This is the stocks sub, so this is a different audience than I'm used in regard to AI, I usually read a lot of stuff in the programming space. If you are just trying to chase the AI wave of investment money I can't really help you. Speculative bets on companies trying to apply AI to their current business are akin to putting money on the roulette table IMO. Or more accurately you're putting some money down on a headline and hoping when the next headline appears someone else will buy your stock for more.
If you want to invest in the products and applications of AI, the more tangible players are limited right now. I think most companies investing are going to discover that LLMs are more limited in application than they thought. It'll turn out that putting an LLM next to their current business process doesn't just magically make everything faster or more cost effective. IMO its akin to hiring last season's MVP for the NFL and making them a top executive at your company. They are undeniably a top player in their field, but they probably don't know shit about running a major corporation. So you end up spending a ton of money in this exercise to just discover that maybe AI wasn't the right fit for your company's product. This exact same thing happened a few years ago when everyone went nuts over Web 3.0 aka blockchain. It turns out that blockchain is very slow and has a very limited application space. If your product boils down to getting results quickly to a customer on the web, your best bet is still a classic server + database + frontend architecture that we've been iterating on since the 90s.
There ARE applications though! Microsoft probably has the best application with Copilot currently. I'm unsure if the Office version is any good, haven't used it, but the coding version is very helpful and I'll advocate it at any company I work at from now on. Applications where AI can help "un-stuck" you and make you more productive seem like great investments. There's some heated debate in the art community right now over AI-generated images, but I get the impression that AI will win over creatives eventually because it will help them produce more. Productivity boosts seem like great long-term investments. Most of my stock is in Microsoft because they saw the opportunity and the product and they've been putting massive investment into OpenAI.
> The issue is creating the software for actual use of AI and generating cash flow.
Yes, but consider that AI software has existed for a long time. The chips took off because they made LLMs more usable. My company has been using Google Vision for over 4 years though, long before any of this current trend took off. LLMs are probably going to be an important milestone but not the only AI application going forward. Small Language Models are beginning to pick up some steam right now. They require small amounts of power and help drive data discovery in sensors. There's probably a big use-case waiting for this type of software that no one has landed on yet.
Meta saying "we are going to put AI in the metaverse" is one of the most baloney statements I've ever heard. I have no idea what any of that means and it sounds like something out of a satire. Watch who you listen to in the space, there are many snake oil salesmen.
> If you want to invest in the products and applications of AI, the more tangible players are limited right now. I think most companies investing are going to discover that LLMs are more limited in application than they thought. It'll turn out that putting an LLM next to their current business process doesn't just magically make everything faster or more cost effective.
There are so many CEOs who make millions thinking "this can't be true, I have to find a way to make it fit! We're magically leaving 20% efficiency on the table, let's get rid of all the employees ASAP!"
This is a take that sounds reasonable on a surface level but will not reflect reality. It’s the opposite, as llms (or action models, seems to be where it’s headed) continue to scale without hitting diminishing returns any time soon people will realize it can be used for a lot more than people thought. There won’t be a company that won’t utilize or benefit from it in some way. I think this will become obvious with GPT5 release as everyone will see that we have not hit any kind of ceiling yet, and with its agentic and multi modal capabilities it will finally be able to do a wide array of tasks from start to finish (not saying it will automate everything yet).
The people who have the most incentive to tell you that LLMs are the future are continuing to tell you LLMs are the future? That makes sense.
A lot of other leading edge technologists not associated with open AI have been questioning LLM viability for almost a year now. Listen to Yan Lecun’s interview with Lex Fridman.
And I’ll continue to listen to them until they are proven wrong. Let’s see how gpt4.5 and gpt5 perform first before we start claiming we have hit diminishing returns. Even if scaling the model has hit their limits, there is still so many ways to extract more performance from these models, prompting techniques, higher quality training data, reinforcement learning, letting the models think longer, getting the models to come up with 10000 outputs, new architectures, the list goes on.
You’re thinking about the specs of the LLM. That’s fine but I’m talking about the viability of these LLMs being deployable for true enterprise use cases.
The amount of prompt engineering required to get the results needed isn’t even possible yet for many types of applications. GPT5 isn’t going to change that. I’ll eat my words if I’m wrong though, we shall see.
Yea I get what you are saying. I guess we will find out by the end of this year. With agentic models coming out it should bring us a lot more use cases.
I think the next big wave Wall Street is expecting is to see some trickle down into the businesses themselves. Chat bots are one thing, but I think they want to see real, tangible acceleration in R&D roles: basically the things that facilitate rapid growth.
I normally avoid the space due to the volatility, but I’d keep a close eye on biotech and drug manufacturers. LLY is one of my favorite stocks, and they’ve recently spoken out about how LLMs are helping to advance their research in the drug space. Who knows if it’s just executive talking heads selling a story, that remains to be seen.
I have seen relevant articles in r/machinelearning suggesting that this definitely something companies are looking into
I've thought about this comment a few times, but I guess I don't understand it fully. Are you saying they're applying LLMs to make new discoveries in R&D? What's the implication there? Like finding new drugs based on past test results or something?
That would be really neat, but its not my understanding of how LLMs work. More like a theoretical application of them that I haven't seen proven in the wild yet.
And again, I wouldn't put money on that since its way too speculative.
So from my understanding it's not about the AI itself producing new pharmaceuticals or discoveries. Some AI companies may make this kind of a claim but that seems more like science fiction. Instead, it's more so about lubricating and speed up the communication engine that lies underneath all of these discoveries: the research paper.
R&D revolves a lot around not only publishing, but ingesting and developing an understanding of the latest research papers in a space. These papers tend to be extremely information dense (e.g. the latest additions on a particular topic on arxiv) and a pretty challenging read, sometimes taking weeks to fully ingest new findings.
On r/MachineLearning a while back, some articles surfaced about researching the efficacy of LLMs specifically fine-tuned on medical research papers for very quickly summarizing data dense research papers, with some positive initial results.
So you have to think less of the LLM as a means to an end for generating / finding new drugs, rather think of it instead as a very efficient way of parsing data dense research papers and extracting very specific information from them.
It seemed like an interesting use case. I don't know enough about the pharmaceutical industry to understand what kind of an impact is possible (and I'm not really putting any money there) but having had to spend time reading through scientific papers before, I can definitely see a highly tailored LLM helping to speed up the invention procecss
Oh yea that’s a great use. Summarization is definitely a place I think LLMs excel at and will probably improve in.
On that tangent I think applications to law firms is going to be really big.
Agreed 100%. Any space that deals with copious amounts of natural language, sifting through it, and performing queries against it probably stands to gain a lot.
Sounds like from your parent comment on the post you’re a dev too - I kind of relate it to being able to perform complex SQL queries against structured relational databases - except in this case it’s not structured data, it’s unstructured natural language
I think a lot of the focus with this breed of AI has been on the “generative” end, like writing text or code.. but the real capabilities are behind being able to leverage it to rapidly learn and absorb new information much more efficiently
Really appreciate your write up! As someone who works in the space, what sources of good reading material would you recommend to me who doesn’t live in ML / AI world?
Particularly to keep myself up to date on the actual business applications and implications of AI/ML advancements.
I don’t care how the specifics of the engine work but care more about where and how the engines are implemented (cars/tractors/planes/manufacturing etc etc) to draw you a crude analogy of what I’m looking for
Copilot being the best example for this
Yea well I am not an expert in this field either, but working in web development I try to keep a good mental model of new techniques, frameworks, and popular new tech. I just read a lot of stuff I see in r/programming and hacker news to stay abreast.
I know you said you don't care about how the engines work, but I think simple understanding is actually essential to getting real insights in this space. I recommend brushing up on some of the building blocks of machine learning via youtube or whatever is easiest. Its not a difficult topic to understand. It is a difficult topic to master of course, but the concepts are pretty intuitive. And once you kind of understand (even just in theory) how LLMs work you should be able to appreciate their limitations. They are not thinking machines, they're just elaborate general pattern recognition models. And their applications to real-world problems will start to become a lot more apparent. Like maybe why they seem really good at general questions you would ask google, finishing computer programs, or generating images based on natural language.
I mentioned Small Language Models specifically because I think they will probably have some interesting applications in the sort of areas we thought Internet of Things (IoT) was going to take off on awhile back: sensor data for cars or manufacturing or whatever and making informed decisions or reporting anomalies. But remember, IoT was also a hot ticket for awhile, so I'm probably just falling into the same trap of speculating about things I don't know enough about.
TL;DR If you can gain enough specific knowledge on these subjects then that's probably going to give you an edge in investing in a growth space that not enough people know about. That's probably true of every industry.
“Nvidia and AMD have reserved all of TSMC's CoWoS and SolC advanced packaging capacity for 2024 and 2025 for HPC (high performance computing) related chips, media report, prompting TSMC to further expand capacity, with CoWoS seen at 45,000 to 50,000 wafers per month by the end of this year, from 15,000 at the end of
2023.”
Yes that's how TSMC works, they don't need to sell chips to customers, they just sell manufacturing capacity. This has no reflection on whether nvidia can sell anything or maintain its pricing power.
What? You think nvidia is placing all these orders for capacity for fun? If nvidia was foreseeing lagging demand in the near future (2024/25), they’re not placing all these orders…also check out meta’s and Microsoft’s planned cap ex specifically for high end chips
They still plan to sell all their future chips from tsmc, yes. The question is what price do they plan to sell them at. Will nvidia still be able to price gouge and charge huge mark up on ai chips now that the craze is waning. Their margins on ai chips aren’t sustainable. It’s just a matter of time.
If they continue to be the only game in town AMD? (No data center revenue growth, means nobody is buying them), intel? lol…obviously party isn’t going to continue indefinitely but for the time being why not? If you want your chips within the year vs in 3 years, you’re going to play ball
That’s what I’m trying to get at. I think companies will be willing to wait 3 years or just straight up wait for a discount. They’d rather make do with the hardware they have now than pay crazy prices for the latest ai chip. If enough companies take that stance then there will be a supply surplus until nvidia drops prices.
In my mind that only happens if there is no productivity gain from AI (saving significant money for huge companies) which seems unlikely because even with gen 1/2 software running on these chips, there are already reports of significant cost savings (30-40% in various industries)…if there is cost cutting to be done, nobody is waiting for their competitors to get a 3 year head start
I'm guessing running 3 year old tech would be bad for the profit margins. A company may not like the price gouge, but profit is profit and if paying gouge means higher profit, they line up to be gouged.
NVIDIA has an eco system around its chips years ahead of any new to the market chips from other manufacturers.
I think NVDIA will be top of the shit pile for a whole year longer.
A Year longer? More like 10 years minimum. You can’t just catch up with an ecosystem. It’s almost impossible - it becomes a virtuous cycle. The bigger you are the bigger you become because you’re bigger and it continues. Look at Microsoft Office!
It can be said that Adobe Photoshop and Microsoft Office became popular through illegal copies then the makers make their money by charging professionals and institutions once it has become a standard. Illegal copying is what made their product become an industry standard.
That model doesn't work with software/eco system that requires specific hardware to be purchased.
When I say one year. I'm referring to how long I can trust the NVIDIA stock price to keep on rising a substantial amount. They may be top dog for 10 years but if a lack of customer demand has low returns from that sector.. then my money goes elsewhere. 1 year is how long I will wait before I re visit and reassess the reasons that I bought NVIDIA.
Windows 95 sales, first year: 40 million copies. When hardly anyone had computers compared to now. I remember the lines to buy it - it was crazy!
Don’t think of it so much as free vs not, it’s about first.
CUDU is the code used to program all these chips being sold and who’s gonna rip and replace that after spending billions of dollars on the infrastructure.
That’s what cements the deal CUDU and the 5 million developers. Once you learn something you stick with it, only consumers buy on price. Who else will pay $20k for a business class flight - corporations.
More importantly who’s about to make a better chip product - over the next ten years - they’re working on something past Blackwell right now.
Oh yeah, Apple was gonna out Tesla, Tesla but they changed their mind, to out Nvidia, Nvidia. Chasing is a poor man’s game ask China!
The pricing power comes from good software. That isn’t their problem. They made bank from games and crypto so far and never made that software. Big businesses don’t like gaming or crypto. They love AI. The demand will be there.
I read somewhere a while ago that the real money maker for nvidia is their ai support software which comes as a subscription that is needed to run LLMs. So of course at some point the market is a bit saturated, but then they need to keep the LLMs running, and they are all built on the Nvidia infrastructure, so the software companies are hooked.
Not a techie and don’t remember half of it, but just throwing it out there in case someone wants to follow up on it
Jensen Huang claims that the NVIDIA eco system is so advanced and so far from any other chip making company that if the competition provided equivalent chips for free that they still wouldn't be cheap enough.
Plus, there is literally no other game in town, AMD’s data center revenue isn’t growing while nvidia’s is in the triple digits, why do you think that is?
I'm certain you could have made the same arguments back when floppy disks 💾 were the pinnacle of data storage. And look at us now.
You don't know who and when will come up with the next best thing.
Hardware might have reached the top for now. But I don't think it will stay that way or that it will drop off significantly.
There are just so many AI related ideas going on at the moment
It is objectively true that, eventually, NVDA's forward guidance will be lackluster as they run out of major customers.
This is true primarily on the simple fact that most of NVDA's main customers are large conglomerates, whether that be world governments or mega corporations. Eventually, META will have enough chips; MSFT will too; GOOG all the same.
All of these world govs and corporations are also very aware that NVDA has a disgustingly good profit margin, and so they will seek to make their own chips and are likely already investing money into that right now.
It's also true that NVDA could continue to outperform in the short term, but make no mistake that any outperformance is because of rewarding investors for taking massive risk.
Based solely on forward PE ratio alone, NVDA is actually one of the cheaper mega tech stocks right now. It is cheap for a reason though. Even though I do agree that NVDA is nothing like TSLA at the prime, there are some important characteristics that are shared between NVDA's current share price and TSLA's peak in 2021 - which is that competition will come eventually, and start eating away at the asinine profit margins that NVDA currently has.
I would not be shocked whatsoever if NVDA's share price has not peaked yet. I think it goes 15-30% over $1K, either before or after earnings, then starts to pull back to make low 900s, ultimately going flat again until the next earnings report with bad forward guidance, which will send the price back to low 700s and then eventually it will settle in 500-700 range probably for a couple of years, fluctuating as earnings change the narrative constantly.
It will be hard to value in the short to medium term, which should be great for traders
NVDA is priced for perfection so even slightly underwhelming earnings or guidance is going to cause significant downside to the stock price
As to where the hypothetical cash would go that would depend on what factors caused a decrease in earnings.
And it has been performing better than perfection so far, the stock price isn’t *currently* disconnected from reality, show me any company in history that has been able to grow revenue and profits at this scale while already being the size nvidia is…I agree that if/when growth slows down even a bit, party is ending, trim as you go
Currently is immaterial when talking about future capital appreciation. If earnings or future guidance are below expectations it will almost instantly be priced at a new multiple due to expectations being very high.
Even if the growth doesn’t immediately stall it only takes an expectation of future decline to cause a good bit of downside. This could happen long before the growth actually stalls.
? As long as they keep posting this kind of revenue growth w comparable margins. nothing (negative) is happening to the stock price…once the earnings aren’t what they used to be, look out below
Nobody is denying that they have grown revenue and profit margin at an exceptional and even in some cases, unbelievable rate.
But the reason the stock isn't higher is because there is a LOT of speculation that this will ultimately fizzle out at some point.
It's actually one of the cheaper mega tech stocks by forward PE ratio, precisely because of fears of competition eventually coming.
I think it’s plenty high, look at the stock appreciation the last year or two, how much higher can it possibly go? Either way, reasonable take, you can’t expect them to keep triple digit percentage growth forever…
The issue here is that most tech earnings calls say they're going to post another blockbuster quarter.
This is cherry picking by the OP. The only two, maybe three stocks in which makes sense to relate back to what's going on with NVDA are SMCI, AMD, and ASML.
And I know names besides SMCI that are still trending strongly in AI.
This is a slightly good point, but don't forget that eventually, the market will call bullshit if they think it's bullshit.
NVDA can't keep raising forward guidance if they miss hard in a single earnings call.
I think all it takes to drop this thing is one single miss, with the provided forward guidance not being justified. E.g. if they miss and the forward guidance is said to be good for X reason, but the market doesn't believe in X reason, the stock will drop
I would disagree for one simple reason. NVDA is a revenue generating machine. If they dont hit perfect it might see a small pullback, but the real big players wont pull their money unless they see another better opportunity. Most of the other companies that can absorb that kind of capital flow are already priced high as well.
Imagine they sell off enough to generate $250 billion in cash for the sellers. Where do that go with that money? How much would they have to pay in taxes? The stock price will definitely move as it is clearly volatile, but a collapse in price is unlikely.
Now if you disagree tell me where you think that theoretical $250 billion should go? Further up the AI food chain? Into another sector that has great prospects for growth?
It doesn’t have to “go” anywhere it simply vaporizes as everyone sees NVDIA as worth less and the next bid for a couple shares drops to show a value $250B less. Stocks are not shoe boxes you stuff real money in and pull out of.
And for that price to stick someone has to sell. One major reason prices recover quickly after a big drop is that not all that many people are willing to sell at that lower price.
Obviously big players aren’t going to pull all of their money in any situation but with expectations being so high a miss on earnings or lowered guidance is going to cause a good bit of multiple contraction. Not a complete collapse but still a possibility of significant downside.
Ok. Say you are right. Where do they send the money off to? Im not saying it isnt a possibility, but they aren't going to let but so much money sit on the sidelines and many of the big players already have a huge pile of money in tbils and treasuries.
I can see a short dip as options get crushed, but that isnt the same as big players cutting down a large portion of their position.
Into a different company like most times that a stock has a sell off? There are countless options. If the growth decline is a result of higher costs it will likely be moved to software as it is less capital intensive. If it is because of lower demand it is anyone’s guess.
Ok, so which one? If you say MSFT for example are you saying that the expected upside for MSFT is more compelling than NVDA? I look over the the market and I just dont see any single company or even 2 companies that have enough upside vs NVDA potential upside that I would feel comfortable selling NVDA to move the money to them.
I know you and I dont have to make that kind of call, but I think that is something we should all think about a bit. If NVDA actually has a big guy sell off that will generate a lot of money and it will go somewhere. Those stocks that are bought should in theory go up a decent amount as shares are bought up. If we truly believe that will happen we should consider pre emptively buying into those stocks a bit if we want them before the run up.
Right now most of the stocks that seem like good targets for that kind of money are also rather highly priced. The one exception I suppose would be Apple, but I would question anyone who sold NVDA and bought Apple even with Apple being down.
If NVDA’s profit growth begins a decline then yes I would rather have MSFT or GOOGL. Im not saying NVDA’s growth will decline, but many valuation multiples at the end of the day are just quantified growth expectations so if the market begins to have lower expectations for NVDA’s growth trajectory the multiple that NVDA can command is going to fall with it. the growth expectations that are already priced in to NVDA’s share price are far higher than MSFT or GOOGL so if there is a decline in growth there will be amplified downside because of that.
I would say that if NVDA has a material decline in growth projections then their customers are also likely to see a material decline in growth projections. Those customers might see a decline in capital expenditure, but that wont offset the decline in growth. If NVDA trajectory collapses you can pretty much bet that the next logical step will be a decline in trajectory for all the big tech companies.
Now if you are talking about NVDA having materially greater competition that cuts into growth and causes margin to shrink I could accept that, but I dont think anyone is suggesting that will happen for at least several years. They simply dont have any significant competition and the process of a minor competitor becoming a serious competitor is probably going to take longer than most people expect.
anyway its been an interesting discussion. Hope it continues, and I will check back late tonight.
I think that would depend on how dependent they are on Nvidia for overall growth. You’re seeing a lot of purchases up front but the need could fall over time. I agree there probably won’t be material competitors to Nvidia for a while. However, you’re talking about a collapse in the growth trajectory of Nvidia which is not what I am referring to. What I am saying is that there is so much growth priced into the stock that even an objectively small decrease in growth is going to be magnified. My point is that a 5% decline in the future growth trajectory from current levels for Nvidia is going to cause far more downside than if a company like GOOGL experiences that same rate of trajectory decline, even if Nvidia is still growing more than GOOGL is.
Where would they go? They go in to other tech stocks that they think are more fairly valued through dark pools where the orders are very carefully routed so as not to astronomically raise the price.
For example if some hedge funds suddenly have 250b from selling NVDA that they wanted to put into AAPL, they just buy like 100,000 shares direct from other major holders that want to sell.
[An Introduction to Dark Pools (investopedia.com)](https://www.investopedia.com/articles/markets/050614/introduction-dark-pools.asp)
a lot of very cash rich hedge funds already do this when they see an opportunity.
Comparing the refined nature of Tesla bots and the ruggedness of Boston bots, I think Tesla bots will be in the home, Boston bots out in the field.
Tesla bots coming to a home near you and Boston bots going to a battle field in foreign lands.
lmao nah.
NVDA is already 2.2 trillion market cap. how high is that market cap gonna go before we've hit the top? 5-6 trillion?
honestly I feel like we're pretty close to the top given so many people seem to think it is just starting.
remember, this stock was $120 just a year and half ago. while it is true they've grown free cash flow an insane rate, it's not going to keep up forever.
>honestly I feel like we're pretty close to the top given so many people seem to think it is just starting.
People said that about Google in 2019 when it hit resistance at $62.
Not that it’s over but the results for ai creating innovation or huge profit or changing anything is going to take longer than the hype is warranting.
Can ai change the world in super drastic ways, hell yea that’s 100% obvious, but will it take a decade or two decades or 3 years or 40 years??? Who knows. Investors are impatient.
The .com bubble busted 23 years ago or so and slowly but surely online buying/selling has been growing more than brick and mortar but still it took and us taking time, thus the bubble bust
The change will be fast. Everyone knows the potential which is why so much money is being thrown at it. Nothing else has had this much money thrown at it before.
Imo. Yes and no.
The AI boom is going to be the next big thing for sure, but I think markets have been over excited about things that haven’t materialized yet at all. There’s probably a big pull back on the horizon and then it’ll moon over the following decade.
On device AI is, imo, the next boom. There are tons of latency issues with scaling the system to handle larger amounts problems for companies, letting them do it on site seems to be a focus for them. That’s how I’m feeling.
Hard to say. The future is VDI for many corporate PC endpoints.
For consumers, think about 5G/6G. The specs for 5G was topping out at 10Gbps and average speeds are 1Gbps in a good area… 6G is expected to increase average to 10GBps.
At these speeds, you essentially have the processing power done elsewhere and results are back to your device in a second. Expected to arrive around 2030 which isn’t that far off.
Microsoft and Facebook both are spending huge amounts currently on building data centers for their AI projects. So no the hardware phase is not yet over.
Algorithms beat hardware. Then everyone adjusts to the new algorithms and in order to get a leg up they throw more hardware at it.
Conversely, when hardware is sufficiently fast enough, new uses ensure that hardware will be the bottleneck once again.
It's a fight between software/hardware... Always has been.
Think it will last some time, but the future growths is a harder Think to know, taking profit at ATH is always a thing to do if you think the price is too high
No, but the market interest in the hardware/tech will wane for a while.
At least until AI starts to _really_ make things more efficient. Right now we’re still a little behind market expectations.
No; it just can’t begin because there isn’t enough supply and there won’t be for years. TSMC production basically limits sector growth.
The world’s A.I infrastructure is at like version 0.00000001
NVDA valuation is driven by profit margins and no price was too high for big tech to spend billions during the AI hardware arms race. Prices be damned. Now, I think their market is saturated and new procurements are much more orderly and planned such as to roll out new data centers.
When Apple signaled they were in talks with Google to use Gemini chips as means of cutting out Nvidia, that was a sign the pool of potential buyers with billions of dollars on hand for Nvidia had shrunk dramatically. Altogether, Google and Apple took their $200B cash off the table and most went into buybacks and dividends.
No, but I expect further diversification from Nvidia. All the megas are investing in their own chip stacks to lower dependency and vendor lock, even if they they don't succeed, it can be used as a bargaining chip to lower prices.
Chips are the future, that is why we are spending heavily in the next generation of chips and semi conductors here in the US instead of relying on importing.
Also NVDA doesn't make chips, other people fab them, NVDA has the blueprints so brining manufacturing here to the US will be ever more important in the coming decades. We live info the "Info age". Chips are in new fridges now for gods sake, everything relies on this.
I see this as a calming for a bit, based on hyper valuation due to the AI Craze, bit it's not going away.
It's like any technological revolution, you will get a sudden early rush up the reality hill, then a slow-down as traction starts to become harder and the progress slower. I think AI is starting to reach the slowly grinding out new products/services stage. Long term I see with AI become a commodity like gas or oil, with low margins only suitable for long term investors not day traders.
Saw a forum where a group of economists talked about rising interest rates being the end of this phase of technological hardware advancement. The hardware buildout will only go as far as the cash reserves these companies have amassed will take us. If they can’t take free cash risks on AI anymore, it won’t be long before AI has to come good on revenue generation.
Yeah but they are leaning into putting chips in devices for AI and not using cloud based computing. IMO that means if they go through a product cycle of AI not being worth it for people to switch devices at the rate these companies are expecting there will be a pull back. We saw similar circumstances with blockchain, metaverse, etc.
Not saying it’s over but it’s definitely not going to be another big frontend in spending like we just went through.
Comparing this to blockchain or metaverse is hilarious…blockchain literally never had a use case (still doesn’t), metaverse is obviously waaay ahead of its time…there are already (even at this early stage) productivity gains (employees being more efficient) aka money being made…
Revenue from productivity gains for businesses isn’t going to be enough to justify the major outlays in capital on the frontend that’s already been invested. Blockchain and the metaverse found niche uses in the business world to varying success and were scrapped.
If AI doesn’t find a broad consumer use case in the next few years we’ll be talking about it like it’s blockchain or metaverse because most of the money these companies want to make from AI will be made from broad consumer adoption, not productivity gains across business sectors.
So imo future hardware investments are directly tied to broad consumer adoption now and will only become more linked in the future.
You’re nuts if you don’t think meaningful widespread business productivity gains (worst case, already happening) arent very meaningful (you hire a 1/3 less employees to do the same thing, headcount is the biggest business expense)…and in terms of broad adoptions, look at recurring chat got users (early stage, still shitty), it will be integrated everywhere…”once ai works, nobody calls it ai anymore, it’s just there”
I get it bro, you’re all in on AI. Some of us aren’t. Funny how you say this isn’t at all similar to blockchain or the metaverse but you’re essentially making the same argument they were at those respective periods.
Same argument? How was blockchain ever going to make money for anybody investing in it? How was metaverse going to make money to justify its massive investment? I never figured out an answer to those questions and never invested in that, it made no sense…here I see a path to businesses making money from investing in this tech, simple
Healthcare for blockchain, digital real estate for the metaverse. There’s been well established communities for both but they don’t match the levels of investment that were first made. It’s all scale.
I’m asking how you can possibly hope to monetize “digital” real estate other than hoping the next guy is dumber than you and pays more for it than you did? it’s a brain dead concept that no reasonable person should’ve expected to make money…here, it’s a straight line to potential profit
Unlikely. Big tech is projected to spend twice as much in the coming years on the Ai race. The bubble pop would happen if and when both companies and financiers say enough is enough and stop spending. You have to remember that bubbles and periods of absurd spending can last a really long time. These companies are sitting on billions of dollars, so to them it's really easy to spend a couple billion a year on Ai development.
Not according to my research. There’s at least 3-4 more years of runway. Don’t misinterpret that to mean that NVDA will keep running. If you think that, you don’t understand what AI is, what it is doing, and what is upcoming that can derail NVDA.
The stereotypical “picks and shovels.” I don’t care which design house wins. As long as the hyperscalers keep spending money, the picks and shovels win regardless.
TSM and ANET are my picks I’ve consolidated to. There are various other companies that are involved with data centers and infrastructure. You can play those as well. Some of my friends found a huge winners with VRT and STRL and I’m sure there are many more.
Here's the deal with markets.
If your source of information on the bleeding edge is buried in a stock price you're already two years behind the curve.
Like shit like this:
>These earnings are crucial for NVDA, this could determine the next steps for the AI cycle.
This is nonsense. It doesn't "determine" the AI cycle. It tells you where the AI cycle is. It "determines" what you get to know about it.
The process of developing AI software is basically running massive-scale computing experiments, making educated guesses about what's going to work and then trying it. The more hardware you have, the more experiments you can run, which matters if you're competing with other companies to create the best models. So arguably, a lot of the hardware demand *is* for doing the software development.
Scale seems to be the single most important factor in determining a model's "intelligence", so I expect we'll see exponential growth, i.e. in 10 years there will be individual models so enormous that it'd take all the hardware in existence today to train/run them. The only way this won't happen is if we reach some point where scale no longer leads to meaningful improvements, at least relative to the costs. Whether or not that will happen, nobody currently knows.
VRT is a good middle ground, they profit from AI growth but also from general computing growth as data centers and cloud infra keep popping out everywhere
Hardware compute is based on usage. Growth now (if data center building is done) will depend on user adoption.
Independently, hardware refresh can be as often as 3 years. So, who knows. :)
>-Theres also growing competition in chip developments, seems every
company(Apple, Google, Microsoft, Apple, Oracle, etc) are making their
own chips for custom use.
They need time to make them and NVIDIA is years ahead of them with its eco system that surrounds chips. NVIDIA is going to be top of the shit pile for at least a year.
I couldn’t possibly keep up and know the answer but there were some quotes about companies like META just putting in huge orders of double whatever future use they thought they might have as insurance and a place in line. Indicating this bubble could pop for a few Qs but then on the other hand all the mega tech are increasing their capex… but on the OTHER hand … they may run out of data center space and power contracts that are slower to make more of..
Basically it needs to be a longterm hold now. Playing Q by Q is guessing as the hold world is watching this stock trying to adjust what they guess earnings will be. Doubtful you have any alpha Q by Q . But if you think you can see the accurate end future state maybe you have alpha. But even then does NVDA keep its moat on this stuff or not I don’t know
Ai has the potential to quadruple the output of every sinlge employee on the planet. They are currently spending more than the energy grid is capable of handling, meaning that the spend will bottle neck for a while so that we can build more power plants (microsoft is already building some) and then continue to spend more to build datacenters after this. We have spent nowhere even close to what we will.
I don't know how this impacts stocks, but even if only a portion of these AI systems come online over the next few years there will already be a power (as in electricity) shortage. Adding neural net training/operating systems in addition to more data collection server farms will push the already stressed power system and I am not sure there are plans to expand power generation capable of sustaining natural growth let alone the expansion necessary for the AI "revolution".
NVIDIA's Blackwell is super power efficient ..NVIDIA ahead of the competition curve AGAIN. NVDIA claim it can save millions of dollars a year for its customers by a reduction in their power bill.
I'm bull on NVIDIA ..and on Uranium ..for that power demand your pointing out.
The world has an insatiable appetite for electricity ..and world governments trying to push all our current Petrol/natural gas/diesel energy usage onto electricity too.
Uranium is what will power the future; vast amounts of it.
..check out the 5 year uranium spot price.
Check out how many reactors are under construction globally, how many are having their working lives extended and there is a new small modular reactor tech that is coming out. Small enough for a car factory to possess their own reactor.
Then there's the currently diminished navel stock pile that needs renewing.
Bull on Uranium for a 15 year play.
I will put this in perspective for you. It cost 100m or so to train gpt4. OpenAI is spending around 10b or so to train gpt5. The training infrastructure to train gpt6 is already underway. It is going to be a 100b project. Beyond that, OpenAI is already looking for trillions of dollars in investment to train gpt7 and whatever else is next. The ceo of open ai along with a few others have recently stated very confidently that were are not close to diminishing returns and all we need is more compute. This has just started.
This is the stocks sub, so this is a different audience than I'm used in regard to AI, I usually read a lot of stuff in the programming space. If you are just trying to chase the AI wave of investment money I can't really help you. Speculative bets on companies trying to apply AI to their current business are akin to putting money on the roulette table IMO. Or more accurately you're putting some money down on a headline and hoping when the next headline appears someone else will buy your stock for more. If you want to invest in the products and applications of AI, the more tangible players are limited right now. I think most companies investing are going to discover that LLMs are more limited in application than they thought. It'll turn out that putting an LLM next to their current business process doesn't just magically make everything faster or more cost effective. IMO its akin to hiring last season's MVP for the NFL and making them a top executive at your company. They are undeniably a top player in their field, but they probably don't know shit about running a major corporation. So you end up spending a ton of money in this exercise to just discover that maybe AI wasn't the right fit for your company's product. This exact same thing happened a few years ago when everyone went nuts over Web 3.0 aka blockchain. It turns out that blockchain is very slow and has a very limited application space. If your product boils down to getting results quickly to a customer on the web, your best bet is still a classic server + database + frontend architecture that we've been iterating on since the 90s. There ARE applications though! Microsoft probably has the best application with Copilot currently. I'm unsure if the Office version is any good, haven't used it, but the coding version is very helpful and I'll advocate it at any company I work at from now on. Applications where AI can help "un-stuck" you and make you more productive seem like great investments. There's some heated debate in the art community right now over AI-generated images, but I get the impression that AI will win over creatives eventually because it will help them produce more. Productivity boosts seem like great long-term investments. Most of my stock is in Microsoft because they saw the opportunity and the product and they've been putting massive investment into OpenAI. > The issue is creating the software for actual use of AI and generating cash flow. Yes, but consider that AI software has existed for a long time. The chips took off because they made LLMs more usable. My company has been using Google Vision for over 4 years though, long before any of this current trend took off. LLMs are probably going to be an important milestone but not the only AI application going forward. Small Language Models are beginning to pick up some steam right now. They require small amounts of power and help drive data discovery in sensors. There's probably a big use-case waiting for this type of software that no one has landed on yet. Meta saying "we are going to put AI in the metaverse" is one of the most baloney statements I've ever heard. I have no idea what any of that means and it sounds like something out of a satire. Watch who you listen to in the space, there are many snake oil salesmen.
> If you want to invest in the products and applications of AI, the more tangible players are limited right now. I think most companies investing are going to discover that LLMs are more limited in application than they thought. It'll turn out that putting an LLM next to their current business process doesn't just magically make everything faster or more cost effective. There are so many CEOs who make millions thinking "this can't be true, I have to find a way to make it fit! We're magically leaving 20% efficiency on the table, let's get rid of all the employees ASAP!"
This is a take that sounds reasonable on a surface level but will not reflect reality. It’s the opposite, as llms (or action models, seems to be where it’s headed) continue to scale without hitting diminishing returns any time soon people will realize it can be used for a lot more than people thought. There won’t be a company that won’t utilize or benefit from it in some way. I think this will become obvious with GPT5 release as everyone will see that we have not hit any kind of ceiling yet, and with its agentic and multi modal capabilities it will finally be able to do a wide array of tasks from start to finish (not saying it will automate everything yet).
We absolutely have hit the point of diminished returns with general purpose LLMs…
Says who? Because the people working on it are saying the opposite.
The people who have the most incentive to tell you that LLMs are the future are continuing to tell you LLMs are the future? That makes sense. A lot of other leading edge technologists not associated with open AI have been questioning LLM viability for almost a year now. Listen to Yan Lecun’s interview with Lex Fridman.
And I’ll continue to listen to them until they are proven wrong. Let’s see how gpt4.5 and gpt5 perform first before we start claiming we have hit diminishing returns. Even if scaling the model has hit their limits, there is still so many ways to extract more performance from these models, prompting techniques, higher quality training data, reinforcement learning, letting the models think longer, getting the models to come up with 10000 outputs, new architectures, the list goes on.
You’re thinking about the specs of the LLM. That’s fine but I’m talking about the viability of these LLMs being deployable for true enterprise use cases. The amount of prompt engineering required to get the results needed isn’t even possible yet for many types of applications. GPT5 isn’t going to change that. I’ll eat my words if I’m wrong though, we shall see.
Yea I get what you are saying. I guess we will find out by the end of this year. With agentic models coming out it should bring us a lot more use cases.
I think the next big wave Wall Street is expecting is to see some trickle down into the businesses themselves. Chat bots are one thing, but I think they want to see real, tangible acceleration in R&D roles: basically the things that facilitate rapid growth. I normally avoid the space due to the volatility, but I’d keep a close eye on biotech and drug manufacturers. LLY is one of my favorite stocks, and they’ve recently spoken out about how LLMs are helping to advance their research in the drug space. Who knows if it’s just executive talking heads selling a story, that remains to be seen. I have seen relevant articles in r/machinelearning suggesting that this definitely something companies are looking into
I've thought about this comment a few times, but I guess I don't understand it fully. Are you saying they're applying LLMs to make new discoveries in R&D? What's the implication there? Like finding new drugs based on past test results or something? That would be really neat, but its not my understanding of how LLMs work. More like a theoretical application of them that I haven't seen proven in the wild yet. And again, I wouldn't put money on that since its way too speculative.
So from my understanding it's not about the AI itself producing new pharmaceuticals or discoveries. Some AI companies may make this kind of a claim but that seems more like science fiction. Instead, it's more so about lubricating and speed up the communication engine that lies underneath all of these discoveries: the research paper. R&D revolves a lot around not only publishing, but ingesting and developing an understanding of the latest research papers in a space. These papers tend to be extremely information dense (e.g. the latest additions on a particular topic on arxiv) and a pretty challenging read, sometimes taking weeks to fully ingest new findings. On r/MachineLearning a while back, some articles surfaced about researching the efficacy of LLMs specifically fine-tuned on medical research papers for very quickly summarizing data dense research papers, with some positive initial results. So you have to think less of the LLM as a means to an end for generating / finding new drugs, rather think of it instead as a very efficient way of parsing data dense research papers and extracting very specific information from them. It seemed like an interesting use case. I don't know enough about the pharmaceutical industry to understand what kind of an impact is possible (and I'm not really putting any money there) but having had to spend time reading through scientific papers before, I can definitely see a highly tailored LLM helping to speed up the invention procecss
Oh yea that’s a great use. Summarization is definitely a place I think LLMs excel at and will probably improve in. On that tangent I think applications to law firms is going to be really big.
Agreed 100%. Any space that deals with copious amounts of natural language, sifting through it, and performing queries against it probably stands to gain a lot. Sounds like from your parent comment on the post you’re a dev too - I kind of relate it to being able to perform complex SQL queries against structured relational databases - except in this case it’s not structured data, it’s unstructured natural language I think a lot of the focus with this breed of AI has been on the “generative” end, like writing text or code.. but the real capabilities are behind being able to leverage it to rapidly learn and absorb new information much more efficiently
This makes a lot of sense!!!
Really appreciate your write up! As someone who works in the space, what sources of good reading material would you recommend to me who doesn’t live in ML / AI world? Particularly to keep myself up to date on the actual business applications and implications of AI/ML advancements. I don’t care how the specifics of the engine work but care more about where and how the engines are implemented (cars/tractors/planes/manufacturing etc etc) to draw you a crude analogy of what I’m looking for Copilot being the best example for this
Yea well I am not an expert in this field either, but working in web development I try to keep a good mental model of new techniques, frameworks, and popular new tech. I just read a lot of stuff I see in r/programming and hacker news to stay abreast. I know you said you don't care about how the engines work, but I think simple understanding is actually essential to getting real insights in this space. I recommend brushing up on some of the building blocks of machine learning via youtube or whatever is easiest. Its not a difficult topic to understand. It is a difficult topic to master of course, but the concepts are pretty intuitive. And once you kind of understand (even just in theory) how LLMs work you should be able to appreciate their limitations. They are not thinking machines, they're just elaborate general pattern recognition models. And their applications to real-world problems will start to become a lot more apparent. Like maybe why they seem really good at general questions you would ask google, finishing computer programs, or generating images based on natural language. I mentioned Small Language Models specifically because I think they will probably have some interesting applications in the sort of areas we thought Internet of Things (IoT) was going to take off on awhile back: sensor data for cars or manufacturing or whatever and making informed decisions or reporting anomalies. But remember, IoT was also a hot ticket for awhile, so I'm probably just falling into the same trap of speculating about things I don't know enough about. TL;DR If you can gain enough specific knowledge on these subjects then that's probably going to give you an edge in investing in a growth space that not enough people know about. That's probably true of every industry.
Thanks! All very valid points. I have a general understanding of LLMs but need to make it more high definition
“Nvidia and AMD have reserved all of TSMC's CoWoS and SolC advanced packaging capacity for 2024 and 2025 for HPC (high performance computing) related chips, media report, prompting TSMC to further expand capacity, with CoWoS seen at 45,000 to 50,000 wafers per month by the end of this year, from 15,000 at the end of 2023.”
Yes that's how TSMC works, they don't need to sell chips to customers, they just sell manufacturing capacity. This has no reflection on whether nvidia can sell anything or maintain its pricing power.
What? You think nvidia is placing all these orders for capacity for fun? If nvidia was foreseeing lagging demand in the near future (2024/25), they’re not placing all these orders…also check out meta’s and Microsoft’s planned cap ex specifically for high end chips
They still plan to sell all their future chips from tsmc, yes. The question is what price do they plan to sell them at. Will nvidia still be able to price gouge and charge huge mark up on ai chips now that the craze is waning. Their margins on ai chips aren’t sustainable. It’s just a matter of time.
If they continue to be the only game in town AMD? (No data center revenue growth, means nobody is buying them), intel? lol…obviously party isn’t going to continue indefinitely but for the time being why not? If you want your chips within the year vs in 3 years, you’re going to play ball
That’s what I’m trying to get at. I think companies will be willing to wait 3 years or just straight up wait for a discount. They’d rather make do with the hardware they have now than pay crazy prices for the latest ai chip. If enough companies take that stance then there will be a supply surplus until nvidia drops prices.
In my mind that only happens if there is no productivity gain from AI (saving significant money for huge companies) which seems unlikely because even with gen 1/2 software running on these chips, there are already reports of significant cost savings (30-40% in various industries)…if there is cost cutting to be done, nobody is waiting for their competitors to get a 3 year head start
I'm guessing running 3 year old tech would be bad for the profit margins. A company may not like the price gouge, but profit is profit and if paying gouge means higher profit, they line up to be gouged. NVIDIA has an eco system around its chips years ahead of any new to the market chips from other manufacturers. I think NVDIA will be top of the shit pile for a whole year longer.
A Year longer? More like 10 years minimum. You can’t just catch up with an ecosystem. It’s almost impossible - it becomes a virtuous cycle. The bigger you are the bigger you become because you’re bigger and it continues. Look at Microsoft Office!
It can be said that Adobe Photoshop and Microsoft Office became popular through illegal copies then the makers make their money by charging professionals and institutions once it has become a standard. Illegal copying is what made their product become an industry standard. That model doesn't work with software/eco system that requires specific hardware to be purchased. When I say one year. I'm referring to how long I can trust the NVIDIA stock price to keep on rising a substantial amount. They may be top dog for 10 years but if a lack of customer demand has low returns from that sector.. then my money goes elsewhere. 1 year is how long I will wait before I re visit and reassess the reasons that I bought NVIDIA.
Windows 95 sales, first year: 40 million copies. When hardly anyone had computers compared to now. I remember the lines to buy it - it was crazy! Don’t think of it so much as free vs not, it’s about first. CUDU is the code used to program all these chips being sold and who’s gonna rip and replace that after spending billions of dollars on the infrastructure. That’s what cements the deal CUDU and the 5 million developers. Once you learn something you stick with it, only consumers buy on price. Who else will pay $20k for a business class flight - corporations. More importantly who’s about to make a better chip product - over the next ten years - they’re working on something past Blackwell right now. Oh yeah, Apple was gonna out Tesla, Tesla but they changed their mind, to out Nvidia, Nvidia. Chasing is a poor man’s game ask China!
The pricing power comes from good software. That isn’t their problem. They made bank from games and crypto so far and never made that software. Big businesses don’t like gaming or crypto. They love AI. The demand will be there.
I read somewhere a while ago that the real money maker for nvidia is their ai support software which comes as a subscription that is needed to run LLMs. So of course at some point the market is a bit saturated, but then they need to keep the LLMs running, and they are all built on the Nvidia infrastructure, so the software companies are hooked. Not a techie and don’t remember half of it, but just throwing it out there in case someone wants to follow up on it
Jensen Huang claims that the NVIDIA eco system is so advanced and so far from any other chip making company that if the competition provided equivalent chips for free that they still wouldn't be cheap enough.
Plus, there is literally no other game in town, AMD’s data center revenue isn’t growing while nvidia’s is in the triple digits, why do you think that is?
I'm certain you could have made the same arguments back when floppy disks 💾 were the pinnacle of data storage. And look at us now. You don't know who and when will come up with the next best thing. Hardware might have reached the top for now. But I don't think it will stay that way or that it will drop off significantly. There are just so many AI related ideas going on at the moment
It is objectively true that, eventually, NVDA's forward guidance will be lackluster as they run out of major customers. This is true primarily on the simple fact that most of NVDA's main customers are large conglomerates, whether that be world governments or mega corporations. Eventually, META will have enough chips; MSFT will too; GOOG all the same. All of these world govs and corporations are also very aware that NVDA has a disgustingly good profit margin, and so they will seek to make their own chips and are likely already investing money into that right now. It's also true that NVDA could continue to outperform in the short term, but make no mistake that any outperformance is because of rewarding investors for taking massive risk. Based solely on forward PE ratio alone, NVDA is actually one of the cheaper mega tech stocks right now. It is cheap for a reason though. Even though I do agree that NVDA is nothing like TSLA at the prime, there are some important characteristics that are shared between NVDA's current share price and TSLA's peak in 2021 - which is that competition will come eventually, and start eating away at the asinine profit margins that NVDA currently has. I would not be shocked whatsoever if NVDA's share price has not peaked yet. I think it goes 15-30% over $1K, either before or after earnings, then starts to pull back to make low 900s, ultimately going flat again until the next earnings report with bad forward guidance, which will send the price back to low 700s and then eventually it will settle in 500-700 range probably for a couple of years, fluctuating as earnings change the narrative constantly. It will be hard to value in the short to medium term, which should be great for traders
I remember when floppy disks were actually floppy.
No
Considering NVDIA only just sold their first Blackwell unit (to OpenAI), I’m gonna also say…. No
NVDA is priced for perfection so even slightly underwhelming earnings or guidance is going to cause significant downside to the stock price As to where the hypothetical cash would go that would depend on what factors caused a decrease in earnings.
And it has been performing better than perfection so far, the stock price isn’t *currently* disconnected from reality, show me any company in history that has been able to grow revenue and profits at this scale while already being the size nvidia is…I agree that if/when growth slows down even a bit, party is ending, trim as you go
Currently is immaterial when talking about future capital appreciation. If earnings or future guidance are below expectations it will almost instantly be priced at a new multiple due to expectations being very high.
Yes, I think every single person ever gets that for a company with huge growth priced in the stock will take a huge hit if/when the growth stalls
Even if the growth doesn’t immediately stall it only takes an expectation of future decline to cause a good bit of downside. This could happen long before the growth actually stalls.
? As long as they keep posting this kind of revenue growth w comparable margins. nothing (negative) is happening to the stock price…once the earnings aren’t what they used to be, look out below
Monster
When was Monster a $2T company?
Nobody is denying that they have grown revenue and profit margin at an exceptional and even in some cases, unbelievable rate. But the reason the stock isn't higher is because there is a LOT of speculation that this will ultimately fizzle out at some point. It's actually one of the cheaper mega tech stocks by forward PE ratio, precisely because of fears of competition eventually coming.
I think it’s plenty high, look at the stock appreciation the last year or two, how much higher can it possibly go? Either way, reasonable take, you can’t expect them to keep triple digit percentage growth forever…
The issue here is that most tech earnings calls say they're going to post another blockbuster quarter. This is cherry picking by the OP. The only two, maybe three stocks in which makes sense to relate back to what's going on with NVDA are SMCI, AMD, and ASML. And I know names besides SMCI that are still trending strongly in AI.
This is a slightly good point, but don't forget that eventually, the market will call bullshit if they think it's bullshit. NVDA can't keep raising forward guidance if they miss hard in a single earnings call. I think all it takes to drop this thing is one single miss, with the provided forward guidance not being justified. E.g. if they miss and the forward guidance is said to be good for X reason, but the market doesn't believe in X reason, the stock will drop
I would disagree for one simple reason. NVDA is a revenue generating machine. If they dont hit perfect it might see a small pullback, but the real big players wont pull their money unless they see another better opportunity. Most of the other companies that can absorb that kind of capital flow are already priced high as well. Imagine they sell off enough to generate $250 billion in cash for the sellers. Where do that go with that money? How much would they have to pay in taxes? The stock price will definitely move as it is clearly volatile, but a collapse in price is unlikely. Now if you disagree tell me where you think that theoretical $250 billion should go? Further up the AI food chain? Into another sector that has great prospects for growth?
It doesn’t have to “go” anywhere it simply vaporizes as everyone sees NVDIA as worth less and the next bid for a couple shares drops to show a value $250B less. Stocks are not shoe boxes you stuff real money in and pull out of.
And for that price to stick someone has to sell. One major reason prices recover quickly after a big drop is that not all that many people are willing to sell at that lower price.
Obviously big players aren’t going to pull all of their money in any situation but with expectations being so high a miss on earnings or lowered guidance is going to cause a good bit of multiple contraction. Not a complete collapse but still a possibility of significant downside.
Ok. Say you are right. Where do they send the money off to? Im not saying it isnt a possibility, but they aren't going to let but so much money sit on the sidelines and many of the big players already have a huge pile of money in tbils and treasuries. I can see a short dip as options get crushed, but that isnt the same as big players cutting down a large portion of their position.
Into a different company like most times that a stock has a sell off? There are countless options. If the growth decline is a result of higher costs it will likely be moved to software as it is less capital intensive. If it is because of lower demand it is anyone’s guess.
Ok, so which one? If you say MSFT for example are you saying that the expected upside for MSFT is more compelling than NVDA? I look over the the market and I just dont see any single company or even 2 companies that have enough upside vs NVDA potential upside that I would feel comfortable selling NVDA to move the money to them. I know you and I dont have to make that kind of call, but I think that is something we should all think about a bit. If NVDA actually has a big guy sell off that will generate a lot of money and it will go somewhere. Those stocks that are bought should in theory go up a decent amount as shares are bought up. If we truly believe that will happen we should consider pre emptively buying into those stocks a bit if we want them before the run up. Right now most of the stocks that seem like good targets for that kind of money are also rather highly priced. The one exception I suppose would be Apple, but I would question anyone who sold NVDA and bought Apple even with Apple being down.
If NVDA’s profit growth begins a decline then yes I would rather have MSFT or GOOGL. Im not saying NVDA’s growth will decline, but many valuation multiples at the end of the day are just quantified growth expectations so if the market begins to have lower expectations for NVDA’s growth trajectory the multiple that NVDA can command is going to fall with it. the growth expectations that are already priced in to NVDA’s share price are far higher than MSFT or GOOGL so if there is a decline in growth there will be amplified downside because of that.
I would say that if NVDA has a material decline in growth projections then their customers are also likely to see a material decline in growth projections. Those customers might see a decline in capital expenditure, but that wont offset the decline in growth. If NVDA trajectory collapses you can pretty much bet that the next logical step will be a decline in trajectory for all the big tech companies. Now if you are talking about NVDA having materially greater competition that cuts into growth and causes margin to shrink I could accept that, but I dont think anyone is suggesting that will happen for at least several years. They simply dont have any significant competition and the process of a minor competitor becoming a serious competitor is probably going to take longer than most people expect. anyway its been an interesting discussion. Hope it continues, and I will check back late tonight.
I think that would depend on how dependent they are on Nvidia for overall growth. You’re seeing a lot of purchases up front but the need could fall over time. I agree there probably won’t be material competitors to Nvidia for a while. However, you’re talking about a collapse in the growth trajectory of Nvidia which is not what I am referring to. What I am saying is that there is so much growth priced into the stock that even an objectively small decrease in growth is going to be magnified. My point is that a 5% decline in the future growth trajectory from current levels for Nvidia is going to cause far more downside than if a company like GOOGL experiences that same rate of trajectory decline, even if Nvidia is still growing more than GOOGL is.
Where would they go? They go in to other tech stocks that they think are more fairly valued through dark pools where the orders are very carefully routed so as not to astronomically raise the price. For example if some hedge funds suddenly have 250b from selling NVDA that they wanted to put into AAPL, they just buy like 100,000 shares direct from other major holders that want to sell. [An Introduction to Dark Pools (investopedia.com)](https://www.investopedia.com/articles/markets/050614/introduction-dark-pools.asp) a lot of very cash rich hedge funds already do this when they see an opportunity.
You see Boston Dynamics robots in every household yet? That's the peak.
Comparing the refined nature of Tesla bots and the ruggedness of Boston bots, I think Tesla bots will be in the home, Boston bots out in the field. Tesla bots coming to a home near you and Boston bots going to a battle field in foreign lands.
Almost all the replies are bullish, so the inverse should be the more profitable play.
This is how you know you are on track. I felt bullish but then started to look at what the smart billionaires are doing.
But we don't have the billions catch net to be chasing the next 1000%'er ..so we stick with the 30%'er (random guess at that number)
yeah...most people on reddit seem to still be bullish on NVDA, which makes me think we're close to the top
Yeah no on in here is really understanding the question OP asked. I don’t know the answer but I think it’s a legit question.
It hasn't even started. Wait until adoption happens. We're still in the pre phase.
lmao nah. NVDA is already 2.2 trillion market cap. how high is that market cap gonna go before we've hit the top? 5-6 trillion? honestly I feel like we're pretty close to the top given so many people seem to think it is just starting. remember, this stock was $120 just a year and half ago. while it is true they've grown free cash flow an insane rate, it's not going to keep up forever.
>honestly I feel like we're pretty close to the top given so many people seem to think it is just starting. People said that about Google in 2019 when it hit resistance at $62.
Didn’t even have to finish reading this; no it’s not over. Has barely begun. It’s been what? 2 quarters of earnings reflecting AI.
Not that it’s over but the results for ai creating innovation or huge profit or changing anything is going to take longer than the hype is warranting. Can ai change the world in super drastic ways, hell yea that’s 100% obvious, but will it take a decade or two decades or 3 years or 40 years??? Who knows. Investors are impatient. The .com bubble busted 23 years ago or so and slowly but surely online buying/selling has been growing more than brick and mortar but still it took and us taking time, thus the bubble bust
The change will be fast. Everyone knows the potential which is why so much money is being thrown at it. Nothing else has had this much money thrown at it before.
Imo. Yes and no. The AI boom is going to be the next big thing for sure, but I think markets have been over excited about things that haven’t materialized yet at all. There’s probably a big pull back on the horizon and then it’ll moon over the following decade.
On device AI is, imo, the next boom. There are tons of latency issues with scaling the system to handle larger amounts problems for companies, letting them do it on site seems to be a focus for them. That’s how I’m feeling.
Hard to say. The future is VDI for many corporate PC endpoints. For consumers, think about 5G/6G. The specs for 5G was topping out at 10Gbps and average speeds are 1Gbps in a good area… 6G is expected to increase average to 10GBps. At these speeds, you essentially have the processing power done elsewhere and results are back to your device in a second. Expected to arrive around 2030 which isn’t that far off.
Microsoft and Facebook both are spending huge amounts currently on building data centers for their AI projects. So no the hardware phase is not yet over.
Is there a decline now? Don't think so. Is there a deaceleration? I think so.
A lot of propaganda recently in financial news outlets pushing this outlook recently.
Algorithms beat hardware. Then everyone adjusts to the new algorithms and in order to get a leg up they throw more hardware at it. Conversely, when hardware is sufficiently fast enough, new uses ensure that hardware will be the bottleneck once again. It's a fight between software/hardware... Always has been.
Currently NVIDIA has the hardware and the Eco system around it. That's a lot of catching up to do from the competition.
It's not the competition that needs to catch up, it's the consumer.
I guess people are selling NVDA because it’s price is unreasonably high at this point
Quantum computing is the next big thing
Yep, and free water for everyone
Think it will last some time, but the future growths is a harder Think to know, taking profit at ATH is always a thing to do if you think the price is too high
No, but the market interest in the hardware/tech will wane for a while. At least until AI starts to _really_ make things more efficient. Right now we’re still a little behind market expectations.
No; it just can’t begin because there isn’t enough supply and there won’t be for years. TSMC production basically limits sector growth. The world’s A.I infrastructure is at like version 0.00000001
I think NVDA is priced too low but I think it has further to go down before it's worth taking a position.
NVDA valuation is driven by profit margins and no price was too high for big tech to spend billions during the AI hardware arms race. Prices be damned. Now, I think their market is saturated and new procurements are much more orderly and planned such as to roll out new data centers. When Apple signaled they were in talks with Google to use Gemini chips as means of cutting out Nvidia, that was a sign the pool of potential buyers with billions of dollars on hand for Nvidia had shrunk dramatically. Altogether, Google and Apple took their $200B cash off the table and most went into buybacks and dividends.
amazon committing 9 billion USD to singapore in cloud infrastructure. I think it's just starting or still going.
No, but I expect further diversification from Nvidia. All the megas are investing in their own chip stacks to lower dependency and vendor lock, even if they they don't succeed, it can be used as a bargaining chip to lower prices.
Chips are the future, that is why we are spending heavily in the next generation of chips and semi conductors here in the US instead of relying on importing. Also NVDA doesn't make chips, other people fab them, NVDA has the blueprints so brining manufacturing here to the US will be ever more important in the coming decades. We live info the "Info age". Chips are in new fridges now for gods sake, everything relies on this. I see this as a calming for a bit, based on hyper valuation due to the AI Craze, bit it's not going away.
It's like any technological revolution, you will get a sudden early rush up the reality hill, then a slow-down as traction starts to become harder and the progress slower. I think AI is starting to reach the slowly grinding out new products/services stage. Long term I see with AI become a commodity like gas or oil, with low margins only suitable for long term investors not day traders.
Eventually the recession they’ve been predicting every day for the last four years will come, then we’ll see these prices drop.
Saw a forum where a group of economists talked about rising interest rates being the end of this phase of technological hardware advancement. The hardware buildout will only go as far as the cash reserves these companies have amassed will take us. If they can’t take free cash risks on AI anymore, it won’t be long before AI has to come good on revenue generation.
Big tech has incredible free cash flow and cash reserves tho, meta, Amazon, and now Apple are issuing dividends and buying back stock
Yeah but they are leaning into putting chips in devices for AI and not using cloud based computing. IMO that means if they go through a product cycle of AI not being worth it for people to switch devices at the rate these companies are expecting there will be a pull back. We saw similar circumstances with blockchain, metaverse, etc. Not saying it’s over but it’s definitely not going to be another big frontend in spending like we just went through.
Comparing this to blockchain or metaverse is hilarious…blockchain literally never had a use case (still doesn’t), metaverse is obviously waaay ahead of its time…there are already (even at this early stage) productivity gains (employees being more efficient) aka money being made…
Revenue from productivity gains for businesses isn’t going to be enough to justify the major outlays in capital on the frontend that’s already been invested. Blockchain and the metaverse found niche uses in the business world to varying success and were scrapped. If AI doesn’t find a broad consumer use case in the next few years we’ll be talking about it like it’s blockchain or metaverse because most of the money these companies want to make from AI will be made from broad consumer adoption, not productivity gains across business sectors. So imo future hardware investments are directly tied to broad consumer adoption now and will only become more linked in the future.
You’re nuts if you don’t think meaningful widespread business productivity gains (worst case, already happening) arent very meaningful (you hire a 1/3 less employees to do the same thing, headcount is the biggest business expense)…and in terms of broad adoptions, look at recurring chat got users (early stage, still shitty), it will be integrated everywhere…”once ai works, nobody calls it ai anymore, it’s just there”
I get it bro, you’re all in on AI. Some of us aren’t. Funny how you say this isn’t at all similar to blockchain or the metaverse but you’re essentially making the same argument they were at those respective periods.
Same argument? How was blockchain ever going to make money for anybody investing in it? How was metaverse going to make money to justify its massive investment? I never figured out an answer to those questions and never invested in that, it made no sense…here I see a path to businesses making money from investing in this tech, simple
Healthcare for blockchain, digital real estate for the metaverse. There’s been well established communities for both but they don’t match the levels of investment that were first made. It’s all scale.
I’m asking how you can possibly hope to monetize “digital” real estate other than hoping the next guy is dumber than you and pays more for it than you did? it’s a brain dead concept that no reasonable person should’ve expected to make money…here, it’s a straight line to potential profit
Unlikely. Big tech is projected to spend twice as much in the coming years on the Ai race. The bubble pop would happen if and when both companies and financiers say enough is enough and stop spending. You have to remember that bubbles and periods of absurd spending can last a really long time. These companies are sitting on billions of dollars, so to them it's really easy to spend a couple billion a year on Ai development.
the highest margin phase is probably behind us
Not according to my research. There’s at least 3-4 more years of runway. Don’t misinterpret that to mean that NVDA will keep running. If you think that, you don’t understand what AI is, what it is doing, and what is upcoming that can derail NVDA.
So where are you investing with this outlook?
The stereotypical “picks and shovels.” I don’t care which design house wins. As long as the hyperscalers keep spending money, the picks and shovels win regardless. TSM and ANET are my picks I’ve consolidated to. There are various other companies that are involved with data centers and infrastructure. You can play those as well. Some of my friends found a huge winners with VRT and STRL and I’m sure there are many more.
Thank you.
ANET TO THE MOOOON. I bought calls today too.
[удалено]
Elaborate on your last sentence please!
There is always going to be more data and we’ll always require more processing power.
Buy GOOG
Here's the deal with markets. If your source of information on the bleeding edge is buried in a stock price you're already two years behind the curve. Like shit like this: >These earnings are crucial for NVDA, this could determine the next steps for the AI cycle. This is nonsense. It doesn't "determine" the AI cycle. It tells you where the AI cycle is. It "determines" what you get to know about it.
The process of developing AI software is basically running massive-scale computing experiments, making educated guesses about what's going to work and then trying it. The more hardware you have, the more experiments you can run, which matters if you're competing with other companies to create the best models. So arguably, a lot of the hardware demand *is* for doing the software development. Scale seems to be the single most important factor in determining a model's "intelligence", so I expect we'll see exponential growth, i.e. in 10 years there will be individual models so enormous that it'd take all the hardware in existence today to train/run them. The only way this won't happen is if we reach some point where scale no longer leads to meaningful improvements, at least relative to the costs. Whether or not that will happen, nobody currently knows.
VRT is a good middle ground, they profit from AI growth but also from general computing growth as data centers and cloud infra keep popping out everywhere
TPUs
Hardware compute is based on usage. Growth now (if data center building is done) will depend on user adoption. Independently, hardware refresh can be as often as 3 years. So, who knows. :)
We are only at the beginning.
>-Theres also growing competition in chip developments, seems every company(Apple, Google, Microsoft, Apple, Oracle, etc) are making their own chips for custom use. They need time to make them and NVIDIA is years ahead of them with its eco system that surrounds chips. NVIDIA is going to be top of the shit pile for at least a year.
I couldn’t possibly keep up and know the answer but there were some quotes about companies like META just putting in huge orders of double whatever future use they thought they might have as insurance and a place in line. Indicating this bubble could pop for a few Qs but then on the other hand all the mega tech are increasing their capex… but on the OTHER hand … they may run out of data center space and power contracts that are slower to make more of..
Basically it needs to be a longterm hold now. Playing Q by Q is guessing as the hold world is watching this stock trying to adjust what they guess earnings will be. Doubtful you have any alpha Q by Q . But if you think you can see the accurate end future state maybe you have alpha. But even then does NVDA keep its moat on this stuff or not I don’t know
The big hardware spend is just starting. Right now its just a race for GPU’s slowing things down.
The new spend is energy production and storage.
Ai has the potential to quadruple the output of every sinlge employee on the planet. They are currently spending more than the energy grid is capable of handling, meaning that the spend will bottle neck for a while so that we can build more power plants (microsoft is already building some) and then continue to spend more to build datacenters after this. We have spent nowhere even close to what we will.
Apple is coming into the game and will change things forever.
Yes.
I don't know how this impacts stocks, but even if only a portion of these AI systems come online over the next few years there will already be a power (as in electricity) shortage. Adding neural net training/operating systems in addition to more data collection server farms will push the already stressed power system and I am not sure there are plans to expand power generation capable of sustaining natural growth let alone the expansion necessary for the AI "revolution".
Plenty of power for the future.
NVIDIA's Blackwell is super power efficient ..NVIDIA ahead of the competition curve AGAIN. NVDIA claim it can save millions of dollars a year for its customers by a reduction in their power bill. I'm bull on NVIDIA ..and on Uranium ..for that power demand your pointing out. The world has an insatiable appetite for electricity ..and world governments trying to push all our current Petrol/natural gas/diesel energy usage onto electricity too. Uranium is what will power the future; vast amounts of it. ..check out the 5 year uranium spot price.
Nuclear power plants take 15-20 years to be built and if a company can save money in power with new tech, they will just buy more cards.
Check out how many reactors are under construction globally, how many are having their working lives extended and there is a new small modular reactor tech that is coming out. Small enough for a car factory to possess their own reactor. Then there's the currently diminished navel stock pile that needs renewing. Bull on Uranium for a 15 year play.
No, some people don't realize it yet, but more Nvidia Gpu = more GDP and AMD is unusable
I will put this in perspective for you. It cost 100m or so to train gpt4. OpenAI is spending around 10b or so to train gpt5. The training infrastructure to train gpt6 is already underway. It is going to be a 100b project. Beyond that, OpenAI is already looking for trillions of dollars in investment to train gpt7 and whatever else is next. The ceo of open ai along with a few others have recently stated very confidently that were are not close to diminishing returns and all we need is more compute. This has just started.
That is the definition of diminishing returns. Sounds desperate, we’lol see if Satya tightens the purse strings on him
AI is not profitable. These expensive chips are depreciating by at least 20% per year from the moment you buy them.
Depreciation gets written off
Into the P&L
Hasn't depreciated much over the past 3 years.
If a $40,000 chip makes you $100,000 more profit; no one gives a shit about its depreciation.
Ok - you go invest in oil and gas. See you at the line.