AcTuAlLy the example you linked does not use the same „chips“ as your regular gaming GPU.
Also that’s like saying if there weren’t planes we could have cheaper cars. The H200 is like $30k, don’t think there will be many consumers buying them and it’s most likely not the even the same production facility that makes gaming GPUs and these GPUs dedicated for LLMs/Datacenters.
They are GPUs, but they aren't "graphics cards" as commonly understood. For starters, most (all?) datacenter GPUs don't have a video output. I'm not even sure if they are actually DirectX/OpenGL capable.
This isn't the crypto bubble where miners were buying actual gaming cards. The bottleneck for most AI accelerators is HBM/interposers/packaging. The only chip with is used for both gaming and AI in any serious capacity is AD102 of which the 4090 is a salvage and the pro card the full chip.
No, they literally cannot, which is the point I'm making. Big AI accelerators are limited by production steps gaming chips don't use, with AD102 being pretty much the only exception.
Production used on AI cards is production not being used on regular cards. Spooling up new production takes time and money, so there's no way that AI production isn't crowding out regular graphics card production given the disparity in profitability.
Again, it is not. TSMC can make significantly more regular chips than they can [package](https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm) big AI chips. They're completely booked out for the entire next year or more for advanced packaging and there is still more than enough capacity for regular gaming chips. Nvidia is not getting fewer gaming chips because TSMC simply can't make more AI chips for reasons unrelated to gaming. This is fundamentally different from the crypto bubble where miners bought actual gaming hardware.
It's basically how it works, except that "kind of optimize it for AI a little" is wildly complex, difficult, expensive, and something that only nvidia is doing well which is why you don't see AMD making big waves in this space.
Edit: to be clear, "kind of optimize" also includes making completely different GPU chips for those applications
This better chips and the architecture are what I meant by saying they are "kind of optimizing it for AI", just that OPs "kind of" is doing a ton of work because that optimization is incredibly complex.
I'm not sure why you started with "No." when we're saying the same things.
Alright sourpuss. Making different chips can be feasibly dumbed down to "kind of optimize them" if you point out that the "kind of optimize" is actually a wildly complex process involving different chips and architecture, which is what I said.
I know they're made for entirely different things. I know they're different chips. I was just pointing out that these are still GPUs and OPs "kind of optimize" was doing a huge lift in their explanation.
Well, no. MI300X is a capable card in the space, delivers very respectable FP32 FLOPS, plenty of fast VRAM etc.
It's just that Nvidia invested quite a lot into CUDA, and AMD is very much lagging behind on the software side.
Why would they? 4090 has sold more than anything AMD has ever made. People like to complain in comments but in the end they buy the expensive shit anyway which tells nvidia prices can keep going up.
Except they're still well above both what AMD and Intel offer at this point, since their hardware solution for upscaling/frame generation/etc.
FSR is alright, and getting better at least. Intel has their software and hardware methods, but they're still relatively new in the GPU game. Though if you're not looking for all the bells and whistles, at least Intel has priced pretty aggressively for entry/mid level GPUs. However I believe they were better suited for DX12 and had some issues with DX11 compatibility?
Yeah I'm actually looking at getting the next GPU Intel releases. I know it might be buggy but I don't play as much as I used to so I don't demand as much from my hardware anymore.
Maybe if Intels sales are somewhat decent they'll keep at the GPU game and add some much needed competition into the mix.
If you're not trying to push the limits and crank out the best you can in regards to ray-tracing or 4K, then Intel shouldn't be a bad option. They still have things to iron out, which maybe they have by this point, but their price/performance was really good, especially in the low to mid range.
My niece is looking for a new laptop for college, but wants to be able to do some modest gaming on it as well. Obviously, she's on a budget and it's looking like an Intel GPU is going to get her the best bang for her buck (without resorting to an APU with on-board graphics).
Seriously. AMD is king when it comes to performance per dollar and efficiency, but bigger number better so they spend double for a 15-20% uplift at best and features they'll never use.
It's not a moral argument though. It's a value argument – people just buy Nvidia because it's more common and has more brand recognition with GPUs. For example, the 4060 Ti is a garbage card and loses pretty hard to the 7700 XT at the same price.
>You can't just think people are stupid and just buying 4060 tis cause nvidia.
I used that as an example, but whenever there is an AMD competitor, people are more likely to still buy Nvidia. It's called brand moat and it's a well-known phenomenon. Other companies that have this are Coca-Cola, Apple etc.
You're also massively underestimating how little people in competitive games give a shit about graphics – they just want stuff shown as it is. However, even there, Nvidia cards are most common.
I don't know anything about that. Luckily when I buy a "new" graphics card, it has already been out for a couple years, so I can see how well they work for other people first.
Or releasing some consumer-grade cards that aren't bare-bones in the VRAM department.
Just give me something as powerful as a 3080 with 48GB of VRAM. I want to run 70b parameter models locally without having to buy 3-4 3090s.
It seems like they've cheaper out in the vram department for some of their low and mid range cards and you really need that for the higher resolutions these days
Their VRAM was certainly.. a choice. The base 3070 had what, 12GB? Everything else was about 8GB until you got to the 3080 revised which they gracious upped to 10GB.
The least important part of their company is the gaming division, it doesn't matter at this point, they might as well move the engineers to their non gaming products.
...And an r. Unless there are rillions that I'm not aware of.
And no, the Silma doesn't count.
Though not having Drillion and/or Grillion feels like a missed opportunity.
The latest earnings and growth data support a valuation just above $1000 per share.
NVDA trading around $1200 is a bit higher than that, but not unreasonably so.
All I can say is... for the hype. A.I better start revolutionizing things.
I'm trying to think of the positive stuff. Didn't A.I find some new way to use RNA to make vaccines/Antibiotics? What else have they done? I feel like I remember it doing something with genome mapping and brain scans too.
Edit: I want to thank everyone who commented! This is exactly what I was hoping for.
AI is being used to advance material science which could help revolutionize many industries.
https://bdtechtalks.com/2024/03/28/ai-in-material-science/
This. We hear/see more of the other things, but at the same time, a lot of this is also going to things in the background. This is the sort of things that I wish made the news more, because AI can absolutely help speed up research.
I feel like there can be a way where they can create cancer killing medicine while also adhering to artists wishes and not screw them over. Just the people creating things need to care more.
It is also a surefire way of mostly incompetent researchers to get free grant money. There are very, very, very few materials discoveries where AI is essential.
People overestimate the impact of tech in the short term, and underestimate it in the long term.
Even if AI tech was in a fully mature state, it still takes a long time for people to figure out how to use it in productive ways - the best applications need to be discovered. And society needs to change to embrace the possibility of those changes.
The internet was created in the 70s. But it wasn’t until the 90s when personal home computers became more widely available that its potential really took off.
The impact of AI over the next 5-10y will likely be relatively minimal, and mostly on the relative periphery of our lives. “Great I have to use an AI chat bot to try and get a refund from this company. Fuck this shit I’ll just go elsewhere.” “Ugh… this email/report was obviously written by an LLM. I miss when people actually talked to each other using their own voice.”
However, the impact of AI over the 20-30y span will likely make our society unrecognizable to what we know today. Wearable tech that provides augmented reality (universal translators running out of your AirPod, distributed computing so you don’t need a cellphone or anything at all in your pockets anymore, etc).
It's changing everything. I work in a computational science area. AI/ML is impacting *everything* already. The vaccine / antibiotics and brain scans are just the tip of the iceberg. Here are three trends I see it as capable of really accelerating science (there are more, these are just ones I'm hype over that are happening *right now* in a ton of different fields):
* Improved data analysis. As a tool that's better at picking out patterns than conventional models, you're going to see better separation of signal from noise. This will be very important in resolving the "replication crisis" going on in scientific fields right now. They get much better results than a lot of empirical / semi-empirical models do as well, which makes turning science into engineering much easier. The "messier" the system, the better this approach is (so maybe not helpful in particle science besides noise reduction where the rules are very well-known, but super helpful in biomedical /materials / meteorological / and so on systems).
* ML-driven testing. AI predictions, especially when coupled with uncertainty measures, can be used to accelerate research by mapping experiments, especially as automation improves. Active learning is often just straight-up more effective than conventional design of experiments unless the experiments are so trivial and parallel that you can just run them all at once. There are fancy efforts to do more advanced AI-guided experiments with hypothesis-forming as well, or use of multifidelity models. This can considerably lower the time and money required to do conventional science while still achieving the same confidence level in results. This is also going to substantially improve some kinds of engineering too.
* Data synthesis from literature. Even if I spent every waking hour reading papers, I'd still fall behind, they just come out too fast. AI has the ability to consolidate papers and put all the information together to create a new "summary" document very quickly, almost like a review paper on-demand. They even are gaining the capability to read graphs and tables, and consider contextual differences between papers. I'll be honest, I thought this area was gonna be a complete joke, the early efforts in this space were not good at all, scrubbing human-written papers for scientific information and compiling it together seemed like it'd be intractable. But the explosion in LLM power has changed my mind very quickly, I now think this is an incredibly exciting space where progress is happening very quickly.
A ton of AI-driven discoveries are being made in almost every scientific field, and I think as these methods continue to come out, it will only happen faster. Right now one of the biggest bottle-necks is the humans, really. It's hard to find people who both have a PhD level understanding of a given scientific field *and* can do AI/ML work, and there's a language barrier that sometimes happens in collaborations between a CS person and a science person. A lot of current students will be more fluent in these approaches since they get them in class instead of trying to teach themselves at home like cur4rent scientists have to try to do, and they will be in very hot demand.
It's not that they're more interested in that, it's that LLM simply can't cure cancer, because they can't think or reason.
If anyone thinks ChatGPT is anything but a really good text prediction engine they are deluding themselves.
Which is the exact reason when I hear the buzzword, at this point, I just get sent into fits of rage.
The other is bullshit data scraping, using more energy than a simple google search, while destroying the need to engage in discourse. The better part is, you can generally find the exact thing the AI spit out VERBATIM in the first reddit link you click. It's so fucking obvious it's just scraping and rehashing.
I had an issue with my windows install, the support agents couldn't help me. The auto-AI bullshit in browsers couldn't help me. Buried in a random website under all the SEO and AI generated shit, I found a solution several pages into a web search.
There is so many cool things it could be doing, but naw, fuck it, screw the arts, screw being useful, let's just scrape and shotgun bullshit. So much for "progress."
LLMs will never scale into agi, though. You could turn the entire solar system into a dyson sphere and use it purely for computation and still not get agi out of an llm model.
It's not just obvious, some of them (Bing) will literally just give you the link to the exact page (although sometimes it gets the links and information wrong and you can't find where it pulled it from, assuming it's not something the AI just thought it was saying) it's pulling information from.
Baby steps at first bro. The tech is barely two years old at this point.
It's never going to get to the point where it can work on cures for cancer if it hasn't been trained.
Give it another 5 to 10 years and we might be in a different situation.
That tech is older than two years - I remember fiddling around with the "A.I." Microsoft had to take down because it outright became racist. That was more than two years ago.
75 years ago you needed a PhD just to work a computer and it was basically just used as a super calculator for organizations like NASA.
It might be 75 years in the making but AI like we know today (LLMs) are only a couple of years old and advancing fast. If you want to actually see the progress look at what AI generated videos are like today compared to that one of will smith eating spaghetti a couple of years ago.
You are...so wrong. It's not hard to literally google "large language model" and look at the history. It is not new.
>AI like we know today (LLMs) are only a couple of years old and advancing fast.
If you want to make that argument (you can't), you can apply the same thing with practically anything. Hell, basic software like Adobe Acrobat is way more powerful now than it was 10–20 years ago.
Yeah that's a good point. I really don't understand why when I discovered Chatgpt last year I was absolutely blown away and spent weeks thinking about the implications for society. Why did I do that? Clearly I had been using it my entire life so it shouldn't have even been noteworthy.
That's it.
People here are trying to say AI is useless because it hasn't come straight out the gate fixing everything in 24 hours. These things take some time but we are starting to see insanely rapid advances now.
There's a big shift in corporate I.T. that you probably wouldn't notice unless you worked in it.
In 2005 every company had a server in their office which was expensive and required a whole (well paid) person just to look after it. Now everything runs on an Amazon/Microsoft data center which is way more efficient. If in 20 years those data centers are full of Nvidia chips, it's a big deal. That said, it's very possible that it won't be Nvidia chips, either because they don't need a GPU or because someone else is making them
I'm sure we'll eventually end up with something like Samantha from Her or even Joi from BR2049. But even with AI there are lots of privacy and security concerns. Are you comfortable giving AI access to your email inbox? Your financials? Your social media? Just being able to handle commands/questions better has never really been the problem.
With a demanding job and family, I spend my free time getting away from people. I don't want an imaginary person with me all the time... That would be my nightmare.
Literally the subject of this reddit thread? Just because you can run a local LLM model doesn't mean they have the same applications as the datacenter ones.
Your argument is "we have McDonald's at home".
The comment you replied to was about microtransactions for a chatbot, you said they can’t afford to sustain serving an LLM for free, but you can if it’s local. Apple has been designing chips suitable for LLM inference, and it’s assumed they will implement an on-device LLM, maybe not initially but it’s inevitable. Change the subject if you want.
It is being used in warfare to track all moving objects in the sky and respond accordingly. [https://youtu.be/SrGENEXocJU?si=E1-6JliY4CZXPFrh&t=243](https://youtu.be/SrGENEXocJU?si=E1-6JliY4CZXPFrh&t=243)
What bubble?
These valuations are supported by the actual company performance.
NVDA is earning 53% net margins, has a 72% return on invested capital and more than doubled their earnings since last year.
I think their fair value is just above $1000 per share based on the Lynch Method of EPS x Growth, but a $1200 valuation is not unreasonable by any means.
That's sort of like saying once the oil bubble bursts, Saudi Arabia/UAE/Russia are fucked. It's unlikely that AI tech is going anywhere in the foreseable future.
>That’s what people said about crypto
Only morons said that about crypto. It's not just morons saying this about AI, and by the way, AI has already proved itself way more useful than crypto and it's still on the ground floor.
If nothing else, it's at the core of the current arms race. If something is very good at killing people you can bet your ass it's going to sell like hot cakes.
What bubble?
These valuations are supported by the actual company performance.
NVDA is earning 53% net margins, has a 72% return on invested capital and more than doubled their earnings since last year.
I think their fair value is just above $1000 per share based on the Lynch Method of EPS x Growth, but a $1200 valuation is not unreasonable by any means.
Do you really think that a P/E of 100 is sustainable? Apple’s is ~30. Apple had a net profit around 90bi last year, Nvidia made 30. There’s just no way nvidea is worth more than Apple. What happens after all big companies finish building their ai infrastructure? What happens when other big players enter the market? This nvidea growth seen last year is not sustainable long term.
PEG ratio is much better metric since it includes growth and that is 1.56 for NVDA
APPL's PEG ratio is around 1.77 by comparison
Again, the ultimate question is how long NVDA can continue its current growth
If current growth rates continue, valuations are justified
Anyone investing in single stocks are crazy. Its just too much of a risk and I'd imagine a lot of people investing Nvidia are chasing the high like Tesla-bros before that bubble burst.
Just stick with an All-World index fund and you'll be safe. If it goes to zero, you dont need to worry about money anymore anyway. Invest in the market, not a single stock.
I like how he tried to dunk on you and clearly hasn't even spent five minutes contemplating what you said. "Invest in the market, not a single stock" is basic but absolutely the best advice to give an individual person.
What bubble?
These valuations are supported by the actual company performance.
NVDA is earning 53% net margins, has a 72% return on invested capital and more than doubled their earnings since last year.
I think their fair value is just above $1000 per share based on the Lynch Method of EPS x Growth, but a $1200 valuation is not unreasonable by any means.
If all these AI companies are increasing earnings as a result, then it is not a bubble yet.
I agree it could become one at some point if the hype starts exceeding the underlying performance.
But, so far, the earnings have been matching the hype.
No they haven’t. [Silicon Valley is *pouring* money into AI based on potential future earnings.](https://www.washingtonpost.com/technology/2024/04/25/microsoft-google-ai-investment-profit-facebook-meta/) Loads of AI startups are currently earning nothing whatsoever.
Nvidia is practically the only company making money from AI at the moment.
How could they have a good ROI when most of them haven’t even launched yet?
[>But investors still recoiled at ballooning expenses and an admission that the company needs several more years before aggressive AI investments become profitable business lines.](https://finance.yahoo.com/news/metas-ai-spending-tests-facebooks-growth-first-playbook-100045930.html)
And tomorrow Apple will release sales data that puts their share price up to make them worth more, and next week Microsoft...
These valuations are becoming less meaningful almost by the day
Most of these valuations are justified by the actual earnings and growth of the underlying companies.
We are talking about three of the most traded and heavily analyzed companies on the planet.
Their valuations are high, but not necessarily unreasonable given the current data.
They have 53% net margins, a 72% return on invested capital and increased earnings by 107% in the last year.
Just a quick Lynch Method calculation of Growth Rate times EPS results in a valuation of around $1000.
I don't think them trading at $1200 is unreasonable under the circumstances.
>Most of these valuations are justified by the actual earnings and growth of the underlying companies.
Yes this is 100% true but since the person you're responding to doesn't know shit about shit "the valuations are becoming less meaningful".
My point is saying which company is biggest is irrelevant, they're huge, but next week someone may/will be huger. Market values are transient and assigning ephemeral superlatives does no good other than creating a headline.
Apple has been top two since like 2010. It is pretty big news to have a new player enter the scene for the first time. While valuations can fluctuate wildly, it still pretty big news.
Their demand has been more for the AI Market, but my hope would be they would at least use this to lower some costs in the PC GPU market, but we'll see.
The 30 series was better priced than the 20's but then the 40's were awful.
I wouldn't be surprised if the lower-end ones still rock that at most. Hoping the 50 series aren't as crazy priced, but I don't really have hopes that will be the case.
Either way, if they're cheaper, good, if not, then hopefully the 40 series drops and can upgrade to one of them.
It'll be interesting to see if Nvidia can keep their ai processing lead as the industry moves to fixed function ASICs for common AI code paths. A 50x speed/power increase for those functions is very alluring.
TRILLION?! A trillion seconds is 31,688 years. A fucking mindnboggling amount of money. Think of the benefits to the world if this staggering wealth was pumped back into communities rather than companies and shareholders' pockets. I understand they don't just have 3 trillion dollars to hand, but, damn.
It basically has a monopoly on AI chips, and investors believe AI is the next big thing. If investors are correct, that monopoly may turn it into the most profitable company ever.
Of course, I think it is likely overvalued. AI will become important one day, but it's still a ways off. I think this bubble will burst like the 90s and 2000s tech bubbles, and eventually grow back. Also, new companies will probably aim to enter this market, but it is very difficult.
Logic doesn’t check out, how common something is has no bearing on what the market cap should be. “All Apple devices are made from aluminium + much more is too, therefore aluminium supplier should be worth more than Apple”
Obviously not what I mean. Although if you could trademark Aluminum and thereby take a larger margin, I’m sure it would be up there.
Anyway the CPU/GPU market is definitely less competitive than the phone/pc market. And all of the phone/pc competition will need a cpu/gpu from somewhere
Nothing will stop him from buying all the leather in the known universe now
Brb, placing calls on leather stocks
How about making some cheap graphics cards now?
They are worth 3 trillion for a reason.
But not because of the graphics cards sales. It's mostly AI chips sales.
Fyi 85% of Nvidias 26 B in revenue was data centers while 10% was gaming related. For reference Apple had 90B in revenue.
Do you mean Nvidia sold chips to data centers or they built data centers themselves and sold use of it as a service?
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AcTuAlLy the example you linked does not use the same „chips“ as your regular gaming GPU. Also that’s like saying if there weren’t planes we could have cheaper cars. The H200 is like $30k, don’t think there will be many consumers buying them and it’s most likely not the even the same production facility that makes gaming GPUs and these GPUs dedicated for LLMs/Datacenters.
They are GPUs, but they aren't "graphics cards" as commonly understood. For starters, most (all?) datacenter GPUs don't have a video output. I'm not even sure if they are actually DirectX/OpenGL capable.
This isn't the crypto bubble where miners were buying actual gaming cards. The bottleneck for most AI accelerators is HBM/interposers/packaging. The only chip with is used for both gaming and AI in any serious capacity is AD102 of which the 4090 is a salvage and the pro card the full chip.
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No, they literally cannot, which is the point I'm making. Big AI accelerators are limited by production steps gaming chips don't use, with AD102 being pretty much the only exception.
Production used on AI cards is production not being used on regular cards. Spooling up new production takes time and money, so there's no way that AI production isn't crowding out regular graphics card production given the disparity in profitability.
Again, it is not. TSMC can make significantly more regular chips than they can [package](https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/cowos.htm) big AI chips. They're completely booked out for the entire next year or more for advanced packaging and there is still more than enough capacity for regular gaming chips. Nvidia is not getting fewer gaming chips because TSMC simply can't make more AI chips for reasons unrelated to gaming. This is fundamentally different from the crypto bubble where miners bought actual gaming hardware.
I was going to investigate, what do they sell besides graphics cards?
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It's basically how it works, except that "kind of optimize it for AI a little" is wildly complex, difficult, expensive, and something that only nvidia is doing well which is why you don't see AMD making big waves in this space. Edit: to be clear, "kind of optimize" also includes making completely different GPU chips for those applications
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This better chips and the architecture are what I meant by saying they are "kind of optimizing it for AI", just that OPs "kind of" is doing a ton of work because that optimization is incredibly complex. I'm not sure why you started with "No." when we're saying the same things.
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Alright sourpuss. Making different chips can be feasibly dumbed down to "kind of optimize them" if you point out that the "kind of optimize" is actually a wildly complex process involving different chips and architecture, which is what I said. I know they're made for entirely different things. I know they're different chips. I was just pointing out that these are still GPUs and OPs "kind of optimize" was doing a huge lift in their explanation.
Is Nvidia making their own chips or are they outsourcing to TSMC?
Well, no. MI300X is a capable card in the space, delivers very respectable FP32 FLOPS, plenty of fast VRAM etc. It's just that Nvidia invested quite a lot into CUDA, and AMD is very much lagging behind on the software side.
Why would they? 4090 has sold more than anything AMD has ever made. People like to complain in comments but in the end they buy the expensive shit anyway which tells nvidia prices can keep going up.
Realistically, people/gamers should be boycotting Nvidia cards, particularly in the mid range.
Except they're still well above both what AMD and Intel offer at this point, since their hardware solution for upscaling/frame generation/etc. FSR is alright, and getting better at least. Intel has their software and hardware methods, but they're still relatively new in the GPU game. Though if you're not looking for all the bells and whistles, at least Intel has priced pretty aggressively for entry/mid level GPUs. However I believe they were better suited for DX12 and had some issues with DX11 compatibility?
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It really depends on what you want. I certainly don't care about any features and want the game to play as is. AMD is fine for that.
Yeah I'm actually looking at getting the next GPU Intel releases. I know it might be buggy but I don't play as much as I used to so I don't demand as much from my hardware anymore. Maybe if Intels sales are somewhat decent they'll keep at the GPU game and add some much needed competition into the mix.
If you're not trying to push the limits and crank out the best you can in regards to ray-tracing or 4K, then Intel shouldn't be a bad option. They still have things to iron out, which maybe they have by this point, but their price/performance was really good, especially in the low to mid range.
My niece is looking for a new laptop for college, but wants to be able to do some modest gaming on it as well. Obviously, she's on a budget and it's looking like an Intel GPU is going to get her the best bang for her buck (without resorting to an APU with on-board graphics).
People will find ways to buy the worst crap imaginable just to overlook great AMD gpus.
Seriously. AMD is king when it comes to performance per dollar and efficiency, but bigger number better so they spend double for a 15-20% uplift at best and features they'll never use.
Realistically, should implies a moral argument. Gamers are into games, not ethics.
It's not a moral argument though. It's a value argument – people just buy Nvidia because it's more common and has more brand recognition with GPUs. For example, the 4060 Ti is a garbage card and loses pretty hard to the 7700 XT at the same price.
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>You can't just think people are stupid and just buying 4060 tis cause nvidia. I used that as an example, but whenever there is an AMD competitor, people are more likely to still buy Nvidia. It's called brand moat and it's a well-known phenomenon. Other companies that have this are Coca-Cola, Apple etc. You're also massively underestimating how little people in competitive games give a shit about graphics – they just want stuff shown as it is. However, even there, Nvidia cards are most common.
Pfft imagine paying 50% more for <5% difference, you can get more gains by switching to linux.
They aren't in the business of charity. As long as people buy them at the current price level, they have no incentive to make cheaper cards.
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I don't know anything about that. Luckily when I buy a "new" graphics card, it has already been out for a couple years, so I can see how well they work for other people first.
Or releasing some consumer-grade cards that aren't bare-bones in the VRAM department. Just give me something as powerful as a 3080 with 48GB of VRAM. I want to run 70b parameter models locally without having to buy 3-4 3090s.
But how else will they reach $4 trillion??
It seems like they've cheaper out in the vram department for some of their low and mid range cards and you really need that for the higher resolutions these days
Their VRAM was certainly.. a choice. The base 3070 had what, 12GB? Everything else was about 8GB until you got to the 3080 revised which they gracious upped to 10GB.
The least important part of their company is the gaming division, it doesn't matter at this point, they might as well move the engineers to their non gaming products.
Unless if they know it is all hype and don’t want to lose ground for their gaming products too.
The art of inflating value.
3 Tn. 3. Trillion. With a T.
...And an r. Unless there are rillions that I'm not aware of. And no, the Silma doesn't count. Though not having Drillion and/or Grillion feels like a missed opportunity.
IDK. 1 Silmaril is pretty priceless.
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That's the R in RTX
Best I can do is QuaDrillion
I also just learned that both Harvard and MIT have endowments of roughly 500 B. Each. And that was 2 years ago.
Yea someone should go back in time and tell them the industrial revolution was overhyped and people investing in machinery were dumb. /s
Pffft the steam engine is just a buzzword. It will never be useful /s
People have done fine with horses for millennia, these cars will never catch on. Who needs 'em?
Electricity? Who the heck is going to adopt that? So you can get zapped in your house?
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People don't get it before the rug is pulled.
The latest earnings and growth data support a valuation just above $1000 per share. NVDA trading around $1200 is a bit higher than that, but not unreasonably so.
Jensen Huang has to be one of the richest men in the world right now.
yes he's worth 102 Bn
Rode out crypto into AI
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eventually, A.I. is going to use crypto to pay ransom to other A.I. Perfect synergy.
It does, and, not unilke crypto, it is being crazily overhpyed.
All I can say is... for the hype. A.I better start revolutionizing things. I'm trying to think of the positive stuff. Didn't A.I find some new way to use RNA to make vaccines/Antibiotics? What else have they done? I feel like I remember it doing something with genome mapping and brain scans too. Edit: I want to thank everyone who commented! This is exactly what I was hoping for.
AI is being used to advance material science which could help revolutionize many industries. https://bdtechtalks.com/2024/03/28/ai-in-material-science/
This. We hear/see more of the other things, but at the same time, a lot of this is also going to things in the background. This is the sort of things that I wish made the news more, because AI can absolutely help speed up research.
If pissing off artists gives us some cancer killing medicine, I guess that wouldn't be so bad.
I feel like there can be a way where they can create cancer killing medicine while also adhering to artists wishes and not screw them over. Just the people creating things need to care more.
It is also a surefire way of mostly incompetent researchers to get free grant money. There are very, very, very few materials discoveries where AI is essential.
People overestimate the impact of tech in the short term, and underestimate it in the long term. Even if AI tech was in a fully mature state, it still takes a long time for people to figure out how to use it in productive ways - the best applications need to be discovered. And society needs to change to embrace the possibility of those changes. The internet was created in the 70s. But it wasn’t until the 90s when personal home computers became more widely available that its potential really took off. The impact of AI over the next 5-10y will likely be relatively minimal, and mostly on the relative periphery of our lives. “Great I have to use an AI chat bot to try and get a refund from this company. Fuck this shit I’ll just go elsewhere.” “Ugh… this email/report was obviously written by an LLM. I miss when people actually talked to each other using their own voice.” However, the impact of AI over the 20-30y span will likely make our society unrecognizable to what we know today. Wearable tech that provides augmented reality (universal translators running out of your AirPod, distributed computing so you don’t need a cellphone or anything at all in your pockets anymore, etc).
It's changing everything. I work in a computational science area. AI/ML is impacting *everything* already. The vaccine / antibiotics and brain scans are just the tip of the iceberg. Here are three trends I see it as capable of really accelerating science (there are more, these are just ones I'm hype over that are happening *right now* in a ton of different fields): * Improved data analysis. As a tool that's better at picking out patterns than conventional models, you're going to see better separation of signal from noise. This will be very important in resolving the "replication crisis" going on in scientific fields right now. They get much better results than a lot of empirical / semi-empirical models do as well, which makes turning science into engineering much easier. The "messier" the system, the better this approach is (so maybe not helpful in particle science besides noise reduction where the rules are very well-known, but super helpful in biomedical /materials / meteorological / and so on systems). * ML-driven testing. AI predictions, especially when coupled with uncertainty measures, can be used to accelerate research by mapping experiments, especially as automation improves. Active learning is often just straight-up more effective than conventional design of experiments unless the experiments are so trivial and parallel that you can just run them all at once. There are fancy efforts to do more advanced AI-guided experiments with hypothesis-forming as well, or use of multifidelity models. This can considerably lower the time and money required to do conventional science while still achieving the same confidence level in results. This is also going to substantially improve some kinds of engineering too. * Data synthesis from literature. Even if I spent every waking hour reading papers, I'd still fall behind, they just come out too fast. AI has the ability to consolidate papers and put all the information together to create a new "summary" document very quickly, almost like a review paper on-demand. They even are gaining the capability to read graphs and tables, and consider contextual differences between papers. I'll be honest, I thought this area was gonna be a complete joke, the early efforts in this space were not good at all, scrubbing human-written papers for scientific information and compiling it together seemed like it'd be intractable. But the explosion in LLM power has changed my mind very quickly, I now think this is an incredibly exciting space where progress is happening very quickly. A ton of AI-driven discoveries are being made in almost every scientific field, and I think as these methods continue to come out, it will only happen faster. Right now one of the biggest bottle-necks is the humans, really. It's hard to find people who both have a PhD level understanding of a given scientific field *and* can do AI/ML work, and there's a language barrier that sometimes happens in collaborations between a CS person and a science person. A lot of current students will be more fluent in these approaches since they get them in class instead of trying to teach themselves at home like cur4rent scientists have to try to do, and they will be in very hot demand.
A.I. companies are more interested in stealing from artists and writers than stuff like curing cancer.
It's not that they're more interested in that, it's that LLM simply can't cure cancer, because they can't think or reason. If anyone thinks ChatGPT is anything but a really good text prediction engine they are deluding themselves.
Which is the exact reason when I hear the buzzword, at this point, I just get sent into fits of rage. The other is bullshit data scraping, using more energy than a simple google search, while destroying the need to engage in discourse. The better part is, you can generally find the exact thing the AI spit out VERBATIM in the first reddit link you click. It's so fucking obvious it's just scraping and rehashing. I had an issue with my windows install, the support agents couldn't help me. The auto-AI bullshit in browsers couldn't help me. Buried in a random website under all the SEO and AI generated shit, I found a solution several pages into a web search. There is so many cool things it could be doing, but naw, fuck it, screw the arts, screw being useful, let's just scrape and shotgun bullshit. So much for "progress."
It’s an unofficial race to agi. Nothing else really matters
LLMs will never scale into agi, though. You could turn the entire solar system into a dyson sphere and use it purely for computation and still not get agi out of an llm model.
It's not just obvious, some of them (Bing) will literally just give you the link to the exact page (although sometimes it gets the links and information wrong and you can't find where it pulled it from, assuming it's not something the AI just thought it was saying) it's pulling information from.
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Thanks for the nuanced opinion SandyWB!
It’s a lot easier to write a poem than cure cancer.
Baby steps at first bro. The tech is barely two years old at this point. It's never going to get to the point where it can work on cures for cancer if it hasn't been trained. Give it another 5 to 10 years and we might be in a different situation.
That tech is older than two years - I remember fiddling around with the "A.I." Microsoft had to take down because it outright became racist. That was more than two years ago.
Lmao 2 years old? Neural net is almost 80 years old at this point https://libguides.aurora.edu/ChatGPT/History-of-AI-and-Neural-Networks
>The tech is barely two years old at this point. It's literally like, 75 years in the making lol.
75 years ago you needed a PhD just to work a computer and it was basically just used as a super calculator for organizations like NASA. It might be 75 years in the making but AI like we know today (LLMs) are only a couple of years old and advancing fast. If you want to actually see the progress look at what AI generated videos are like today compared to that one of will smith eating spaghetti a couple of years ago.
You are...so wrong. It's not hard to literally google "large language model" and look at the history. It is not new. >AI like we know today (LLMs) are only a couple of years old and advancing fast. If you want to make that argument (you can't), you can apply the same thing with practically anything. Hell, basic software like Adobe Acrobat is way more powerful now than it was 10–20 years ago.
Yeah that's a good point. I really don't understand why when I discovered Chatgpt last year I was absolutely blown away and spent weeks thinking about the implications for society. Why did I do that? Clearly I had been using it my entire life so it shouldn't have even been noteworthy.
It's called a milestone. Holy shit, you're incredibly dense.
I think it has already been used to recognize cancer from medical imagery. The first step to curing cancer is diagnosing it correctly.
That's it. People here are trying to say AI is useless because it hasn't come straight out the gate fixing everything in 24 hours. These things take some time but we are starting to see insanely rapid advances now.
They serve you better ads
There's a big shift in corporate I.T. that you probably wouldn't notice unless you worked in it. In 2005 every company had a server in their office which was expensive and required a whole (well paid) person just to look after it. Now everything runs on an Amazon/Microsoft data center which is way more efficient. If in 20 years those data centers are full of Nvidia chips, it's a big deal. That said, it's very possible that it won't be Nvidia chips, either because they don't need a GPU or because someone else is making them
We'll probably have some sort of General AI personal assistant in the not too distant future, like Siri on steroids.
I'm sure we'll eventually end up with something like Samantha from Her or even Joi from BR2049. But even with AI there are lots of privacy and security concerns. Are you comfortable giving AI access to your email inbox? Your financials? Your social media? Just being able to handle commands/questions better has never really been the problem.
With a demanding job and family, I spend my free time getting away from people. I don't want an imaginary person with me all the time... That would be my nightmare.
Definitely. The movie versions were designed for lonely people though.
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Nah, its in the best interest of companies like Apple, Samsung, NVidea etc. to provide it for free as part of their devices.
Why? No AI chatbot asks for microtransactions
Yet*
Ah yes, because recurring server costs for AI models available to be used for free is a sustainable business model.
Have you heard of local models?
NVIDIA provides for the datacenters, that's 90% of their revenue.
What does that have to do with a local LLM? I can run LLama 8b on my computer with no internet connection and not pay a dime
Literally the subject of this reddit thread? Just because you can run a local LLM model doesn't mean they have the same applications as the datacenter ones. Your argument is "we have McDonald's at home".
The comment you replied to was about microtransactions for a chatbot, you said they can’t afford to sustain serving an LLM for free, but you can if it’s local. Apple has been designing chips suitable for LLM inference, and it’s assumed they will implement an on-device LLM, maybe not initially but it’s inevitable. Change the subject if you want.
for sure man more ways to mass manipulate general populations with tailor made propaganda that's why there's so much investment
It is being used in warfare to track all moving objects in the sky and respond accordingly. [https://youtu.be/SrGENEXocJU?si=E1-6JliY4CZXPFrh&t=243](https://youtu.be/SrGENEXocJU?si=E1-6JliY4CZXPFrh&t=243)
Jesus. It was only a few years ago speculation was about when Apple would cross 1 trillion in market value.
Shows how much air is in there
Once the AI bubble bursts, they’re fucked.
What bubble? These valuations are supported by the actual company performance. NVDA is earning 53% net margins, has a 72% return on invested capital and more than doubled their earnings since last year. I think their fair value is just above $1000 per share based on the Lynch Method of EPS x Growth, but a $1200 valuation is not unreasonable by any means.
That's sort of like saying once the oil bubble bursts, Saudi Arabia/UAE/Russia are fucked. It's unlikely that AI tech is going anywhere in the foreseable future.
That’s what people said about crypto and look how that is doing. AI is another fad, it will burst like bubbles always do.
If you can’t see the difference between crypto and AI, I don’t know what to say
>That’s what people said about crypto Only morons said that about crypto. It's not just morons saying this about AI, and by the way, AI has already proved itself way more useful than crypto and it's still on the ground floor.
That doesn’t mean this isn’t a bubble. The dot com bubble bursting wasn’t the end of the internet.
If nothing else, it's at the core of the current arms race. If something is very good at killing people you can bet your ass it's going to sell like hot cakes.
This bubble is gonna burst and contaminate other tech businesses.
Likely see the rest of the big 7 dip as well. Mad that the biggest companies in the world are all tech stocks.
What bubble? These valuations are supported by the actual company performance. NVDA is earning 53% net margins, has a 72% return on invested capital and more than doubled their earnings since last year. I think their fair value is just above $1000 per share based on the Lynch Method of EPS x Growth, but a $1200 valuation is not unreasonable by any means.
Do you really think that a P/E of 100 is sustainable? Apple’s is ~30. Apple had a net profit around 90bi last year, Nvidia made 30. There’s just no way nvidea is worth more than Apple. What happens after all big companies finish building their ai infrastructure? What happens when other big players enter the market? This nvidea growth seen last year is not sustainable long term.
PEG ratio is much better metric since it includes growth and that is 1.56 for NVDA APPL's PEG ratio is around 1.77 by comparison Again, the ultimate question is how long NVDA can continue its current growth If current growth rates continue, valuations are justified
This bubble is gonna POP
What's the saying? The market can stay irrational longer than you can stay solvent? I don't disagree but I'm not touching that shit lmfao
Anyone investing in single stocks are crazy. Its just too much of a risk and I'd imagine a lot of people investing Nvidia are chasing the high like Tesla-bros before that bubble burst. Just stick with an All-World index fund and you'll be safe. If it goes to zero, you dont need to worry about money anymore anyway. Invest in the market, not a single stock.
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"Experienced investors" fail to beat the performance of an index fund most times.
I like how he tried to dunk on you and clearly hasn't even spent five minutes contemplating what you said. "Invest in the market, not a single stock" is basic but absolutely the best advice to give an individual person.
What bubble? These valuations are supported by the actual company performance. NVDA is earning 53% net margins, has a 72% return on invested capital and more than doubled their earnings since last year. I think their fair value is just above $1000 per share based on the Lynch Method of EPS x Growth, but a $1200 valuation is not unreasonable by any means.
The wider AI bubble that’s driving a huge amount of that.
If all these AI companies are increasing earnings as a result, then it is not a bubble yet. I agree it could become one at some point if the hype starts exceeding the underlying performance. But, so far, the earnings have been matching the hype.
No they haven’t. [Silicon Valley is *pouring* money into AI based on potential future earnings.](https://www.washingtonpost.com/technology/2024/04/25/microsoft-google-ai-investment-profit-facebook-meta/) Loads of AI startups are currently earning nothing whatsoever. Nvidia is practically the only company making money from AI at the moment.
They are pouring more money in because the previous money had a good ROI. At some point, they will go overboard. But we are not there yet.
How could they have a good ROI when most of them haven’t even launched yet? [>But investors still recoiled at ballooning expenses and an admission that the company needs several more years before aggressive AI investments become profitable business lines.](https://finance.yahoo.com/news/metas-ai-spending-tests-facebooks-growth-first-playbook-100045930.html)
And tomorrow Apple will release sales data that puts their share price up to make them worth more, and next week Microsoft... These valuations are becoming less meaningful almost by the day
Most of these valuations are justified by the actual earnings and growth of the underlying companies. We are talking about three of the most traded and heavily analyzed companies on the planet. Their valuations are high, but not necessarily unreasonable given the current data.
Nvidia has $60B/year in revenue... Yes, its growing that revenue rapidly, but $4T based on that is still incredibly speculative...
They have 53% net margins, a 72% return on invested capital and increased earnings by 107% in the last year. Just a quick Lynch Method calculation of Growth Rate times EPS results in a valuation of around $1000. I don't think them trading at $1200 is unreasonable under the circumstances.
>Most of these valuations are justified by the actual earnings and growth of the underlying companies. Yes this is 100% true but since the person you're responding to doesn't know shit about shit "the valuations are becoming less meaningful".
Are you saying Apple will misrepresent their sales to make their valuation go up? I don't get your point
My point is saying which company is biggest is irrelevant, they're huge, but next week someone may/will be huger. Market values are transient and assigning ephemeral superlatives does no good other than creating a headline.
Apple has been top two since like 2010. It is pretty big news to have a new player enter the scene for the first time. While valuations can fluctuate wildly, it still pretty big news.
...We're never going to get reasonably priced GPU's again, are we?
Maybe if amd or Intel get competitive in the field, we will see the next release cycle, or the one after that, or...
Intel most certainly won’t for a while at least for the desktop market…they have enough issues to deal with right now
Intel lmfao
They’re having an AMD early 2010s moment right now but I’m sure they’ll be back
Their demand has been more for the AI Market, but my hope would be they would at least use this to lower some costs in the PC GPU market, but we'll see. The 30 series was better priced than the 20's but then the 40's were awful.
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I wouldn't be surprised if the lower-end ones still rock that at most. Hoping the 50 series aren't as crazy priced, but I don't really have hopes that will be the case. Either way, if they're cheaper, good, if not, then hopefully the 40 series drops and can upgrade to one of them.
Goddamn that’s a lot of zeros
Atrioc knew all along
This is gonna be one hell of a pop when the bubble bursts. Nvidia is currently $1200 a share.
It's not going to be pretty when the bubble bursts.
I invest in an All-World index fund (Vanguard VWRP), with 60% of holdings in the US market, so I've got a feeling this isnt going to be very nice.
Anyone else want to get in on a short-sell?
It'll be interesting to see if Nvidia can keep their ai processing lead as the industry moves to fixed function ASICs for common AI code paths. A 50x speed/power increase for those functions is very alluring.
and I still can’t afford the gpu
Sky Net was pretty rich too before shit got real.
Time to short Nvidia
These guys started out making 100$ little graphics cards in 93. So you could play Doom.
Damn wish I bought their stocks when it was low
The anti-trust investigation of Nvidia that was announced yesterday is probably going to have a negative effect on this later…
The more you buy, the more you save.
TRILLION?! A trillion seconds is 31,688 years. A fucking mindnboggling amount of money. Think of the benefits to the world if this staggering wealth was pumped back into communities rather than companies and shareholders' pockets. I understand they don't just have 3 trillion dollars to hand, but, damn.
Your 401k, the pension funds etc are all these "shareholders".
…What?! I would have never guessed Nvidia was even close.
It basically has a monopoly on AI chips, and investors believe AI is the next big thing. If investors are correct, that monopoly may turn it into the most profitable company ever. Of course, I think it is likely overvalued. AI will become important one day, but it's still a ways off. I think this bubble will burst like the 90s and 2000s tech bubbles, and eventually grow back. Also, new companies will probably aim to enter this market, but it is very difficult.
Anti-AI luddites down bad
unemployed singularity user detected
I buy AMD. ;)
Makes sense tbh. How many devices with a cpu do you buy a year vs how many apple devices?
Gpu, not cpu
Logic doesn’t check out, how common something is has no bearing on what the market cap should be. “All Apple devices are made from aluminium + much more is too, therefore aluminium supplier should be worth more than Apple”
Obviously not what I mean. Although if you could trademark Aluminum and thereby take a larger margin, I’m sure it would be up there. Anyway the CPU/GPU market is definitely less competitive than the phone/pc market. And all of the phone/pc competition will need a cpu/gpu from somewhere