recursive 9mo ago
      Personally, I try to predict how others are going to predict that yet others will react.
      - MrOrelliOReilly 9mo ago
        And I just predict how you’ll predict
        Nevermark 9mo ago
        So we have a closed instability/volatility amplification loop. Great: Time for the straddle with finger-cross trade.
      - svnt 9mo ago
        [flagged]
cheschire 9mo ago
Well, not to be too egregiously reductive… but when the M2 money supply spiked in the 2020 to 2022 timespan, a lot of new money entered the middle class. That money was then funneled back into the hands of the rich through “inflation”. That left the rich with a lot of spare capital to invest in finding the next boom. Then AI came along. Once the money dries up, a new bubble will be invented to capture the middle class income, like NFTs and crypto before that, and commissionless stocks, etc etc It’s not all pump-and-dump. Again, this is a pretty reductive take on market forces. I’m just saying I don’t think it’s quite as unsustainable as you might think.
agentcoops 9mo ago
I hear your argument, but short of major algorithmic breakthroughs I am not convinced the global demand for GPUs will drop any time soon. Of course I could easily be wrong, but regardless I think the most predictable cause for a drop in the NVIDIA price would be that the CHIPS act/recent decisions by the CCP leads a Chinese firm to bring to market a CUDA compatible and reliable GPU at a fraction of the cost. It should be remembered that NVIDIA's /current/ value is based on their being locked out of their second largest market (China) with no investor expectation of that changing in the future. Given the current geopolitical landscape, in the hypothetical case where a Chinese firm markets such a chip we should expect that US firms would be prohibited from purchasing them, while it's less clear that Europeans or Saudis would be. Even so, if NVIDIA were not to lower their prices at all, US firms would be at a tremendous cost disadvantage while their competitors would no longer have one with respect to compute. All hypothetical, of course, but to me that's the most convincing bear case I've heard for NVIDIA.
- coryrc 9mo ago
  Not that locked out: https://www.cnbc.com/2025/12/31/160-million-export-controlled-nvidia-gpus-allegedly-smuggled-to-china.html https://www.cnbc.com/2025/12/31/160-million-export-controlle...
  - deleted 9mo ago
    [deleted]
  - agentcoops 9mo ago
    Yeah, that's the bull case for sure. Chinese firms might not accept training setbacks even given CCP regulations that they dogfood X homegrown chip.
- iLoveOncall 9mo ago
  > short of major algorithmic breakthroughs I am not convinced the global demand for GPUs will drop any time soon Or, you know, when LLMs don't pay off.
  - 9mo ago
bArray 9mo ago
> My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. Right now Nvidia is flying high because datacenters are breaking ground everywhere but eventually that will come to an end as the supply of compute goes up. Exactly, it is currently priced as though infinite GPUs are required indefinitely. Eventually most of the data centres and the gamers will have their GPUs, and demand will certainly decrease. Before that, though, the data centres will likely fail to be built in full. Investors will eventually figure out that LLMs are still not profitable, no matter how many data centres you produce. People are interested in the product derivatives at a lower price than it costs to run them. The math ain't mathin'. The longer it takes to get them all built, the more exposed they all are. Even if it turns out to be profitable, taking three years to build a data centre rather than one year is significant, as profit for these high-tech components falls off over time. And how many AI data centres do we really need? I would go further and say that these long and complex supply chains are quite brittle. In 2019, a 13 minute power cut caused a loss of 10 weeks of memory stock [1]. Normally, the shops and warehouses act as a capacitor and can absorb small supply chain ripples. But now these components are being piped straight to data centres, they are far more sensitive to blips. What about a small issue in the silicon that means you damage large amounts of your stock trying to run it at full power through something like electromigration [2]. Or a random war...? > The counterargument to this is that the "economic lifespan" of an Nvidia GPU is 1-3 years depending on where it's used so there's a case to be made that Nvidia will always have customers coming back for the latest and greatest chips. The problem I have with this argument is that it's simply unsustainable to be spending that much every 2-3 years and we're already seeing this as Google and others are extending their depreciation of GPU's to something like 5-7 years. Yep. Nothing about this adds up. Existing data centres with proper infrastructure are being forced to extend use for previously uneconomical hardware because new data centres currently building infrastructure have run the price up so high. If Google really thought this new hardware was going to be so profitable, they would have bought it all up. [1] https://blocksandfiles.com/2019/06/28/power-cut-flash-chip-production/ https://blocksandfiles.com/2019/06/28/power-cut-flash-chip-p... [2] https://www.pcworld.com/article/2415697/intels-crashing-13th-14th-gen-cpu-nightmare-explained.html https://www.pcworld.com/article/2415697/intels-crashing-13th...
cortesoft 9mo ago
> The problem I have with this argument is that it's simply unsustainable to be spending that much every 2-3 years Isn’t this entirely dependent on the economic value of the AI workloads? It all depends on whether AI work is more valuable than that cost. I can easily see arguments why it won’t be that valuable, but if it is, then that cost will be sustainable.
- alfalfasprout 9mo ago
  100% this. all of this spending is predicated on a stratospheric ROI on AI investments at the proposed investment levels. If that doesn't pan out, we'll see a lot of people left holding the cards including chip fabs, designers like Nvidia, and of course anyone that ponied up for that much compute.
  - jiggawatts 9mo ago
    Chip fabs will be fine. The demand for high end processors will remain because of the likes of Apple and AMD.
stego-tech 9mo ago
Add in the fact companies seriously invested in AI (and like workloads typically reliant on GPUs) are also investing more into bespoke accelerators, and the math for nVidia looks particularly grim. Google’s TPUs set them apart from the competition, as does Apple’s NPU; it’s reasonable to assume firms like Anthropic or OpenAI are also investigating or investing into similar hardware accelerators. After all, it’s easier to lock-in customers if your models cannot run on “standard” kit like GPUs and servers, even if it’s also incredibly wasteful. The math looks bad regardless of which way the industry goes, too. A successful AI industry has a vested interest in bespoke hardware to build better models, faster. A stalled AI industry would want custom hardware to bring down costs and reduce external reliance on competitors. A failed AI industry needs no GPUs at all, and an inference-focused industry definitely wants custom hardware, not general-purpose GPUs. So nVidia is capitalizing on a bubble, which you could argue is the right move under such market conditions. The problem is that they’re also alienating their core customer base (smaller datacenters, HPC, gaming market) in the present, which will impact future growth. Their GPUs are scarce and overpriced relative to performance, which itself has remained a near-direct function of increased power input rather than efficiency or meaningful improvements. Their software solutions - DLSS frame-generation, ray reconstruction, etc - are locked to their cards, but competitors can and have made equivalent-performing solutions of their own with varying degrees of success. This means it’s no longer necessary to have an nVidia GPU to, say, crunch scientific workloads or render UHD game experiences, which in turn means we can utilize cheaper hardware for similar results. Rubbing salt in the wound, they’re making cards even more expensive by unbundling memory and clamping down on AIB designs. Their competition - Intel and AMD primarily - are happily enjoying the scarcity of nVidia cards and reaping the fiscal rewards, however meager they are compared to AI at present. AMD in particular is sitting pretty, powering four of the five present-gen consoles, the Steam Deck (and copycats), and the Steam Machine, not to mention outfits like Framework; if you need a smol but capable boxen on the (relative) cheap, what used to be nVidia + ARM is now just AMD (and soon, Intel, if they can stick the landing with their new iGPUs). The business fundamentals paint a picture of cannibalizing one’s evergreen customers in favor of repeated fads (crypto and AI), and years of doing so has left those customer markets devastated and bitter at nVidia’s antics. Short of a new series of GPUs with immense performance gains at lower price and power points with availability to meet demand, my personal read is that this is merely Jenson Huang’s explosive send-off before handing the bag over to some new sap (and shareholders) once the party inevitably ends, one way or another.
kqr 9mo ago
Fundamental analysis is great! But I have trouble answering concrete questions of probability with it. How do you use fundamental analysis to assign a probability to Nvidia closing under $100 this year, and what probability do you assign to that outcome? I'd love to hear your reasoning around specifics to get better at it.
- esafak 9mo ago
  Don't you need a model for how people will react to the fundamentals? People set the price.
  - kqr 9mo ago
    Possibly? I don't know -- hence the question! GP was presenting fundamental analysis as an alternative to the article's method for answering the question, but then never answered the question. This is a confusion I have around fundamental analysis. Some people appear to do it very well (Buffett?) but most of its proponents only use it to ramble about possibilities without making any forecasts speciic enough to be verifiable. I'm curious about that gap.
- djeastm 9mo ago
  I think the idea of fundamental analysis that you focus on return on equity and see if that valuation is appreciably more than the current price (as opposed to assigning a probability)
- deleted 9mo ago
  [deleted]
richardw 9mo ago
I’m sad about Grok going to them, because the market needs the competition. But ASIC inference seems to require a simpler design than training does, so it’s easier for multiple companies to enter. It seems inevitable that competition emerges. And eg a Chinese company will not be sold to Nvidia. What’s wrong with this logic? Any insiders willing to weigh in?
- bigyabai 9mo ago
  I'm not an insider, but ASICs come with their own suite of issues and might be obsolete if a different architecture becomes popular. They'll have a much shorter lifespan than Nvidia hardware in all likelihood, and will probably struggle to find fab capacity that puts them on equal footing in performance. For example, look at the GPU shortage that hit crypto despite hundreds of ASIC designs existing. The industry badly needs to cooperate on an actual competitor to CUDA, and unfortunately they're more hostile to each other today than they were 10 years ago.
  - zozbot234 9mo ago
    You can build ASICs to be a lot more energy efficient than current GPUs, especially if your power budget is heavily bound by raw compute as opposed to data movement bandwidth. The tradeoff is much higher latency for any given compute throughput, but for workloads such as training or even some kinds of "deep thinking inference" you don't care much about that.
jpadkins 9mo ago
How much did you short the stock?
m12k 9mo ago
I think the way to think about the AI bubble is that we're somewhere in 97-99 right now, heading toward the dotcom crash. The dotcom crash didn't kill the web, it kept growing in the decades that followed, influencing society more and more. But the era where tons of investments were uncritically thrown at anything to do with the web ended with a bang. When the AI bubble bursts, it won't stop the development of AI as a technology. Or its impact on society. But it will end the era of uncritically throwing investments at anyone that works "AI" into their pitch deck. And so too will it end the era of Nvidia selling pickaxes to the miners and being able to reach soaring heights of profitability born on wings of pretty much all investment capital in the world at the moment.
- enos_feedler 9mo ago
  Bubble or not it’s simply strange to me that people confidently put a timeline on it. To name the phases of the bubble and calling when they will collapse just seems counter intuitive to what a bubble is. Brad Gerstner was the first “influencer” I heard making these claims of a bubble time line. It just seems downright absurd.
deleted 9mo ago
[deleted]
JakeSc 9mo ago
Agree on looking at the company-behind-the-numbers. Though presumably you're aware of the Efficient Market Hypothesis. Shouldn't "slowed down datacenter growth" be baked into the stock price already? If I'm understanding your prediction correctly, you're asserting that the market thinks datacenter spending will continue at this pace indefinitely, and you yourself uniquely believe that to be not true. Right? I wonder why the market (including hedge fund analysis _much_ more sophisticated than us) should be so misinformed. Presumably the market knows that the whole earth can't be covered in datacenters, and thus has baked that into the price, no?
- testdelacc1 9mo ago
  I saw a $100 bill on the ground. I nearly picked it up before I stopped myself. I realised that if it was a genuine currency note, the Efficient Market would have picked it up already.
- matthewdgreen 9mo ago
  The EMH does not mean that markets are free of over-investment and asset bubbles, followed by crashes.
throwaway85825 9mo ago
It's not flat growth that's currently priced in, but continuing high growth. Which is impossible.
WalterBright 9mo ago
> technical analysis of the stock AKA pictures in clouds
TacticalCoder 9mo ago
> This article goes more into the technical analysis of the stock rather than the underlying business fundamentals that would lead to a stock dump. My 30k ft view is that the stock will inevitably slide as AI Actually "technical analysis" (TA) has a very specific meaning in trading: TA is using past prices, volume of trading and price movements to, hopefully, give probabilities about future price moves. https://en.wikipedia.org/wiki/Technical_analysis https://en.wikipedia.org/wiki/Technical_analysis But TFA doesn't do that at all: it goes in detail into one pricing model formula/method for options pricing. In the typical options pricing model all you're using is current price (of the underlying, say NVDA), strike price (of the option), expiration date, current interest rate and IV (implied volatility: influenced by recent price movements but independently of any technical analysis). Be it Black-Scholes-Merton (european-style options), Bjerksund-Stensland (american-style options), binomial as in TFA, or other open options pricing model: none of these use technical analysis. Here's an example (for european-style options) where one can see the parameters: https://www.mystockoptions.com/black-scholes.cfm https://www.mystockoptions.com/black-scholes.cfm You can literally compute entire options chains with these parameters. Now it's known for a fact that many professional traders firms have their own options pricing method and shall arb when they think they find incorrectly priced options. I don't know if some use actual so forms of TA that they then mix with options pricing model or not. > My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. No matter if you're right or not, I'd argue you're doing what's called fundamental analysis (but I may be wrong). P.S: I'm not debatting the merits of TA and whether it's reading into tea leaves or not. What I'm saying is that options pricing using the binomial method cannot be called "technical analysis" for TA is something else.
ramijames 9mo ago
This seems to take for granted that China and their foundries and engineering teams will never catch up. This seems foolish. I'm working under the assumption that sometime in the next ten years some Chinese company will have a breakthrough and either meet Nvidia's level or leapfrog them. Then the market will flood with great, cheap chips.
amelius 9mo ago
> My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. This is like saying Apple stock will inevitably slide once everybody owns a smartphone.
pjmlp 9mo ago
Even though I like CUDA, I think the point is when do compute centers reach the point that they can run their workloads with other vendors, or custom accelerators.

KeplerBoy 9mo ago

Also there's no way Nvidia's market share isn't shrinking. Especially in inference.

blackoil 9mo ago
But will the whole pie grow or shrink?
gpapilion 9mo ago
The large api/token providers, and large consumers are all investing in their own hardware. So, they are in an interesting position where the market is growing, and NVIDIA is taking the lion's share of enterprise, but is shrinking at the hyperscaler side (google is a good example as they shift more and more compute to TPU). So, they have a shrinking market share, but its not super visible.
- zozbot234 9mo ago
  > The large api/token providers, and large consumers are all investing in their own hardware. Which is absolutely the right move when your latest datacenter's power bill is literally measured in gigawatts. Power-efficient training/inference hardware simply does not look like a GPU at a hardware design level (though admittedly, it looks even less like an ordinary CPU), it's more like something that should run dog slow wrt. max design frequency but then more than make up for that with extreme throughput per watt/low energy expense per elementary operation. The whole sector of "neuromorphic" hardware design has long shown the broad feasibility of this (and TPUs are already a partial step in that direction), so it looks like this should be an obvious response to current trends in power and cooling demands for big AI workloads.
dogma1138 9mo ago
Market share can shrink but if the TAM is growing you can still grow.

jwoods19 9mo ago

“In a gold rush, sell shovels”… Well, at some point in the gold rush everyone already has their shovels and pickaxes.

krupan 9mo ago
Or people start to realize that the expected gold isn't really there and so stop buying shovels
- deleted 9mo ago
  [deleted]
gopher_space 9mo ago
The version I heard growing up was "In a gold rush, sell eggs."
- FergusArgyll 9mo ago
  Selling jeans is the one that actually worked

clownpenis_fart 9mo ago

[dead]

baxtr 9mo ago

I no AI fanboy at all. I think it there won’t be AGI anytime soon. However, it’s beyond my comprehension how anyone would think that we will see a decline in demand growth for compute. AI will conquer the world like software or the smartphone did. It’ll get implemented everywhere, more people will use it. We’re super early in the penetration so far.

marricks 9mo ago
> I no AI fanboy at all. While thinking computers will replace human brains soon is rabid fanaticism this statement... > AI will conquer the world like software or the smartphone did. Also displays a healthy amount of fanaticism.
- jwoods19 9mo ago
  Even suggesting that computers will replace human brains brings up a moral and ethical question. If the computer is just as smart as a person, then we need to potentially consider that the computer has rights. As far as AI conquering the world. It needs a "killer app". I don't think we'll really see that until AR glasses that happen to include AI. If it can have context about your day, take action on your behalf, and have the same battery life as a smartphone...
- xenospn 9mo ago
  I don’t see this as fanaticism at all. No one could predict a billion people mindlessly scrolling tiktok in 2007. This is going to happen again, only 10x. Faster and more addictive, with content generated on the fly to be so addictive, you won’t be able to look away.
  - Yossarrian22 9mo ago
    Vine was around then
Ekaros 9mo ago
At this point computation is in essence commodity. And commodities have demand cycles. If other economic factors slowdown or companies go out of business they stop using compute or start less new products that use compute. Thus it is entirely realistic to me that demand for compute might go down. Or that we are just now over provisioning compute in short or medium term.

mnky9800n 9mo ago

I really don't understand the argument that nvidia GPUs only work for 1-3 years. I am currently using A100s and H100s every day. Those aren't exactly new anymore.

iancmceachern 9mo ago
They're no longer energy competitive. I.e. the amount of power per compute exceeds what is available now. It's like if your taxi company bought taxis that were more fuel efficient every year.
- bob1029 9mo ago
  Margins are typically not so razor thin that you cannot operate with technology from one generation ago. 15 vs 17 mpg is going to add up over time, but for a taxi company it's probably not a lethal situation to be in.
  - deleted 9mo ago
    [deleted]
  - iancmceachern 9mo ago
    Tell that to the airline industry
    - bob1029 9mo ago
      I don't think the airline industry is a great example from an IT perspective, but I agree with regard to the aircraft.
    - hibikir 9mo ago
      And yet they aren't running planes and engines all from 2023 or beyond: See the MD-11 that crashed in Louisville: Nobody has made a new MD-11 in over 20 years. Planes move to less competitive routes, change carriers, and eventually might even stop carrying people and switch to cargo, but the plane itself doesn't get to have zero value when the new one comes out. An airline will want to replace their planes, but a new plane isn't fully amortized in a year or three: It still has value for quite a while

nospice 9mo ago

> My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. Their stock trajectory started with one boom (cryptocurrencies) and then seamlessly progressed to another (AI). You're basically looking at a decade of "number goes up". So yeah, it will probably come down eventually (or the inflation will catch up), but it's a poor argument for betting against them right now. Meanwhile, the investors who were "wrong" anticipating a cryptocurrency revolution and who bought NVDA have not much to complain about today.

munk-a 9mo ago
That's the rub - it's clearly overvalued and will readjust... the question is when. If you can figure out when precisely then you've won the lottery, for everyone else it's a game of chicken where for "a while" money that you put into it will have a good return. Everyone would love if that lasted forever so there is a strong momentum preventing that market correction.
- jama211 9mo ago
  It was overvalued when crypto was happening too, but another boom took its place. Of course, lightening rarely strikes twice and all that, but it proves overvalued doesn’t mean the price is guaranteed to go down it seems. Predicting the future is hard.
  - sidrag22 9mo ago
    if there was anything i was going to bet against between 2019 and now, it was nvidia... and wow it feels wild how much in the opposite direction it went. I do wonder what people would think the reasoning would be for them to increase in value this much back then, prolly would just assume crypto related still.
    - jama211 9mo ago
      It’s not impossible they could’ve seen AI investment coming but it would’ve been very hard

AnotherGoodName 9mo ago

I'll also point out there were insane takes a few years ago before nVidia's run up based on similar technical analysis and very limited scope fundamental analysis. Technical analysis fails completely when there's an underlying shift that moves the line. You can't look at the past and say "nvidia is clearly overvalued at $10 because it was $3 for years earlier" when they suddenly and repeatedly 10x earnings over many quarters. I couldn't get through to the idiots on reddit.com/r/stocks about this when there was non-stop negativity on nvidia based on technical analysis and very narrow scoped fundamental analysis. They showed a 12x gain in quarterly earnings at the time but the PE (which looks on past quarters only) was 260x due to this sudden change in earnings and pretty much all of reddit couldn't get past this. I did well on this yet there were endless posts of "Nvidia is the easiest short ever" when it was ~$40 pre-split.

lairv 9mo ago

NVIDIA stock tanked in 2025 when people learned that Google used TPUs to train Gemini, which everyone in the community knows since at least 2021. So I think it's very likely that NVIDIA stock could crash for non-rationale reasons edit: 2025* not 2024

readthenotes1 9mo ago
It also tanked to ~$90 when Trump announced tariffs on all goods for Taiwan except semiconductors. I don't know if that's non-rational, or if people can't be expected to read the second sentence of an announcement before panicking.
- Loudergood 9mo ago
  The market is full of people trying to anticipate how other people are going to react and exploit that by getting there first. There's a layer aimed at forecasting what that layer is going to do as well. It's guesswork all the way down.
  - recursive 9mo ago
    Personally, I try to predict how others are going to predict that yet others will react.
    - MrOrelliOReilly 9mo ago
      And I just predict how you’ll predict
      - Nevermark 9mo ago
        So we have a closed instability/volatility amplification loop. Great: Time for the straddle with finger-cross trade.
    - svnt 9mo ago
      [flagged]

cheschire 9mo ago

Well, not to be too egregiously reductive… but when the M2 money supply spiked in the 2020 to 2022 timespan, a lot of new money entered the middle class. That money was then funneled back into the hands of the rich through “inflation”. That left the rich with a lot of spare capital to invest in finding the next boom. Then AI came along. Once the money dries up, a new bubble will be invented to capture the middle class income, like NFTs and crypto before that, and commissionless stocks, etc etc It’s not all pump-and-dump. Again, this is a pretty reductive take on market forces. I’m just saying I don’t think it’s quite as unsustainable as you might think.

agentcoops 9mo ago

I hear your argument, but short of major algorithmic breakthroughs I am not convinced the global demand for GPUs will drop any time soon. Of course I could easily be wrong, but regardless I think the most predictable cause for a drop in the NVIDIA price would be that the CHIPS act/recent decisions by the CCP leads a Chinese firm to bring to market a CUDA compatible and reliable GPU at a fraction of the cost. It should be remembered that NVIDIA's /current/ value is based on their being locked out of their second largest market (China) with no investor expectation of that changing in the future. Given the current geopolitical landscape, in the hypothetical case where a Chinese firm markets such a chip we should expect that US firms would be prohibited from purchasing them, while it's less clear that Europeans or Saudis would be. Even so, if NVIDIA were not to lower their prices at all, US firms would be at a tremendous cost disadvantage while their competitors would no longer have one with respect to compute. All hypothetical, of course, but to me that's the most convincing bear case I've heard for NVIDIA.

coryrc 9mo ago
Not that locked out: https://www.cnbc.com/2025/12/31/160-million-export-controlled-nvidia-gpus-allegedly-smuggled-to-china.html https://www.cnbc.com/2025/12/31/160-million-export-controlle...
- deleted 9mo ago
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- agentcoops 9mo ago
  Yeah, that's the bull case for sure. Chinese firms might not accept training setbacks even given CCP regulations that they dogfood X homegrown chip.
iLoveOncall 9mo ago
> short of major algorithmic breakthroughs I am not convinced the global demand for GPUs will drop any time soon Or, you know, when LLMs don't pay off.
- 9mo ago

bArray 9mo ago

> My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. Right now Nvidia is flying high because datacenters are breaking ground everywhere but eventually that will come to an end as the supply of compute goes up. Exactly, it is currently priced as though infinite GPUs are required indefinitely. Eventually most of the data centres and the gamers will have their GPUs, and demand will certainly decrease. Before that, though, the data centres will likely fail to be built in full. Investors will eventually figure out that LLMs are still not profitable, no matter how many data centres you produce. People are interested in the product derivatives at a lower price than it costs to run them. The math ain't mathin'. The longer it takes to get them all built, the more exposed they all are. Even if it turns out to be profitable, taking three years to build a data centre rather than one year is significant, as profit for these high-tech components falls off over time. And how many AI data centres do we really need? I would go further and say that these long and complex supply chains are quite brittle. In 2019, a 13 minute power cut caused a loss of 10 weeks of memory stock [1]. Normally, the shops and warehouses act as a capacitor and can absorb small supply chain ripples. But now these components are being piped straight to data centres, they are far more sensitive to blips. What about a small issue in the silicon that means you damage large amounts of your stock trying to run it at full power through something like electromigration [2]. Or a random war...? > The counterargument to this is that the "economic lifespan" of an Nvidia GPU is 1-3 years depending on where it's used so there's a case to be made that Nvidia will always have customers coming back for the latest and greatest chips. The problem I have with this argument is that it's simply unsustainable to be spending that much every 2-3 years and we're already seeing this as Google and others are extending their depreciation of GPU's to something like 5-7 years. Yep. Nothing about this adds up. Existing data centres with proper infrastructure are being forced to extend use for previously uneconomical hardware because new data centres currently building infrastructure have run the price up so high. If Google really thought this new hardware was going to be so profitable, they would have bought it all up. [1] https://blocksandfiles.com/2019/06/28/power-cut-flash-chip-production/ https://blocksandfiles.com/2019/06/28/power-cut-flash-chip-p... [2] https://www.pcworld.com/article/2415697/intels-crashing-13th-14th-gen-cpu-nightmare-explained.html https://www.pcworld.com/article/2415697/intels-crashing-13th...

cortesoft 9mo ago

> The problem I have with this argument is that it's simply unsustainable to be spending that much every 2-3 years Isn’t this entirely dependent on the economic value of the AI workloads? It all depends on whether AI work is more valuable than that cost. I can easily see arguments why it won’t be that valuable, but if it is, then that cost will be sustainable.

alfalfasprout 9mo ago
100% this. all of this spending is predicated on a stratospheric ROI on AI investments at the proposed investment levels. If that doesn't pan out, we'll see a lot of people left holding the cards including chip fabs, designers like Nvidia, and of course anyone that ponied up for that much compute.
- jiggawatts 9mo ago
  Chip fabs will be fine. The demand for high end processors will remain because of the likes of Apple and AMD.

stego-tech 9mo ago

Add in the fact companies seriously invested in AI (and like workloads typically reliant on GPUs) are also investing more into bespoke accelerators, and the math for nVidia looks particularly grim. Google’s TPUs set them apart from the competition, as does Apple’s NPU; it’s reasonable to assume firms like Anthropic or OpenAI are also investigating or investing into similar hardware accelerators. After all, it’s easier to lock-in customers if your models cannot run on “standard” kit like GPUs and servers, even if it’s also incredibly wasteful. The math looks bad regardless of which way the industry goes, too. A successful AI industry has a vested interest in bespoke hardware to build better models, faster. A stalled AI industry would want custom hardware to bring down costs and reduce external reliance on competitors. A failed AI industry needs no GPUs at all, and an inference-focused industry definitely wants custom hardware, not general-purpose GPUs. So nVidia is capitalizing on a bubble, which you could argue is the right move under such market conditions. The problem is that they’re also alienating their core customer base (smaller datacenters, HPC, gaming market) in the present, which will impact future growth. Their GPUs are scarce and overpriced relative to performance, which itself has remained a near-direct function of increased power input rather than efficiency or meaningful improvements. Their software solutions - DLSS frame-generation, ray reconstruction, etc - are locked to their cards, but competitors can and have made equivalent-performing solutions of their own with varying degrees of success. This means it’s no longer necessary to have an nVidia GPU to, say, crunch scientific workloads or render UHD game experiences, which in turn means we can utilize cheaper hardware for similar results. Rubbing salt in the wound, they’re making cards even more expensive by unbundling memory and clamping down on AIB designs. Their competition - Intel and AMD primarily - are happily enjoying the scarcity of nVidia cards and reaping the fiscal rewards, however meager they are compared to AI at present. AMD in particular is sitting pretty, powering four of the five present-gen consoles, the Steam Deck (and copycats), and the Steam Machine, not to mention outfits like Framework; if you need a smol but capable boxen on the (relative) cheap, what used to be nVidia + ARM is now just AMD (and soon, Intel, if they can stick the landing with their new iGPUs). The business fundamentals paint a picture of cannibalizing one’s evergreen customers in favor of repeated fads (crypto and AI), and years of doing so has left those customer markets devastated and bitter at nVidia’s antics. Short of a new series of GPUs with immense performance gains at lower price and power points with availability to meet demand, my personal read is that this is merely Jenson Huang’s explosive send-off before handing the bag over to some new sap (and shareholders) once the party inevitably ends, one way or another.

kqr 9mo ago

Fundamental analysis is great! But I have trouble answering concrete questions of probability with it. How do you use fundamental analysis to assign a probability to Nvidia closing under $100 this year, and what probability do you assign to that outcome? I'd love to hear your reasoning around specifics to get better at it.

esafak 9mo ago
Don't you need a model for how people will react to the fundamentals? People set the price.
- kqr 9mo ago
  Possibly? I don't know -- hence the question! GP was presenting fundamental analysis as an alternative to the article's method for answering the question, but then never answered the question. This is a confusion I have around fundamental analysis. Some people appear to do it very well (Buffett?) but most of its proponents only use it to ramble about possibilities without making any forecasts speciic enough to be verifiable. I'm curious about that gap.
djeastm 9mo ago
I think the idea of fundamental analysis that you focus on return on equity and see if that valuation is appreciably more than the current price (as opposed to assigning a probability)
deleted 9mo ago
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richardw 9mo ago

I’m sad about Grok going to them, because the market needs the competition. But ASIC inference seems to require a simpler design than training does, so it’s easier for multiple companies to enter. It seems inevitable that competition emerges. And eg a Chinese company will not be sold to Nvidia. What’s wrong with this logic? Any insiders willing to weigh in?

bigyabai 9mo ago
I'm not an insider, but ASICs come with their own suite of issues and might be obsolete if a different architecture becomes popular. They'll have a much shorter lifespan than Nvidia hardware in all likelihood, and will probably struggle to find fab capacity that puts them on equal footing in performance. For example, look at the GPU shortage that hit crypto despite hundreds of ASIC designs existing. The industry badly needs to cooperate on an actual competitor to CUDA, and unfortunately they're more hostile to each other today than they were 10 years ago.
- zozbot234 9mo ago
  You can build ASICs to be a lot more energy efficient than current GPUs, especially if your power budget is heavily bound by raw compute as opposed to data movement bandwidth. The tradeoff is much higher latency for any given compute throughput, but for workloads such as training or even some kinds of "deep thinking inference" you don't care much about that.

jpadkins 9mo ago

How much did you short the stock?

m12k 9mo ago

I think the way to think about the AI bubble is that we're somewhere in 97-99 right now, heading toward the dotcom crash. The dotcom crash didn't kill the web, it kept growing in the decades that followed, influencing society more and more. But the era where tons of investments were uncritically thrown at anything to do with the web ended with a bang. When the AI bubble bursts, it won't stop the development of AI as a technology. Or its impact on society. But it will end the era of uncritically throwing investments at anyone that works "AI" into their pitch deck. And so too will it end the era of Nvidia selling pickaxes to the miners and being able to reach soaring heights of profitability born on wings of pretty much all investment capital in the world at the moment.

enos_feedler 9mo ago
Bubble or not it’s simply strange to me that people confidently put a timeline on it. To name the phases of the bubble and calling when they will collapse just seems counter intuitive to what a bubble is. Brad Gerstner was the first “influencer” I heard making these claims of a bubble time line. It just seems downright absurd.

deleted 9mo ago

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JakeSc 9mo ago

Agree on looking at the company-behind-the-numbers. Though presumably you're aware of the Efficient Market Hypothesis. Shouldn't "slowed down datacenter growth" be baked into the stock price already? If I'm understanding your prediction correctly, you're asserting that the market thinks datacenter spending will continue at this pace indefinitely, and you yourself uniquely believe that to be not true. Right? I wonder why the market (including hedge fund analysis _much_ more sophisticated than us) should be so misinformed. Presumably the market knows that the whole earth can't be covered in datacenters, and thus has baked that into the price, no?

testdelacc1 9mo ago
I saw a $100 bill on the ground. I nearly picked it up before I stopped myself. I realised that if it was a genuine currency note, the Efficient Market would have picked it up already.
matthewdgreen 9mo ago
The EMH does not mean that markets are free of over-investment and asset bubbles, followed by crashes.

throwaway85825 9mo ago

It's not flat growth that's currently priced in, but continuing high growth. Which is impossible.

WalterBright 9mo ago

> technical analysis of the stock AKA pictures in clouds

TacticalCoder 9mo ago

> This article goes more into the technical analysis of the stock rather than the underlying business fundamentals that would lead to a stock dump. My 30k ft view is that the stock will inevitably slide as AI Actually "technical analysis" (TA) has a very specific meaning in trading: TA is using past prices, volume of trading and price movements to, hopefully, give probabilities about future price moves. https://en.wikipedia.org/wiki/Technical_analysis https://en.wikipedia.org/wiki/Technical_analysis But TFA doesn't do that at all: it goes in detail into one pricing model formula/method for options pricing. In the typical options pricing model all you're using is current price (of the underlying, say NVDA), strike price (of the option), expiration date, current interest rate and IV (implied volatility: influenced by recent price movements but independently of any technical analysis). Be it Black-Scholes-Merton (european-style options), Bjerksund-Stensland (american-style options), binomial as in TFA, or other open options pricing model: none of these use technical analysis. Here's an example (for european-style options) where one can see the parameters: https://www.mystockoptions.com/black-scholes.cfm https://www.mystockoptions.com/black-scholes.cfm You can literally compute entire options chains with these parameters. Now it's known for a fact that many professional traders firms have their own options pricing method and shall arb when they think they find incorrectly priced options. I don't know if some use actual so forms of TA that they then mix with options pricing model or not. > My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. No matter if you're right or not, I'd argue you're doing what's called fundamental analysis (but I may be wrong). P.S: I'm not debatting the merits of TA and whether it's reading into tea leaves or not. What I'm saying is that options pricing using the binomial method cannot be called "technical analysis" for TA is something else.

ramijames 9mo ago

This seems to take for granted that China and their foundries and engineering teams will never catch up. This seems foolish. I'm working under the assumption that sometime in the next ten years some Chinese company will have a breakthrough and either meet Nvidia's level or leapfrog them. Then the market will flood with great, cheap chips.

amelius 9mo ago

> My 30k ft view is that the stock will inevitably slide as AI datacenter spending goes down. This is like saying Apple stock will inevitably slide once everybody owns a smartphone.

pjmlp 9mo ago

Even though I like CUDA, I think the point is when do compute centers reach the point that they can run their workloads with other vendors, or custom accelerators.