Well, stock price is not a good short term indicator about Nvidia developments, nor any company for that matter. Nvidia is doing a very good job.
That being said, their stock is absolutely and hilariously overvalued.
That being said, their stock is absolutely and hilariously overvalued.
If you're convinced the stock is that overvalued, go short some or, if you like to live dangerously, buy some long-term put options (don't be an idiot and buy short-term options.)
I have no idea if NVDA is like Cisco Systems in 2000, or if it's something unique. What I am aware of is that there's around 5-7 trillion that were moved from stocks to t-bills since the Fed raised rates in March 2022. If and when they drop their rates back to the historical ~2.5%, it's reasonable to predict these funds will go back into stocks, which will presumably drive up prices.
Buying long-term put options on Nvidia now is extremely expensive - the stock was so volatile that the price you pay for those options almost annihilate any gains you could expect, even if the stock losses 50% in 12 months.
You got me curious about those 5-7 trillions. Where these numbers come from ?
For us, older folks, we've seen this 'new normal' several times already - it will end up as usual. There are no free lunches and as it appears to me that have not entered any permanently high plateau.
It's even quite funny that ~100 years ago, we've had the previous big pandemic, and the biggest stock market crash. Epidemic of this century is done, now waiting for the second part !
To clarify, I’m not saying NVDA won’t crash from here or bear markets no longer exist. I’m simply saying that historic PE valuations are a poor metric for assessing the potential of a stock in todays market conditions.
Yes, it's probably the first time that retail is allowed to trade options. But it's not the first time that retail is all in in stocks. I've tried to find a funny number to back it up - just check the Wiki on 1929 crash - https://en.wikipedia.org/wiki/Wall_Street_Crash_of_1929 - there was more money lent to 'small investors' so they can buy on margin ... than the entire amount of currency circulating at the time.
On average, all those retail guys will loose money - that's the sad truth. In the long term, the stocks simply follow the earnings - all other movements around this trends are pretty much a zero sum game - and most skilled operators are not loosing money in that game.
Price to earning ratio is just the number of years the company 'pays for itself' if you buy it. PER at 40s for big chunks of main indexes mean that either there will be tremendous progress in the economy that will boost the earnings or people are hoping to resell to a bigger fool.
Note: I work in finance, and I very much see the retail involvement in stocks. Hedge Funds and banks, are making a ton of money out of them, that's for sure.
Frankly, I don't understand why we made it possible for individuals to gamble by selling options. As Charlie Munger used to say, Wall Street will sell shit as long as shit can be sold.
Selling cash secured puts or selling covered calls would be less risky than just holding stock.
This doesn't make much financial sense. Since every T-Bill is held by someone the amount of T-Bill outstanding is completely determined by government issuance. And since the amount of T-Bill outstanding will only grow over time, no "money" will ever flow out of it. Now if you narrow you inclusion of T-Bill holders to a specific group of people the amount this group holds could certainly go up and down over time. But then I wonder how you know this group sold stocks to buy T-Bills, and why this is more significant than the action of their counterparties: every share they sold was bought by someone else after all.
You've also had three or four bona fide bubbles in that span, starting around 2017. First was Bitcoin along with the stock market as a whole (with Nvidia being one of the leading stocks of that bull market advance).
Then you had Tesla go parabolic and lots of people become rich. Then you had the whole post-COVID speculative mania.
The result of this has been extreme credulity by the average person. Today's keynote is the perfect summation of this phenomenon. I saw multiple people who almost certainly couldn't explain in any level of detail how Nvidia GPUs are used for training and inference, but rather rely on the secondhand talking points like CUDA that they've learned by watching Jim Cramer, watching this keynote with excitement and anticipating how much it would pump their shares or call options.
Contrast this with Steve Jobs keynotes from 15 years ago when Apple's best days were well ahead of them. Most keynotes were questioned, in some cases even mocked. When Tesla stock broke out, many people couldn't make sense of it. Ditto for cryptocurrencies. But now, taking their cues from those cycles, the average person wants to ride the next bubble to riches and is trying to catch the wave and so now believes every story attached to a rising asset price.
CEO's aren't blind to this and are using every opportunity to create favorable storylines. The leadup to a keynote like this carries with it an enormous amount of pressure to deliver. Hence a company like Nvidia leaning into generative artwork and straight up made up storylines like robot development.
At the end of the day, I'm afraid that there likely isn't all that much substance and the evidence is beginning to pile up that the megacap tech stocks have run out of ideas which is why they are laying off people en masse and appealing to the AI hype cycle to carry their stocks higher.
Consider that Nvidia has gone up 8x- 800%!- in just over a year. The cycles are moving faster and faster. I remember just a year ago when lots of people said Nvidia at $250 was insane. Now here we are with the stock at more than three times that level and most people are calling it cheap. The stock market seems to have in certain areas like semis, completely disconnected from the fundamentals and taken flight. Yes, Nvidia earnings have grown. But understand that this is all part of a positive feedback loop where tech CEO's are pressured by their competitors and shareholders to show that they are investing in AI. Thus they all talk about it on their earnings calls and spend massively. All of their stocks rise in unison as you have a market that increasingly looks like its chasing momentum stock trends up. Nvidia's moves of late have almost nothing to do with any fundamental developments in the company. It has been routinely trading upwards of $45 billion a day. The Friday before last that number was over $100 billion. These are absolutely insane figures. Compare that to Microsoft, the largest company by market cap in the world, which trades on average around $8 billion per day.
I think this is generally how bull markets end and I think we may be actually forming the top of the great bull market for the megacaps that began around 2010 but really hit its stride starting in 2017.
However they went up 8x because (neglecting crypto) they overnight transitioned from providing accessories to PC gamers and high end engineering workstations (both increasingly niche markets with tapering growth or decline) to being for the moment the only substrate of an entirely new consumer product segment that has seen the most rapid adoption of any new technology in the history of the world.
This could be the way things work now: the time constants shrink as the pipeline efficiency increases.
In the past year, they had a revenue of 60B $ and net income of 30B $. Absolutely amazing numbers, I agree. The year before they had a revenue of 30B $ and a net income of 4.5B $ - and it was a rather good year. What happens next of course depend of how you judge the situation - was it a peak hype demand ? Will it stabilize now ? Grow at current extraordinary rates ?
Scenario 1 - margins get back to normal due to hype going down, competition improving etc - in this case the company is worth at best ~200B $ - or 1/10 of what it is now.
Scenario 2 - they maintain current revenue and the exceptional margins - the company would be worth ~1T - or 1/2 of what it is now.
Scenario 3 - they current growth rate (based on past 12 months) continue for ~5 years. This is the case the company is worth ~2T $.
But they are in a business where most money come from a handful of customers, all of which are working on similar chips - and given the sums in play now, the incentives are *very* strong.
My opinion, is that the company is already priced for perfection - basically the current price reflects the perfect scenario. I struggle to see any upside, unless we have AGI in the next 5 years and it decides it can only run on Nvidia chips.
All of this is akin to Tesla in the past years. They grew from a small startup to a medium car maker - the % growth rate was huge of course - an amazing achievement in itself. But people projected that the % growth rate would continue - and the stock was priced accordingly. Reality is catching up on Tesla, even if some projections are still absolutely crazy.
Apple is in talks with Google to bring Gemini to the iPhone, and it will obviously also be on android phones. So almost every phone on earth is poised to be using Gemini in the near future, and Gemini runs entirely on Google's own custom hardware (which is at parity or better than nVidia's offerings anyway).
Making a graphics chip that is as good as Nvidia: Very difficult. Huge moat, huge effort, lots of barriers, lots of APIs, lot of experience, lots of decades of experience to overcome.
Making something that can run a NN: Much, much easier. I'd guess, start-up level feasible. The math is much simpler. There's a lot of it, but my biggest concern would be less about pulling it off and more around whether my custom hardware is still the correct custom hardware by the time it is released. You'd think you could even eke out a bit of a performance advantage in not having all the other graphics stuff around. LLMs in their current state are characterized by vast swathes of input data and unbelievably repetitive number crunching, not complicated silicon architectures and decades-refined algorithms. (I mean, the algorithms are decades refined, but they're still simple as programs go.)
I understand nVidia's graphics moat. I do not understand the moat implied by their stock valuation, that as you say, they are the only people who will ever be able to build AI hardware. That doesn't seem remotely true.
So... correct me Internet. Explain why nVidia has persistent advantages in the specific field of neural nets that can not be overcome. I'm seriously listening, because I'm curious; this is a deliberate Cunningham's Law invocation, not me speaking from authority.
After 10 years of pretending to care about compute, AMD has filled the industry with burned-once experts who, when weighing nvidia against competitors, instinctively include "likely boondoggle" against every competitor's quote because they've seen it happen, possibly several times. Combine this with nvidia's deep experience and and huge rich-get-richer R&D budget keeping them always one or two architecture and software steps ahead, like it did in graphics, and their rich-get-richer TSMC budget buying them a step ahead in hardware, and you have a scenario where it continues makes sense to pay the green tax for the next generation or three. Red/blue/other rebels get zinged and join team "just pay the green tax." NV continues to dominate. Competitors go green with envy, as was fortold.
More like burned 2x / 3x / 4x of this time it's different people.
Looking at you Intel
But (as a reply to some other repliers as well), AMD was also chasing them on the entire graphics stack as well as compute. That is trying to cross the moat. Even reimplementing CUDA as a whole is trying to cross a moat, even a smaller one.
But just implementing a chip that does AI, as it stands today, full stop, seems like it would be a lot easier. There's a lot of people doing it and I can't imagine they're all going to fail. I would consider by far the more likely scenario to be that the AI research community finds something other than neural nets to run on and thus the latest hotness becomes something other than a neural net and the chips become much less relevant or irrelevant.
And with the valuation of nVidia basically being based not on their graphics, or CUDA, but specifically just on this one feeding frenzy of LLM-based AI, it seems to me there's a lot of people with the motivation to produce a chip that can do this.
To become a person who writes driver infrastructure for this sort of thing, you need to be a smart person who commits, probably, several of their most productive years to becoming an expert in a particular niche skillset. This only makes sense if you get a job somewhere that has a proven commitment of taking driver work seriously and rewarding it over multiple years.
NVidia is the only company in history that has ever written non-awful drivers, and therefore it's not so implausible to believe that it might be the only company that can ever hire people who write non-awful drivers, and will continue to be the only company that can write non-awful drivers.
I don't think they have a crazy advantage HW wise. Couple of start-ups are able to achieve this. If SW infrastracture end is standardized, we will have a more level playground.
Without CUDA you have a chip that runs on premise without anyone having a clue how good that is which is supposedly what Google does. Your only offering is cloud services. As big as this is, corporations would want to build their own datacenters.
I think nobody had the time to port any of these architectures away from CUDA because: * the leaders want to maintain their lead and everyone needs to catch up asap so no time to waste, * and progress was _super_ fast so doubly no time to waste, * there was/is plenty of money that buys some perceived value in maintaining the lead or catching up.
But imo: 1. progress has slowed a bit, maybe there's time to explore alternatives, 2. nvidia GPUs are pretty hard to come by, switching vendors may actually be a competitive advantage (if performance/price pans out and you can actually buy the hardware now as opposed to later).
In terms of ML "compilers"/frameworks, afaik there's:
* Google JAX/Tensorflow XLA/MLIR, * OpenAI Triton, * Meta Glow, * Apple PyTorch+Metal fork.
Zen 1 showed that absolute performance is not the end-all metric ( Zen lost on single-core performance vs Intel). A lot of people care for bang-for-buck metric. If AMD can squeak out good-enough drivers for cards with good-enough performance for a TCO[1] significantly lower than NVidia, they break Nvidia's current positive feedback cycle.
1. Initial cost and cooling - I imagine for AI data center usage, opex exceeds capex.
Competition WILL come. Maybe it's Groq, maybe AMD, maybe Cerebras. Maybe there's a stealth startup out there. Point is, they're going to be challenged soon.
It's almost impossible to manufacture at scale with good yields and leading edge fabs are almost all bought out.
Yes, CUDA, but CUDA is maaaaaybe a few tens of billion USD deep and a few (more) years wide. When the rest of the industry saw compute as a vanity market, that was sufficient. Now, it's a matter of time before margins go to, uhhh, less than 90%.
Does that make shorting a good idea? I wouldn't count on it. The market can always remain irrational longer than you can remain solvent.
However, given that the nearest competitor AMD has basically given up on building a CUDA alternative, despite the fact that this could grow the company by literal trillions of dollars, I suspect the CUDA moat is much bigger than I give it credit for.
At this point AMD investors should be rebelling, it's pissing money out there but they are not getting wet, and management might have doubled the stock price but that's little consolation if "order of magnitude" is what could have been.
Looking at the chart for $AMD over the past 5 years gives plenty od reasons to be happy, and no reason to rebel. A rational AMD investor should not be Jonesing Nvidia's catching lightning in a bottle via crypto + AI. The Transformers paper was published a few months before AMD released Zen 1 chips - they did not have a lot of money for GPU R&D then.
The timing of the LLM-craze was very fortuitous for Nvidia.
Tesla went after them with Dojo and has still ended up splurging on big H100 clusters.
The move from PoW to PoS for most crypto networks in combination with bust of ‘22. NVDA slid down in value.
OpenAI debuts ChatGPT in late 2022 and now it’s suddenly bumping in price as the hype and rush for GPUs from companies of all types buys up their stock of GPUs. Demand is far outpacing the supply. Nvda can’t keep up.
Thus, share price is brittle. Competition in the GPU market is dominantly owned by Nvidia. That can change, but so far openai loves using nvidia for some reason.
You may wish to look at history to see how things can work out: Cisco had a P/E ratio of 148 in 1999:
* https://www.dividendgrowthinvestor.com/2022/09/cisco-systems...
The share price tanked, but that does not mean that people got bored of the Internet and the need for routers and switches. QCOM had a P/E of 166: did people decide that mobile communications was a fad?
The connection between technological revolutions and financial bubbles dates back to (at least) Canal Mania:
* https://en.wikipedia.org/wiki/Canal_Mania
* https://en.wikipedia.org/wiki/Technological_Revolutions_and_...
It is possible for both AI to be a big thing and for NVDA to drop.
> https://en.wikipedia.org/wiki/Tulip_mania
While widely used as an example, most of the well-known stories about this were actually made up, and it wasn't as bad as it is often made out to be.
Quinn and Turner, when they wrote about bubbles:
* https://www.goodreads.com/book/show/48989633-boom-and-bust
* https://old.reddit.com/r/AskHistorians/comments/i2wfsm/i_am_...
purposefully excluded it because their research found it wasn't actually a thing. (Though for the general public it can be an illustrative parable.)
The compute for a direct answer like that is fractions of a penny, it might be better to create answers on the fly than store an index of every question anyone has asked (well, that's essentially what the weights are after all)
https://www.linkedin.com/pulse/rising-cost-llm-based-search-...