You seem to misunderstand the dot com bubble. Sure, there were companies like Pets.com and companies adding an 'e' to the beginning of their names. But there were also companies like Cisco and Sun Microsystems. Companies making profits selling real goods needed by the growing internet. Go look up those companies and their stock charts. Also, if you think random companies aren't mentioning AI to boost their stock you haven't been paying much attention.

I would be comparing how someone like Intel did during dot.com instead of Pets.com etc. Of course it far from being the same and Intel did struggle in the early 00’s but they still ended up dominating their market which had significant growth in the 20 years after dot.com.

Did Intel ever ‘grow’ into their massively overvalued valuation? No.. their stock never even reached it’s September, 2000 peak yet.

There is a chance that AMD, Intel, maybe Google etc. catch up with Nvidia in a year or two and data center GPUs become a commodity (clearly the entry bar should be lower than what it was for x86 CPUs back in) and what happens then?

Exactly. In the current situation the "dotcom boom" would be any companies who are currently forcing themselves to use AI for the sake of using AI so that they can say "we use AI to [task that can be done without AI]".

Nvidia is different in that they're the ones selling the hardware, AI isn't going anywhere imo, the spike Nvidia is seeing atm may subside a little but I doubt it, as minor players give up, stronger players will still need more hardware anyway.

Tbh imagine being Nvidia: * Known for dominating in the gaming market, consumers buy plenty of Nvidia cards and always will do * Workstation cards have always been used for CAD/rendering digital media and always will be * Nvidia hardware used in plenty of supercomputers * Crypto craze hit and Nvidia sold a bajillion cards for that, I imagine 2nd-hand mining cards have impacted the consumer arm of their biz but probably not too much, I've seen people avoid buying crypto cards unless they're offered at a very low price * Nvidia has sold cards to people doing AI for a long time, but now the AI boom has started and they're making bank

Basically they've enjoyed the crypto boom and are now enjoying the AI boom, but even if AI boom declines to 0 (it won't) they can still fall back on their workstation/consumer hardware.

Reason I don't think the AI boom will end is that besides companies smashing AI in for no reason, actual applications of it are incredibly useful. I still remember friends being amazed that they could search their Google Photos by "dog" or "cat" (which as furries it's hilarious that it comes up with fursuiters).

Are there numbers available on current ML applications GPU sales volume, is it really a big share of NV revenue? Dedicated ML hardware like TPUs would seem to be the logical perf/$ competitor longer term, they're so far proprietary but so are NV sw and hw after all.

SpotifAI

> The ironic bit of course is that my own research here is powered by Bard which probably used an NVDA gpu to train it

Google uses in-house TPUs for Bard.

https://www.hpcwire.com/2023/04/10/google-ai-supercomputer-s...

What ElevenLabs is doing with synthesised voices is absolutely amazing. Not quite fully realistic yet, but they're the best I've ever heard.

In addition 2minute papers viewers have seen that AI generated media is coming fast, soon we'll go from Unity/Unreal having an AI "assistant" that can generate models "make a chair for two characters in the same style as this single person chair" to "based on the current information you know about this game world, generate a new zone for the player that includes x, y, z challenges, resources. Create models, textures, animations for all of this" etc. And this is only implications for making games, let along all the other stuff we could get it to do.

The video on automatic animations (https://www.youtube.com/watch?v=wAbLsRymXe4 and others) is super cool, once refined it's going to be possible to have a system that can: generate a character model, texture it, automatically animate it for that particular character (young, old, how many limbs) and adjust as needed "right foot becomes injured, so limp" generated voices and unique dialogue set within the realm of the overall game world. I think main plots will still be controlled by game makers, but interaction with rando npcs/side-quests could be totally organic.

You are correct that the overall economic backdrop is quite different from the late 90s.

Nonetheless, the AI news cycle is continuous (like .COM was) and the attribution of NVDA's +25% romp to the prospects of AI grabs the attention of retail investors, who tuned in to see AVGO +20% and the likes of MSFT, TSLA, NFLX and GOOG add 5% in 2 days. The longer that goes on, the more we'll see investors looking for reasons that companies will benefit from AI and want to buy in, then, companies that don't have a strong AI story will need to get on the train and start buying all the AI startups that have materialized over the last couple of years. Then, we start seeting AI IPOs with increasingly sketchy histories. (sorry, .COM PTSD kicking in...)

All this could happen in a weak market. In fact, strong returns in AI during a weak overall market will simply call more attention to it.

I mean it's completely wrong though as you still have shares in the company after getting paid.

A very good rule of thumb is: if someone's mentions dividends when discussing valuation they are clueless. It doesn't always work (paying high dividends has implications ranging from clueless management to political pressure on the company) but it's a very good rule that the argument is nonsense.

This ignores inflation and other factors in the macro environment. But ultimately, any argument that a stock is mispriced is definitionally wrong, because the price of a stock is what someone is willing to pay for it. It's a cliche but it's also an incontrovertible fact, even if people like to ignore it because it invalidates all their arguments.

I agree with you, especially on un-regulated white-collar work (e.g. no one with magic letters after their name is in danger just yet).

But give it a few years and I'm really curious how regulatory and licensing bodies react because they have almost always moved uniformly in whichever direction is necessary to suppress wages. There are few exceptions to this (e.g. physicians). The output benefits of worker + AI could potentially lead to some professional services becoming dirt cheap, while others become ludicrously expensive.

I'm also curious what this means for immigration. For the West, the primary justification to siphon the world's talent fundamentally vanishes. That's talent that potentially stays put and develops in non-Western countries. For countries where the entire country is a demographic ponzi using immigrants to prevent collapse, it's potentially an existential problem.

Could you please detail why do you think Machine Learning will obviate jobs that are already useless?

You're right, but I don't think so. From the moment that 80/99% realizes they're out of work, it's over. That's why you see idiot anti-AI spokespeople showing up, why Altman is invited to Bilderberg, why EU is making AI-laws. They're not against AI, as such, but please do not "awaken" the working class. Keep it for "trusted parties" or the military only. What I am curious about is how NVIDIA will position itself against that background.

Personally, I did really wish this would have been a new-era moment where society would take a step back and evaluate how we are organizing ourselves (and living, even), but I fear that AI comes too late for us, in the sense that we're so rusted and backwards now that we cannot accept it. Or any important change, in fact. It's pretty depressing.

Massively decreasing pay, while not solving the asset inflation problem... this ain't going to go well at all.

This is because you're looking at trailing P/E instead of forward.

NVDA forward P/E is still eye watering, but it's much lower.

Correct. I bought 1000 shares in early Feb, and it's up over 82%.

You cannot look at the prior price to make a purchase decision. You have to look at the future projected revenues per share, and apply an industry standard multiple.

If you hesitate to buy a stock you like because you feel annoyed that you didn't buy it for cheaper the day/week/month before, you will nerf yourself.

I suppose I could sell now and be happy with my $350 profit...

And NVDA added more than AMDs entire market cap on that day alone, including the gains AMD had.

Yeah but I didn't buy AMD stock! Clearly I should have though.

As others have intimated, you'll never go bankrupt by selling [for a profit] too early. I put $10k into bitcoin when it was $1500, and sold it when it hit $4k. Yeah, I can do the math at $60k and feel bad, but realistically if I had the mentality to hold it from $1500 to $60k I would have waited for it to hit $80k and I'd feel objectively worse today about those paper losses, albeit with a little bit more money in the bank.

At the end of the day doubling your money is exceedingly rare, especially on any single security, no sense feeling bad you didn't 10x it.

You made a profit, no self-kicking allowed. Otherwise Old Man Mikestew is going to tell us stories about how he rode $STOCK all the way up, didn't sell, and rode it all the way back down to where he bought it, and then watched it dip below that. (Please note that "stories" is plural; slow learner, he is.)

Don't be like me: never, never, never, never feel bad about selling shares for a profit. Sell it, go one about your day (IOW, quit looking at $STOCK, you don't own it anymore), take the spouse/SO out for a nice dinner if you made some serious bank.

Which reminds me that now might be a good time to unload that NVDA I've been holding. I'm not completely unteachable.

Just... don't. Enjoy the profits when you get 'em. :)

This forum is filled with people who sold all sorts of tech stocks way too early (or too late), and people nerding out over things and tossing them and them magically gaining tons of value over time - I'm thinking about all of my super early CCGs that I tossed when cleaning house, the 20 bitcoin I mined for fun way back in 2012 or whenever and then deleted from my laptop (that I then sold on eBay for $100), the 10k of AAPL I bought for like $5 and sold for $10, etc. etc.

Same with all the early job opps and what not too - but we're the sum of our life choices till now and that's OK. :)

I bought 100 shares of AMD for 8$ and sold at 16$ thinking I was a genius

Hey, a win is a win, and profit is profit!

I'm still holding ~600 shares of NVDA from a $1,200 investment back when I thought it was amazing that this company made cards that made Quake 2 look incredible.

300k Investment on $900 dollars.

Did you say foundry? Nations (including US and Germany) have tried to out smart TSMC, and yet here we are.

If you meant outsmart nvidia, Google’s TPU is already more efficient but a GPU is much more than an efficient design .

They don't set the forward P/E - it's literally what the price of the stock the market bid up / actual earnings points to. The market is expecting them to double or triple their income in the coming quarters/years.

The TTM Price/Earnings ratio is even crazier as the market is expecting them to grow revenue 9x from what they made in the last year (to get back to a 20x P/E).

When I spent time playing individual stocks I actually made decent money waiting for big spikes like this, hopping on the bandwagon intraday and just taking 1-2% in the hype train. It's part day trading part picking up pennies in front of a steamroller. The few times I really got burned is getting greedy and holding overnight or over a weekend.

I'm really curious to see where NVDA stands on Tuesday morning.

With respect to the incompatabilities with PyTorch and TensorFlow - given that the AMD and Intel GPU drivers are more likely to be open sourced - do you believe the open source community or a third party vendors will step in to close the gap for AMD/Intel?

It would seem a great startup idea with the intent to get acqui-hired by AMD or Intel to get into the details of these incompatibilities and/performance differences.

At worst it seems you could pivot into some sort of passive income AI benchmarking website/YT channel similar to the ones that exist for Gaming GPU benchmarks.

Theoretically the ARC should work with llama.cpp using OpenCL, but I haven't seen benchmarks or even a confirmation that it works.

This has been the case for a while because AMD never had the resources to do software well. But their market cap is 10x what it was 5 years ago, so now they do. That still takes time, and having resources isn't a guarantee of competent execution, but it's a lot more likely now than it used to be.

On top of that, Intel is making a serious effort to get into this space and they have a better history of making usable libraries. OpenVINO is already pretty good. It's especially good at having implementations in both Python and not-Python, the latter of which is a huge advantage for open source development because it gets you out of Python dependency hell. There's a reason the thing that caught on is llama.cpp and not llama.py.

The only real remaining fronts in the war are consoles and smartphones, and NVIDIA just signed a deal to license GeForce IP to mediatek so that nut is being cracked as well, mediatek gives them mass-market access for CUDA tech, DLSS, and other stuff. Nintendo has essentially a mobile console platform and will be doing DLSS too on an Orin NX 8nm chip soon (very cheap) using that same smartphone-level DLSS (probably re-optimized for lower resolutions). Samsung 8nm is exactly Nintendo's kind of cheap, it'll happen.

The "NVIDIA they might leave graphics and just do AI in the future!" that people sometimes do is just such a batshit take because it's graphics that opens the door to all these platforms, and it's graphics that a lot of these accelerators center around. What good is DLSS without a graphics platform? Do you sign the Mediatek deal without a graphics platform? Do you give up workstation graphics and OptiX and raysampling and all these other raytracing techs they've spent billions developing, or do you just choose to do all the work of making Quadros and all this graphics tech but then not do gaming drivers and give up that gaming revenue and all the market access that comes with it? It's faux-intellectualism and ayymd wish-casting at its finest, it makes zero sense when you consider the leverage they get from this R&D spend across multiple fields.

CUDA is unshakeable precisely because NVIDIA is absolutely relentless in getting their foot in the door, then using that market access to build a better mousetrap with software that everyone else is constantly rushing to catch up to. Every segment has some pain points and NVIDIA figures out what they are and where the tech is going and builds something to address that. AMD's approach of trying to surgically tap high-margin segments before they have a platform worth caring about is fundamentally flawed, they're putting the cart before the horse, and that's why they keep spinning their wheels on GPGPU adoption for the last 15 years. And that's what people are clamoring for NVIDIA to do with this idea of "abandon graphics and just do AI" and it's completely batshit.

Intel gets it, at least. OneAPI is focused on being a viable product and they'll move on from there. ROCm is designed for supercomputers where people get paid to optimize for it - it's an embedded product, not a platform. Like you can't even use the binaries you compile on anything except one specific die (not even a generation, "this is binary is for Navi 21, you need the Navi 23 binary"). CUDA is an ecosystem that people reach for because there's tons of tools and libraries and support, and it works seamlessly and you can deliver an actual product that consumers can use. ROCm is something that your boss tells you you're going to be using because it's cheap, you are paying to engineer it from scratch, you'll be targeting your company's one specific hardware config, and it'll be inside a web service so it'll be invisible to end-users anyway. It's an embedded processor inside some other product, not a product itself. That's what you get from the "surgically tap high-margin segments" strategy.

But the Mediatek deal is big news. When we were discussing the ARM acquisition etc people totally scoffed that NVIDIA would ever license GeForce IP. And when that fell through, they went ahead and did it anyway. Because platform access matters, it's the foot in the door. The ARM deal was never about screwing licensees or selling more tegras, that would instantly destroy the value of their $40b acquisition. It was 100% always about getting GeForce as the base-tier graphics IP for ARM and getting that market access to crack one of the few remaining segments where CUDA acceleration (and other NVIDIA technologies) aren't absolutely dominant.

And graphics is the keystone of all of it. Market access, software, acceleration, all of it falls apart without the graphics. They'd just be ROCm 2.0 and nobody wants that, not even AMD wants to be ROCm. AMD is finally starting to see it and move away from it, it would be wildly myopic for NVIDIA to do that and Jensen is not an idiot.

Not entirely a direct response to you but I've seen that sentiment a ton now that AI/enterprise revenue has passed graphics and it drives me nuts. Your comment about "what would it take to get Radeon ahead of CUDA mindshare" kinda nailed it, CUDA literally is winning so hard that people are fantasizing about "haha but what if NVIDIA got tired of winning and went outside to ride bikes and left AMD to exploit graphics in peace" and it's crazy to think that could ever be a corporate strategy. Why would they do that when Jensen has spent the last 25 years building this graphics empire? Complete wish-casting, “so dominant that people can’t even imagine the tech it would take to break their ubiquity” is exactly where Jensen wants to be, and if anything they are still actively pushing to be more ubiquitous. That's why their P/E are insane (probably overhyped even at that, but damn are they good).

If there is a business to be made doing only AI hardware and not a larger platform (and I don’t think there is, at that point you’re a commodity like dozens of other startups) it certainly looks nothing like the way nvidia is set up. These are all interlocking products and segments and software, you can’t cut any one of them away without gutting some other segment. And fundamentally the surgical revenue approach doesn’t work, AMD has continuously showed that for the last 15 years.

Being unwilling to catch a falling knife by cutting prices to the bone doesn’t mean they don’t want to be in graphics. The consumer GPU market is just unavoidably soft right now, almost irregardless of actual value (see: 4070 for $600 with a $100 GC at microcenter still falling flat). Even $500 for a 4070 is probably flirting with being unsustainably low (they need to fund R&D for the next gen out of these margins) but if a de-facto $500 price doesn’t spark people’s interests/produce an increase in sales they’re absolutely not going any lower than that this early in the cycle. They’ll focus on margin on the sales they can actually make, rather than chasing the guy who is holding out for 4070 to be $329. People don't realize it but obstinently refusing to buy at any price (even a good deal) is paradoxically creating an incentive to just ignore them and chase margins.

It doesn’t mean they don’t want to be in that market but they’re not going to cut their own throat, mis-calibrate consumer expectations, etc.

Just as AMD is finding out with the RX 7600 launch - if you over-cut on one generation, the next generation becomes a much harder sell. Which is the same lesson nvidia learned with the 1080 ti and 20-series. AMD is having their 20-series moment right now, they over-cut on the old stuff and the new stuff is struggling to match the value. And the expectations of future cuts is only going to dampen demand further, they’re Osborne Effect’ing themselves with price cuts everyone knows are coming. Nvidia smartened up - if the market is soft and the demand just isn’t there… make less gaming cards and shift to other markets in the meantime. Doesn’t mean they don’t want to be in graphics.

Unrelated question for the HN experts:

My sibling commenter is shadowbanned, but if you look into their comment history, there are occasionally comments that are not dead. How does this happen?

Isn't the coral stick a TPU?

Google's first TPU was developed a year after Tensorflow. And for that matter, Tensorflow works fine with CUDA, was originally entirely built for CUDA, and it's super weird the way it's being referenced in here.

Tensorflow lost out to Pytorch because the former is grossly complex for the same tasks, with a mountain of dependencies, as is the norm for Google projects. Using it was such a ridiculous pain compared to Pytorch.

And anyone can use a mythical TPU right now on the Google Cloud. It isn't magical, and is kind of junky compared to an H100, for instance. I mean...Google's recent AI supercomputer offerings are built around nvidia hardware.

CUDA keeps winning because everyone else has done a horrendous job competing. AMD, for instance, had the rather horrible ROCm, and then they decided that they would gate their APIs to only their "business" offerings while nvidia was happy letting it work on almost anything.

Every tech giant is sprinting into this space. I highly doubt nVidia will still have a moat as big in 12 months.

Yes, well, everyone else already had that idea with AMD in the last month.

TSMC's P/E is under 20. Disclaimer: I hold

Goog, Meta? They are by far leading in AI research, and they've both developed their own chip. Apple is also going to come out ahead with their Neural chip - imagine chatGPT and stable diffusion becoming part of the iOS SDK

Just use hckrnews.com , it shows frontpage posts from previous days.

“The market can stay irrational longer than you can stay solvent.” - John Maynard Keynes

Particularly applicable here, couldn't resist myself.

Gaming might be their worst business from a growth and narrative perspective. Wall street in general doesn't really care about gaming, just see how those companies are priced.

Enterprise compute has been and will continue to be NVidias bread and butter going forward, and they have been betting on this for the past decade. Whether enterprise compute will be for AI, studio graphics, simulation, FSD, etc. those are all more lucrative and imo more interesting from a growth perspective vs their gaming segment. b2b companies have much higher ceilings than b2c.

What signals to you that other chip makers are capable of competing in learning and inference computation?

We know they'll be motivated, but can they actually compete is the question.

Gaming revenue is down. Check their earnings release.

The best part about this if you have that much conviction, you can buy 2025 puts and make a ton of money if you're right. Good luck!

Which hardware/software pairing do you see dethroning NVIDIA that quickly?

https://blogs.nvidia.com/blog/category/auto/

PS - you can literally go to https://www.nvidia.com/en-us/ and read the menu to see what they do...

Even if the 4090 costs $1999 it's still cheaper than a $15000 H100 considering you get similar cuda cores & can buy enough to balance VRAM between the two

Thanks

> CUDA lock in

The amount of software written for CUDA pales in comparison to the amount that has been written for Intel x86, yet two large companies migrated off it.

The lock-in with Intel was due to binary distribution (Windows software), and binary ABIs.

Everything to do with large language models is compiled from scratch, using high level languages.

The LLM codes themselves themselves are trivial things, easily replicated in a matter of hours on some other platforms. The hard part is gathering the training data and the compute.

The hard parts are not dependent on CUDA.

Look at it this way: Google developed Transformers and trained multiple LLMs using TPUs, not CUDA GPUs! The reason their LLMs are stupid is not because of the TPUs.

This has been my experience as well with TPUs and A100s. I haven’t used H100s yet (OOM on 1) but I believe the training throughout benchmarks from Nvidia on transformer workloads is 2.5x from A100s.

The effort to make (PyTorch) code run on TPUs is not worth it and my lab would rather rent (discounted) Nvidia GPUs than use free TRC credits we have at the moment. Additionally, at least in Jan 2023 when I last tried this, PyTorch XLA had a significant reduction in throughput so to really take advantage you would probably need to convert to Jax/TF which are used internally at Google and better supported.

It baffles me to this day that Google never made TPUs more widely available. Then again it is Google...

For transformer, v4 chip has 70-100% compute capacity and 40% memory of A100 for pretty much the same price. The only benefit is better networking speed for TPU compared to GPU cluster, allowing very large models to scale better, where for GPU model need to fit in NVlink connected GPUs, which is 320 billion parameters for 8*80 GB A100.

As someone closer to this in the industry (embedded ML.. and trying to compete) I agree with the sentiment. Their software is good, I willingly admit. Porting a model to embedded is hard. With NVIDIA, you basically don’t have to port. This has paid dividends for them, pun not intended.

I don’t really see the Nvidia monopoly on ML training stopping anytime soon.

But their valuation is based on forward (future) earnings, using an already obsolete technology.

AWS has their own accelerators, and they're a much better value than their GPU instances.