5 ms·

Good time to buy then, I don’t understand how stupid some traders can be. A more efficient model is better for NVIDIA not worse. More compute is still better g

Good time to buy then, I don’t understand how stupid some traders can be. A more efficient model is better for NVIDIA not worse. More compute is still better given the same model. And as more efficient models proliferate it means more edge computing which means more customers with lower negotiating power than Meta and Google… This is like thinking that if people need to dig only 1 day instead of an entire month to get to their nugget of gold in the midst of a gold rush the trading post will somehow sell fewer shovels…

digitcatphd 2y ago
This doesn't have anything to do with DS, despite what the media claims, it comes to a heightened sense of fear people have with playing with fire.
diegocg 2y ago
Nvidia is way too overvalued regardless of deepseek or the success of AI. This is just some correction (not even too big even considering the current bubble), these traders are not stupid.
- dogma1138 2y ago
  NVIDIA has a P/E ratio of 56 that’s double that of the S&P 500 but half that of AMD and the same one as Meta. And whether it’s overvalued or not isn’t relevant that selling a stock because the product the company produces is now even more effective is mind bogglingly stupid.
  - InkCanon 2y ago
    It's arguable how good a strategy it is to check against other P/E. During the tech bubble people would say X is cheap, because Y is trading at 100P/E instead of 200
    - dogma1138 2y ago
      Again that may reasonable but it’s a completely different argument. Whether there is a bubble or not and whether NVDA is overvalued is irrelevant to the subject at hand. If it’s cheaper to train models it means far more customers that will try their luck. If you reduce training requirement from a 100,000 GPUs to a 1000 you’ve now opened the market to 1000’s and 1000’s of potential players instead of like the 10 that can afford dumping so much money into a compute cluster.
      - fragmede 2y ago
        the holy grail is to not have a separate train and inference steps. when the model can be updated while it is inferencing is where we're headed. deepseek only accelerates the need for more compute, not less
        Jlagreen 2y ago
        THIS is the only correct statement in all of this. The goal for AGI and ASI MUST BE to train, inference, train, inference and so on and that all on the fly in fractions of a second from every token produced. Now good luck calculating the compute and hard work in algorithms to get there. Not possible? Then AGI won't ever work because how can AGI beat a human if it can't learn on the fly? Not to mention ASI lol.
    - nejsjsjsbsb 2y ago
      P/E alone is useless anyway. A growth company is likely not making a profit as they are reinvesting. But not a profit doesn't implies good either of course.
  - nobunaga 2y ago
    AMD does not have a PE double of NVIDIA. PE is high because of amortisation of an acquisition. People on hackernews talk a lot but have no idea what they talk about. You might know how to write javascript or some other language but clearly you have not read the earnings reports or financials of AMD and probably alot of the other companies you talk about. So please stop spreading nonsense. Just for those that clearly have no idea https://old.reddit.com/r/AMD_Stock/comments/1d2okn1/when_will_the_xlnx_amortization_end/ https://old.reddit.com/r/AMD_Stock/comments/1d2okn1/when_wil...
    - malinens 2y ago
      You are correct but please read: https://news.ycombinator.com/newsguidelines.html#comments https://news.ycombinator.com/newsguidelines.html#comments
  - locallost 2y ago
    Well the price has a built in presumption that the earnings will keep growing. That's why PER is not that relevant for them, it's been over 50-70 since forever, but the stock went up 10x, which means earnings went up as well. DeepSeek might be good for their business overall, but it might mean earnings will not continue growing exponentially like they have been for the past two years. So it's time to bail. You shouldn't underestimate the fact that a large amount of these trades are on margin. Sometimes you can't wait it out because you'll get margin called and if you can't pony up additional cash you're basically getting caught with your pants down. Disclaimer: I am not a trader, so could be way off
    - dogma1138 2y ago
      Why? The compute requirements would still continue to grow the more efficient and more capable the models become. If it’s cheaper to inference you end up using the model for more task, it it’s cheaper to train you train more than models. And if you now need only 1000’s of GPUs instead of 10’s or 100’s of thousands you’ve just unlocked a massive client base of those who can afford to invest high six to low seven figures instead of 100’s of millions or billions into to try their luck.
      - margorczynski 2y ago
        Doesn't this situation also imply to some degree that China is focused on beating the US on AI and probably they will develop a competitor to NVIDIA that will cause margins to drop significantly? They have a lot of very smart people and the will to do it, seems like a matter of time before they succeed.
      - locallost 2y ago
        It could be, but maybe the feeling is the investments now are already massive and everyone has jumped on the AI train. If you are suddenly 10x efficient, and everyone gets 10x more efficient, there's less room to grow than before. What you're saying makes a lot of sense, but it's one thing to write it on a message board and another to use it to back up your decision that affects billions of dollars you have in your fund. The proof is in the pudding, you're welcome to prove "everyone" wrong.
  - cbg0 2y ago
    > selling a stock because the product the company produces is now even more effective is mind bogglingly stupid. No it isn't. Investors are most likely expecting there will be less demand for Nvidia's product long-term due to these alleged increased training efficiencies.
    - PeterStuer 2y ago
      There is afaict no inherent limit to expand on the bottom end of the market. My gut feeling is lower training costs will expand the market for hardware horizontaly far faster than any vertical scaling by a select 2 digit of mega corps could.
  - redwood 2y ago
    This is hackernews, not some boilerroom pump n dump forum. Please use more professional language and take your confidence down a notch. Try to learn and add to the discussion. You seem to believe that the more inference or training value per piece of tech the more demand there will be for that piece of tech full stop when there are multiple forces at play. As a simple example, you can think of this as a supply spike; while you can make the bet that the demand will follow there could be a lag on that demand spike due to the time it takes to find use cases with product/market fit. That could collapse prices over the near term which could in turn decrease revenue. As a reminder the stock value isn't a bet on whether "the gold trader" will sell more gold or not, it's a bet on whether the net future returns of the gold trader will occur in line with expectations, expectations that are sky high and have zero competition built in.
- randomcarbloke 2y ago
  agreed but ASML has been chronically undervalued forever.
  - nejsjsjsbsb 2y ago
    I went for some Asian index funds to balance things out for this reason.
  - api 2y ago
    The people who really make the magic generally do not capture the hype.
  - PeterStuer 2y ago
    Have you priced in the extremely limited freedom to operate they have? There is an extreme systemic risk to being a monopoly in a strategic position. It's an extreme beneficial position to be in, until it isn't.
    - randomcarbloke 2y ago
      do you have a model for "short-leash monopolies" would definitely put that in The Book.
    - aix1 2y ago
      Would you mind expanding on what you mean by this? I'm struggling to follow. Thanks.
      - PeterStuer 2y ago
        ASML for now has a monopoly on cutting edge EUV. Since this is considered a strategic technology, the US dictates what they can sell to whom. This places ASML in a pincer. The US will develop a competitor as soon as they can if they can't get enough control over ASML, and at that point ASML would still be forbidden to sell to BRICS while losing the 'western' market as well. So they're in a plushy seat, until the US decides they aren't.
- matwood 2y ago
  I agree with Aswath Damodaran here. NVDA is priced for perfection in AI, but also whatever is next. In addition, IMO NVDA’s margins are a gift and a curse. They look great to investors, but also mean all their customers are aggressively looking to produce their own GPUs.
  - goeiedaggoeie 2y ago
    Exactly. gpu's have become too profitable and of strategic importance, to not see several deep pocketed existing technology companies invest more and try and acquire market share. there is a mini moat here with cuda and existing work, but some the start of commodification must be on the <10 year horizon
  - api 2y ago
    They are also priced on the idea that nothing will challenge them. If AMD, Intel, or anyone else comes out with a challenger for their top GPUs at competitive prices, that’s a problem. I’m surprised they haven’t yet.
    - matwood 2y ago
      The biggest challengers are likely the hyperscalers and companies like Meta. It sort of flew under the radar when Meta released an update on their GPU plans last year and said their cluster would be as powerful as X NVDA GPUs, and not that it would have X NVDA GPUs [1]. Also, I should add that Deepseek just showed the top GPUs are not necessary to deliver big value. [1] https://engineering.fb.com/2024/03/12/data-center-engineering/building-metas-genai-infrastructure/ https://engineering.fb.com/2024/03/12/data-center-engineerin... This announcement is one step in our ambitious infrastructure roadmap. By the end of 2024, we’re aiming to continue to grow our infrastructure build-out that will include 350,000 NVIDIA H100 GPUs as part of a portfolio that will feature compute power equivalent to nearly 600,000 H100s.
HPsquared 2y ago
In said gold rush scenario, the price of gold itself would have collapsed.
- lovasoa 2y ago
  And since the gold supply is limited, fewer shovels would indeed be required.
belter 2y ago
NVDA is a totally manipulated stock. The company beat earnings in the last three quarters and the stock dropped 15% to 20% immediately after the results release. Every single time...
- sitkack 2y ago
  What do you think is going on here? Why is it dropping?
  - belter 2y ago
    DeepSeek is only partial to this. DeepSeek might be the trigger, but the core reasons are the overvaluations.
- baal80spam 2y ago
  I don't think it's manipulated, just hot. As the old adage goes: "Buy the rumor, sell the news".
WithinReason 2y ago
Indeed: https://en.wikipedia.org/wiki/Jevons_paradox https://en.wikipedia.org/wiki/Jevons_paradox In economics, the Jevons paradox occurs when technological progress increases the efficiency with which a resource is used, but the falling cost of use induces increases in demand enough that resource use is increased, rather than reduced.
- belter 2y ago
  I beat your Jevons paradox and raise you the Theory of Constraints..
- ReptileMan 2y ago
  Yes but it will also mean that people wouldn't need cutting edge NVIDIA chips - it will be able to run on older node chips. Or from different manufacturers. So NVIDIA wouldn't be able to command the margins they do now. It may be great news for VRAM manufacturers tough.
  - WithinReason 2y ago
    They only need cutting edge to be competitive, and that will be true independently of efficiency. That's the point.
sitkack 2y ago
You are right, it is a Jevon's paradox thing. We were already going to spend all the gigawatts on AI, it is just more AI.
Etheryte 2y ago
While everything you say may be true, this shows a fundamental misunderstanding about how the modern stock market functions. How much value a company creates is at best tangential and often completely orthogonal to how much the stock is worth. The stock market has always been a Keynesian beauty contest, but in the past few decades, strongly shaped and morphed by attention economies. A good example of this is DJT, a company which functionally doesn't do much anything, but in the last year has traded at wildly differing prices. P/E, EBITDA, etc, are all useless metrics in trying to explain this phenomenon. In other words, NVIDIA is in the red not because the company is suddenly doing worse, but because traders think other traders think it will trade down. That is a self fulfilling prophecy, but only so long as there is sufficient attention to drive that. The same works the other way around as well, so long as there is sufficient attention to drive the AI hype train upwards, related stocks will do well as well.
- Cumpiler69 2y ago
  >In other words, NVIDIA is in the red not because the company is suddenly doing worse, but because traders think other traders think it will trade down. Well put. People need to unterstand that some stocks are basically one giant casino poker table. There was a comment with a link here that a lot of Nvidia buyers don't even know what products Nvidia is making and they don't care, they just want to buy low and sell high. Insert old famous comment abut shoe shine boy giving investment advice to Wall Street stock traders.
- Dalewyn 2y ago
  Put more simply: The stock market is not a reflection of the economy. Wall Street is not Main Street.
  - nejsjsjsbsb 2y ago
    Wall St is not Main St even if they price it perfectly.
  - WJW 2y ago
    It's a reflection of expectations about the future economy. Obviously, such expectations are not always accurate because humans are quite fallible when trying to predict the future. This is even more true when there is a lot of hype about a certain product. Yesterdays price of (say) NVidia was based on the expectation that companies would need to buy N billion of USD of GPUs per year. Now Deepseek comes out and makes a point that N/10 would be enough. From there it can go two ways: - NVidia's expected future sales drop by 90%. - The reduced price for LLMs should allow companies to push AI into markets that were previously not cost effective. Maybe this can 10x the total available market, but since the estimated total available market was already ~everything (due to hype) that seems unlikely. - NVidia finds another usecase for GPUs to offset the reduced demand from AI companies. In practice, it will probably be some combination of all three. The real problems are not caused for the "shovel sellers" but for companies like OpenAI and Anthropic, who now suddenly have to compete against a competitor that can produce the same product at (apparently) a fraction of the price.
mistercow 2y ago
I think it's because the media coverage is all focused on how this means the big AI players have lost their competitive advantage, rather than the other side of the equation. But that's also dumb, because "huge leap forward in training efficiency" is not exactly bad news for the major players in even the medium term. Short term, it means their models are less competitive, but I don't see any reason that they can't leverage e.g. these new mixed precision training techniques on their giant GPU farms and train something even bigger and smarter. There seems to be this weird baked in assumption that AI is at a permanent (or at least semi-permanent) plateau, and that open source models catching up is the end of the game. But this is an arms race, and we're nowhere near the finish line.
nejsjsjsbsb 2y ago
Good time to buy is % of income via tax efficient methods into the in SP500 for most. But I agree in the sense that Deepseek just creates more demand. Because people desire to get AI to do more work. This makes bang for buck greater opening new opportunities. This sell off is like selling Intel in 2010 because of a new C compiler.
csomar 2y ago
Not if the current architecture plateaus around the level of O1/3.5/R1. Then any further training is useless and inference is relatively cheap.
amazingamazing 2y ago
maybe Nvidia is fine but I don't understand this logic. suppose it turns out GPUs are unnecessary at all, but they still provide a performance boost, but you can do everything you can do right now with CPUs w.r.t performance. would that be good or bad for Nvidia? unless it can be said we need more performance than is currently possible, e.g. new demand, it would be catastrophic. it is unclear that throwing more compute actually expands what is possible. if that is not the case, efficiency is bad for nvidia because it simply results in less demand.
- diggan 2y ago
  I could see arguments be made in both ways here. If GPUs end up being more efficient/powerful (like today) it could induce even more demand, but also if CPU gets within ~20% of how fast you can do something with a GPU, people might start opting for something like Macs with unified memory instead of GPUs. Today a CPU setup is still nowhere near as fast as a GPU setup (for ML/AI), but who knows how it looks like in the future. > it is unclear that throwing more compute actually expands what is possible Wasn't that demonstrated to be true already in the GPT1/2 days? AFAIK, LLMs became a thing very much because OpenAI "discovered" that "throwing more compute (and training data) at the problem/solution expands what is possible"
fintechie 2y ago
> I don’t understand how stupid some traders can be. 90% of traders lose money, so that's a data point... You're trying to apply rational thinking but that's not how markets work. In the end valuations are more about narratives in the collective mind than technological merit.
ransom1538 2y ago
"dig only 1 day instead of an entire month" You answered your own question. People do not dig in the Sacramento right anymore for gold, because, it is gone. If you can train models for 1/100 the cost, and you sell model training chips, you probably are not going to sell as many chips.
- Jlagreen 2y ago
  That's why the shovel maker from back then are selling mining machines today. Everyone here thinks Nvidia is dommed because of training efficiency. But what has Nvidia been doing for the past decade? Correct increasing training and inferencing efficiency by magnitudes. Try to train GPT4 on 10k of Volta, Ampere, Hopper and then Blackwell. What has happened since then? Nvidia has increased their sales in magnitudes. Why? Because thanks to improvement in data, in algorithms, compute efficiency ChatGPT was possible in the first place. Imagine Nvidia wouldn't exist. When do you think the ChatGPT moment would happen on CPUs? LOL Going back to my first sentence. Nvidia started also with small shovels which were GeForce cards with CUDA. Today Nvidia is selling huge GPU clusters (mining machines, yes pun intended ^^).
chvid 2y ago
It is a demonstration that progress is no longer due to llm scaling.
croes 2y ago
But a more efficient model doesn't need the top notch hardware
zozbot234 2y ago
nVidia is also about HPC in general, not just AI. It's remarkably silly that the stock would plunge 13% just because someone made a more compute-efficient LLM.
csomar 2y ago
> Good time to buy then No. The stock is still x10 after this dip from 2 years ago and x40 from a few years ago.
gadders 2y ago
>>>I don’t understand how stupid some traders can be. I believe the saying is "The market can stay wrong for longer than you can stay solvent."
omgJustTest 2y ago
> Good time to buy then, I don’t understand how stupid some traders can be. Likely a "how solid is the technical moat" evaluation - this could be a one-off or could be that there are an avalanche of advancements to continue along the efficiency side of the process. Given the style and hype of logic in the AI space, I fully believe resources are not well allocated in compute and _actual_ thinking as to how they are spent. Deepseek's apparent 10x more efficient per inference token... implies a lot of other hardware meets the general use-case. We also know that reasoning should be about 10W for human speed-of-thought... maybe another 1-2 orders of power efficiency. "Pre-Training: Towards Ultimate Training Efficiency We design an FP8 mixed precision training framework and, for the first time, validate the feasibility and effectiveness of FP8 training on an extremely large-scale model. Through co-design of algorithms, frameworks, and hardware, we overcome the communication bottleneck in cross-node MoE training, nearly achieving full computation-communication overlap. This significantly enhances our training efficiency and reduces the training costs, enabling us to further scale up the model size without additional overhead. At an economical cost of only 2.664M H800 GPU hours, we complete the pre-training of DeepSeek-V3 on 14.8T tokens, producing the currently strongest open-source base model. The subsequent training stages after pre-training require only 0.1M GPU hours." [1] [1] https://huggingface.co/deepseek-ai/DeepSeek-V3 https://huggingface.co/deepseek-ai/DeepSeek-V3
deleted 2y ago
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llm_nerd 2y ago
>the trading post will somehow sell fewer shovels There is a point where there are enough shovels circulating that the demand for new shovels falters, even with zero drawback in the rush. And if so much gold was being mined that it overwhelmed the market and reduced the commodity price, the value of better shovels is reduced. DeepSeek and friends basically reduce the commodity value of AI (and to be fair, Facebook, Microsoft et al are trying to do the same thing with their open source models, trying to chop the legs out of the upstart AI cos). If AI is worth less, there are going to be fewer mega capitalized AI ventures buying a trillion dollars worth of rapidly-depreciating GPUs in hopes at eeking out some minor advantage. I wouldn't short nvidia stock, but at the same time there is a point where the spend of GPUs just isn't rational anymore. >And as more efficient models proliferate it means more edge computing which means more customers with lower negotiating power than Meta and Google Edge compute has infinitely more competition than the data center.

digitcatphd 2y ago

This doesn't have anything to do with DS, despite what the media claims, it comes to a heightened sense of fear people have with playing with fire.

diegocg 2y ago

Nvidia is way too overvalued regardless of deepseek or the success of AI. This is just some correction (not even too big even considering the current bubble), these traders are not stupid.

dogma1138 2y ago
NVIDIA has a P/E ratio of 56 that’s double that of the S&P 500 but half that of AMD and the same one as Meta. And whether it’s overvalued or not isn’t relevant that selling a stock because the product the company produces is now even more effective is mind bogglingly stupid.
- InkCanon 2y ago
  It's arguable how good a strategy it is to check against other P/E. During the tech bubble people would say X is cheap, because Y is trading at 100P/E instead of 200
  - dogma1138 2y ago
    Again that may reasonable but it’s a completely different argument. Whether there is a bubble or not and whether NVDA is overvalued is irrelevant to the subject at hand. If it’s cheaper to train models it means far more customers that will try their luck. If you reduce training requirement from a 100,000 GPUs to a 1000 you’ve now opened the market to 1000’s and 1000’s of potential players instead of like the 10 that can afford dumping so much money into a compute cluster.
    - fragmede 2y ago
      the holy grail is to not have a separate train and inference steps. when the model can be updated while it is inferencing is where we're headed. deepseek only accelerates the need for more compute, not less
      - Jlagreen 2y ago
        THIS is the only correct statement in all of this. The goal for AGI and ASI MUST BE to train, inference, train, inference and so on and that all on the fly in fractions of a second from every token produced. Now good luck calculating the compute and hard work in algorithms to get there. Not possible? Then AGI won't ever work because how can AGI beat a human if it can't learn on the fly? Not to mention ASI lol.
  - nejsjsjsbsb 2y ago
    P/E alone is useless anyway. A growth company is likely not making a profit as they are reinvesting. But not a profit doesn't implies good either of course.
- nobunaga 2y ago
  AMD does not have a PE double of NVIDIA. PE is high because of amortisation of an acquisition. People on hackernews talk a lot but have no idea what they talk about. You might know how to write javascript or some other language but clearly you have not read the earnings reports or financials of AMD and probably alot of the other companies you talk about. So please stop spreading nonsense. Just for those that clearly have no idea https://old.reddit.com/r/AMD_Stock/comments/1d2okn1/when_will_the_xlnx_amortization_end/ https://old.reddit.com/r/AMD_Stock/comments/1d2okn1/when_wil...
  - malinens 2y ago
    You are correct but please read: https://news.ycombinator.com/newsguidelines.html#comments https://news.ycombinator.com/newsguidelines.html#comments
- locallost 2y ago
  Well the price has a built in presumption that the earnings will keep growing. That's why PER is not that relevant for them, it's been over 50-70 since forever, but the stock went up 10x, which means earnings went up as well. DeepSeek might be good for their business overall, but it might mean earnings will not continue growing exponentially like they have been for the past two years. So it's time to bail. You shouldn't underestimate the fact that a large amount of these trades are on margin. Sometimes you can't wait it out because you'll get margin called and if you can't pony up additional cash you're basically getting caught with your pants down. Disclaimer: I am not a trader, so could be way off
  - dogma1138 2y ago
    Why? The compute requirements would still continue to grow the more efficient and more capable the models become. If it’s cheaper to inference you end up using the model for more task, it it’s cheaper to train you train more than models. And if you now need only 1000’s of GPUs instead of 10’s or 100’s of thousands you’ve just unlocked a massive client base of those who can afford to invest high six to low seven figures instead of 100’s of millions or billions into to try their luck.
    - margorczynski 2y ago
      Doesn't this situation also imply to some degree that China is focused on beating the US on AI and probably they will develop a competitor to NVIDIA that will cause margins to drop significantly? They have a lot of very smart people and the will to do it, seems like a matter of time before they succeed.
    - locallost 2y ago
      It could be, but maybe the feeling is the investments now are already massive and everyone has jumped on the AI train. If you are suddenly 10x efficient, and everyone gets 10x more efficient, there's less room to grow than before. What you're saying makes a lot of sense, but it's one thing to write it on a message board and another to use it to back up your decision that affects billions of dollars you have in your fund. The proof is in the pudding, you're welcome to prove "everyone" wrong.
- cbg0 2y ago
  > selling a stock because the product the company produces is now even more effective is mind bogglingly stupid. No it isn't. Investors are most likely expecting there will be less demand for Nvidia's product long-term due to these alleged increased training efficiencies.
  - PeterStuer 2y ago
    There is afaict no inherent limit to expand on the bottom end of the market. My gut feeling is lower training costs will expand the market for hardware horizontaly far faster than any vertical scaling by a select 2 digit of mega corps could.
- redwood 2y ago
  This is hackernews, not some boilerroom pump n dump forum. Please use more professional language and take your confidence down a notch. Try to learn and add to the discussion. You seem to believe that the more inference or training value per piece of tech the more demand there will be for that piece of tech full stop when there are multiple forces at play. As a simple example, you can think of this as a supply spike; while you can make the bet that the demand will follow there could be a lag on that demand spike due to the time it takes to find use cases with product/market fit. That could collapse prices over the near term which could in turn decrease revenue. As a reminder the stock value isn't a bet on whether "the gold trader" will sell more gold or not, it's a bet on whether the net future returns of the gold trader will occur in line with expectations, expectations that are sky high and have zero competition built in.
randomcarbloke 2y ago
agreed but ASML has been chronically undervalued forever.
- nejsjsjsbsb 2y ago
  I went for some Asian index funds to balance things out for this reason.
- api 2y ago
  The people who really make the magic generally do not capture the hype.
- PeterStuer 2y ago
  Have you priced in the extremely limited freedom to operate they have? There is an extreme systemic risk to being a monopoly in a strategic position. It's an extreme beneficial position to be in, until it isn't.
  - randomcarbloke 2y ago
    do you have a model for "short-leash monopolies" would definitely put that in The Book.
  - aix1 2y ago
    Would you mind expanding on what you mean by this? I'm struggling to follow. Thanks.
    - PeterStuer 2y ago
      ASML for now has a monopoly on cutting edge EUV. Since this is considered a strategic technology, the US dictates what they can sell to whom. This places ASML in a pincer. The US will develop a competitor as soon as they can if they can't get enough control over ASML, and at that point ASML would still be forbidden to sell to BRICS while losing the 'western' market as well. So they're in a plushy seat, until the US decides they aren't.
matwood 2y ago
I agree with Aswath Damodaran here. NVDA is priced for perfection in AI, but also whatever is next. In addition, IMO NVDA’s margins are a gift and a curse. They look great to investors, but also mean all their customers are aggressively looking to produce their own GPUs.
- goeiedaggoeie 2y ago
  Exactly. gpu's have become too profitable and of strategic importance, to not see several deep pocketed existing technology companies invest more and try and acquire market share. there is a mini moat here with cuda and existing work, but some the start of commodification must be on the <10 year horizon
- api 2y ago
  They are also priced on the idea that nothing will challenge them. If AMD, Intel, or anyone else comes out with a challenger for their top GPUs at competitive prices, that’s a problem. I’m surprised they haven’t yet.
  - matwood 2y ago
    The biggest challengers are likely the hyperscalers and companies like Meta. It sort of flew under the radar when Meta released an update on their GPU plans last year and said their cluster would be as powerful as X NVDA GPUs, and not that it would have X NVDA GPUs [1]. Also, I should add that Deepseek just showed the top GPUs are not necessary to deliver big value. [1] https://engineering.fb.com/2024/03/12/data-center-engineering/building-metas-genai-infrastructure/ https://engineering.fb.com/2024/03/12/data-center-engineerin... This announcement is one step in our ambitious infrastructure roadmap. By the end of 2024, we’re aiming to continue to grow our infrastructure build-out that will include 350,000 NVIDIA H100 GPUs as part of a portfolio that will feature compute power equivalent to nearly 600,000 H100s.

HPsquared 2y ago

In said gold rush scenario, the price of gold itself would have collapsed.

lovasoa 2y ago
And since the gold supply is limited, fewer shovels would indeed be required.

belter 2y ago

NVDA is a totally manipulated stock. The company beat earnings in the last three quarters and the stock dropped 15% to 20% immediately after the results release. Every single time...

sitkack 2y ago
What do you think is going on here? Why is it dropping?
- belter 2y ago
  DeepSeek is only partial to this. DeepSeek might be the trigger, but the core reasons are the overvaluations.
baal80spam 2y ago
I don't think it's manipulated, just hot. As the old adage goes: "Buy the rumor, sell the news".

WithinReason 2y ago

Indeed: https://en.wikipedia.org/wiki/Jevons_paradox https://en.wikipedia.org/wiki/Jevons_paradox In economics, the Jevons paradox occurs when technological progress increases the efficiency with which a resource is used, but the falling cost of use induces increases in demand enough that resource use is increased, rather than reduced.

belter 2y ago
I beat your Jevons paradox and raise you the Theory of Constraints..
ReptileMan 2y ago
Yes but it will also mean that people wouldn't need cutting edge NVIDIA chips - it will be able to run on older node chips. Or from different manufacturers. So NVIDIA wouldn't be able to command the margins they do now. It may be great news for VRAM manufacturers tough.
- WithinReason 2y ago
  They only need cutting edge to be competitive, and that will be true independently of efficiency. That's the point.

sitkack 2y ago

You are right, it is a Jevon's paradox thing. We were already going to spend all the gigawatts on AI, it is just more AI.

Etheryte 2y ago

While everything you say may be true, this shows a fundamental misunderstanding about how the modern stock market functions. How much value a company creates is at best tangential and often completely orthogonal to how much the stock is worth. The stock market has always been a Keynesian beauty contest, but in the past few decades, strongly shaped and morphed by attention economies. A good example of this is DJT, a company which functionally doesn't do much anything, but in the last year has traded at wildly differing prices. P/E, EBITDA, etc, are all useless metrics in trying to explain this phenomenon. In other words, NVIDIA is in the red not because the company is suddenly doing worse, but because traders think other traders think it will trade down. That is a self fulfilling prophecy, but only so long as there is sufficient attention to drive that. The same works the other way around as well, so long as there is sufficient attention to drive the AI hype train upwards, related stocks will do well as well.

Cumpiler69 2y ago
>In other words, NVIDIA is in the red not because the company is suddenly doing worse, but because traders think other traders think it will trade down. Well put. People need to unterstand that some stocks are basically one giant casino poker table. There was a comment with a link here that a lot of Nvidia buyers don't even know what products Nvidia is making and they don't care, they just want to buy low and sell high. Insert old famous comment abut shoe shine boy giving investment advice to Wall Street stock traders.
Dalewyn 2y ago
Put more simply: The stock market is not a reflection of the economy. Wall Street is not Main Street.
- nejsjsjsbsb 2y ago
  Wall St is not Main St even if they price it perfectly.
- WJW 2y ago
  It's a reflection of expectations about the future economy. Obviously, such expectations are not always accurate because humans are quite fallible when trying to predict the future. This is even more true when there is a lot of hype about a certain product. Yesterdays price of (say) NVidia was based on the expectation that companies would need to buy N billion of USD of GPUs per year. Now Deepseek comes out and makes a point that N/10 would be enough. From there it can go two ways: - NVidia's expected future sales drop by 90%. - The reduced price for LLMs should allow companies to push AI into markets that were previously not cost effective. Maybe this can 10x the total available market, but since the estimated total available market was already ~everything (due to hype) that seems unlikely. - NVidia finds another usecase for GPUs to offset the reduced demand from AI companies. In practice, it will probably be some combination of all three. The real problems are not caused for the "shovel sellers" but for companies like OpenAI and Anthropic, who now suddenly have to compete against a competitor that can produce the same product at (apparently) a fraction of the price.

mistercow 2y ago

I think it's because the media coverage is all focused on how this means the big AI players have lost their competitive advantage, rather than the other side of the equation. But that's also dumb, because "huge leap forward in training efficiency" is not exactly bad news for the major players in even the medium term. Short term, it means their models are less competitive, but I don't see any reason that they can't leverage e.g. these new mixed precision training techniques on their giant GPU farms and train something even bigger and smarter. There seems to be this weird baked in assumption that AI is at a permanent (or at least semi-permanent) plateau, and that open source models catching up is the end of the game. But this is an arms race, and we're nowhere near the finish line.

nejsjsjsbsb 2y ago

Good time to buy is % of income via tax efficient methods into the in SP500 for most. But I agree in the sense that Deepseek just creates more demand. Because people desire to get AI to do more work. This makes bang for buck greater opening new opportunities. This sell off is like selling Intel in 2010 because of a new C compiler.

csomar 2y ago

Not if the current architecture plateaus around the level of O1/3.5/R1. Then any further training is useless and inference is relatively cheap.

amazingamazing 2y ago

maybe Nvidia is fine but I don't understand this logic. suppose it turns out GPUs are unnecessary at all, but they still provide a performance boost, but you can do everything you can do right now with CPUs w.r.t performance. would that be good or bad for Nvidia? unless it can be said we need more performance than is currently possible, e.g. new demand, it would be catastrophic. it is unclear that throwing more compute actually expands what is possible. if that is not the case, efficiency is bad for nvidia because it simply results in less demand.

diggan 2y ago
I could see arguments be made in both ways here. If GPUs end up being more efficient/powerful (like today) it could induce even more demand, but also if CPU gets within ~20% of how fast you can do something with a GPU, people might start opting for something like Macs with unified memory instead of GPUs. Today a CPU setup is still nowhere near as fast as a GPU setup (for ML/AI), but who knows how it looks like in the future. > it is unclear that throwing more compute actually expands what is possible Wasn't that demonstrated to be true already in the GPT1/2 days? AFAIK, LLMs became a thing very much because OpenAI "discovered" that "throwing more compute (and training data) at the problem/solution expands what is possible"

fintechie 2y ago

> I don’t understand how stupid some traders can be. 90% of traders lose money, so that's a data point... You're trying to apply rational thinking but that's not how markets work. In the end valuations are more about narratives in the collective mind than technological merit.

ransom1538 2y ago

"dig only 1 day instead of an entire month" You answered your own question. People do not dig in the Sacramento right anymore for gold, because, it is gone. If you can train models for 1/100 the cost, and you sell model training chips, you probably are not going to sell as many chips.

Jlagreen 2y ago
That's why the shovel maker from back then are selling mining machines today. Everyone here thinks Nvidia is dommed because of training efficiency. But what has Nvidia been doing for the past decade? Correct increasing training and inferencing efficiency by magnitudes. Try to train GPT4 on 10k of Volta, Ampere, Hopper and then Blackwell. What has happened since then? Nvidia has increased their sales in magnitudes. Why? Because thanks to improvement in data, in algorithms, compute efficiency ChatGPT was possible in the first place. Imagine Nvidia wouldn't exist. When do you think the ChatGPT moment would happen on CPUs? LOL Going back to my first sentence. Nvidia started also with small shovels which were GeForce cards with CUDA. Today Nvidia is selling huge GPU clusters (mining machines, yes pun intended ^^).

chvid 2y ago

It is a demonstration that progress is no longer due to llm scaling.

croes 2y ago

But a more efficient model doesn't need the top notch hardware

zozbot234 2y ago

nVidia is also about HPC in general, not just AI. It's remarkably silly that the stock would plunge 13% just because someone made a more compute-efficient LLM.

csomar 2y ago

> Good time to buy then No. The stock is still x10 after this dip from 2 years ago and x40 from a few years ago.

gadders 2y ago

>>>I don’t understand how stupid some traders can be. I believe the saying is "The market can stay wrong for longer than you can stay solvent."

omgJustTest 2y ago

> Good time to buy then, I don’t understand how stupid some traders can be. Likely a "how solid is the technical moat" evaluation - this could be a one-off or could be that there are an avalanche of advancements to continue along the efficiency side of the process. Given the style and hype of logic in the AI space, I fully believe resources are not well allocated in compute and _actual_ thinking as to how they are spent. Deepseek's apparent 10x more efficient per inference token... implies a lot of other hardware meets the general use-case. We also know that reasoning should be about 10W for human speed-of-thought... maybe another 1-2 orders of power efficiency. "Pre-Training: Towards Ultimate Training Efficiency We design an FP8 mixed precision training framework and, for the first time, validate the feasibility and effectiveness of FP8 training on an extremely large-scale model. Through co-design of algorithms, frameworks, and hardware, we overcome the communication bottleneck in cross-node MoE training, nearly achieving full computation-communication overlap. This significantly enhances our training efficiency and reduces the training costs, enabling us to further scale up the model size without additional overhead. At an economical cost of only 2.664M H800 GPU hours, we complete the pre-training of DeepSeek-V3 on 14.8T tokens, producing the currently strongest open-source base model. The subsequent training stages after pre-training require only 0.1M GPU hours." [1] [1] https://huggingface.co/deepseek-ai/DeepSeek-V3 https://huggingface.co/deepseek-ai/DeepSeek-V3

deleted 2y ago

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llm_nerd 2y ago

>the trading post will somehow sell fewer shovels There is a point where there are enough shovels circulating that the demand for new shovels falters, even with zero drawback in the rush. And if so much gold was being mined that it overwhelmed the market and reduced the commodity price, the value of better shovels is reduced. DeepSeek and friends basically reduce the commodity value of AI (and to be fair, Facebook, Microsoft et al are trying to do the same thing with their open source models, trying to chop the legs out of the upstart AI cos). If AI is worth less, there are going to be fewer mega capitalized AI ventures buying a trillion dollars worth of rapidly-depreciating GPUs in hopes at eeking out some minor advantage. I wouldn't short nvidia stock, but at the same time there is a point where the spend of GPUs just isn't rational anymore. >And as more efficient models proliferate it means more edge computing which means more customers with lower negotiating power than Meta and Google Edge compute has infinitely more competition than the data center.