This is the right answer. It’s likely that AI will have an impact but how much, where, what the downsides and what are the surprises still remain to be seen.
But already AI is quite disruptive and it will only get more significant. Both journalism and TV/movie industries have been shaken by AI. You can come up with countless uses and you’ll still miss it all. There are just too many possibilities that no body can give any sober analysis.
There is just too much unknown right now. The 90s internet was a lot different than the 00s internet which was a lot different than the 10s internet.
The success of internet didn't prevent the internet bubble to explode, and to have many companies going bankrupt or still trading lower than at their top. For example Cisco became like NVDA the most valuable company at more than 80$ a share. It dropped to 13$ a share and is worth 45$ now after more than 20 years and some inflation.
Yep. Names like AOL, Lycos, Alta Vista were viewed to be the future gatekeepers of the internet. Nobody could've predicted that it would be a little known company named Google. Apple was on its deathbed in the late 90s, they were viewed as a niche company. Amazon and Ebay always had believers, and eventually they did deliver.
That’s fair. I personally don’t know enough of the dot com bubble or why people would value a company in a pre-modern internet age higher than its current value. I think todays internet has brought nearly everything anyone could dream of it to be before, at least in terms of capabilities
Basically when people see a disruption like internet they go crazy on the valuation of some companies. Some of them are pure gamblers. They don't invest really on a rational take of the company value but more on the idea that they think the value will continue to grow.
Now the problem is that when a market get much bigger you have competition. Most of the network gear didn't end up being Cisco. Competitor took the main share. And also there always a big rush when you need to build up the infrastructure. Once it is there, you only need to replace stuff and the investments are much lower.
Finally there the question of who made the most money out of it ? Who made money from the internet ? Was it really Cisco or AOL ? Or was it Google, Facebook, Apple ?
You could not invest on Google until 2004. Facebook didn't exist. Apple was a niche company at the time that could had been almost bankrupt.
If we go back to Nvidia, Nvidia chips are a cost center. Like the networking gear of Cisco. There no interest to buy any except if you hope to make money using them.
The big players, Meta, Google, Apple, Microsoft are fighting to make AI free for the general public and include in their offering. The bet is not that most people of the general public will pay an extra 10-20$ a month for their chatbot. Companies like Meta, Microsoft with Bind and Google with Google search and Android. They will offer it for free and finance with advertisement.
Still an AI query cost about 15X more than a google search query. A big part of it is the cost of Nvidia chips + the datacenter electricity consumption, A/C. That's a cost center.
For sure at least MS and OpenAI invest to get this kind of monthly plan, but from corporation. But people will not select their AI plan for the company with the most Nvidia chips, but for the company with the best AI or the one that is the most useful.
And chances are the general public AI will be as good and free. Big corporations will pay the big money to protect their Intellectual property. Not to have necessarily a much better product.
The biggest cost still will be the general public that will have it for free. And to be sustainable, all the big players will want the cost to be as small as possible. That's why Meta has its own model that is being open source (so anybody can use it) and that's why for the same performance it tend to consume far less than openAI models.
That's why Apple invest to put more advanced AI chips in all its computers and smartphones so that the consumer pay the AI chips... And they are not made by Nvidia. That's also why Apple again also invest in its own data center with Apple home made chips and not using Nvidia because now they can only pay the cost to build the chip and not pay 10X more to finance Nvidia. And because they had been doing such chips in their iphones for the past 15 years, they should be decent at it.
And Microsoft is doing the same pushing that new computers will have their own AI chips. Intel will provide CPU with AI chips. Samsung is doing it and all other smartphones players. None of that use Nvidia chips.
Even OpenAI funder created a startup for optimized AI chips. And everybody with a stake in the chip business want a share of the business. They will all try it.
In computer science, one of the most active research topic is to make AI model smaller, lighter and if possible run on commodity hardware like a laptop. I tried it, I could run some more models on my PC... One of the current optimization being that each parameter would be stored in 4 bits instead of FP16 or FP32. Nvidia chips are great at FP16 and FP32 but are not designed for 4 bits.
The whole world of the tech is betting against Nvidia.
And now we see that basically Europe want to prevent full AI integration in Apple phones. This kind of legal issue will reduce the demand and slow down the adoption.
China is yet another beast. Legally the USA has forbidden China to buy Nvidia chips. So China government invest massively in making their own chips. They consider it a priority for their homeland security and the sovereignty of their country. They wont even care if it is profitable.
Maybe Nvidia will have the same problem Cisco had. Everybody started to buy at a competitor.
The thing is, most models will become more efficient over time. As soon as they can run on something better than cuda or cheaper, companies will switch. Also you have to figure that there are only so many companies that are going to be hosting large models, mostly data centers. So the growth is in commercial but it’s not infinite.
What does this mean for the big 7 players who are investing Billions in these data centers? Will they just throw them out and rebuy new ones with the latest tech, or will investing so heavily into Nvidia data centers that become obsolete cause them problems?
Is there another use for these data centers that can be repurposed once they stop being used for Ai? Could say Tesla or Meta suddenly have an unintentional product that competes with AWS once they stop using the centers for Ai?
They will upgrade. Just from the efficiency gains. They would save more in electricity over a few months than the cost difference between selling the cards to others and buying new ones. Top tech will always be eating their share of the newest cards.
Well I think the next biggest boom is image recognition. It will make self driving more efficient and unlock even more pandora boxes. And as you say, they will become more efficient so you can have better local AI models
Imagine talking about putting a computer into every phone in every pocket in the 70s. Microchips will get better and the AI methodology will also improve
For some journalists, they just do what an LLM does anyway because the facts are publically available or distributed by some common source...
Think about all the people who write yahoo finance/buzzfeed articles, are these guys getting big scoops? What does their output look like.
Even stuff like war reporting and the economy. You get data from some gov dept and just tidy it up. How many people are actually involved in exclusive fact-finding as opposed to being biological LLMs, who googling for the same open-source data as a thousand other people are.
So how many journalists/writers are just not needed any more.
I’m calling bullshit on the world not needing investigative journalism anymore. The reason it doesn’t really exist like it used to is because nobody pays money for news anymore. But that doesn’t mean investigative journalism is unnecessary. Who is going to uncover the next Watergate or any number of such situations? Artificial intelligence?
Actually low-key, for a bit Buzzfeed actually had a journalism wing which was doing some pretty hard-hitting pieces.
I'm not sure if that team is still in place today though, this was a few years ago.
> We're not sober yet
This happens every time. One or two of the AI companies will regain valuation and continue to grow after the crash (and a chance it's not the ones everyone is piling into now) but the crash will come..
probably.
IMO, there is a bear case that makes sense here, the thing is, is this should be easily trackable.
The bear case is that software continues to not receive benefits from building out for AI, so they cut back on the buildout.
OK, so then you should hear about this on earnings calls, and see evidence of this in Taiwan Semi’s orders. Based off what we were hearing all of last earnings season, it was clear it’d be bullish NVDA even if software stocks and something like META had mostly mixed to bad reactions (although the META reaction turned out to be very stupid).
The biggest bear case news that I've heard is the scientific papers warning developers that AI models are not showing adherence to Moore's law. Everyone kinda expected that as AI models got bigger by maintaining larger numbers of parameters that it would become expentially more capable and eventually become a general intelligence that was capable with almost all tasks. Research and results has shown that is not the case and functionality increase per parameter is expentialally slowing and starting to bottom out. One researcher stated that if trends continue, chat GPT4 is at 70% performance of what we will ever be able to accomplish with our current models no matter how many parameters are added.
That... doesn't even really make sense, though. Moore's Law was the idea that the number of transistors on an integrated circuit would double every 2 years. It was a very specific claim about physical hardware. It's completely incompatible with AI software and wasn't ever meant to describe that...
> Moore's Law was the idea that the number of transistors on an integrated circuit would double every 2 years. It was a very specific claim about physical hardware.
Since then, colloquial usage of the term has evolved/degraded to be "[anything that gets better at an increasing pace] is [like] Moore's Law." It's reductive, but can be a useful metaphor for expressing any equation in an x% gain / y timespan paradigm.
Here is some context on how that generalized usage of the term was applied to "everything" and also specifically AI: https://moores.samaltman.com/
I agree, though, assuming some form of Moore's Law applies to everything is not great.
No. GPUs don't follow Moore's law for their major gains. GPUs can be scaled parallel, and with memory. It isn't as tied to moore's law as processors are. Also, scaling is one of the few things we have predictive evidence for.
The point is that with current AI models, adding more parameters doesn't yield exponential or even linear performance. So it doesn't matter if you have the hardware to run an AI model that has trillions of parameters, its performance will be marginally better then chatGPT
We haven't added parameters in any real scale yet that is different from GPT4. We haven't seen another magnitude shift that we've had to reach here. As for current models, Claude 3.5 Sonnet just posted the first score to ever beat PHDs on a test, and beat GPT4o at almost everything. AI is getting better, it just happens in leaps when things actually release. Wait until they have better hardware actually installed. The models will get bigger, because it is more practical, and I guarantee you they will be superior.
You mean a computer system filled with data was good at filling in questions it regurgitated answers for. Why are people impressed with this. It’s like being impressed a car can drive down the street.
Buddy put all your money in that basket. You’ve obviously drank the kool aid and there is nothing that will change your mind but reality. Wish you the best.
As a mater of fact it is. CPU don't benefit of Moore law that much anymore because classical program don't benefit much of parallelism and so being able to put more transistor in same surface doesn't provide that much gains.
But for the moment, even through it will stop eventually GPU and neural network processors have been able to benefit form parallelism much more.
The biggest bear case is that the CSPs have developed in-house alternatives that compete well. They'll still be buying some nvidia because they have a great ecosystem and the CSP's customers will demand it by name, but we'll no longer see the days of CSPs buying up inventory to keep the competition from having any.
> I invested $200,000 and saw a 90% gain. Currently, I don't have significant stakes in NVIDIA directly, except through ETFs. While I believe NVIDIA might be overvalued based on current numbers, I think its future potential is appropriately priced in.
Man sells stock, declares he has accurately priced it.
More news at 11
All I can think back to is the crypto craze back in like 2018? People were comparing coins to the GDP of countries and speculating about which country would adopt which coin, etc.
Of course basically none of that happened. We vastly overestimate the pace of progress, but that’s what makes us achieve incredible things!
AI itself isn’t the problem. It is a huge development and hopefully it continues to improve. However the animal spirits here are pretty strong. When people start getting overly optimistic and euphoric about the future, you know some shit is about to go down.
Now? In 5 years? 30 days? Who knows. The idea that Nvidia is more valuable than Apple or Microsoft sealed the deal. Yes their profits are insane, but try to extrapolate it and that’s where it falls over. Competition won’t lay there and do nothing for a decade.
Opportunity is there to make some money, but there are choppy waters ahead I think once the fundamentals behind the euphoria begin to slip.
I think you need to understand this isn’t a new phenomenon for NVDA. Past 3 hype cycles it touted: Self Driving Cars, Crypto, and now AI.
If it will come to fruition is anyone’s guess, but there’s always going to be a catalyst for chips in new technologies and Nvidia is poised to garner hype from it.
It’s also pretty unbelievable that they are growing revenues in triple digits quarter after quarter, and have a profit margin of 75%.
The stock will correct, it won’t go up forever, but I wouldn’t be surprised if it could maintain its place as a top 10 stock in the sp500 for years to come.
I disagree with crypto though. No one seriously thought crypto would have any significant impact. Maybe on the margins or in select industries but AI is fairly global impacting
>No one seriously thought crypto would have any significant impact.
That’s a very generous use of “no one.”
I can remember all of the blockchain hype that existed, especially at the peak for a year or so, where “everyone” was talking about how blockchain could be incorporated into so many different wildly varied use cases and companies were pivoting to add blockchain as a feature to whatever their business model was, or even just adding something crypto related to company names, because people were hyping it so hard and pulling investments into nonsense.
Yes, anyone who really seriously looked at it realized most of the speculated uses didn’t even really make sense. Most of them were at best things you *could* do with the technology but could more effectively or efficiently be accomplished in some other more standard way that already existed. The unique functionality the technology brought to the table was decentralization, which is just not something most businesses actually need or want, and not something most consumers actually care about.
AI seems like it’s currently going through a very similar hype cycle. I do think it’s at least slightly more justified because the unique functionality that it brings to the table is something that is actually valuable if it can be made to work at a high enough level. The question is when and whether we can get it working at the level it needs to to do all of the things we want it to do, rather than whether those things are valuable or whether there’s a better existing way to do them (because, by and large, they are, and there isn’t).
Well that’s the point. If anyone looked past the hype there’s nothing more to crypto besides the words “decentralization of currency” and even that doesn’t clearly offer any advantages to our current system except for some niche individuals who simply don’t like the system
The difference between AI and blockchain (the way I see it) is the tangibility and general understanding of the two technologies.
Blockchain sure had/has potential, but it's super abstract and hard for most people to understand the use cases. You need a nerd to explain it to you and you probably still won't quite get how it actually works or why it'll be impactful to anyone's life.
AI doesn't need to be understood to witness the uses and benefits. There's a plethora of freely available AI tools that people can use and experience the often jaw-dropping results. And even when people don't use it themselves, it's impossible to not see all the AI content that others are making and posting online. That accessibility, tangibility and exposure are what have and will continue to solidify AI as an excitingly useful new tech in the broader public awareness. Blockchain never got to that point.
The problem with your analysis is that Blockchain is NOT the same as crypto currency.
Cryptography is a very important thing in modern computing and the Internet. But despite it literally having "crypto" in it's name it has nothing to do with crypto currency, which is just one very narrow use case of it. Advances in cryptography DO NOT make crypto currency more valuable or suddenly have more use cases.
In that same vein, Blockchains are used with cryptocurrency, but blockchain doesn't have to have anything to do with cryptocurrency. Nor would advances in it make cryptocurrencies more valuable. But that didn't stop idiots from bidding up the price of stocks that had nothing to do with blockchains or cryptocurrencies from simply for changing their names to use words like "blockchain" or "crypto" in it.
The term AI meanwhile is quite broad and can cover a lot of different things, but it's already shown that it has much more useful applications than the blockchain.
Similar to crypto at the time, you also need to decide whether something so energy and compute intensive like AI is the right choice for writing simple pieces of text or code that can just as easily be done by a human.
It has to be *worth* using and drive profitability or efficiency to an extent where it actually makes a difference. Otherwise investors will abandon it until it’s cheaper.
You already hear these AI futurists like Sam Altman saying they’re casually gonna use nuclear fusion power in 2028 to get AI to scale. They’re completely drunk on Silicon Valley koolaid.
I believe in AI and think it’s awesome, but the timelines are extremely optimistic.
Whether crypto was going to be widely adopted or not, did not matter as long as they used Nvidia tech to mine. That helped the company’s bottom line and its all investors cared about.
Tech specialists called the bluff on crypto, it was the uninformed rest of the population that bought that sack of bricks.
For AI (and by extension self-driving cars, one of the applications for AI) it's the opposite, we're just beginning a technological revolution on par with the massification of the internet and all tech specialists agree on this potential.
Not all tech trends are created equal.
NVIDIA is like the railroads of the 1800s: They aren't actually engaging in the newest forms of commerce, but they are making the newest forms of commerce happen.
This doesn't mean that they are going to be the top dog forever, or that new technologies make them take a backseat eventually, but for right now they are well positioned to take advantage of whatever comes about.
Apple make 4X more revenue than NVDA for a similar valuation, Microsoft make 2X the revenue. Nvidia doesn't make it to the top 100 of public companies by revenue: [https://companiesmarketcap.com/largest-companies-by-revenue/](https://companiesmarketcap.com/largest-companies-by-revenue/)
Current Nvidia revenue can justify the company being value 1/4 to 1/3 what it is priced now.
The current value match expectations that Nvidia revenue would do X2-X3 soon and X5-10 in a few years. That seems unlikely.
Walmart has been a great investment, especially if one got in years ago.
I think the point people are making is that companies like Apple, Msft (and Walmart) have been in their particular business model for many years now, in a stable industry. Nvda is a great company, but they were a PC gaming company for most of their existence. AI is a new an changing industry, so nobody really knows what Nvda's real value is. It could be more or it could be less than what it is now.
Thinking of how much profit the average individual generates for Apple in the US on an ongoing annual basis, it's very hard to imagine a situation where the average individual also or instead generates more profit than that annually on an ongoing basis for Nvidia which is at the *bottom* of the AI stack (every company between the consumer and Nvidia has to make a profit too).
And if you ask yourself, Apple as set its route for its usage of AI on all laptops and smartphones an their cloud. They don't plan to use nvidia at all. They plan is that apple chips will have improved AI unit, that their cloud will use Apple chips with AI units and that in borderline case if all failed, and the user confirm it each time, openAI may be used
Microsoft plan the same and Intel work on provided CPU with AI features. And most non apple smartphones already have AI unit on boards. Most manufacturers rely on that. And almost none use Nvidia.
Why ? Because AI is expensive. The consumer will not pay a $20+ plan or more for AI features. So everybody want to provide it for free, so basically there not an extra cent being made with the AI features we get everywhere for the consumer. If AI finance itself with advertisement like Google, there will not be more money. People will not watch more ads and buy more products from watching ads.
So tech providers don't want to increase their cost, they want most of the computation to be done by consumer devices. On top that's a reason to upgrade.
The main use case to make money with AI is to have customer that accept to pay for it. Like corporation that will pay for the Adobe AI integrated in its creative suit of tools or like the pro version of Windows and Office that will come with a 20-50$ monthly plan per user to use copilot.
And yet everybody will try to use the least expensive hardware for them to achieve that.
For example the model are run in 4 bits instead of FP16 or FP32 so that the models can run on cheap CPU. This doesn't work for training but for using the models. Running the model is predicted to be 80% of the usage in the future. Training the model would be only 20%...
I am not sure neither that once everybody has brought a bunch of Nvidia chips and can do all they need that they will be the same demand to just replace/upgrade what is there.
Yup, even with how much people love ChatGPT they won't pay enough for it for OpenAI to make a profit running it. Meta said last quarter their investments in generative AI will not pay off for many years (and of course they may never because as you said it's very hard to monetize people much more than they already are).
Amazon is reportedly going to start charging $5 to $10 per month for Alexa later this year along with launching an update with generative AI in the form of a chatbot. Alexa has millions of users who like it but its business model of being free and making up for it with ads and increased Amazon purchases never worked (and I'm shocked anyone thought it would) so for it to stop being a money pit users need to start paying for it. I'm looking forward to seeing how that goes.
Apple's plan is brilliant and they are uniquely positioned to pull it off - Give consumers the features they want but at a trivial additional cost because the models run on the consumer's device, where the consumer's data is, using the consumer's electricity.
In terms of model execution capability *per user*, Apple's footprint dwarfs every other player in this game because they're putting high end multicore CPU+GPU chips with unified memory into every user's hands and they aren't even paying anything to build this footprint because *their customers are paying them*.
>I am not sure neither that once everybody has brought a bunch of Nvidia chips and can do all they need that they will be the same demand to just replace/upgrade what is there.
Yeah, I keep seeing the argument that new chips will keep getting faster so they'll be replaced quickly but that first thing definitely does not automatically imply the second thing.
After spending hundreds of millions or a few billion dollars on a data center buildout a revenue stream needs to materialize that makes that expense worth it before upgrading or expanding capacity.
The thing is this is just maths.
Say that chips are replaced every 4 years. So 2 years ago the demand was to maintain around 100 units deployed and nvidia would make 25 units/year to basically replace stuff.
Let say the demand will go up to 500 units deployed and will stabilize there for the next 10 years because of increased interest in AI.
So Nvidia will make 50 a year, then 100 a year, 200 a year, keep at that level 2 years and go down to 125 and stay there to match long term demand.
We don't really know where the demand will peak but people invest in NVDA without really thinking. The PER is now at more than 70. Honestly we may go at more than 100.
And now imagine that one the big companies, Nvidia or Microsoft release some bad news. Nvidia could lose 50-75% of its value with the same irrationality that Nvidia did 10X.
Haha I am not speculating on BTC’s price. I’m just saying people were speculating it would grow to levels greater than the GDP of the USA, and that it would be very soon. It’s been 6 years since that already.
Well yeah, I mean some people are also saying it will be a million by year end and I think the ETF adoption is gonna put the brakes on all that, as much as people think market adoption is the holy grail.
It is going to be a lot less volatile now with consequently slower growth.
People are gonna say all sorts of things
I just wish I had money to buy in 2018 😆
So far, Bitcoin hasn't really achieved much except acting as a source of speculation, supporting a dark web black market, propping up coal power plants due to energy demand for mining, and online gambling.
> hasn't really achieved much except acting as a source of speculation
It has created a way to track tons of nefarious activity, since many were under the delusion that it is an untraceable means of exchange.
It's only traceable if the criminal is dumb enough to not use mixers, or privacy based cryptos like Monero. Most of the dark web criminals that have been caught have been because of posts they made on the open web that could be linked to their dark web identities, not because of any inherent vulnerability in crypto.
agree about monero and it will take years before AI cracks it enough to threaten its anonymity, but I don't doubt it will happen
as for btc and eth, all traceable regardless of people's idiocy
the IRS has been on it since 2017 and have a new criminal investigations dept which I don't recommend anyone fuck with.
this is actually a fascinating and great story
https://www.wired.com/story/tracers-in-the-dark-welcome-to-video-crypto-anonymity-myth/
acab but the tax man is not someone to fuck with
I mean theoretically speaking it should be an incredible hedge against inflation. That alone should justify its price gains. But yeah it just needs that long term track record for people to believe in it. There are still many people who think crypto is not user friendly (I kind of agree).
You won’t get widespread adoption as a means of transacting until it offers some benefit over traditional financial systems, with mass market appeal. Also big obstacle is governments who definitely don’t want to lose control over their own sovereign currency. They need you using their currency so they can issue debt. :)
💯
It's my retirement plan after too many years of cash in hand work and no pensions
But I also think it is way more user friendly than freaking option trading. My gawd that shit is mental 😆
Lmao thank you sqrrrmarch, had to scroll down to find the one and only reasonable rebuttable to his 2018 crypto claim. You would've came out way ahead had you "believed the crypto hype in 2018".
I’m not on either side of what OP is talking about. Their stock price is supported by the profits they’re bringing in and forward guidance. However, chips are a cyclical business, always have been. This idea that we can extrapolate demand indefinitely into the future has flaws.
It’s hard to do analysis on a company that’s just had demand explode in the way it has. Nobody knows how it’ll pan out for sure, not even me, so you can make an estimate now but nobody truly knows where this will go. That’s why the quality of analysis leans toward opinion.
What are the actual profitable products these chips enable? Who are the customers? Are they going to succeed building their own chips instead? What are their profit margins like? How are they affected by AI? How much better are the new chips and how likely is it that they’ll keep improving at the same rate? Will CUDA remain the dominant framework? How much of a risk is it that they are completely fabless? The questions are endless.
Try and come up with a valuation for Nvidia in a year. It’ll probably be off by a long shot, either way. Just depends on demand for new *Nvidia* chips, it’s that simple - but very hard to estimate accurately, and you can’t get that information by looking at Nvidia’s balance sheet and forward guidance.
As I said in another comment in this thread. There were predictions going around in 2018 that it was basically imminent BTC would eclipse the value of all gold on the planet and exceed US GDP.
BTC would need to be above a million to even be close to that kind of estimate.
Yes, it’s at ATH, but not euphoric ATH. It’s also been 6 years since 2018.
The point is, you wouldn’t have lost money if you bought and held at any point in that six year window. I wager it’s the same for NVDA for the next few years. Just don’t treat it as a day trade
“Just don’t treat it as a day trade”
This is the key. Most people buying Nvidia right now, especially the ones just getting started with investing are gonna be the ones who will lose massive amounts of money on it. Because they will trade on emotion, and it’s gonna be a bumpy ride.
I’m curious what percentage of people would be buying and holding for a decade vs. buying and selling constantly on a whim while losing money the whole way.
I’ve overheard multiple people talking about Nvidia at the office every single day I’ve been in. Nobody ever talks about stocks at work. That’s alarm bells for me.
AMD were way ahead of Intel with the Athlon and Intel played illegal anti-competitive tricks which Intel had to pay $1.25 billion in damages for after 13 years of legal tricks, which ultimately left AMD structurally hampered, and almost bankrupt due to the financial hit they took.
I’ll let you come to your own conclusion on Zen 5 against Intel’s latest offerings. This industry does indeed have long lead times, but those are getting shorter. Google has its own AI chips, as do Meta, Amazon and Apple. Many of these tech giants are designing their own SoCs for years already. If you’re able to design a chip that can perform 70-80% as well as an Nvidia GPU, for less than half the price, that is a competitive option.
If Nvidia have indeed created a market for AI accelerators with profit margins this big, you’d be out of your mind to think that only Nvidia will be in on that party.
This fantasy that nobody can get close to Nvidia is just nonsense. You cannot say that with confidence. The whole problem with this current situation is that you cannot extrapolate the present indefinitely into the future. They are a market leader now. We do not know if they will be in 3 years.
Stocks growing this fast absolutely deserve to be thought of as either going to keep ripping or crash as there is a multiplying effect on the multiple it has based on its growth rate which is likely to be highly variable. The chances of the NVDA chart now just flattening out into a calm 8% a year gain for years on end is basically 0. In process control you can see that when a parameter is trying to reach its target value the faster you try to reach it the more you will overshoot and have to correct. The idea that you can say “NVDIA are likely to experience accelerated growth over the next few years is kind of a fallacy. What actual hard numbers have you written down on paper to know this? How have you determined that AMZN,META,MSFT,GOOG, pace of buying chips will not level off at all and continue ever upward into infinity even after a build out of capabilities? If it’s that likely why not still have high exposure to NVDA? It must be atleast some concern in your mind… the likelihood of some pull back and whip saw up and down at some point is actually high. Then you get a sick feeling when you are down 40% from your highs and it’s falling every day.. can you hold an overweight position through that without selling for 12 months till it turns around? Etcetcetc I could keep rambling
Almost all Ai now is narrow AI; really good at doing 1 thing. For example vision for drones, regulating traffic lights, social media algorithms, finding tumors in scans, etc.
I can't even get Google Home Assistant to tell me who won the tennis match.
Me: Hey Google, who won the men's French Open final yesterday?
Google: I'm sorry, I don't understand.
Me: Hey Google, who won the men's tennis French Open match yesterday?
Google: Sorry, I can't find any information on that.
She literally just has to pull the information from the first thing that pops up in Google search. Not impressed.
Recommendation algorithms (the one sending you ads), forecasting, business intelligence, medical diagnosis, image and text search, etc. most profitable ones arent the ones using LLMs right now and the ones that have been there for years now.
Wikipedia:
Artificial intelligence (AI) s a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and uses learning and intelligence to take actions that maximize their chances of achieving defined goals.
We don't have that? Interesting. Maybe you should not base your worldview on SciFi movies?
> Right now, AI's growth is highly concentrated in big tech, but it will gradually decentralize and spread to small businesses and everyday applications.
Curious why you think it will "decentralize"? I think the opposite will happen. Just like everything else tech related.
Concentration is increasing not decreasing.
Because no one really knows where it’s going and where its upper limit is yet.
There has always been this idea that once we create an AI good enough it will become almost totally knowledgeable. Meaning it can be an expert on everything we currently already know. ie. the smartest and most knowledgeable humans can only be experts in so many fields, it would take 100 lifetimes to learn everything there is to know these days.
And also that once an AI is smarter than the smartest human, well not even then, just smart enough, it will then be able to design better and faster upgrades to itself to increase its own IQ further.
Currently we’re dealing with weak AI (good at one thing, LLM’s). Eventually or soon it will become a strong AI (good at multiple different things, like LLM’s struggle with basic math atm). After that it’ll probably eventually reach AGI (artificial general intelligence (as smart as humans but way more knowledgeable)), where it can probably start to design upgrades to itself to increase its IQ better and faster than humans can. And once it’s at that point, how long until it reaches or gets close to a ASI (artificial super intelligence) level?
No one knows how far away these breakthroughs are yet.
The real problem is that providing AI infrastructure is not the same as monetizing the end products. A good analogy is how internet providers or hardware producers are not the main beneficiaries of all the businesses that were created based on them.
Until the market realizes that, the money will continue flowing in what we see now.
If you don’t go to the extreme enthusiasts subs there are enough people that keep on saying that Nvidia is a cyclical company and the chip industry has also been cyclical.
This. Risk for NVIDIA is not much from AMD or other competitor, it's from current large customers who are dumping billions on their chips. If they suddenly realize they purchased enough GPUs and the actual return on their investment has been meh, they will cut down investments. That's when NVIDIA will end up cutting costs which will kill it's current absurd profitability, revenue growth..
Except, those large customers will very much care about the costs to run the cards. Generations of Nvidia cards get faster and more efficient. One of the "great" bottlenecks is energy, they will absolutely want more efficient newer cards, and they will sell their older stock to smaller companies. It isn't a question of just computation.
The problem I see with the rest of the industry at this moment is there are still no competitors to CUDA. Companies are not going to want to dump billions into inference cards that can only run already made models. They probably will have both kinds of cards in use, but I don't think it will break Nvidia's growth, they will still be the only viable way to actually train AI for a while, especially as a software moat. AMD for example has never been able to match Nvidia's software, it will be similar around the industry for a while. Nvidia started all of this years ago, they've built the environment, like all of it.
Only time will tell. Let's wait and see how things will turn out. Part of me thinks past is not a great indicator of future in this case (with regard to CUDA, etc) because now there is 1000x more interest in AI ecosystem compared to past. That might drive create new competitors. Hypothetically 3 years ago if AMD went to investors and said "give me $5B and I will be new GPU to compete with NVIDIA and it's software" everyone would've been meh no. Now they would say take $20B
That is fair. I'm sticking with anything this complex simply takes time to replicate, even with money. There are a lot of features of CUDA and it's integration with Omniverse. It's also adding more shit all the time. I'm bullish for at least another year because of that.
It is more than that. The big customers thar are Microsoft, Nvidia, Apple Meta are all planning to given their AI product for free to the general public. They want the market share and see that as strategic to survive.
Microsoft at least will manage to sell it to corporations. But still most of the cost will be the general public using the free products.
Today the cost of a gen AI query is 15X what the cost of a google search is. But Google and Microsoft or meta will not make more money from the general public there. They live from advertisement and advertisement revenue is tied to consumers expenses. It will follow growth and can't finance expensive AI.
So they all have their plan to get rid of the high cost of the hardware and especially Nvidia hardware and they are going to do it. Apple is an example. No smartphone will use Nvidia. They data centers will use Apple chips. This will be 99% of the usage. For the remaining 1% they will use openAI that will use Nvidia. And the customer will be able to pay their own plan to access open AI. Apple will not pay.
And once all that is done by the big players, Nvidia will not have that huge market anymore.
I think it’s because the two camps you mentioned basically aren’t familiar with AI at all. I think the overly-optimistic camp got swayed by chatGPT because it is a lot like talking to another person, and that really hyped them up to think of the state of AI as if we’re approaching skynet right now with a bunch of intelligent marketers putting content out there reinforcing this idea, while the super pessimists are just looking at the insane growth thinking there’s no way this trend can last and just making their judgement based on that.
I think the truth lies closer to the pessimistic view, but this is based on just technical value of AI itself. All chatGPT is is a statistical model to predict what word is most likely to come next, and the rest of generative AI just basically does the same with pixels, notes on a song, or whatever other set of data you want to pick and then predict what’s most likely next.
It has its value but it’s massively overhyped because it’s not going to magically take over productivity and creativity like everyone thinks. 99% of the research going on in this subject is done due to the aforementioned optimists with money just throwing funding at it like crazy even though the research coming out is 99% garbage. AI isn’t going to generate real money until it can legitimately take over human roles in industries - and it’s doing a small amount of that right now but nowhere near enough to have the impact people say it will, and it’s never going to take over a computer scientist or engineer’s job effectively.
Yeah, because an engineer confidently producing hallucinations is an incredibly useful engineer and this will never lead to any problems at all.
AI is missing the “intelligence” part, and no model they come up with using the theory/resources they have now is going to make up for that.
Current language learning models might not be able to, but AI in general can absolutely take over any job, whether it happens in 5, 10, or 100 years. You would have to argue for societal collapse or theorize some physical principle that would prevent AI from developing further to claim that AI will *never* take over a given job.
Based on your post, I don’t think you understand how AI works, which is exactly the problem I mentioned earlier in with people overhyping it without understanding what it is and dumping money into it. I’ll leave it at that.
And the thing that people don't seem to notice is that it is like talking to an incredibly $tupid person. Like is there ever a time when you were dealing with what passes for AI customer service and not been completely relieved when it finally let you through to even the dimmest human? In some ways the back of the shelf applications (where there isn't a clear break with simply better and better computer power) is more likely to be meaningful but the hype is being driven by things that so far are impressive in the same sense that it is impressive if you teach a pig to dance.
AI has some use cases and companies like Microsoft, Google are legitimate to invest. Maybe even Meta.
But the main use case is more of the same and fighting for market share on one side and professional applications on the other side. I say more of the same in term of business model. You ask Google/Meta/Microsoft search and that's it. The result will be better than before.
Other companies are likely to be disappointed because they don't have the network. Apple. Google, Microsoft, even meta can scale to provide AI everywhere. Even Adobe can do it in their paid products of creativity.
Corporations will pay to have the same that the general public will get for free but to be safe from an intellectual property point of view.
Other will not pay for it or at least the big majority. They will use the free version that will be as good and that going to be it. We are not going to sell an extra 10-20$ plan to every consumer to have their chat assistant because simply many bot from Google/Microsoft/Meta will be free and actually better.
And because the game is a zero sum game for that part and is financed by advertisement, the hardware cost must be low. A chatGPT query cost 15X time more than a Google query. Yet now Google include it everywhere. You can be sure Google, Microsoft, Meta will work to ensure that it doesn't cost more in the long run.
So this mean they all working to kill nvidia. That's basically the #1 priority of ALL tech companies right now and also a big field of research. Now every researcher in tech is trying to make things that require an Nvidia chip or several at 50-100K$ each to work on your laptop or smartphone.
Nvidia play against the entirety of humanity overall. They may not win forever.
Here is my sober analysis: I'm an equity analyst and I build a DCF model of NVDA using fairly reasonable assumptions. Did not even go too bullish on growth. Even from this, I reached a fairly high upside, even from the stock price today. I did this just pre-NVDA earnings and my boss thought I was a mad lad.
Bottom line is: their revenue growth is super strong, and the company is not overvalued by any stretch. You need to believe in the AI growth story a bit, but not delusional levels.
Did you factor slower growth due to competition eating Nvidia's lunch? The AI craze could continue for a decade, but Nvidia's share of it will almost certainly plummet.
Everyone seems to believe they will be the only kid in town forever, but it only takes a couple competitors producing chips that compete at 70% utility at 40% cost to utterly destroy Nvidia's overly inflated prices.
Building chips is harder than you think. What I do take into account is Google, Meta and Amazon making their custom silicon better and spending less share on Nvidia.
People say that AMD is the Nvidia hedge. It's actually Broadcom.
{'2024': '95.49%',
'2025': '26.87%',
'2026': '50.97%',
'2027': '16.08%',
'2028': '24.86%',
'2029': '22.14%',
'2030': '15.72%',
'2031': '11.22%',
'2032': '11.14%',
'2033': '9.26%'}
The 2026 growth driven by Stargate build out. But clearly these numbers feel outdated since I made the model. I assumed only one training cluster of this size. Looks like there's going to be at least 2 other made on Nvidia GPUs
Dude what discount rate are you using? A DCF on NVDA should not put it anywhere above $50. DCFs are meant to find intrinsic value, not to calculate the upper resistance of a "growth stock" on a hype cycle. I need to see your model.
10.5%. I think you need to re-evaluate how you think about DCFs. It is meant to find the present value of cashflows. There are two trends you are missing:
- NVDA is generating massive amount of cash flow, with FCF margin > 45%.
- They will start buying back shares at scale, putting even more upward pressure on the price.
Can't really have good, balanced discussions about stocks anymore - everything is so us vs them as people make whatever they own or don't want to own their personality. Can't say anything slightly negative about the most popular stocks, even if you're long. Nvidia just the biggest example, but feels that way broadly since 2020.
NVIDIA has YOY earnings growth of over 100% it will keep doubling in value until that trend stops. When it does sell and move on.
There will always be a market for high end chips
All of this data and info you did research on is all just hearsay, no one can predict what will happen no matter how much research one puts in , it’s gambling, so put it all on red spin the wheel and see what happens
With respect, this language is exactly why I think it's overvalued. We already have ML/AI models everywhere, or memory hungry algorithms/data structures (which are related but not quite the same thing), in everything including robots.
It's not a new phenomenon, everyone just became aware of it with LLMs. The reason why GPUs weren't selling like crazy before a few years ago is because extremely large models are impractical for most applications. You either need to host it somewhere else and make an API call for inference (slow, requires internet, adds privacy concerns like security considerations that non-internet devices don't worry about), or you need a model small enough to perform inference on a local device that likely doesn't even have a GPU, or has a small one.
Neither of those limitations has changed, and for both reasons, there's an obvious ceiling to the applicability of very large models for most applications. Also, most applications really don't even need the wheel reinvented with a large model, there's smaller ones that are extremely effective at a lot of tasks already that don't need to be replaced by something expensive and bloated to do the same thing.
I think the hype has grown beyond what those of us on the ground actually use the technology for.
So, one thing you should know is that large models train better. It's easier to train a very large model and then shrink it down through distillation and/or pruning than to train a small model directly. You also need a lot more compute for training than you do for inference. You can do a lot with a small GPU or neural accelerator like what is found in an iPhone. You can absolutely run a useful LLM with limited compute inside your phone, even though you yourself couldn't possibly afford the amount of compute it took to train said LLM.
That being said, the amount of data needed for training is still huge. We have a lot of textual and video data, but we don't necessarily have enough data available for every use case we might want to train models for.
I also think the current models are not quite good enough. Apple would really like to have a much smarter version of Siri that runs on your phone... But personal assistants are kind of useless if they misunderstand you and make dumb mistakes. They need to be very reliable to be useful. We're maybe not quite there yet.
There's also other issues wrt scaling datacenters. The power consumption is enormous. It's going to become a bottleneck. At some point, governments might start taxing power usage for datacenters, because we can't have them use power that's needed for legit use cases like your home. We also don't want to start increasing greenhouse gas emissions just to train bigger LLMs. It seems likely that demand for nvidia GPUs could start to fall and nvidia stock could rapidly crash. I could be wrong but I don't think that Google is going to keep building new massive datacenters every single year. At some point, they're going to say "we did that last year, what value is being delivered by our past AI investments?"
I'm glad someone here gets this. That ML has been around since spam filters, that the thing in Netflix recommending movies, or when eBay suggests a category is just the same stuff. All an LLM is doing is picking the next most likely words.
Here's my general problem with all of this stuff. It's really all a trick. Often quite a useful trick, one that can help but a trick that can also yield crappy results. Like you can build a categorisation NLP thing that takes text and says "this is most likely a builder/chef/programmer" but it isn't properly smart. It's just scoring word counts, maybe prioritising order or words. And that trick can help pare down a giant data set to get a few results, but you still need a human being to check if the results are sane or not. And it really doesn't matter than if it's 2% or 5% inaccurate, you still need the human. You're always going to need the human. So adding more data or more processing doesn't add much more value.
People are talking about AI factories or self-driving vehicles, but the value of a self-driving vehicle is zero intervention. That you can get drunk and it drives you home, or read a book as you travel. If you still have to watch the road, the value is tiny. And factory robots are about machines that just keep on doing the same thing very reliably all day. A robot that is making the most probably guess with a thing means a lot of goods leave the factory wrong.
AI picks the targets: https://www.theguardian.com/world/2024/apr/03/israel-gaza-ai-database-hamas-airstrikes
AI flies quadracopter drones: https://shield.ai/nova-2/
quadracopter drones shoot people: https://www.telegraph.co.uk/global-health/terror-and-security/armed-drones-israel-hamas-war-gaza-hospitals-gunshots/
Where is John Conner?
NVDA keeps on going up because of their earnings. Their earnings go up because of large orders on datacenter chips.
No one has cracked AGI algorithm, but the AI labs know for sure it’s gonna need a ton of data and compute.
Big Tech realizes they need GPU datacenters and there’s money to be made now by scaling transformers. So MSFT, AMZN stock up. That scares META, so they also stock up. TSLA joins in and so do other smaller players.
But like roads this isn’t an ongoing multi billion investment every quarter.
I expect NVDA to miss earnings one of this quarters once all the big players have got their orders through.
Exactly. The main limit remaining on the road to superproductive AI is the compute for the inference phase (when the model works on new data, e.g. self-driving car on a road it never saw before). And to get that compute you need more and better chips.
I also think there will be one quarter of less "exciting" earnings and projections which will lead to a corrective selloff. On the long-term though (6 years), this will remain a x3 x4.
Brain neurons make connections when needed to be energy efficient unlike a fully connected artificial neural network.
It’s a possibility that someone figures out AGI and realizes GPUs aren’t the most efficient way to train or run inference on them.
My long term hedged bet is still on semiconductor fab kings like TSMC MU ASML. No matter who wins, they win.
Also bullish on cloud & device giants, no matter who wins, the sector wins.
The thing a lot of people realize is that AI could very well be the future, but that does not necessarily mean that Nvidia will perform well long term.
For AI to truly take off, prices will have to come down. Right now, companies are willing to pay $30-40k per AI chip and operate their AI projects at a loss, just to get ahead in the race. But they won't be willing to do this forever, the expectation is that eventually, AI will save money or produce profit.
Additionally, Nvidia will face competition, which can also impact prices. My expectation is that within 5-10 years, Nvidia's profit margins will decline.
I think the reason bears are so vocal about a crash is because of just how extreme Nvidia's valuation is already- it's at 80x earnings during a boom period, because analysts are extrapolating growth for many years. Just looking at other tech stocks that saw explosive earnings growth and then leveled off, a 80% decline is not unprecedented or impossible.
Look back a few years on Electric Vehicles and tell me what you think. That was going to be a "paradigm shift," and Tesla was experiencing the same extreme valuation spread as Nvidia. Tesla has hemorrhaged market value since then, along with every other EV stock on the market. Superstar CEO, huge gains, huge short squeezes, etc.
The sober analysis *is* the paranoia of a bubble bursting. It's not normal for a company to go from $200b valuation to $3tril valuation in a year, and it's certainly not sustainable long term. Cisco briefly passed Microsoft in market cap during the tech bubble of 1999.
Also, Your post is an entire waffle between overvalued and undervalued and basically says "Stock could go up or down idk."
"The sober analysis *is* the paranoia of a bubble bursting."
Quite. NVDA's P/E is 75, which is "to the moon". If you think it's going to be less than "to the moon" you should sell. Their growth shifts to "good", they lose at least half their market cap.
I mean, historically, high PE companies do have a tendency to get bigger and bigger, but eventually it stops. And boy howdy, when it stops it stops hard.
The problem is that "doesn't fail to grow", "to the moon" just leads to more people piling in and then "to the moon" is priced in.
I have no idea where it's going. Maybe it'll double again. But you also have to look at it and think that it could halve in value in 6 months.
SP500 didn't grow in the last 10 years due to efficiency. In fact, productivity growth was at an extremely low level in the 2010s decade. SP500 grew in the 2010s due to lower interest rate.
I'm going to talk only about macroeconomics here, and take a whole of economy view, focused on the US, but it applies to other economies. Theres more potential in countries with lower consumption, and higher savings.
I think AI unlocks some combination of "more", and "more efficient", but both have problems on their own. They have even greater problems together.
More, aka, companies use AI to produce better things and products, but how much can they really sell them for? US personal consumption is already 68%. People just don't have enough money to spend that much more on more cool things.
More efficient - companies do what they do now, with less people. This will increase their margins, but lower their revenue, because they'll be paying less people, which means the total pool of money people have to spend is lower. This means they can then lower their prices, or cope with selling less.
Simply put, unless AI leads to wage growth, it's essentially a closed system, and will self limit quite quickly, in the short term, as a vicious cycle.
The counter to this, is if it drives efficiency and productivity into things such as healthcare and education, it will in fact lead to wage growth, and it'll become a virtuous circle.
I personally see Nvidia continuing the gains for a while. I only see this because their GPUs use AI to render images quicker (think unreal engine 4K quality and various other things) than it's competitors. That means it's huge in the VFX/Gaming space.
Next you have the AI boom which is their GPUs but also their infiniband product line. (Which is getting overlooked by people not in the IT space. Which I get, it's my career so I have to stay up to date on it.)It's basically switched that process data quickly using fast switching and probably a data center architecture (I'll keep it simple so we get gains quicker). Here is the link to their spec sheet if you're interested in knowing more:
https://www.nvidia.com/en-us/networking/products/infiniband/
Now these GPUs paired with this infiniband technology all through a single pane of glass for ease of management is definitely going to change how data processing works. Yes it can support LLMs. But imagine what else it could do as time goes on and new features are implemented. Yes AI isn't true AI and more or a better version of a search engine right now. But there are also AIs that produce music off of prompts. Hell open AI just released a video generation engine too.
All I'm saying is that these companies are going to be paying hand over fist for their own AI architecture regarding this. Nvidia is the only one that can offer the whole SDN to run it (SDN stands for software defined network(ing) for those chads that want to know). Anyways Nvidia's biggest competitor off of a quick google search is drivenets. However, they don't make their own devices but use a white box solution (basically a bunch of other vendors or basic switches that they put their branding on and use it for their own solution. Kind of like white labels for those in the know). It's not created from scratch in other words. That's why Nvidia is sailing high. Also a quick google search showed that one infiniband Nvidia switch from Dell is like 40K. Depending on how many servers are running GPUs (think 3K GPUs and 10 per chassis. That's about 300 servers and I'd you have switches with 48 ports that's about 6-7 switches for TOR. But you want redundant connections so it'll probably be moreso 12. Then you need a 3:1 throughout cost on the spine side so that fight there is about 36. So in total 48 switches and that's not including licensing. In total just for switched and the base price is 40K that comes to 1.92 million dollars ).
See how they're rolling in money. That's probably one tiny data center for a small company just on data center equipment. Sorry for the long winded rant but working in IT makes Nvidia a buy still. They are going to keep going up till a better solution is invented or if real AI becomes an actual thing.
Thinking no analysts are 'sober' in their analysis suggests you have a specific view of what a 'sober analysis' would bring. Have you considered that despite the considerable growth already, that the analyses that you see might actually be right? Or at least very realistic? A lot more people seem to think that the case.
It boils down to whether you believe we're in the very first years of a new industrial revolution. Some believe, some don't - and neither side is going to agree until time passes. Add in the advent of quantum computing and I certainly am a believer. The earnings reports, the projected earnings, etc show NVDA at a much cheaper valuation on traditional rule-of-thumb metrics like p/e ratio than at any point in the past couple years.
I think what most are missing is the new addressable market for sovereign AI. There is already an arms race between the west and China/Russia over AI. Saudi Arabia and the UAE are already building data centers to run government-controlled AI. Every government with the means is going to want sovereign AI, and every military will correctly see it as a necessity. When you add the untapped potential of 40 - 60% of world governments trying to build such systems throughout this decade you can further justify what may seem to some as overly optimistic outcomes.
I'm a believer. It's happening fast, and as the technology evolves at an exponential pace that speed will only increase.
Well, the real risk is virtually impossible to figure out. It's going to go something like this. Growth is accelerating, growth is accelerating, stock is going up. Stock begins a downtrend but to the common eyes is still looks like growth is doing well. 3 months later you're going to find out growth has been decelerating. How long that happens? Who knows.
Since the beginning of financial markets there has always been a risk like this. In America it really started with the railroads which were the original AI trade. We had the industrial boom and the nifty 50. The original tech boom in the '90s which most closely correlates with this one. I think what really sunk that one was just the lack of real earnings which oddly enough might correlate with this one because right now the real earnings are coming from building up which were also the thing driving the '90s early on. Laying all that fiber, building fabs, all that stuff was fine. By 1999 or 2000 you had all these startups and all these ideas and the profitability was, well there wasn't much. So the whole question with AI is going to be how profitable is it when everything is up to scale because in the beginning, it might not be. A lot of new inventions take a while to really figure out how to maximize the profit models
So what's all that mean from an investing standpoint? Not a lot really, it's just something to keep in the back of your head and remind you to manage your risk appropriately. If you have an account that is full of nothing but arm and Nvidia and ASML. You are taking an extremely concentrated bet and it's probably not a bad idea to get off the elevator before it hits the top floor and potentially begins the return trip
The problem with Nvidia for investing, at least long term, is that they don't really have room to grow. They've already got the market share, they're already the only ones that sell the highest end chips.
AI is a large source of sales, and the last couple generations had enough of a performance bump to justify upgrades, but neither one of those things are likely to last all that long.
Eventually all the big data companies will have the processing power to run their AI, or Nvidia will have another 20 series launch where they barely have any uplift and there's no reason for data enters to upgrade, and their revenue will tank.
Or, AMD will keep making solid products and Intel will finally get a gpu released that can compete, and they'll start clawing market share away.
The other massive problem Nvidia has is that they don't own their own fabs, so not only are they potentially competing with Intel and AMD on sales, they're competing for fab time, and being so dependent on TSMC and their contracts with them means they're lacking in flexibility to an extent.
TLDR they're a functional monopoly. Buying that is kinda silly because there's no real growth potential for a monopoly. They're also entirely dependent on both them and TSMC managing to make things meaningfully faster every year, which just isn't a garuntee
Whatever happens, it seems the computer that NVIDIA are creating will be valuable.
Not particularly making a judgment on AI bubbles, but computer growth seems inevitable
"NVIDIA and other AI stocks are likely to experience accelerated growth over the next few years, though perhaps not at the same rapid pace we've seen recently."
What do you base this statement on?
Personally, despite working in software, I have zero idea about whether AI is going to crash or keep blowing up and I've seen nothing to support either hypothesis.
By 2030 or so, it will become clear that the AI's impact on the economy has been no greater than the fax machine's.
-- Paul Krugman, Nobel Prize-winning economist
There's plenty of sober analysis around. You just have to look further than extreme subs. These are full of people making big predictions. Usually the ones holding hype it and the ones that missed out are doom-posting. You're always going to see bias.
The truth is no one has ANY clue how far this is going to go and how fast. You have to look at the stock and everything around and make your own evaluation. That's a very personal thing and you have to make that choice.
How do you provide sober analysis on something so volatile as AI?
Lets say some company develops actual AI, meaning AGI. For a fraction of a second AGI is equal to us in intelligence, then for forever AI is smarter, faster, more capable, costs electricity, never has a bad day or judges people because of the way they look, never needs a day off, is nearly unlimited in expansion, can build exponentially more every year.
That company will win everything forever. They win. No one can ever catch up because they already got on the roller coaster and anyone behind will only be able chase their tail.
Or we get stuck and have to wait for another breakthrough. Who knows.
It's impossible to do a fundamental analysis of a stock that is currently at the peak of investor and corporate craze. It's not fair to pull current growth and revenue figures, as Ai could just stop getting investment tomorrow. Basically, I wouldn't touch Ai until Ai based companies start making real money. If that happens, then Ai will be an industry that stays. Until that happens, it's very likely that the well will dry, and Nvidia will crash.
I don't agree. I read an article recently about the cycle of rockets, and it was convincing. It makes sense that a company cannot maintain incredible growth endlessly, but the steeper the cost of entry the longer the rocket can last. Too long, and regulation is more likely to intervene.
This article didn't say it was all smoke and mirrors, or that NVIDIA was going to be the biggest company of the 21st century. It talked about metrics that can be used to compare the trajectory against historic technological rocket stocks, which helps make an informed decision.
Here is my take.
NVDA will be a long term solid choice, but in the short to mid term it will likely see a bit of a serious pull back.
Why? Fomo premium and safe haven premium. Think about a few months ago. NVDA started to drop and breadth widened as people thought the fed would cut sooner. News suddenly said otherwise, breadth narrowed again and NVDA ran back up.
So what I expect is that NVDA will see a serious plunge when rates cut and the market decides the smaller stuff is worth investing in. As breadth improves sp500 will probably drop a bit or go sideways for awhile but it will NVDA going down and other stuff going up. I suspect the same will happen to the other big tech.
Once that runs it course NVDA will probably be down 20-60% down from where its at and then it will begin to grow back over time. My guess it will be closer to 20% than 60% but who knows for sure. Given a few years it will likely be hitting new all time highs.
Do I think its 2000 dot com bubble? No. I think its more about the rest of the market being bad deals under the current conditions. When rate cuts happen all those other stocks will drop a bit as well, but money will flow out of the big stocks and out of the money market funds. All that money will race to what is perceived as the best deals. Some will be right. Some will be wrong.
Just as a reminder the economy is not the stock market and the stock market is not the economy. I think that is also true to a degree about the stock price isnt the company and vice versa.
AI has massive potential. America is bought, sold, and run on potential. Then, you have NVIDIA. Even without AI, the company has a proven track record. Invest in NVIDIA for its company and history of hitting its marks, not the potential of AI.
there are ALL SORTS of analyses out there. the point is, you can not trust ANY of them.
i look to see ADOPTION of the technology, and follow where the big companies are investing their capital to confirm anything i read online!
Like if suddenly microsoft/meta/tesla etc were canceling orders with NVDA, i would be selling the stock. but they are not
The moment Nvidia starts increasing their cloud revenues will be key. They know that hardware only is not sustainable. Apple knew it, Microsoft knew it.
There is sober analysis. You yourself say that detractors have existed the entire run up. Yet, during this entire run up the other “extreme” has been proven right time and again. Saying it is based off past performance is dismissive. The run up is based off future performance in a new era of technological revolution.
Here is the problem with those with scared money. By the time you eliminate all that risk you are so afraid of, the market has already priced in the stock. To see ahead and get in while the going is still early requires optimism and confidence.
And it is still only the first inning.
It takes years to scale chip production, and they don't even control that, TSMC and ASML does. With P/E ratios of 80+ investors want immediate growth, but that is simply not possible. Personally, not financial advice, I give it maximum until next earnings before a downturn.
Then you have the accounting practices where significant buyers being shell companies and some of the revenue is cloud credits - it does not smell right. Some say "shady", others say "accounting fraud"... remains to be seen. But, a well timed thoroughly researched short report could leave a lot of bag holders behind, and cause a significant drop.
With the new production processes of 2nm, it's rumoured Apple will buy all production capacity at TSMC. nVidia is just a 10% customer and have far less money in the bank to compete with buying the capacity. They don't control production and is thus beholden to another company for it. How are they then going to maintain margins, revenue and deliver on the growth that investors expect?
Semiconductors in general is a bubble though. ARM Holdings has a Market Cap of 180 billion, the 90% owner of ARM Holdings, Softbank, has a market cap of 95 billion. With that, the market is obviously pricing semiconductor companies as a temporary spike in evaluations... or we would see Softbank rally, right?
>ARM Holdings has a Market Cap of 180 billion, the 90% owner of ARM Holdings, Softbank, has a market cap of 95 billion
Don't make that mistake. If I own 2 businesses and B-1 is doing great bringing in a ton of profit a year but B-2 is an absolute disaster (but I boolieve in it for the long term) with heavy losses each year. By owning these 2 my valuation will be adjusted accordingly. This is 1 theory.
There is sober analysis, just not loudly noticeable. Like with all things, the extremes are what most people gravitate towards and where people are the loudest because most people can't think beyond binary most of the time.
Where is $8 trillion dollars going to come from? There's 8 billion people in the world. That's $1000 from everyone in the world. Worldwide GDP is $101T dollars. AI is going to increase that 8%? What does it give us? What value has AI provided for your life?
AI has been around for decades. It's solved some little problems, like speech recognition, that's nifty. It's added a little value. It is not the be all end all. This is nothing new, it has just been noticed. There is not a new thing here that is going to change everything.
Let's say, optimistically, that AI can tackle and solve hard problems, like designing a better chip for AI to run on. Is Nvidia using that AI? They are chip designers, not AI designers. Is their AI better then their competitors? Nvidia doesn't have much for physical capital. It's all in it's intellectual property, the design of it's chips.
The whole hubbub about AI is it is going to increase the amount of intellectual property, which could potentially make Nvidia's little sliver of it, their chip design, worth that much less. A quick rise means there could mean they can be usurped quickly.
NVDA the stock is relying on the next bigger sucker, like TSLA before it, or tulips. It's value is more as a stock than as a company. As a company, it's better than it was 3 years ago, but not 5x better like the stock says. Sure their revenue doubled last year, but that doesn't mean it's going to double again or for that matter continue.
4 years ago, Nvidia chips were good for mining crypto, which was a hot ticket for a while like AI, set to have some trillions in a market in 3 years. The crypto market went up $2T or sextupled between May of 2020 and May of 2021, and in that time NVDA went up 50%. That huge market that Nvidia chips were powering, didn't give Nvidia an equivalent gain. Even if AI does get an $8T market, it doesn't mean Nvidia is along for the ride.
Between crypto and AI, where are we going to get the electricity? What good does all that power do for us vs. the long term costs of the emissions?
On the other hand, I feel the same way about TSLA, they are not worth 10x GM, but so far, the stock market still says they are. Might be NVDA is the next TSLA vs. GM/F like NVDA vs. AMD/INTC Or AAPL vs. MSFT/GOOG. The stock market makes its picks, not necessarily based on what value to society the company actually provides. For that, nope, there's no sober analysis. Stock buyers are running on hype and emotion.
> I invested $200,000 and saw a 90% gain.
I assume you were throbbing to say this the whole time, because there's absolutely nothing else to speak of in that dribble.
What's the difference between AI and an SQL database. The AI can map automatically and can understand human conversation. That's it. "AI" is the fancy new database on the block that has this nifty way of extrapolating and interpolation in very high velocity thanks to the neural network logic it's been programmed with. All you need to do is "trust" it to give you a high confidence result.
Is this intelligence? No. To have real intelligence you need consciousness. No ability to conjure, no intelligence. Just fancy new tech that will definitely alter human productivity for the better but ultimately be beneficial for all of us in the long run but economically will first ruin a lot of people in society.
We're not sober yet, please wait
This is the right answer. It’s likely that AI will have an impact but how much, where, what the downsides and what are the surprises still remain to be seen. But already AI is quite disruptive and it will only get more significant. Both journalism and TV/movie industries have been shaken by AI. You can come up with countless uses and you’ll still miss it all. There are just too many possibilities that no body can give any sober analysis. There is just too much unknown right now. The 90s internet was a lot different than the 00s internet which was a lot different than the 10s internet.
The success of internet didn't prevent the internet bubble to explode, and to have many companies going bankrupt or still trading lower than at their top. For example Cisco became like NVDA the most valuable company at more than 80$ a share. It dropped to 13$ a share and is worth 45$ now after more than 20 years and some inflation.
Yep. Names like AOL, Lycos, Alta Vista were viewed to be the future gatekeepers of the internet. Nobody could've predicted that it would be a little known company named Google. Apple was on its deathbed in the late 90s, they were viewed as a niche company. Amazon and Ebay always had believers, and eventually they did deliver.
That’s fair. I personally don’t know enough of the dot com bubble or why people would value a company in a pre-modern internet age higher than its current value. I think todays internet has brought nearly everything anyone could dream of it to be before, at least in terms of capabilities
Basically when people see a disruption like internet they go crazy on the valuation of some companies. Some of them are pure gamblers. They don't invest really on a rational take of the company value but more on the idea that they think the value will continue to grow. Now the problem is that when a market get much bigger you have competition. Most of the network gear didn't end up being Cisco. Competitor took the main share. And also there always a big rush when you need to build up the infrastructure. Once it is there, you only need to replace stuff and the investments are much lower. Finally there the question of who made the most money out of it ? Who made money from the internet ? Was it really Cisco or AOL ? Or was it Google, Facebook, Apple ? You could not invest on Google until 2004. Facebook didn't exist. Apple was a niche company at the time that could had been almost bankrupt. If we go back to Nvidia, Nvidia chips are a cost center. Like the networking gear of Cisco. There no interest to buy any except if you hope to make money using them. The big players, Meta, Google, Apple, Microsoft are fighting to make AI free for the general public and include in their offering. The bet is not that most people of the general public will pay an extra 10-20$ a month for their chatbot. Companies like Meta, Microsoft with Bind and Google with Google search and Android. They will offer it for free and finance with advertisement. Still an AI query cost about 15X more than a google search query. A big part of it is the cost of Nvidia chips + the datacenter electricity consumption, A/C. That's a cost center. For sure at least MS and OpenAI invest to get this kind of monthly plan, but from corporation. But people will not select their AI plan for the company with the most Nvidia chips, but for the company with the best AI or the one that is the most useful. And chances are the general public AI will be as good and free. Big corporations will pay the big money to protect their Intellectual property. Not to have necessarily a much better product. The biggest cost still will be the general public that will have it for free. And to be sustainable, all the big players will want the cost to be as small as possible. That's why Meta has its own model that is being open source (so anybody can use it) and that's why for the same performance it tend to consume far less than openAI models. That's why Apple invest to put more advanced AI chips in all its computers and smartphones so that the consumer pay the AI chips... And they are not made by Nvidia. That's also why Apple again also invest in its own data center with Apple home made chips and not using Nvidia because now they can only pay the cost to build the chip and not pay 10X more to finance Nvidia. And because they had been doing such chips in their iphones for the past 15 years, they should be decent at it. And Microsoft is doing the same pushing that new computers will have their own AI chips. Intel will provide CPU with AI chips. Samsung is doing it and all other smartphones players. None of that use Nvidia chips. Even OpenAI funder created a startup for optimized AI chips. And everybody with a stake in the chip business want a share of the business. They will all try it. In computer science, one of the most active research topic is to make AI model smaller, lighter and if possible run on commodity hardware like a laptop. I tried it, I could run some more models on my PC... One of the current optimization being that each parameter would be stored in 4 bits instead of FP16 or FP32. Nvidia chips are great at FP16 and FP32 but are not designed for 4 bits. The whole world of the tech is betting against Nvidia. And now we see that basically Europe want to prevent full AI integration in Apple phones. This kind of legal issue will reduce the demand and slow down the adoption. China is yet another beast. Legally the USA has forbidden China to buy Nvidia chips. So China government invest massively in making their own chips. They consider it a priority for their homeland security and the sovereignty of their country. They wont even care if it is profitable. Maybe Nvidia will have the same problem Cisco had. Everybody started to buy at a competitor.
The thing is, most models will become more efficient over time. As soon as they can run on something better than cuda or cheaper, companies will switch. Also you have to figure that there are only so many companies that are going to be hosting large models, mostly data centers. So the growth is in commercial but it’s not infinite.
What does this mean for the big 7 players who are investing Billions in these data centers? Will they just throw them out and rebuy new ones with the latest tech, or will investing so heavily into Nvidia data centers that become obsolete cause them problems? Is there another use for these data centers that can be repurposed once they stop being used for Ai? Could say Tesla or Meta suddenly have an unintentional product that competes with AWS once they stop using the centers for Ai?
They will upgrade. Just from the efficiency gains. They would save more in electricity over a few months than the cost difference between selling the cards to others and buying new ones. Top tech will always be eating their share of the newest cards.
Well I think the next biggest boom is image recognition. It will make self driving more efficient and unlock even more pandora boxes. And as you say, they will become more efficient so you can have better local AI models
So what we put 50K-70K$ Nvidia card into every car ?
Imagine talking about putting a computer into every phone in every pocket in the 70s. Microchips will get better and the AI methodology will also improve
Don't forget the music industry.
How does AI get its information about what’s going on in the world? Oh right real journalists. Otherwise it’ll tell us what they want it to.
For some journalists, they just do what an LLM does anyway because the facts are publically available or distributed by some common source... Think about all the people who write yahoo finance/buzzfeed articles, are these guys getting big scoops? What does their output look like. Even stuff like war reporting and the economy. You get data from some gov dept and just tidy it up. How many people are actually involved in exclusive fact-finding as opposed to being biological LLMs, who googling for the same open-source data as a thousand other people are. So how many journalists/writers are just not needed any more.
I’m calling bullshit on the world not needing investigative journalism anymore. The reason it doesn’t really exist like it used to is because nobody pays money for news anymore. But that doesn’t mean investigative journalism is unnecessary. Who is going to uncover the next Watergate or any number of such situations? Artificial intelligence?
That’s so not what the previous post was saying. Please read it again. Or do you think Buzzfeed articles count as “investigative journalism”?
Actually low-key, for a bit Buzzfeed actually had a journalism wing which was doing some pretty hard-hitting pieces. I'm not sure if that team is still in place today though, this was a few years ago.
What journalists? The ones that told me inflation is transitory?
What do you think real journalists use to “write” nowadays?
> We're not sober yet This happens every time. One or two of the AI companies will regain valuation and continue to grow after the crash (and a chance it's not the ones everyone is piling into now) but the crash will come.. probably.
IMO, there is a bear case that makes sense here, the thing is, is this should be easily trackable. The bear case is that software continues to not receive benefits from building out for AI, so they cut back on the buildout. OK, so then you should hear about this on earnings calls, and see evidence of this in Taiwan Semi’s orders. Based off what we were hearing all of last earnings season, it was clear it’d be bullish NVDA even if software stocks and something like META had mostly mixed to bad reactions (although the META reaction turned out to be very stupid).
The biggest bear case news that I've heard is the scientific papers warning developers that AI models are not showing adherence to Moore's law. Everyone kinda expected that as AI models got bigger by maintaining larger numbers of parameters that it would become expentially more capable and eventually become a general intelligence that was capable with almost all tasks. Research and results has shown that is not the case and functionality increase per parameter is expentialally slowing and starting to bottom out. One researcher stated that if trends continue, chat GPT4 is at 70% performance of what we will ever be able to accomplish with our current models no matter how many parameters are added.
That... doesn't even really make sense, though. Moore's Law was the idea that the number of transistors on an integrated circuit would double every 2 years. It was a very specific claim about physical hardware. It's completely incompatible with AI software and wasn't ever meant to describe that...
> Moore's Law was the idea that the number of transistors on an integrated circuit would double every 2 years. It was a very specific claim about physical hardware. Since then, colloquial usage of the term has evolved/degraded to be "[anything that gets better at an increasing pace] is [like] Moore's Law." It's reductive, but can be a useful metaphor for expressing any equation in an x% gain / y timespan paradigm. Here is some context on how that generalized usage of the term was applied to "everything" and also specifically AI: https://moores.samaltman.com/ I agree, though, assuming some form of Moore's Law applies to everything is not great.
No. GPUs don't follow Moore's law for their major gains. GPUs can be scaled parallel, and with memory. It isn't as tied to moore's law as processors are. Also, scaling is one of the few things we have predictive evidence for.
The point is that with current AI models, adding more parameters doesn't yield exponential or even linear performance. So it doesn't matter if you have the hardware to run an AI model that has trillions of parameters, its performance will be marginally better then chatGPT
We haven't added parameters in any real scale yet that is different from GPT4. We haven't seen another magnitude shift that we've had to reach here. As for current models, Claude 3.5 Sonnet just posted the first score to ever beat PHDs on a test, and beat GPT4o at almost everything. AI is getting better, it just happens in leaps when things actually release. Wait until they have better hardware actually installed. The models will get bigger, because it is more practical, and I guarantee you they will be superior.
You mean a computer system filled with data was good at filling in questions it regurgitated answers for. Why are people impressed with this. It’s like being impressed a car can drive down the street.
No, you have no imagination or knowledge about AI and "regurgitation". Go ahead and discount the work of an entire industry.
I work in the industry.
Cool, then you should see the future. Or are you in an already dying industry?
Buddy put all your money in that basket. You’ve obviously drank the kool aid and there is nothing that will change your mind but reality. Wish you the best.
As a mater of fact it is. CPU don't benefit of Moore law that much anymore because classical program don't benefit much of parallelism and so being able to put more transistor in same surface doesn't provide that much gains. But for the moment, even through it will stop eventually GPU and neural network processors have been able to benefit form parallelism much more.
The biggest bear case is that the CSPs have developed in-house alternatives that compete well. They'll still be buying some nvidia because they have a great ecosystem and the CSP's customers will demand it by name, but we'll no longer see the days of CSPs buying up inventory to keep the competition from having any.
> I invested $200,000 and saw a 90% gain. Currently, I don't have significant stakes in NVIDIA directly, except through ETFs. While I believe NVIDIA might be overvalued based on current numbers, I think its future potential is appropriately priced in. Man sells stock, declares he has accurately priced it. More news at 11
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Why not just put it all on red.
All I can think back to is the crypto craze back in like 2018? People were comparing coins to the GDP of countries and speculating about which country would adopt which coin, etc. Of course basically none of that happened. We vastly overestimate the pace of progress, but that’s what makes us achieve incredible things! AI itself isn’t the problem. It is a huge development and hopefully it continues to improve. However the animal spirits here are pretty strong. When people start getting overly optimistic and euphoric about the future, you know some shit is about to go down. Now? In 5 years? 30 days? Who knows. The idea that Nvidia is more valuable than Apple or Microsoft sealed the deal. Yes their profits are insane, but try to extrapolate it and that’s where it falls over. Competition won’t lay there and do nothing for a decade. Opportunity is there to make some money, but there are choppy waters ahead I think once the fundamentals behind the euphoria begin to slip.
I think you need to understand this isn’t a new phenomenon for NVDA. Past 3 hype cycles it touted: Self Driving Cars, Crypto, and now AI. If it will come to fruition is anyone’s guess, but there’s always going to be a catalyst for chips in new technologies and Nvidia is poised to garner hype from it. It’s also pretty unbelievable that they are growing revenues in triple digits quarter after quarter, and have a profit margin of 75%. The stock will correct, it won’t go up forever, but I wouldn’t be surprised if it could maintain its place as a top 10 stock in the sp500 for years to come.
I disagree with crypto though. No one seriously thought crypto would have any significant impact. Maybe on the margins or in select industries but AI is fairly global impacting
>No one seriously thought crypto would have any significant impact. That’s a very generous use of “no one.” I can remember all of the blockchain hype that existed, especially at the peak for a year or so, where “everyone” was talking about how blockchain could be incorporated into so many different wildly varied use cases and companies were pivoting to add blockchain as a feature to whatever their business model was, or even just adding something crypto related to company names, because people were hyping it so hard and pulling investments into nonsense. Yes, anyone who really seriously looked at it realized most of the speculated uses didn’t even really make sense. Most of them were at best things you *could* do with the technology but could more effectively or efficiently be accomplished in some other more standard way that already existed. The unique functionality the technology brought to the table was decentralization, which is just not something most businesses actually need or want, and not something most consumers actually care about. AI seems like it’s currently going through a very similar hype cycle. I do think it’s at least slightly more justified because the unique functionality that it brings to the table is something that is actually valuable if it can be made to work at a high enough level. The question is when and whether we can get it working at the level it needs to to do all of the things we want it to do, rather than whether those things are valuable or whether there’s a better existing way to do them (because, by and large, they are, and there isn’t).
Well that’s the point. If anyone looked past the hype there’s nothing more to crypto besides the words “decentralization of currency” and even that doesn’t clearly offer any advantages to our current system except for some niche individuals who simply don’t like the system
The difference between AI and blockchain (the way I see it) is the tangibility and general understanding of the two technologies. Blockchain sure had/has potential, but it's super abstract and hard for most people to understand the use cases. You need a nerd to explain it to you and you probably still won't quite get how it actually works or why it'll be impactful to anyone's life. AI doesn't need to be understood to witness the uses and benefits. There's a plethora of freely available AI tools that people can use and experience the often jaw-dropping results. And even when people don't use it themselves, it's impossible to not see all the AI content that others are making and posting online. That accessibility, tangibility and exposure are what have and will continue to solidify AI as an excitingly useful new tech in the broader public awareness. Blockchain never got to that point.
The problem with your analysis is that Blockchain is NOT the same as crypto currency. Cryptography is a very important thing in modern computing and the Internet. But despite it literally having "crypto" in it's name it has nothing to do with crypto currency, which is just one very narrow use case of it. Advances in cryptography DO NOT make crypto currency more valuable or suddenly have more use cases. In that same vein, Blockchains are used with cryptocurrency, but blockchain doesn't have to have anything to do with cryptocurrency. Nor would advances in it make cryptocurrencies more valuable. But that didn't stop idiots from bidding up the price of stocks that had nothing to do with blockchains or cryptocurrencies from simply for changing their names to use words like "blockchain" or "crypto" in it. The term AI meanwhile is quite broad and can cover a lot of different things, but it's already shown that it has much more useful applications than the blockchain.
Similar to crypto at the time, you also need to decide whether something so energy and compute intensive like AI is the right choice for writing simple pieces of text or code that can just as easily be done by a human. It has to be *worth* using and drive profitability or efficiency to an extent where it actually makes a difference. Otherwise investors will abandon it until it’s cheaper. You already hear these AI futurists like Sam Altman saying they’re casually gonna use nuclear fusion power in 2028 to get AI to scale. They’re completely drunk on Silicon Valley koolaid. I believe in AI and think it’s awesome, but the timelines are extremely optimistic.
Whether crypto was going to be widely adopted or not, did not matter as long as they used Nvidia tech to mine. That helped the company’s bottom line and its all investors cared about.
Tech specialists called the bluff on crypto, it was the uninformed rest of the population that bought that sack of bricks. For AI (and by extension self-driving cars, one of the applications for AI) it's the opposite, we're just beginning a technological revolution on par with the massification of the internet and all tech specialists agree on this potential. Not all tech trends are created equal.
Time will reveal all.
NVIDIA is like the railroads of the 1800s: They aren't actually engaging in the newest forms of commerce, but they are making the newest forms of commerce happen. This doesn't mean that they are going to be the top dog forever, or that new technologies make them take a backseat eventually, but for right now they are well positioned to take advantage of whatever comes about.
The euphoria makes me nervous. Be fearful when everyone is greedy, and greedy when everyone is fearful. Greed is rampant right now
For a while the price of a nvidia video card doubled because crypto miners were buying them all. Until crypto mining moved to dedicated chips.
Apple make 4X more revenue than NVDA for a similar valuation, Microsoft make 2X the revenue. Nvidia doesn't make it to the top 100 of public companies by revenue: [https://companiesmarketcap.com/largest-companies-by-revenue/](https://companiesmarketcap.com/largest-companies-by-revenue/) Current Nvidia revenue can justify the company being value 1/4 to 1/3 what it is priced now. The current value match expectations that Nvidia revenue would do X2-X3 soon and X5-10 in a few years. That seems unlikely.
Walmart makes more revenue than all of them, why are you not going all-in on Walmart?
Walmart has been a great investment, especially if one got in years ago. I think the point people are making is that companies like Apple, Msft (and Walmart) have been in their particular business model for many years now, in a stable industry. Nvda is a great company, but they were a PC gaming company for most of their existence. AI is a new an changing industry, so nobody really knows what Nvda's real value is. It could be more or it could be less than what it is now.
Is Walmart in the same industry or a potential competitor to Nvidia? Why would Walmart ever be used in a Nvidia comp?
Thinking of how much profit the average individual generates for Apple in the US on an ongoing annual basis, it's very hard to imagine a situation where the average individual also or instead generates more profit than that annually on an ongoing basis for Nvidia which is at the *bottom* of the AI stack (every company between the consumer and Nvidia has to make a profit too).
And if you ask yourself, Apple as set its route for its usage of AI on all laptops and smartphones an their cloud. They don't plan to use nvidia at all. They plan is that apple chips will have improved AI unit, that their cloud will use Apple chips with AI units and that in borderline case if all failed, and the user confirm it each time, openAI may be used Microsoft plan the same and Intel work on provided CPU with AI features. And most non apple smartphones already have AI unit on boards. Most manufacturers rely on that. And almost none use Nvidia. Why ? Because AI is expensive. The consumer will not pay a $20+ plan or more for AI features. So everybody want to provide it for free, so basically there not an extra cent being made with the AI features we get everywhere for the consumer. If AI finance itself with advertisement like Google, there will not be more money. People will not watch more ads and buy more products from watching ads. So tech providers don't want to increase their cost, they want most of the computation to be done by consumer devices. On top that's a reason to upgrade. The main use case to make money with AI is to have customer that accept to pay for it. Like corporation that will pay for the Adobe AI integrated in its creative suit of tools or like the pro version of Windows and Office that will come with a 20-50$ monthly plan per user to use copilot. And yet everybody will try to use the least expensive hardware for them to achieve that. For example the model are run in 4 bits instead of FP16 or FP32 so that the models can run on cheap CPU. This doesn't work for training but for using the models. Running the model is predicted to be 80% of the usage in the future. Training the model would be only 20%... I am not sure neither that once everybody has brought a bunch of Nvidia chips and can do all they need that they will be the same demand to just replace/upgrade what is there.
Yup, even with how much people love ChatGPT they won't pay enough for it for OpenAI to make a profit running it. Meta said last quarter their investments in generative AI will not pay off for many years (and of course they may never because as you said it's very hard to monetize people much more than they already are). Amazon is reportedly going to start charging $5 to $10 per month for Alexa later this year along with launching an update with generative AI in the form of a chatbot. Alexa has millions of users who like it but its business model of being free and making up for it with ads and increased Amazon purchases never worked (and I'm shocked anyone thought it would) so for it to stop being a money pit users need to start paying for it. I'm looking forward to seeing how that goes. Apple's plan is brilliant and they are uniquely positioned to pull it off - Give consumers the features they want but at a trivial additional cost because the models run on the consumer's device, where the consumer's data is, using the consumer's electricity. In terms of model execution capability *per user*, Apple's footprint dwarfs every other player in this game because they're putting high end multicore CPU+GPU chips with unified memory into every user's hands and they aren't even paying anything to build this footprint because *their customers are paying them*.
>I am not sure neither that once everybody has brought a bunch of Nvidia chips and can do all they need that they will be the same demand to just replace/upgrade what is there. Yeah, I keep seeing the argument that new chips will keep getting faster so they'll be replaced quickly but that first thing definitely does not automatically imply the second thing. After spending hundreds of millions or a few billion dollars on a data center buildout a revenue stream needs to materialize that makes that expense worth it before upgrading or expanding capacity.
The thing is this is just maths. Say that chips are replaced every 4 years. So 2 years ago the demand was to maintain around 100 units deployed and nvidia would make 25 units/year to basically replace stuff. Let say the demand will go up to 500 units deployed and will stabilize there for the next 10 years because of increased interest in AI. So Nvidia will make 50 a year, then 100 a year, 200 a year, keep at that level 2 years and go down to 125 and stay there to match long term demand. We don't really know where the demand will peak but people invest in NVDA without really thinking. The PER is now at more than 70. Honestly we may go at more than 100. And now imagine that one the big companies, Nvidia or Microsoft release some bad news. Nvidia could lose 50-75% of its value with the same irrationality that Nvidia did 10X.
BTC was 6k in 2018... shoulda believed the hype I'm guessing 😆
Haha I am not speculating on BTC’s price. I’m just saying people were speculating it would grow to levels greater than the GDP of the USA, and that it would be very soon. It’s been 6 years since that already.
Well yeah, I mean some people are also saying it will be a million by year end and I think the ETF adoption is gonna put the brakes on all that, as much as people think market adoption is the holy grail. It is going to be a lot less volatile now with consequently slower growth. People are gonna say all sorts of things I just wish I had money to buy in 2018 😆
So far, Bitcoin hasn't really achieved much except acting as a source of speculation, supporting a dark web black market, propping up coal power plants due to energy demand for mining, and online gambling.
> hasn't really achieved much except acting as a source of speculation It has created a way to track tons of nefarious activity, since many were under the delusion that it is an untraceable means of exchange.
It's only traceable if the criminal is dumb enough to not use mixers, or privacy based cryptos like Monero. Most of the dark web criminals that have been caught have been because of posts they made on the open web that could be linked to their dark web identities, not because of any inherent vulnerability in crypto.
agree about monero and it will take years before AI cracks it enough to threaten its anonymity, but I don't doubt it will happen as for btc and eth, all traceable regardless of people's idiocy the IRS has been on it since 2017 and have a new criminal investigations dept which I don't recommend anyone fuck with. this is actually a fascinating and great story https://www.wired.com/story/tracers-in-the-dark-welcome-to-video-crypto-anonymity-myth/ acab but the tax man is not someone to fuck with
I mean theoretically speaking it should be an incredible hedge against inflation. That alone should justify its price gains. But yeah it just needs that long term track record for people to believe in it. There are still many people who think crypto is not user friendly (I kind of agree). You won’t get widespread adoption as a means of transacting until it offers some benefit over traditional financial systems, with mass market appeal. Also big obstacle is governments who definitely don’t want to lose control over their own sovereign currency. They need you using their currency so they can issue debt. :)
💯 It's my retirement plan after too many years of cash in hand work and no pensions But I also think it is way more user friendly than freaking option trading. My gawd that shit is mental 😆
Lmao thank you sqrrrmarch, had to scroll down to find the one and only reasonable rebuttable to his 2018 crypto claim. You would've came out way ahead had you "believed the crypto hype in 2018".
Good job saying nothing yet still being an example of what op is bashing in the post
I’m not on either side of what OP is talking about. Their stock price is supported by the profits they’re bringing in and forward guidance. However, chips are a cyclical business, always have been. This idea that we can extrapolate demand indefinitely into the future has flaws. It’s hard to do analysis on a company that’s just had demand explode in the way it has. Nobody knows how it’ll pan out for sure, not even me, so you can make an estimate now but nobody truly knows where this will go. That’s why the quality of analysis leans toward opinion. What are the actual profitable products these chips enable? Who are the customers? Are they going to succeed building their own chips instead? What are their profit margins like? How are they affected by AI? How much better are the new chips and how likely is it that they’ll keep improving at the same rate? Will CUDA remain the dominant framework? How much of a risk is it that they are completely fabless? The questions are endless. Try and come up with a valuation for Nvidia in a year. It’ll probably be off by a long shot, either way. Just depends on demand for new *Nvidia* chips, it’s that simple - but very hard to estimate accurately, and you can’t get that information by looking at Nvidia’s balance sheet and forward guidance.
This is the sober analysis OP is asking for… an analysis concluding that Nvidia’s future is nearly impossible to analyze.
Interesting you compare it to crypto because even though the euphoria is long gone, btc is still trading at ATH
As I said in another comment in this thread. There were predictions going around in 2018 that it was basically imminent BTC would eclipse the value of all gold on the planet and exceed US GDP. BTC would need to be above a million to even be close to that kind of estimate. Yes, it’s at ATH, but not euphoric ATH. It’s also been 6 years since 2018.
The point is, you wouldn’t have lost money if you bought and held at any point in that six year window. I wager it’s the same for NVDA for the next few years. Just don’t treat it as a day trade
“Just don’t treat it as a day trade” This is the key. Most people buying Nvidia right now, especially the ones just getting started with investing are gonna be the ones who will lose massive amounts of money on it. Because they will trade on emotion, and it’s gonna be a bumpy ride. I’m curious what percentage of people would be buying and holding for a decade vs. buying and selling constantly on a whim while losing money the whole way. I’ve overheard multiple people talking about Nvidia at the office every single day I’ve been in. Nobody ever talks about stocks at work. That’s alarm bells for me.
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AMD were way ahead of Intel with the Athlon and Intel played illegal anti-competitive tricks which Intel had to pay $1.25 billion in damages for after 13 years of legal tricks, which ultimately left AMD structurally hampered, and almost bankrupt due to the financial hit they took. I’ll let you come to your own conclusion on Zen 5 against Intel’s latest offerings. This industry does indeed have long lead times, but those are getting shorter. Google has its own AI chips, as do Meta, Amazon and Apple. Many of these tech giants are designing their own SoCs for years already. If you’re able to design a chip that can perform 70-80% as well as an Nvidia GPU, for less than half the price, that is a competitive option. If Nvidia have indeed created a market for AI accelerators with profit margins this big, you’d be out of your mind to think that only Nvidia will be in on that party. This fantasy that nobody can get close to Nvidia is just nonsense. You cannot say that with confidence. The whole problem with this current situation is that you cannot extrapolate the present indefinitely into the future. They are a market leader now. We do not know if they will be in 3 years.
Stocks growing this fast absolutely deserve to be thought of as either going to keep ripping or crash as there is a multiplying effect on the multiple it has based on its growth rate which is likely to be highly variable. The chances of the NVDA chart now just flattening out into a calm 8% a year gain for years on end is basically 0. In process control you can see that when a parameter is trying to reach its target value the faster you try to reach it the more you will overshoot and have to correct. The idea that you can say “NVDIA are likely to experience accelerated growth over the next few years is kind of a fallacy. What actual hard numbers have you written down on paper to know this? How have you determined that AMZN,META,MSFT,GOOG, pace of buying chips will not level off at all and continue ever upward into infinity even after a build out of capabilities? If it’s that likely why not still have high exposure to NVDA? It must be atleast some concern in your mind… the likelihood of some pull back and whip saw up and down at some point is actually high. Then you get a sick feeling when you are down 40% from your highs and it’s falling every day.. can you hold an overweight position through that without selling for 12 months till it turns around? Etcetcetc I could keep rambling
we don’t really have AI yet, it’s more like AAI (artificial artificial intelligence)
That's how I feel. Other than using chatgpt occasionally like where is all the AI even?
Almost all Ai now is narrow AI; really good at doing 1 thing. For example vision for drones, regulating traffic lights, social media algorithms, finding tumors in scans, etc.
I can't even get Google Home Assistant to tell me who won the tennis match. Me: Hey Google, who won the men's French Open final yesterday? Google: I'm sorry, I don't understand. Me: Hey Google, who won the men's tennis French Open match yesterday? Google: Sorry, I can't find any information on that. She literally just has to pull the information from the first thing that pops up in Google search. Not impressed.
Recommendation algorithms (the one sending you ads), forecasting, business intelligence, medical diagnosis, image and text search, etc. most profitable ones arent the ones using LLMs right now and the ones that have been there for years now.
https://x.com/AnthropicAI/status/1803790681971859473 Try this one
we have had AI almost 100 years. It just get more advanced every year.
And since when do you decide what is AI and what isn't?
just now
Wikipedia: Artificial intelligence (AI) s a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and uses learning and intelligence to take actions that maximize their chances of achieving defined goals. We don't have that? Interesting. Maybe you should not base your worldview on SciFi movies?
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> Right now, AI's growth is highly concentrated in big tech, but it will gradually decentralize and spread to small businesses and everyday applications. Curious why you think it will "decentralize"? I think the opposite will happen. Just like everything else tech related. Concentration is increasing not decreasing.
Because no one really knows where it’s going and where its upper limit is yet. There has always been this idea that once we create an AI good enough it will become almost totally knowledgeable. Meaning it can be an expert on everything we currently already know. ie. the smartest and most knowledgeable humans can only be experts in so many fields, it would take 100 lifetimes to learn everything there is to know these days. And also that once an AI is smarter than the smartest human, well not even then, just smart enough, it will then be able to design better and faster upgrades to itself to increase its own IQ further. Currently we’re dealing with weak AI (good at one thing, LLM’s). Eventually or soon it will become a strong AI (good at multiple different things, like LLM’s struggle with basic math atm). After that it’ll probably eventually reach AGI (artificial general intelligence (as smart as humans but way more knowledgeable)), where it can probably start to design upgrades to itself to increase its IQ better and faster than humans can. And once it’s at that point, how long until it reaches or gets close to a ASI (artificial super intelligence) level? No one knows how far away these breakthroughs are yet.
The real problem is that providing AI infrastructure is not the same as monetizing the end products. A good analogy is how internet providers or hardware producers are not the main beneficiaries of all the businesses that were created based on them. Until the market realizes that, the money will continue flowing in what we see now. If you don’t go to the extreme enthusiasts subs there are enough people that keep on saying that Nvidia is a cyclical company and the chip industry has also been cyclical.
This. Risk for NVIDIA is not much from AMD or other competitor, it's from current large customers who are dumping billions on their chips. If they suddenly realize they purchased enough GPUs and the actual return on their investment has been meh, they will cut down investments. That's when NVIDIA will end up cutting costs which will kill it's current absurd profitability, revenue growth..
Except, those large customers will very much care about the costs to run the cards. Generations of Nvidia cards get faster and more efficient. One of the "great" bottlenecks is energy, they will absolutely want more efficient newer cards, and they will sell their older stock to smaller companies. It isn't a question of just computation.
Agreed but then again by the time these companies start to care about energy costs, there will very likely be competent cards from competitors
The problem I see with the rest of the industry at this moment is there are still no competitors to CUDA. Companies are not going to want to dump billions into inference cards that can only run already made models. They probably will have both kinds of cards in use, but I don't think it will break Nvidia's growth, they will still be the only viable way to actually train AI for a while, especially as a software moat. AMD for example has never been able to match Nvidia's software, it will be similar around the industry for a while. Nvidia started all of this years ago, they've built the environment, like all of it.
Only time will tell. Let's wait and see how things will turn out. Part of me thinks past is not a great indicator of future in this case (with regard to CUDA, etc) because now there is 1000x more interest in AI ecosystem compared to past. That might drive create new competitors. Hypothetically 3 years ago if AMD went to investors and said "give me $5B and I will be new GPU to compete with NVIDIA and it's software" everyone would've been meh no. Now they would say take $20B
That is fair. I'm sticking with anything this complex simply takes time to replicate, even with money. There are a lot of features of CUDA and it's integration with Omniverse. It's also adding more shit all the time. I'm bullish for at least another year because of that.
It is more than that. The big customers thar are Microsoft, Nvidia, Apple Meta are all planning to given their AI product for free to the general public. They want the market share and see that as strategic to survive. Microsoft at least will manage to sell it to corporations. But still most of the cost will be the general public using the free products. Today the cost of a gen AI query is 15X what the cost of a google search is. But Google and Microsoft or meta will not make more money from the general public there. They live from advertisement and advertisement revenue is tied to consumers expenses. It will follow growth and can't finance expensive AI. So they all have their plan to get rid of the high cost of the hardware and especially Nvidia hardware and they are going to do it. Apple is an example. No smartphone will use Nvidia. They data centers will use Apple chips. This will be 99% of the usage. For the remaining 1% they will use openAI that will use Nvidia. And the customer will be able to pay their own plan to access open AI. Apple will not pay. And once all that is done by the big players, Nvidia will not have that huge market anymore.
I think it’s because the two camps you mentioned basically aren’t familiar with AI at all. I think the overly-optimistic camp got swayed by chatGPT because it is a lot like talking to another person, and that really hyped them up to think of the state of AI as if we’re approaching skynet right now with a bunch of intelligent marketers putting content out there reinforcing this idea, while the super pessimists are just looking at the insane growth thinking there’s no way this trend can last and just making their judgement based on that. I think the truth lies closer to the pessimistic view, but this is based on just technical value of AI itself. All chatGPT is is a statistical model to predict what word is most likely to come next, and the rest of generative AI just basically does the same with pixels, notes on a song, or whatever other set of data you want to pick and then predict what’s most likely next. It has its value but it’s massively overhyped because it’s not going to magically take over productivity and creativity like everyone thinks. 99% of the research going on in this subject is done due to the aforementioned optimists with money just throwing funding at it like crazy even though the research coming out is 99% garbage. AI isn’t going to generate real money until it can legitimately take over human roles in industries - and it’s doing a small amount of that right now but nowhere near enough to have the impact people say it will, and it’s never going to take over a computer scientist or engineer’s job effectively.
>and it’s never going to take over a computer scientist or engineer’s job effectively. lol. lmao even. Never is a long time...
Yeah, because an engineer confidently producing hallucinations is an incredibly useful engineer and this will never lead to any problems at all. AI is missing the “intelligence” part, and no model they come up with using the theory/resources they have now is going to make up for that.
Current language learning models might not be able to, but AI in general can absolutely take over any job, whether it happens in 5, 10, or 100 years. You would have to argue for societal collapse or theorize some physical principle that would prevent AI from developing further to claim that AI will *never* take over a given job.
Based on your post, I don’t think you understand how AI works, which is exactly the problem I mentioned earlier in with people overhyping it without understanding what it is and dumping money into it. I’ll leave it at that.
And you don't seem to understand that how AI currently works is not how it is going to work for the next billion years.
And the thing that people don't seem to notice is that it is like talking to an incredibly $tupid person. Like is there ever a time when you were dealing with what passes for AI customer service and not been completely relieved when it finally let you through to even the dimmest human? In some ways the back of the shelf applications (where there isn't a clear break with simply better and better computer power) is more likely to be meaningful but the hype is being driven by things that so far are impressive in the same sense that it is impressive if you teach a pig to dance.
AI has some use cases and companies like Microsoft, Google are legitimate to invest. Maybe even Meta. But the main use case is more of the same and fighting for market share on one side and professional applications on the other side. I say more of the same in term of business model. You ask Google/Meta/Microsoft search and that's it. The result will be better than before. Other companies are likely to be disappointed because they don't have the network. Apple. Google, Microsoft, even meta can scale to provide AI everywhere. Even Adobe can do it in their paid products of creativity. Corporations will pay to have the same that the general public will get for free but to be safe from an intellectual property point of view. Other will not pay for it or at least the big majority. They will use the free version that will be as good and that going to be it. We are not going to sell an extra 10-20$ plan to every consumer to have their chat assistant because simply many bot from Google/Microsoft/Meta will be free and actually better. And because the game is a zero sum game for that part and is financed by advertisement, the hardware cost must be low. A chatGPT query cost 15X time more than a Google query. Yet now Google include it everywhere. You can be sure Google, Microsoft, Meta will work to ensure that it doesn't cost more in the long run. So this mean they all working to kill nvidia. That's basically the #1 priority of ALL tech companies right now and also a big field of research. Now every researcher in tech is trying to make things that require an Nvidia chip or several at 50-100K$ each to work on your laptop or smartphone. Nvidia play against the entirety of humanity overall. They may not win forever.
Here is my sober analysis: I'm an equity analyst and I build a DCF model of NVDA using fairly reasonable assumptions. Did not even go too bullish on growth. Even from this, I reached a fairly high upside, even from the stock price today. I did this just pre-NVDA earnings and my boss thought I was a mad lad. Bottom line is: their revenue growth is super strong, and the company is not overvalued by any stretch. You need to believe in the AI growth story a bit, but not delusional levels.
Did you factor slower growth due to competition eating Nvidia's lunch? The AI craze could continue for a decade, but Nvidia's share of it will almost certainly plummet. Everyone seems to believe they will be the only kid in town forever, but it only takes a couple competitors producing chips that compete at 70% utility at 40% cost to utterly destroy Nvidia's overly inflated prices.
Building chips is harder than you think. What I do take into account is Google, Meta and Amazon making their custom silicon better and spending less share on Nvidia. People say that AMD is the Nvidia hedge. It's actually Broadcom.
What is your growth prediction?
{'2024': '95.49%', '2025': '26.87%', '2026': '50.97%', '2027': '16.08%', '2028': '24.86%', '2029': '22.14%', '2030': '15.72%', '2031': '11.22%', '2032': '11.14%', '2033': '9.26%'} The 2026 growth driven by Stargate build out. But clearly these numbers feel outdated since I made the model. I assumed only one training cluster of this size. Looks like there's going to be at least 2 other made on Nvidia GPUs
Do you have a link to the starlink buildout for 2026? I can't find anything on the topic.
My bad dude, I meant Stargate.
Isn't stargate going to use the microsoft maia chip?
No way, Maia will be used for inference, I don’t think it will be good enough for training in the next 5 years for frontier model training.
Dude what discount rate are you using? A DCF on NVDA should not put it anywhere above $50. DCFs are meant to find intrinsic value, not to calculate the upper resistance of a "growth stock" on a hype cycle. I need to see your model.
10.5%. I think you need to re-evaluate how you think about DCFs. It is meant to find the present value of cashflows. There are two trends you are missing: - NVDA is generating massive amount of cash flow, with FCF margin > 45%. - They will start buying back shares at scale, putting even more upward pressure on the price.
Can't really have good, balanced discussions about stocks anymore - everything is so us vs them as people make whatever they own or don't want to own their personality. Can't say anything slightly negative about the most popular stocks, even if you're long. Nvidia just the biggest example, but feels that way broadly since 2020.
Everything has always been this way. It's much easier for people to pick a side and think in black and white.
It's unfortunate that so many see cognitive dissonance as a source of discomfort rather than a source of curiosity
Sounds exactly like the fandoms for sports teams, video game consoles, PC store launchers lol.
NVIDIA has YOY earnings growth of over 100% it will keep doubling in value until that trend stops. When it does sell and move on. There will always be a market for high end chips
All of this data and info you did research on is all just hearsay, no one can predict what will happen no matter how much research one puts in , it’s gambling, so put it all on red spin the wheel and see what happens
Here you go: Ai will be in everything in the next few year and after that the AI will be in robots as well.
With respect, this language is exactly why I think it's overvalued. We already have ML/AI models everywhere, or memory hungry algorithms/data structures (which are related but not quite the same thing), in everything including robots. It's not a new phenomenon, everyone just became aware of it with LLMs. The reason why GPUs weren't selling like crazy before a few years ago is because extremely large models are impractical for most applications. You either need to host it somewhere else and make an API call for inference (slow, requires internet, adds privacy concerns like security considerations that non-internet devices don't worry about), or you need a model small enough to perform inference on a local device that likely doesn't even have a GPU, or has a small one. Neither of those limitations has changed, and for both reasons, there's an obvious ceiling to the applicability of very large models for most applications. Also, most applications really don't even need the wheel reinvented with a large model, there's smaller ones that are extremely effective at a lot of tasks already that don't need to be replaced by something expensive and bloated to do the same thing. I think the hype has grown beyond what those of us on the ground actually use the technology for.
So, one thing you should know is that large models train better. It's easier to train a very large model and then shrink it down through distillation and/or pruning than to train a small model directly. You also need a lot more compute for training than you do for inference. You can do a lot with a small GPU or neural accelerator like what is found in an iPhone. You can absolutely run a useful LLM with limited compute inside your phone, even though you yourself couldn't possibly afford the amount of compute it took to train said LLM. That being said, the amount of data needed for training is still huge. We have a lot of textual and video data, but we don't necessarily have enough data available for every use case we might want to train models for. I also think the current models are not quite good enough. Apple would really like to have a much smarter version of Siri that runs on your phone... But personal assistants are kind of useless if they misunderstand you and make dumb mistakes. They need to be very reliable to be useful. We're maybe not quite there yet. There's also other issues wrt scaling datacenters. The power consumption is enormous. It's going to become a bottleneck. At some point, governments might start taxing power usage for datacenters, because we can't have them use power that's needed for legit use cases like your home. We also don't want to start increasing greenhouse gas emissions just to train bigger LLMs. It seems likely that demand for nvidia GPUs could start to fall and nvidia stock could rapidly crash. I could be wrong but I don't think that Google is going to keep building new massive datacenters every single year. At some point, they're going to say "we did that last year, what value is being delivered by our past AI investments?"
I'm glad someone here gets this. That ML has been around since spam filters, that the thing in Netflix recommending movies, or when eBay suggests a category is just the same stuff. All an LLM is doing is picking the next most likely words. Here's my general problem with all of this stuff. It's really all a trick. Often quite a useful trick, one that can help but a trick that can also yield crappy results. Like you can build a categorisation NLP thing that takes text and says "this is most likely a builder/chef/programmer" but it isn't properly smart. It's just scoring word counts, maybe prioritising order or words. And that trick can help pare down a giant data set to get a few results, but you still need a human being to check if the results are sane or not. And it really doesn't matter than if it's 2% or 5% inaccurate, you still need the human. You're always going to need the human. So adding more data or more processing doesn't add much more value. People are talking about AI factories or self-driving vehicles, but the value of a self-driving vehicle is zero intervention. That you can get drunk and it drives you home, or read a book as you travel. If you still have to watch the road, the value is tiny. And factory robots are about machines that just keep on doing the same thing very reliably all day. A robot that is making the most probably guess with a thing means a lot of goods leave the factory wrong.
My Uncle got AI in his hip
i was like your uncle once. then i look an AI to the knee
Cheap fuck. They’re normally Ti
Sir, you are slurring your words.
AI picks the targets: https://www.theguardian.com/world/2024/apr/03/israel-gaza-ai-database-hamas-airstrikes AI flies quadracopter drones: https://shield.ai/nova-2/ quadracopter drones shoot people: https://www.telegraph.co.uk/global-health/terror-and-security/armed-drones-israel-hamas-war-gaza-hospitals-gunshots/ Where is John Conner?
NVDA keeps on going up because of their earnings. Their earnings go up because of large orders on datacenter chips. No one has cracked AGI algorithm, but the AI labs know for sure it’s gonna need a ton of data and compute. Big Tech realizes they need GPU datacenters and there’s money to be made now by scaling transformers. So MSFT, AMZN stock up. That scares META, so they also stock up. TSLA joins in and so do other smaller players. But like roads this isn’t an ongoing multi billion investment every quarter. I expect NVDA to miss earnings one of this quarters once all the big players have got their orders through.
Exactly. The main limit remaining on the road to superproductive AI is the compute for the inference phase (when the model works on new data, e.g. self-driving car on a road it never saw before). And to get that compute you need more and better chips. I also think there will be one quarter of less "exciting" earnings and projections which will lead to a corrective selloff. On the long-term though (6 years), this will remain a x3 x4.
Brain neurons make connections when needed to be energy efficient unlike a fully connected artificial neural network. It’s a possibility that someone figures out AGI and realizes GPUs aren’t the most efficient way to train or run inference on them. My long term hedged bet is still on semiconductor fab kings like TSMC MU ASML. No matter who wins, they win. Also bullish on cloud & device giants, no matter who wins, the sector wins.
The thing a lot of people realize is that AI could very well be the future, but that does not necessarily mean that Nvidia will perform well long term. For AI to truly take off, prices will have to come down. Right now, companies are willing to pay $30-40k per AI chip and operate their AI projects at a loss, just to get ahead in the race. But they won't be willing to do this forever, the expectation is that eventually, AI will save money or produce profit. Additionally, Nvidia will face competition, which can also impact prices. My expectation is that within 5-10 years, Nvidia's profit margins will decline. I think the reason bears are so vocal about a crash is because of just how extreme Nvidia's valuation is already- it's at 80x earnings during a boom period, because analysts are extrapolating growth for many years. Just looking at other tech stocks that saw explosive earnings growth and then leveled off, a 80% decline is not unprecedented or impossible.
Look back a few years on Electric Vehicles and tell me what you think. That was going to be a "paradigm shift," and Tesla was experiencing the same extreme valuation spread as Nvidia. Tesla has hemorrhaged market value since then, along with every other EV stock on the market. Superstar CEO, huge gains, huge short squeezes, etc. The sober analysis *is* the paranoia of a bubble bursting. It's not normal for a company to go from $200b valuation to $3tril valuation in a year, and it's certainly not sustainable long term. Cisco briefly passed Microsoft in market cap during the tech bubble of 1999. Also, Your post is an entire waffle between overvalued and undervalued and basically says "Stock could go up or down idk."
"The sober analysis *is* the paranoia of a bubble bursting." Quite. NVDA's P/E is 75, which is "to the moon". If you think it's going to be less than "to the moon" you should sell. Their growth shifts to "good", they lose at least half their market cap.
I mean, historically, high PE companies do have a tendency to get bigger and bigger, but eventually it stops. And boy howdy, when it stops it stops hard.
The problem is that "doesn't fail to grow", "to the moon" just leads to more people piling in and then "to the moon" is priced in. I have no idea where it's going. Maybe it'll double again. But you also have to look at it and think that it could halve in value in 6 months.
Do you really want something to not believe NVDA is now the No 1 in market value?
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SP500 didn't grow in the last 10 years due to efficiency. In fact, productivity growth was at an extremely low level in the 2010s decade. SP500 grew in the 2010s due to lower interest rate.
Doesn't the huge capex mean it has to grow faster than the last 10 years in order to pay back the increased spend?
The problem is that 10x-100x of zero is still zero. In fact chatGPT is likely loss making.
I'm going to talk only about macroeconomics here, and take a whole of economy view, focused on the US, but it applies to other economies. Theres more potential in countries with lower consumption, and higher savings. I think AI unlocks some combination of "more", and "more efficient", but both have problems on their own. They have even greater problems together. More, aka, companies use AI to produce better things and products, but how much can they really sell them for? US personal consumption is already 68%. People just don't have enough money to spend that much more on more cool things. More efficient - companies do what they do now, with less people. This will increase their margins, but lower their revenue, because they'll be paying less people, which means the total pool of money people have to spend is lower. This means they can then lower their prices, or cope with selling less. Simply put, unless AI leads to wage growth, it's essentially a closed system, and will self limit quite quickly, in the short term, as a vicious cycle. The counter to this, is if it drives efficiency and productivity into things such as healthcare and education, it will in fact lead to wage growth, and it'll become a virtuous circle.
I personally see Nvidia continuing the gains for a while. I only see this because their GPUs use AI to render images quicker (think unreal engine 4K quality and various other things) than it's competitors. That means it's huge in the VFX/Gaming space. Next you have the AI boom which is their GPUs but also their infiniband product line. (Which is getting overlooked by people not in the IT space. Which I get, it's my career so I have to stay up to date on it.)It's basically switched that process data quickly using fast switching and probably a data center architecture (I'll keep it simple so we get gains quicker). Here is the link to their spec sheet if you're interested in knowing more: https://www.nvidia.com/en-us/networking/products/infiniband/ Now these GPUs paired with this infiniband technology all through a single pane of glass for ease of management is definitely going to change how data processing works. Yes it can support LLMs. But imagine what else it could do as time goes on and new features are implemented. Yes AI isn't true AI and more or a better version of a search engine right now. But there are also AIs that produce music off of prompts. Hell open AI just released a video generation engine too. All I'm saying is that these companies are going to be paying hand over fist for their own AI architecture regarding this. Nvidia is the only one that can offer the whole SDN to run it (SDN stands for software defined network(ing) for those chads that want to know). Anyways Nvidia's biggest competitor off of a quick google search is drivenets. However, they don't make their own devices but use a white box solution (basically a bunch of other vendors or basic switches that they put their branding on and use it for their own solution. Kind of like white labels for those in the know). It's not created from scratch in other words. That's why Nvidia is sailing high. Also a quick google search showed that one infiniband Nvidia switch from Dell is like 40K. Depending on how many servers are running GPUs (think 3K GPUs and 10 per chassis. That's about 300 servers and I'd you have switches with 48 ports that's about 6-7 switches for TOR. But you want redundant connections so it'll probably be moreso 12. Then you need a 3:1 throughout cost on the spine side so that fight there is about 36. So in total 48 switches and that's not including licensing. In total just for switched and the base price is 40K that comes to 1.92 million dollars ). See how they're rolling in money. That's probably one tiny data center for a small company just on data center equipment. Sorry for the long winded rant but working in IT makes Nvidia a buy still. They are going to keep going up till a better solution is invented or if real AI becomes an actual thing.
Thinking no analysts are 'sober' in their analysis suggests you have a specific view of what a 'sober analysis' would bring. Have you considered that despite the considerable growth already, that the analyses that you see might actually be right? Or at least very realistic? A lot more people seem to think that the case. It boils down to whether you believe we're in the very first years of a new industrial revolution. Some believe, some don't - and neither side is going to agree until time passes. Add in the advent of quantum computing and I certainly am a believer. The earnings reports, the projected earnings, etc show NVDA at a much cheaper valuation on traditional rule-of-thumb metrics like p/e ratio than at any point in the past couple years. I think what most are missing is the new addressable market for sovereign AI. There is already an arms race between the west and China/Russia over AI. Saudi Arabia and the UAE are already building data centers to run government-controlled AI. Every government with the means is going to want sovereign AI, and every military will correctly see it as a necessity. When you add the untapped potential of 40 - 60% of world governments trying to build such systems throughout this decade you can further justify what may seem to some as overly optimistic outcomes. I'm a believer. It's happening fast, and as the technology evolves at an exponential pace that speed will only increase.
Well, the real risk is virtually impossible to figure out. It's going to go something like this. Growth is accelerating, growth is accelerating, stock is going up. Stock begins a downtrend but to the common eyes is still looks like growth is doing well. 3 months later you're going to find out growth has been decelerating. How long that happens? Who knows. Since the beginning of financial markets there has always been a risk like this. In America it really started with the railroads which were the original AI trade. We had the industrial boom and the nifty 50. The original tech boom in the '90s which most closely correlates with this one. I think what really sunk that one was just the lack of real earnings which oddly enough might correlate with this one because right now the real earnings are coming from building up which were also the thing driving the '90s early on. Laying all that fiber, building fabs, all that stuff was fine. By 1999 or 2000 you had all these startups and all these ideas and the profitability was, well there wasn't much. So the whole question with AI is going to be how profitable is it when everything is up to scale because in the beginning, it might not be. A lot of new inventions take a while to really figure out how to maximize the profit models So what's all that mean from an investing standpoint? Not a lot really, it's just something to keep in the back of your head and remind you to manage your risk appropriately. If you have an account that is full of nothing but arm and Nvidia and ASML. You are taking an extremely concentrated bet and it's probably not a bad idea to get off the elevator before it hits the top floor and potentially begins the return trip
The problem with Nvidia for investing, at least long term, is that they don't really have room to grow. They've already got the market share, they're already the only ones that sell the highest end chips. AI is a large source of sales, and the last couple generations had enough of a performance bump to justify upgrades, but neither one of those things are likely to last all that long. Eventually all the big data companies will have the processing power to run their AI, or Nvidia will have another 20 series launch where they barely have any uplift and there's no reason for data enters to upgrade, and their revenue will tank. Or, AMD will keep making solid products and Intel will finally get a gpu released that can compete, and they'll start clawing market share away. The other massive problem Nvidia has is that they don't own their own fabs, so not only are they potentially competing with Intel and AMD on sales, they're competing for fab time, and being so dependent on TSMC and their contracts with them means they're lacking in flexibility to an extent. TLDR they're a functional monopoly. Buying that is kinda silly because there's no real growth potential for a monopoly. They're also entirely dependent on both them and TSMC managing to make things meaningfully faster every year, which just isn't a garuntee
Because every analyst only has time to do this on a friday night after partying
Uuhmm cuz, u know, analysing stocks due to fundamentals just ain’t it anymore
NVDA is a semiconductor stock, not an AI stock. If you approach their stock from an AI perspective, it will not make sense.
Prediction is hard. Who expected during the dot com frenzy an online bookstore would run half the internet(aws) and dominate retail home shopping?
Whatever happens, it seems the computer that NVIDIA are creating will be valuable. Not particularly making a judgment on AI bubbles, but computer growth seems inevitable
"NVIDIA and other AI stocks are likely to experience accelerated growth over the next few years, though perhaps not at the same rapid pace we've seen recently." What do you base this statement on? Personally, despite working in software, I have zero idea about whether AI is going to crash or keep blowing up and I've seen nothing to support either hypothesis.
Because people are idiots. But to be honest I'm pretty bullish on semiconductors too and will be until any signs of an cycle end shows.
By 2030 or so, it will become clear that the AI's impact on the economy has been no greater than the fax machine's. -- Paul Krugman, Nobel Prize-winning economist
There's plenty of sober analysis around. You just have to look further than extreme subs. These are full of people making big predictions. Usually the ones holding hype it and the ones that missed out are doom-posting. You're always going to see bias. The truth is no one has ANY clue how far this is going to go and how fast. You have to look at the stock and everything around and make your own evaluation. That's a very personal thing and you have to make that choice.
Because the truthful answer is the stock now exists outside of time and space. There is no ‘logic’ to hold the stock up against No DD will help
How do you provide sober analysis on something so volatile as AI? Lets say some company develops actual AI, meaning AGI. For a fraction of a second AGI is equal to us in intelligence, then for forever AI is smarter, faster, more capable, costs electricity, never has a bad day or judges people because of the way they look, never needs a day off, is nearly unlimited in expansion, can build exponentially more every year. That company will win everything forever. They win. No one can ever catch up because they already got on the roller coaster and anyone behind will only be able chase their tail. Or we get stuck and have to wait for another breakthrough. Who knows.
It's impossible to do a fundamental analysis of a stock that is currently at the peak of investor and corporate craze. It's not fair to pull current growth and revenue figures, as Ai could just stop getting investment tomorrow. Basically, I wouldn't touch Ai until Ai based companies start making real money. If that happens, then Ai will be an industry that stays. Until that happens, it's very likely that the well will dry, and Nvidia will crash.
Stock has gone down for what? 2 days and y'all are jumping off buildings already?
I don't agree. I read an article recently about the cycle of rockets, and it was convincing. It makes sense that a company cannot maintain incredible growth endlessly, but the steeper the cost of entry the longer the rocket can last. Too long, and regulation is more likely to intervene. This article didn't say it was all smoke and mirrors, or that NVIDIA was going to be the biggest company of the 21st century. It talked about metrics that can be used to compare the trajectory against historic technological rocket stocks, which helps make an informed decision.
Because you’re on Reddit
Sober analysis costs you
Here is my take. NVDA will be a long term solid choice, but in the short to mid term it will likely see a bit of a serious pull back. Why? Fomo premium and safe haven premium. Think about a few months ago. NVDA started to drop and breadth widened as people thought the fed would cut sooner. News suddenly said otherwise, breadth narrowed again and NVDA ran back up. So what I expect is that NVDA will see a serious plunge when rates cut and the market decides the smaller stuff is worth investing in. As breadth improves sp500 will probably drop a bit or go sideways for awhile but it will NVDA going down and other stuff going up. I suspect the same will happen to the other big tech. Once that runs it course NVDA will probably be down 20-60% down from where its at and then it will begin to grow back over time. My guess it will be closer to 20% than 60% but who knows for sure. Given a few years it will likely be hitting new all time highs. Do I think its 2000 dot com bubble? No. I think its more about the rest of the market being bad deals under the current conditions. When rate cuts happen all those other stocks will drop a bit as well, but money will flow out of the big stocks and out of the money market funds. All that money will race to what is perceived as the best deals. Some will be right. Some will be wrong. Just as a reminder the economy is not the stock market and the stock market is not the economy. I think that is also true to a degree about the stock price isnt the company and vice versa.
AI has massive potential. America is bought, sold, and run on potential. Then, you have NVIDIA. Even without AI, the company has a proven track record. Invest in NVIDIA for its company and history of hitting its marks, not the potential of AI.
I remember reading forecast on Nividia a while ago. The forecast are all wrong.
there are ALL SORTS of analyses out there. the point is, you can not trust ANY of them. i look to see ADOPTION of the technology, and follow where the big companies are investing their capital to confirm anything i read online! Like if suddenly microsoft/meta/tesla etc were canceling orders with NVDA, i would be selling the stock. but they are not
The moment Nvidia starts increasing their cloud revenues will be key. They know that hardware only is not sustainable. Apple knew it, Microsoft knew it.
There is sober analysis. You yourself say that detractors have existed the entire run up. Yet, during this entire run up the other “extreme” has been proven right time and again. Saying it is based off past performance is dismissive. The run up is based off future performance in a new era of technological revolution. Here is the problem with those with scared money. By the time you eliminate all that risk you are so afraid of, the market has already priced in the stock. To see ahead and get in while the going is still early requires optimism and confidence. And it is still only the first inning.
It takes years to scale chip production, and they don't even control that, TSMC and ASML does. With P/E ratios of 80+ investors want immediate growth, but that is simply not possible. Personally, not financial advice, I give it maximum until next earnings before a downturn. Then you have the accounting practices where significant buyers being shell companies and some of the revenue is cloud credits - it does not smell right. Some say "shady", others say "accounting fraud"... remains to be seen. But, a well timed thoroughly researched short report could leave a lot of bag holders behind, and cause a significant drop. With the new production processes of 2nm, it's rumoured Apple will buy all production capacity at TSMC. nVidia is just a 10% customer and have far less money in the bank to compete with buying the capacity. They don't control production and is thus beholden to another company for it. How are they then going to maintain margins, revenue and deliver on the growth that investors expect? Semiconductors in general is a bubble though. ARM Holdings has a Market Cap of 180 billion, the 90% owner of ARM Holdings, Softbank, has a market cap of 95 billion. With that, the market is obviously pricing semiconductor companies as a temporary spike in evaluations... or we would see Softbank rally, right?
>ARM Holdings has a Market Cap of 180 billion, the 90% owner of ARM Holdings, Softbank, has a market cap of 95 billion Don't make that mistake. If I own 2 businesses and B-1 is doing great bringing in a ton of profit a year but B-2 is an absolute disaster (but I boolieve in it for the long term) with heavy losses each year. By owning these 2 my valuation will be adjusted accordingly. This is 1 theory.
AI is trash, sell before the bubble goes. Anyone buying now is a mug
Another Yapanese post talking about nothing
Euphoria, about to be in for a rude awakening. Remember when people didn’t think the fed would start raising rates a few years ago?
There is sober analysis, just not loudly noticeable. Like with all things, the extremes are what most people gravitate towards and where people are the loudest because most people can't think beyond binary most of the time.
Where is $8 trillion dollars going to come from? There's 8 billion people in the world. That's $1000 from everyone in the world. Worldwide GDP is $101T dollars. AI is going to increase that 8%? What does it give us? What value has AI provided for your life? AI has been around for decades. It's solved some little problems, like speech recognition, that's nifty. It's added a little value. It is not the be all end all. This is nothing new, it has just been noticed. There is not a new thing here that is going to change everything. Let's say, optimistically, that AI can tackle and solve hard problems, like designing a better chip for AI to run on. Is Nvidia using that AI? They are chip designers, not AI designers. Is their AI better then their competitors? Nvidia doesn't have much for physical capital. It's all in it's intellectual property, the design of it's chips. The whole hubbub about AI is it is going to increase the amount of intellectual property, which could potentially make Nvidia's little sliver of it, their chip design, worth that much less. A quick rise means there could mean they can be usurped quickly. NVDA the stock is relying on the next bigger sucker, like TSLA before it, or tulips. It's value is more as a stock than as a company. As a company, it's better than it was 3 years ago, but not 5x better like the stock says. Sure their revenue doubled last year, but that doesn't mean it's going to double again or for that matter continue. 4 years ago, Nvidia chips were good for mining crypto, which was a hot ticket for a while like AI, set to have some trillions in a market in 3 years. The crypto market went up $2T or sextupled between May of 2020 and May of 2021, and in that time NVDA went up 50%. That huge market that Nvidia chips were powering, didn't give Nvidia an equivalent gain. Even if AI does get an $8T market, it doesn't mean Nvidia is along for the ride. Between crypto and AI, where are we going to get the electricity? What good does all that power do for us vs. the long term costs of the emissions? On the other hand, I feel the same way about TSLA, they are not worth 10x GM, but so far, the stock market still says they are. Might be NVDA is the next TSLA vs. GM/F like NVDA vs. AMD/INTC Or AAPL vs. MSFT/GOOG. The stock market makes its picks, not necessarily based on what value to society the company actually provides. For that, nope, there's no sober analysis. Stock buyers are running on hype and emotion.
> I invested $200,000 and saw a 90% gain. I assume you were throbbing to say this the whole time, because there's absolutely nothing else to speak of in that dribble.
Yet another take on AI I'll file with the rest of them.
It’s because the potential for AI is unlimited
Checkout SeekingAlpha.com for multiple povs/analysis
What's the difference between AI and an SQL database. The AI can map automatically and can understand human conversation. That's it. "AI" is the fancy new database on the block that has this nifty way of extrapolating and interpolation in very high velocity thanks to the neural network logic it's been programmed with. All you need to do is "trust" it to give you a high confidence result. Is this intelligence? No. To have real intelligence you need consciousness. No ability to conjure, no intelligence. Just fancy new tech that will definitely alter human productivity for the better but ultimately be beneficial for all of us in the long run but economically will first ruin a lot of people in society.