A 589 billions USD loss (or whatever that means in the context of the stock market because it sure as hell doesn't seem to be anchored to reality)? Over, what, a product release from another...
A 589 billions USD loss (or whatever that means in the context of the stock market because it sure as hell doesn't seem to be anchored to reality)? Over, what, a product release from another company that the market perceived as a threat to... the company that provides the hardware one would want to run this very same product on?
What the fuck?
This makes absolutely no sense to me on several different levels. I'm at a loss for words here, and given what I'm usually like, that's saying a lot, pun intended. I'm already completely unable to even comprehend the mind-shatteringly high value 589,000,000,000 USD represents, let alone how a company could "lose" that amount without instantly ceasing to exist, why this specific event led to NVIDIA suffering this badly from it, and the article has not provided an answer to any of it (or at least that last one) that makes sense to me. Can someone with a better grasp on economics explain this? Because I'm stumped.
Chinese companies are restricted in what GPUs they can buy from NVidia. If China produces major players in AI it means one of two things: You don't need as much GPU power as previously expected to...
Chinese companies are restricted in what GPUs they can buy from NVidia. If China produces major players in AI it means one of two things:
You don't need as much GPU power as previously expected to produce good AI
China can get GPUs from non-USA companies
In this case it's the former. Supposedly the DeepSeek models were trained with far fewer FlOpS than USA models. My guess is that they're catching up because they are copying OpenAI or Meta's work. Either legally or illegally.
Not everything that leads with a $ is money. People like to pretend like a stock portfolio is money. Same with futures and other derivatives. There's this magic that falls upon people when they see that little symbol. But the truth is $ != $
Going from this, I would understand if companies involved mostly on the software side of the AI hype would be impacted... but NVIDIA also makes the kind of hardware these AIs are trained and ran...
Going from this, I would understand if companies involved mostly on the software side of the AI hype would be impacted... but NVIDIA also makes the kind of hardware these AIs are trained and ran on. Shouldn't the fact that you can do more with existing hardware be good news for NVIDIA's customers and by extension their investors? Putting aside the "I am incapable of comprehending the scales involved" issue, why did that lead to a drop in the company's value? With how fast the AI hype train is going, I would suspect people would take that news as incentive to push for even more spread of LLM features, which would in turn increase GPU sales... right?
Because you can do even more with the same or better GPU vs the cheaper one. Maybe. I'm starting to wonder if this was all actuay an insider reaction to forknowledge of Trump's announcement about...
Because you can do even more with the same or better GPU vs the cheaper one. Maybe.
I'm starting to wonder if this was all actuay an insider reaction to forknowledge of Trump's announcement about semi-conductor tarriffs.
People so far have been operating under the premise that LLM performance, as in quality of answers, increases according to the scale of the hardware you run it on (this obviously has a limit that...
People so far have been operating under the premise that LLM performance, as in quality of answers, increases according to the scale of the hardware you run it on (this obviously has a limit that we're reaching rapidly, but so far I haven't seen the market care about that little detail). More GPUs == more smarter, or so the marketing department promises. By extension, if it turns out you can do more with less, I would if anything expect people to take it as an incentive to scale up their LLM use to leverage this unforeseen efficiency increase... to the point of getting even more hardware to take advantage of it where before the investment wouldn't have made sense for the expected improvement. Under that assumption, that would help NVIDIA, shouldn't it?
I agree that the software-focused companies would profit from this more directly, but I still don't get why that ends up being a negative for NVIDIA. For one, they aren't just a hardware...
I agree that the software-focused companies would profit from this more directly, but I still don't get why that ends up being a negative for NVIDIA. For one, they aren't just a hardware manufacturer in that regard (example: StarCoder2 which is an NVIDIA-backed project). Unless investors have no clue what the company they bought stocks in is actually doing, I'd assume they would factor that in regarding whether they think the rise in efficiency of LLMs is a problem or not. ...I just answered my own question, didn't I?
Also, while that's more speculative (pun intended) on my part, there's also the fact that the demand for generative AI isn't tied to a concretely quantifiable need. The desire a company might have for this product (and by extension the amount of hardware they'd need to run it/train models of their own) is fluid. The question executives looking into this technology are asking themselves is "what's the smartest model we can afford the hardware for?". In the case of LLMs, "intelligence" (as in how reliably useful and correct its answers are) roughly correlates with the size of the models, which in turn correlates with the amount of hardware required to train/run it. And while "intelligence" (inaccuracy of the term given LLMs are nonsapient algorithms aside) isn't really quantifiable, model size is with pretty large intervals from one size to the next, and that in turn maps pretty straightforwardly to the amount of hardware needed.
If the efficiency of the models themselves increase, "smarter" models that wouldn't have been worth to buy the GPUs for might suddenly become affordable to a company that would have otherwise bought fewer GPUs for the next best thing that they could afford. And that would drive up sales, which ought to be good news for NVIDIA and their investors. Does my reasoning hold up, or are the investors seeing something I don't?
Because till now it seemed like unless you are backed by absurd money there's no sense in even trying to compete with companies like Microsoft, Google or Meta, and if you want top of the line...
Because till now it seemed like unless you are backed by absurd money there's no sense in even trying to compete with companies like Microsoft, Google or Meta, and if you want top of the line capabilities, you have no other option but give them money and hope they don't change the product or the pricing model.
This to some degree democratizes AI research and use, so considerably more subjects will be able to afford something similar to what the giants are doing. But they're still going to need more hardware than they have now - right now many AI-adjacent have nothing, because even training open models is usually done on rented servers instead of in house.
I also don't see any indication that we're getting close to the point where throwing more hardware at the problem (together with research, of course) stops making the solution better. The big companies are going to keep doing it despite the change in efficiency.
At some point we're going to run out of room with current techniques. Technological innovation isn't one giant exponential. It's a series of linear or S-curve functions. The value in NVDA is...
At some point we're going to run out of room with current techniques. Technological innovation isn't one giant exponential. It's a series of linear or S-curve functions. The value in NVDA is speculative. People thought that NVDA's ability to sell would be limited only by TSMC's capacity. But if we go into another flat-line with AI progress that will no longer be the case. Future earnings are expected to go down because AI companies will find they have more GPUs than they need.
This is not reasonable, there’s plenty of talented AI and HPC people in china, and the methods they used are open and make sense. They just tried a different methodology, made solid engineering...
This is not reasonable, there’s plenty of talented AI and HPC people in china, and the methods they used are open and make sense. They just tried a different methodology, made solid engineering improvements, and got lucky. The only stealing angle here might be that they don’t have their own dataset and used other LLMs to help with this, but plenty of people do this.
This is not a reasonable assumption anymore; China meets or exceeds the US in a large number of research fields at this point. DeepSeek is a small company, and they've said they only hire...
This is not a reasonable assumption anymore; China meets or exceeds the US in a large number of research fields at this point. DeepSeek is a small company, and they've said they only hire graduates from Chinese universities. Most of this AI and deep learning research used to be open source until "AI safety" got really big and gave the major players an excuse to stop publishing their research during the boom.
Say you see NVDA is $80 right now. But, you think NVDA will be worth $100 in a year. This might be because you believe, in a year, GPU sales will double as AI can no longer be improved through...
Say you see NVDA is $80 right now. But, you think NVDA will be worth $100 in a year. This might be because you believe, in a year, GPU sales will double as AI can no longer be improved through more sophisticated training techniques, and simply must require more computational resources. Then, even though its current sales only value it at $80, if you buy in now then in a year you'll have made $20 (assuming you're right). You might be hardpressed to find another way to make 25% of your money in 365 days. But, your purchase at $80 increases demand for NVDA, so others will see this and value it more right now. Eventually, the stock price might become $100 today, even though that value is more representative of its value a year from now.
At a high-level, this is what led to NVDA having a huge valuation. Some might argue this led to an overvaluation, because its price stopped being based on a grounded projected value due to AI growth, but moreso hype.
With DeepSeek coming out, it turns out there is indeed a way to improve LLM performance not just without requiring more GPUs in the future, but without even needing the amount of GPUs people thought were necessary today. So, this projected future value turned out to be incorrect and overinflated, and the price dropped as a result.
The market cap is just the current market rate for the stock * the number of outstanding shares. All it means is that at the start of the day, people were willing to buy nvidia shares for 127...
The market cap is just the current market rate for the stock * the number of outstanding shares.
All it means is that at the start of the day, people were willing to buy nvidia shares for 127 dollars - and now, they’re only willing to pay 118 dollars for them.
Nvidia itself isn’t really harmed in any way. Hypothetically if they needed to raise capital by selling equity they’d get less but a movement of this level isn’t really changing anything.
The upshot to nvidia might be that easier training has more people doing it from scratch. Also, the inference time on DeepSeek is really heavy as it reasons about a lot of things as it goes.
The upshot to nvidia might be that easier training has more people doing it from scratch. Also, the inference time on DeepSeek is really heavy as it reasons about a lot of things as it goes.
I think the rationale for investors is that if a model like this can do what OpenAI can do at a fraction of the compute, it would lower the demand for costly, scarce NVIDIA GPUs. Of course the...
I think the rationale for investors is that if a model like this can do what OpenAI can do at a fraction of the compute, it would lower the demand for costly, scarce NVIDIA GPUs.
Of course the market cap of NVIDIA is not based in reality (as with many other companies historically), but that 589 billion number would be a decrease in investor future earning expectations/potential.
I'm no economist, but in my layman understanding it comes down to the fact that Nvidia's share price already had a concrete estimate of increased sales baked in based on previous information. A...
I'm no economist, but in my layman understanding it comes down to the fact that Nvidia's share price already had a concrete estimate of increased sales baked in based on previous information.
A more optimized product that can make do with a smaller increase in sales means that when you re-run the estimates based on the new information, investors think that Nvidia will sell less than they previously expected. The company will still sell more than they have in the past, but it's "less more" than previously expected.
As to why this doesn't obliterate Nvidia, is that while on paper it's a massive loss, none of this is "real money" that Nvidia actually had any meaningful access to use. It's just a measure of what the market thinks an individual shares are worth, and it's less now than it was, but it's not like Nvidia has to pay anyone 589B. It's just that for the people who own their shares, they'd get that much less trying to sell them now on aggragate based on the new estimates.
Speculation is built into the valuation, and that speculation can go both ways. When speculation is extreme hype, the valuation goes up beyond what the company itself is actually producing (not to...
Speculation is built into the valuation, and that speculation can go both ways. When speculation is extreme hype, the valuation goes up beyond what the company itself is actually producing (not to say Nvidia isn't super successful, but even if you're super successful you can be over-estimated). So this is just a re-adjustment to the speculation. As for why the speculation changed, the other comment covers that pretty well.
They're still over 100% more valuable than they were 1 year ago, or 2000% more valuable than 5 years ago. So why would they be in any kind of trouble because of this? Generally speaking and...
They're still over 100% more valuable than they were 1 year ago, or 2000% more valuable than 5 years ago. So why would they be in any kind of trouble because of this?
Generally speaking and simplifying a tad, a company's money supply isn't directly affected by how its stock behaves. And we're looking now at a very short period of time, which basically only day traders should be doing. The stock price might just as well be up tomorrow because the cheapening attracts new buyers.
That's where the comes in. I understand that we're looking at the perceived value of the company as decided by the evolution of the price that an abstract unit of the company's worth is being...
That's where the
I'm already completely unable to even comprehend the mind-shatteringly high value 589,000,000,000 USD represents
comes in. I understand that we're looking at the perceived value of the company as decided by the evolution of the price that an abstract unit of the company's worth is being traded for, rather than any objective evaluation of its assets and impact on the global economy (is there even a meaningful way to do that?). What I don't understand is how this perception adds up to such gargantuan numbers that it can swing through such extremes without it being an existential threat to the company, even one as big as NVIDIA.
1 billion (1,000,000,000) is big[citation needed]. 589 billions is a lot bigger, more than halfway to a trillion (1,000,000,000,000). Money is difficult enough to map at that scale in an understandable way that entire websites are dedicated to trying to explain what those numbers actually mean (here are twoexamples, although the second one's underlying message clearly doesn't stop there, but that's only tangentially related).
If the stock market is supposed to represent what (the investors think) NVIDIA is worth, how the hell did we get to the point where that value not only can swing to the tune of 500 billion dollars in the first place but it's not even indicative of any drastic consequences for the company? I'm already barely able to comprehend what this amount of money represents, but a context where this mind-boggingly high value poofing out of existence (even if it never really existed in the first place) isn't even a particularly notable event? That's where I'm unable to keep up.
"Investors worried about a related event led to NVIDIA's perceived value falling by 17%, which isn't that big of a deal to the company" is something I can understand (even if I find the specific reason it happened dubious, but I guess that's why I'm not a stock trader). "The 17% in question represent 589 billion dollars" is where my mind comes to a screeching halt.
I'm trying to distill down what you wrote for my own understanding and I get to "why was Nvidia worth so much before this week". Is that a fair understanding? If the large valuations are mind...
I'm trying to distill down what you wrote for my own understanding and I get to "why was Nvidia worth so much before this week". Is that a fair understanding? If the large valuations are mind boggling, I can only say that we will likely see that more often and at even larger magnitudes in the long run as we globalize and countries flock towards a handful of suppliers in certain industries.
For Nvidia specifically, well they're pretty much the only player in town selling shovels to this gold rush of AI. The demand is so hot that there's only a handful of countries able to even purchase them in real bulk. I'd even argue there's only two and one of them was kneecapped by the other. So you have this incredible equipment that everyone in the world would buy if they could, but you sell them faster than you can make them such that if you sold to just two countries, you'd already be over capacity. So of course Nvidia would be mega valued. If only I foresaw that, sigh.
As for why the drop is both large yet unconcerning: Nvidia wasn't cash constrained before the AI spike and they aren't cash constrained now. The company's survival is solely predicated on whether or not they can continue to stay competitive in their product offerings lest a competitor takes market share. To stay competitive, they need to design and architect the next generation, but at some point the funding stops being the bottleneck.
Pretty much. The part I struggle to comprehend is how ~500 billion dollars can possibly be "a relatively small portion of what investors think this company is worth" (17%) and not "more than...
"why was Nvidia worth so much before this week". Is that a fair understanding?
Pretty much. The part I struggle to comprehend is how ~500 billion dollars can possibly be "a relatively small portion of what investors think this company is worth" (17%) and not "more than anyone could possibly think the company is worth by several orders of magnitude". Speculation is one thing and I get logic takes a backseat in that situation, but when you get to the same scale as one trillion dollars, we're talking about the kind of money that could fund world-changing projects, as in the "we could fund a manned mission to Mars with that amount" kind. Am I supposed to understand that not only investors getting spooked can result in a company's worth being lowered by an amount one would use to estimate how to achieve the events history books will use as a civilizational epoch, but that company was already valued so high they can just take it in stride? That question is mostly rhetorical, but I'm astonished nevertheless, to the point where I don't understand why the focus of the article seems to be "why did DeepSeek spook the investors" and not "how did we get to the point where the perceived value of companies and swings thereof can be measured in missions to Mars?". The fact this is happening over glorified text completion engines is the cherry on the cake, but it's not like it would be the first time the market got into a frenzy over something absurd (not that I think LLMs should be dismissed as being as mundane as the tulips trade, but they're definitely not at the "as important as future space travel milestones" level in my book).
The stock market is generally confusing, at least to me. People agree to pay a price for a share of stock. The share price is sort of related to the success of the company. But not exactly. And...
The stock market is generally confusing, at least to me.
People agree to pay a price for a share of stock. The share price is sort of related to the success of the company. But not exactly. And sometimes the price is completely unrelated to the success of the company because there is speculation about future value. The total market value of outstanding shares is the market cap of the company. Sometimes market cap is completely out of control because of speculation. This includes Tesla and Nvidia.
When stocks give dividends, the value of a share of stock makes more sense to me. But NVDA currently pays $0.04 a year and this amount didn't vary wildly during the year while the price zoomed up and then dropped today.
I guess each stock share is sort of ownership of the company. But unless I have a controlling interest, I can't do much with that. I can't go into Nvidia with 100 shares and take a desk chair home or something.
Investors look at the future price as well. So an investor is trying to maximize the difference between what they buy in at, what they can sell at, plus the value of the dividends, share buy...
Investors look at the future price as well. So an investor is trying to maximize the difference between what they buy in at, what they can sell at, plus the value of the dividends, share buy backs, etc in that time period. If I expect NVidia to increase from $50 a share to $60 a share in a year, and I bought 10 shares, then I have enough to buy a desk chair ($60-$50) * 10 shares = $100.
Analysts are able to predict share price by using a lot of projections. So suppose that AI demand will mean that GPU demand will increase by 7% in the next year. That means 12% more revenue which means 11% more profit, which means a stock value increase of 8% (but much more complex obviously). Deep Seek suggest that GPU demand will not be 7% but 3% for example since the algorithm is more efficient.
Nvidia was certainly due for a correction, so I don't see this as a major shock. However, I am surprised it took the investing world this long to catch on. Those who follow the field have been...
Nvidia was certainly due for a correction, so I don't see this as a major shock. However, I am surprised it took the investing world this long to catch on. Those who follow the field have been talking about the quality of Chinese models for a while now.
Karpathy spoke about DeepSeek specifically in December, and how well they're doing with far-less powerful hardware. Ali's Qwen has also been pushing out incredible models that beat out LLaMA 3. They even released a brand new vision model just a couple hours ago with agentic capabilities.
Really, the /r/LocalLLaMA community has been talking about this stuff for months, which is an eternity in AI time. It seems that people have only really been paying attention to OpenAI and Nvidia until this point, but there are absolutely more players in this game.
I can't remember where I read it, about a week ago, that this is China's AI playbook -- essentially, let the Western companies spend billions of dollars coming up with the next generation of...
I can't remember where I read it, about a week ago, that this is China's AI playbook -- essentially, let the Western companies spend billions of dollars coming up with the next generation of models, and then find a way to replicate them and open source them, thereby undercutting the entire "closed source" market.
Thank you China? However I expect these models to be suspiciously ignorant of what happened at Tienanmen Square. Edit: I chatted with DeepSeek R1 about Tienanmen. Attempt #1 and #2
Thank you China?
However I expect these models to be suspiciously ignorant of what happened at Tienanmen Square.
Edit:
I chatted with DeepSeek R1 about Tienanmen. Attempt #1 and #2
Yeah, I saw some side-by-side pics of prompts for Tienanmen Square and Kent State. It gave an answer for the latter but not the former. Wonder if you could prompt engineer it to give you a real...
Yeah, I saw some side-by-side pics of prompts for Tienanmen Square and Kent State. It gave an answer for the latter but not the former.
Wonder if you could prompt engineer it to give you a real response?
I downloaded the 14b model and ran it locally. This is what it answered when I asked about Taiwan then Tiananmen. https://imgur.com/a/9RMvnu6 Edit: I initially accidentally uploaded the same image...
I downloaded the 14b model and ran it locally. This is what it answered when I asked about Taiwan then Tiananmen.
Well, I would assume the model know whatever you trained it on. If DeepSeek is shipped with a profile that didn't include those things, it won't have the knowledge. But if add to its training...
Well, I would assume the model know whatever you trained it on. If DeepSeek is shipped with a profile that didn't include those things, it won't have the knowledge. But if add to its training those things, presumably, it can be corrected.
I found this to be a good technical overview of what's happening and risks to Nvidia's business: https://youtubetranscriptoptimizer.com/blog/05_the_short_case_for_nvda This type of...
I found this to be a good technical overview of what's happening and risks to Nvidia's business:
This type of hyperventilating about $600B value drop or whatever just makes me roll my eyes. There are gads of people trigger trading in the market to try to make a quick buck. Nvidia has had bad days before and they will have bad days in the future. They also have the funds and the brains to adjust their business, if needed. Those same people who caused the $600B drop are frothing at the mouth to buy Nvidia stock "on sale" now that it's down a bit. The media should stop turning everything into a breaking! news! emergency!
In my experience, successful public companies tend to treat their employees consistently pretty decently. Why? (1) They have deep pockets and don't want to be sued for them. (2) If they depend on...
In my experience, successful public companies tend to treat their employees consistently pretty decently. Why? (1) They have deep pockets and don't want to be sued for them. (2) If they depend on human capital, they try to retain it. (3) They're usually big enough to get benefits at an okay price.
The flip side is that they have finance pressure and so they can't afford to stare through difficult times - they have to take layoffs and cost cutting measures. Otherwise, they'll get hit with an activist investor if they don't handle those pressures quickly.
I was on the board for a long time of a labor organization, and where we saw cases of wage theft and safety issues, it was almost always with a mom and pop organization or a fun shell game of holding companies.
I've also worked on the inside of a very large family held conglomerate, and hoo-boy. That was a shit show and the employees really got the short end. I'm stuck under NDA and other things there though.
A 589 billions USD loss (or whatever that means in the context of the stock market because it sure as hell doesn't seem to be anchored to reality)? Over, what, a product release from another company that the market perceived as a threat to... the company that provides the hardware one would want to run this very same product on?
What the fuck?
This makes absolutely no sense to me on several different levels. I'm at a loss for words here, and given what I'm usually like, that's saying a lot, pun intended. I'm already completely unable to even comprehend the mind-shatteringly high value 589,000,000,000 USD represents, let alone how a company could "lose" that amount without instantly ceasing to exist, why this specific event led to NVIDIA suffering this badly from it, and the article has not provided an answer to any of it (or at least that last one) that makes sense to me. Can someone with a better grasp on economics explain this? Because I'm stumped.
Chinese companies are restricted in what GPUs they can buy from NVidia. If China produces major players in AI it means one of two things:
In this case it's the former. Supposedly the DeepSeek models were trained with far fewer FlOpS than USA models. My guess is that they're catching up because they are copying OpenAI or Meta's work. Either legally or illegally.
Not everything that leads with a $ is money. People like to pretend like a stock portfolio is money. Same with futures and other derivatives. There's this magic that falls upon people when they see that little symbol. But the truth is $ != $
Going from this, I would understand if companies involved mostly on the software side of the AI hype would be impacted... but NVIDIA also makes the kind of hardware these AIs are trained and ran on. Shouldn't the fact that you can do more with existing hardware be good news for NVIDIA's customers and by extension their investors? Putting aside the "I am incapable of comprehending the scales involved" issue, why did that lead to a drop in the company's value? With how fast the AI hype train is going, I would suspect people would take that news as incentive to push for even more spread of LLM features, which would in turn increase GPU sales... right?
If you can do more with less GPUs, then why do you need to buy more?
Because you can do even more with the same or better GPU vs the cheaper one. Maybe.
I'm starting to wonder if this was all actuay an insider reaction to forknowledge of Trump's announcement about semi-conductor tarriffs.
People so far have been operating under the premise that LLM performance, as in quality of answers, increases according to the scale of the hardware you run it on (this obviously has a limit that we're reaching rapidly, but so far I haven't seen the market care about that little detail). More GPUs == more smarter, or so the marketing department promises. By extension, if it turns out you can do more with less, I would if anything expect people to take it as an incentive to scale up their LLM use to leverage this unforeseen efficiency increase... to the point of getting even more hardware to take advantage of it where before the investment wouldn't have made sense for the expected improvement. Under that assumption, that would help NVIDIA, shouldn't it?
No that helps the companies producing AI.
I agree that the software-focused companies would profit from this more directly, but I still don't get why that ends up being a negative for NVIDIA. For one, they aren't just a hardware manufacturer in that regard (example: StarCoder2 which is an NVIDIA-backed project). Unless investors have no clue what the company they bought stocks in is actually doing, I'd assume they would factor that in regarding whether they think the rise in efficiency of LLMs is a problem or not.
...I just answered my own question, didn't I?Also, while that's more speculative (pun intended) on my part, there's also the fact that the demand for generative AI isn't tied to a concretely quantifiable need. The desire a company might have for this product (and by extension the amount of hardware they'd need to run it/train models of their own) is fluid. The question executives looking into this technology are asking themselves is "what's the smartest model we can afford the hardware for?". In the case of LLMs, "intelligence" (as in how reliably useful and correct its answers are) roughly correlates with the size of the models, which in turn correlates with the amount of hardware required to train/run it. And while "intelligence" (inaccuracy of the term given LLMs are nonsapient algorithms aside) isn't really quantifiable, model size is with pretty large intervals from one size to the next, and that in turn maps pretty straightforwardly to the amount of hardware needed.
If the efficiency of the models themselves increase, "smarter" models that wouldn't have been worth to buy the GPUs for might suddenly become affordable to a company that would have otherwise bought fewer GPUs for the next best thing that they could afford. And that would drive up sales, which ought to be good news for NVIDIA and their investors. Does my reasoning hold up, or are the investors seeing something I don't?
Because till now it seemed like unless you are backed by absurd money there's no sense in even trying to compete with companies like Microsoft, Google or Meta, and if you want top of the line capabilities, you have no other option but give them money and hope they don't change the product or the pricing model.
This to some degree democratizes AI research and use, so considerably more subjects will be able to afford something similar to what the giants are doing. But they're still going to need more hardware than they have now - right now many AI-adjacent have nothing, because even training open models is usually done on rented servers instead of in house.
I also don't see any indication that we're getting close to the point where throwing more hardware at the problem (together with research, of course) stops making the solution better. The big companies are going to keep doing it despite the change in efficiency.
At some point we're going to run out of room with current techniques. Technological innovation isn't one giant exponential. It's a series of linear or S-curve functions. The value in NVDA is speculative. People thought that NVDA's ability to sell would be limited only by TSMC's capacity. But if we go into another flat-line with AI progress that will no longer be the case. Future earnings are expected to go down because AI companies will find they have more GPUs than they need.
It seems reasonably likely that they have either hired talent from major US AI companies or performed some corporate espionage.
This is not reasonable, there’s plenty of talented AI and HPC people in china, and the methods they used are open and make sense. They just tried a different methodology, made solid engineering improvements, and got lucky. The only stealing angle here might be that they don’t have their own dataset and used other LLMs to help with this, but plenty of people do this.
This is not a reasonable assumption anymore; China meets or exceeds the US in a large number of research fields at this point. DeepSeek is a small company, and they've said they only hire graduates from Chinese universities. Most of this AI and deep learning research used to be open source until "AI safety" got really big and gave the major players an excuse to stop publishing their research during the boom.
Anyone can do this - most LLMs using model distillation. If it were a silver bullet, everyone would have models as good as OpenAI.
If I just did that math right, that one day loss is $1700 for every man, woman, and child in the US.
Say you see NVDA is $80 right now. But, you think NVDA will be worth $100 in a year. This might be because you believe, in a year, GPU sales will double as AI can no longer be improved through more sophisticated training techniques, and simply must require more computational resources. Then, even though its current sales only value it at $80, if you buy in now then in a year you'll have made $20 (assuming you're right). You might be hardpressed to find another way to make 25% of your money in 365 days. But, your purchase at $80 increases demand for NVDA, so others will see this and value it more right now. Eventually, the stock price might become $100 today, even though that value is more representative of its value a year from now.
At a high-level, this is what led to NVDA having a huge valuation. Some might argue this led to an overvaluation, because its price stopped being based on a grounded projected value due to AI growth, but moreso hype.
With DeepSeek coming out, it turns out there is indeed a way to improve LLM performance not just without requiring more GPUs in the future, but without even needing the amount of GPUs people thought were necessary today. So, this projected future value turned out to be incorrect and overinflated, and the price dropped as a result.
The market cap is just the current market rate for the stock * the number of outstanding shares.
All it means is that at the start of the day, people were willing to buy nvidia shares for 127 dollars - and now, they’re only willing to pay 118 dollars for them.
Nvidia itself isn’t really harmed in any way. Hypothetically if they needed to raise capital by selling equity they’d get less but a movement of this level isn’t really changing anything.
The upshot to nvidia might be that easier training has more people doing it from scratch. Also, the inference time on DeepSeek is really heavy as it reasons about a lot of things as it goes.
I think the rationale for investors is that if a model like this can do what OpenAI can do at a fraction of the compute, it would lower the demand for costly, scarce NVIDIA GPUs.
Of course the market cap of NVIDIA is not based in reality (as with many other companies historically), but that 589 billion number would be a decrease in investor future earning expectations/potential.
I'm no economist, but in my layman understanding it comes down to the fact that Nvidia's share price already had a concrete estimate of increased sales baked in based on previous information.
A more optimized product that can make do with a smaller increase in sales means that when you re-run the estimates based on the new information, investors think that Nvidia will sell less than they previously expected. The company will still sell more than they have in the past, but it's "less more" than previously expected.
As to why this doesn't obliterate Nvidia, is that while on paper it's a massive loss, none of this is "real money" that Nvidia actually had any meaningful access to use. It's just a measure of what the market thinks an individual shares are worth, and it's less now than it was, but it's not like Nvidia has to pay anyone 589B. It's just that for the people who own their shares, they'd get that much less trying to sell them now on aggragate based on the new estimates.
Speculation is built into the valuation, and that speculation can go both ways. When speculation is extreme hype, the valuation goes up beyond what the company itself is actually producing (not to say Nvidia isn't super successful, but even if you're super successful you can be over-estimated). So this is just a re-adjustment to the speculation. As for why the speculation changed, the other comment covers that pretty well.
They're still over 100% more valuable than they were 1 year ago, or 2000% more valuable than 5 years ago. So why would they be in any kind of trouble because of this?
Generally speaking and simplifying a tad, a company's money supply isn't directly affected by how its stock behaves. And we're looking now at a very short period of time, which basically only day traders should be doing. The stock price might just as well be up tomorrow because the cheapening attracts new buyers.
That's where the
comes in. I understand that we're looking at the perceived value of the company as decided by the evolution of the price that an abstract unit of the company's worth is being traded for, rather than any objective evaluation of its assets and impact on the global economy (is there even a meaningful way to do that?). What I don't understand is how this perception adds up to such gargantuan numbers that it can swing through such extremes without it being an existential threat to the company, even one as big as NVIDIA.
1 billion (1,000,000,000) is big[citation needed]. 589 billions is a lot bigger, more than halfway to a trillion (1,000,000,000,000). Money is difficult enough to map at that scale in an understandable way that entire websites are dedicated to trying to explain what those numbers actually mean (here are two examples, although the second one's underlying message clearly doesn't stop there, but that's only tangentially related).
If the stock market is supposed to represent what (the investors think) NVIDIA is worth, how the hell did we get to the point where that value not only can swing to the tune of 500 billion dollars in the first place but it's not even indicative of any drastic consequences for the company? I'm already barely able to comprehend what this amount of money represents, but a context where this mind-boggingly high value poofing out of existence (even if it never really existed in the first place) isn't even a particularly notable event? That's where I'm unable to keep up.
"Investors worried about a related event led to NVIDIA's perceived value falling by 17%, which isn't that big of a deal to the company" is something I can understand (even if I find the specific reason it happened dubious, but I guess that's why I'm not a stock trader). "The 17% in question represent 589 billion dollars" is where my mind comes to a screeching halt.
I'm trying to distill down what you wrote for my own understanding and I get to "why was Nvidia worth so much before this week". Is that a fair understanding? If the large valuations are mind boggling, I can only say that we will likely see that more often and at even larger magnitudes in the long run as we globalize and countries flock towards a handful of suppliers in certain industries.
For Nvidia specifically, well they're pretty much the only player in town selling shovels to this gold rush of AI. The demand is so hot that there's only a handful of countries able to even purchase them in real bulk. I'd even argue there's only two and one of them was kneecapped by the other. So you have this incredible equipment that everyone in the world would buy if they could, but you sell them faster than you can make them such that if you sold to just two countries, you'd already be over capacity. So of course Nvidia would be mega valued. If only I foresaw that, sigh.
As for why the drop is both large yet unconcerning: Nvidia wasn't cash constrained before the AI spike and they aren't cash constrained now. The company's survival is solely predicated on whether or not they can continue to stay competitive in their product offerings lest a competitor takes market share. To stay competitive, they need to design and architect the next generation, but at some point the funding stops being the bottleneck.
Pretty much. The part I struggle to comprehend is how ~500 billion dollars can possibly be "a relatively small portion of what investors think this company is worth" (17%) and not "more than anyone could possibly think the company is worth by several orders of magnitude". Speculation is one thing and I get logic takes a backseat in that situation, but when you get to the same scale as one trillion dollars, we're talking about the kind of money that could fund world-changing projects, as in the "we could fund a manned mission to Mars with that amount" kind. Am I supposed to understand that not only investors getting spooked can result in a company's worth being lowered by an amount one would use to estimate how to achieve the events history books will use as a civilizational epoch, but that company was already valued so high they can just take it in stride? That question is mostly rhetorical, but I'm astonished nevertheless, to the point where I don't understand why the focus of the article seems to be "why did DeepSeek spook the investors" and not "how did we get to the point where the perceived value of companies and swings thereof can be measured in missions to Mars?". The fact this is happening over glorified text completion engines is the cherry on the cake, but it's not like it would be the first time the market got into a frenzy over something absurd (not that I think LLMs should be dismissed as being as mundane as the tulips trade, but they're definitely not at the "as important as future space travel milestones" level in my book).
The stock market is generally confusing, at least to me.
People agree to pay a price for a share of stock. The share price is sort of related to the success of the company. But not exactly. And sometimes the price is completely unrelated to the success of the company because there is speculation about future value. The total market value of outstanding shares is the market cap of the company. Sometimes market cap is completely out of control because of speculation. This includes Tesla and Nvidia.
When stocks give dividends, the value of a share of stock makes more sense to me. But NVDA currently pays $0.04 a year and this amount didn't vary wildly during the year while the price zoomed up and then dropped today.
I guess each stock share is sort of ownership of the company. But unless I have a controlling interest, I can't do much with that. I can't go into Nvidia with 100 shares and take a desk chair home or something.
Investors look at the future price as well. So an investor is trying to maximize the difference between what they buy in at, what they can sell at, plus the value of the dividends, share buy backs, etc in that time period. If I expect NVidia to increase from $50 a share to $60 a share in a year, and I bought 10 shares, then I have enough to buy a desk chair ($60-$50) * 10 shares = $100.
Analysts are able to predict share price by using a lot of projections. So suppose that AI demand will mean that GPU demand will increase by 7% in the next year. That means 12% more revenue which means 11% more profit, which means a stock value increase of 8% (but much more complex obviously). Deep Seek suggest that GPU demand will not be 7% but 3% for example since the algorithm is more efficient.
Nvidia was certainly due for a correction, so I don't see this as a major shock. However, I am surprised it took the investing world this long to catch on. Those who follow the field have been talking about the quality of Chinese models for a while now.
Karpathy spoke about DeepSeek specifically in December, and how well they're doing with far-less powerful hardware. Ali's Qwen has also been pushing out incredible models that beat out LLaMA 3. They even released a brand new vision model just a couple hours ago with agentic capabilities.
Really, the /r/LocalLLaMA community has been talking about this stuff for months, which is an eternity in AI time. It seems that people have only really been paying attention to OpenAI and Nvidia until this point, but there are absolutely more players in this game.
I can't remember where I read it, about a week ago, that this is China's AI playbook -- essentially, let the Western companies spend billions of dollars coming up with the next generation of models, and then find a way to replicate them and open source them, thereby undercutting the entire "closed source" market.
Thank you China?
However I expect these models to be suspiciously ignorant of what happened at Tienanmen Square.
Edit:
I chatted with DeepSeek R1 about Tienanmen. Attempt #1 and #2
Yeah, I saw some side-by-side pics of prompts for Tienanmen Square and Kent State. It gave an answer for the latter but not the former.
Wonder if you could prompt engineer it to give you a real response?
From what I understand, the open source version you can download and run locally has full knowledge of these topics.
I downloaded the 14b model and ran it locally. This is what it answered when I asked about Taiwan then Tiananmen.
https://imgur.com/a/9RMvnu6
Edit: I initially accidentally uploaded the same image twice. I have replaced the duplicate with the correct image.
Well, I would assume the model know whatever you trained it on. If DeepSeek is shipped with a profile that didn't include those things, it won't have the knowledge. But if add to its training those things, presumably, it can be corrected.
It's very suspisciously ignorant about a lot of things. Ask it about the King's Roman Group.
I think it hit Stratechery which is much more widely read on the finance side. Once it hit there, it got a lot more market reaction.
I found this to be a good technical overview of what's happening and risks to Nvidia's business:
https://youtubetranscriptoptimizer.com/blog/05_the_short_case_for_nvda
This type of hyperventilating about $600B value drop or whatever just makes me roll my eyes. There are gads of people trigger trading in the market to try to make a quick buck. Nvidia has had bad days before and they will have bad days in the future. They also have the funds and the brains to adjust their business, if needed. Those same people who caused the $600B drop are frothing at the mouth to buy Nvidia stock "on sale" now that it's down a bit. The media should stop turning everything into a breaking! news! emergency!
In my experience, successful public companies tend to treat their employees consistently pretty decently. Why? (1) They have deep pockets and don't want to be sued for them. (2) If they depend on human capital, they try to retain it. (3) They're usually big enough to get benefits at an okay price.
The flip side is that they have finance pressure and so they can't afford to stare through difficult times - they have to take layoffs and cost cutting measures. Otherwise, they'll get hit with an activist investor if they don't handle those pressures quickly.
I was on the board for a long time of a labor organization, and where we saw cases of wage theft and safety issues, it was almost always with a mom and pop organization or a fun shell game of holding companies.
I've also worked on the inside of a very large family held conglomerate, and hoo-boy. That was a shit show and the employees really got the short end. I'm stuck under NDA and other things there though.
Mirror:
https://www.bnnbloomberg.ca/business/technology/2025/01/27/nvidias-465-billion-deepseek-rout-is-largest-in-market-history/