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Ask HN: Could AI be a dot com sized bubble?
159 points by jameslk 5 months ago | hide | past | favorite | 130 comments
AI hype has landed in the laps of retail investors and in general anyone passively investing as NVIDIA and Microsoft shares have risen and become part of major ETFs in the expectation that the AI-driven demand for their products will continue unabated. Other tech stocks seem to be seeing similar treatment around AI hype.

I do expect the current trajectory of generative models will eventually be incredibly important just like the internet was and is, but it seems there’s a lot of high expectations of how useful it can be in the near future with fuzzy ideas around business models like in the dot com era.

If these near future expectations don’t pan out, could companies slow down their R&D expenditures which are floating NVIDIA, Microsoft, et al and lead to a sizable stock market correction?




Yes, it could. It may even surpass the dotcom bubble in size.

But AI hype in 2024 is not even close to dotcom hype in early 2000.

During the dotcom bubble, companies IPOed with no revenue and no profit. In 2024, OpenAI is probably at $2 - $3 billion in revenue right now. All the companies benefiting the most from AI are established companies such as Microsoft, Apple, Nvidia, TSMC. We haven't had any pure AI companies IPO with no revenue in 2024 as far as I know. Heck, I'm not even sure if there is an AI company that IPOed in 2024.

I think AI hype is in the 1996 equivalent of hype - not 1999.

We're at the baby steps of the LLM revolution. There are so many things I want an LLM to do but it hasn't been done yet. I want Slack to be integrated with an LLM so I can ask it business logic discussions that I can't find using its search engine. I want Outlook to summarize long email chains that I just got cc'ed into. I want an powerful but private LLM to ingest all my digital data so it takes into account all those things before doing things for me or answering my requests.


As someone who lived through it, I am always surprised at how dismissive people are of the dotcom bubble and the changes that were underway.

It’s been applied to crypto as an analogy and now here to “AI” though I think you actually mean LLMs.

The thing about the initial web bubble was that the potential using already proven tech was just absolutely gigantic.

Like I used to have to go to an office in a building to buy a plane ticket. Then I didn’t. People used to have to mail me a 500 page catalog for me to order via mail, and there was no way to change price or availability.

To interact with most businesses it had to be synchronous, via phone call. Or very very slow or resource intensive via mail or in person and that was that.

Even immediately it was clear these things would change a lot. You’d be able to browse an online catalog of flights or books, you’d be able to email a business and ask a detailed question and copy and paste the request to whoever.

It was right there. It worked. It was clunky and adoption took a minute but nobody honestly was all that confused about what was happening.

The bubble was almost exclusively about how fast people thought change would happen, and which people would benefit.

The LLM thing feels different. It has clear use cases that work, no doubt. I use it to help draft business docs all the time. That could even be a huge market.

But there’s also an assumption that the cognitive ability of these tactics will grow without bound. We don’t actually know that.

Maybe maybe not. But that’s a difference that makes the dotcom bubble a partial analogy at best.

If that doesn’t happen then it’s not going to be an internet-sized change. Maybe something more on the scale of GPS or something.


This is great for setting some context, and I love your analogy that AI/LLM's could be on par with a very cool and valuable tech like GPS, rather than something as revolutionary as "the internet".

Like GPS is still an insanely cool technology that is massively important/useful/valuable but it's still on a completely different playing field than "the internet".


I appreciate your examples but I have to disagree on your magnitude comparison between the potential of LLMs and the internet.

I think they're the same magnitude. I might give the edge to LLMs.

I think LLMs have the potential to make every field significantly more productive whether you are an accountant or software engineer or lawyer.

The hype around LLMs is that for the first time every, a tool has the potential to replace a massive number of white collar tasks.


you must be young if you think anything at all in 2k compares to the internet. LLM has edge if compared to blockchain, but internet? no


Looking back, it is always very clear, but the usefulness of the Internet at that time may not be much different from LLM today.


During a goldrush, sell shovels.

Nvidia and TSMC are making insane profits, but that just means there's a demand for specialized compute. Like with the crypto bubble, their success is unrelated to the quality of the final AI product sold to the consumer.

OpenAI is in a similar position due to their SaaS model. It's all about pumping the hype and getting other businesses to build AI products on their platform. Not getting good results? Must be your poor prompt engineering!

The real slaughter is going to be in the AI startups, and the companies trying to pivot to AI in an attempt to stay relevant. The general public is already starting to get tired of the whole AI hype, and we haven't seen anyone provide genuinely groundbreaking products yet. All of it is somewhere on a spectrum of "kinda neat, I guess" to "dystopian hellscape".

Unless we see someone come out with a truly innovative must-have product, this hype is probably going to end sooner rather than later.


I'm expecting much less drama. Maybe AI startups will fail at a higher rate than regular startups but there will still be success stories. Are we conveniently forgetting that the vast majority of businesses fail? There are still crypto businesses operating out there and not all of them are based around scams. It's just such a narrow domain of applicability that it's easy to never have contact with it. Language, image and audio models on the other hand are so widely applicable that you're going to wind up running into them everywhere whether you want to or not. The excitement around the novelty of these usecases may die down but it'll be the same way that excitement over sending email or having a video call died down and the technology just became part of everyday life.


I don't think we can include TSMC in the list of AI goldrush companies, they have a pretty diverse client base.


> no revenue and no profit.

Revenue has gone up, but fewer publicly traded companies are making a profit than ever before [0].

I could never understand why so many people just talk about revenue. Revenue without profits is meaningless. There's the old logic of "get enough revenue and then figure out profits and you're highly profitable", but it's very clear that switching the "profit switch" is not so easy in practice.

Investors are still basically waiting for the fed to drop rates, which means that people have abandoned rationally thinking about businesses and are just holding until the free money starts pouring in again.

I honestly don't think the AI bubble is anything like the dotcom bubble. There's something much stranger happening here since the entire market is basically hallucinating and AI is just one manifestation of that.

0. https://finimize.com/content/beware-the-rise-of-unprofitable...


>and are just holding until the free money starts pouring in again.

What guarantee is there that "free money" will come back again?

Wasn't the last free money printer run something like a first time in history, and supposed to be only a temporary measure that went on for far too long leading to inflation and assets spiraling out of control creating various speculative bubbles like crypto, Gamestop fiasco, housing, and dozens to hundreds of crappy overhyped "start-ups" adn food delivery apps, that were never able to be very profitable on their own but still grew like crazy thanks to that free money and gullible investors to stay afloat, leading to an artificial over demand of SW devs which also crashed with them.

Seeing all it lead to, do we even want/need it to come back again? And "But this time will be different" doesn't scan for me as a believable answer since we all know it'll definitely be the same.


The free money printer was running for a solid 20 years or so.


Wasn't that post-2009?


started in 2002


"Now, [the unprofitable companies] might not be the big publicly traded kahunas – collectively they hold just a 10% slice of the market’s total revenue pie"

It's detailed in the article, but that graph is way misleading because it isn't weighted by revenue size and the unprofitable part is dominated by tiny companies.


Yes, it’s interesting but mostly a shift of concentration of earnings. Market weighted PE multiples are slightly elevated historically but not insane; forward PE even less so (taken with a grain of salt of course).


> Revenue has gone up, but fewer publicly traded companies are making a profit than ever before

That chart is deceiving. (from your link)

If you look carefully, you'll see that "very profitable" companies over the decades is unchanged.

What changed is the balance between "barely positive" and "negative".


I guess we'll see when we are well past the yield curve inversion. If we get past far enough without a collapse I would say we are in a paradigm shift.


> During the dotcom bubble, companies IPOed with no revenue and no profit.

One caution about using this as a metric: in the last 25 years, for a variety of reasons, early IPOs have, in general (and not just amongst hyped-up tech companies) become way less desireable. A company that might have IPO'd in the 90s today might simply take a few hundred million from VCs. And there have been a number of no-revenue, no-profit VC investments at that level in the current bubble.

Granted, a VC-driven bubble is less dangerous to the general public than an IPO-driven bubble; when it collapses it's mostly VCs holding the can, rather than peoples' retirement funds.


"During the dotcom bubble, companies IPOed with no revenue and no profit. In 2024, OpenAI is probably at $2 - $3 billion in revenue right now."

That's cheating; you moved from "companies" to "a specific company". Some specific companies had revenue in the dotcom bubble. There are plenty of AI companies today being valuated sky-high with currently no revenues (dunno how many have gone public, that has changed a lot since 2000), and there are plenty of "real", normal companies getting their valuations goosed by saying "AI" and not having any current revenues to show for that valuation rise. Most recently Apple put on something like 300 billion in valuation for their deal with OpenAI, but if you dig into the deal, neither of them are paying the other anything.

The people selling shovels are doing well, if not necessarily as well as their stocks indicate, but so far there really isn't that much gold being found for all the shovels being sold. Not zero, not claiming it's zero, but it's nowhere near what the valuations imply.


Yes even for some companies with current revenue the multiples are extremely high.

Really struggling to decide if AI is ultimately a winner take all market. Of course the very best models will require trillions in capital to train, but seems there also will be a long tail of local, smaller, and specialized models doing a majority of the workloads.


The way I've seen the dot-com bubble portrayed as bigger is:

It was more likely that someone would throw money at your idea back then if it ended with ".com" than it is for someone to fund your idea today that ends with "using AI".

I don't know why. Maybe it's interest rates. Maybe it is because the AI hype is so recently after the cryptocurrency hype. It was quite easy to make people dump their money into a cryptocurrency, and the crypto winners are still actively fishing for bigger fools while the AI hype is going on.


One thing to note is the barrier to IPO is much higher now, so the comparison doesn’t exactly hold.

Companies are taking on massive investment larger than any IPO take, with zero revenues! OpenAI’s investment predated its revenue push.

I’ve seen people suggest this cycle is malinvestment… if you think the goal of AGI which is exceeding unlikely to emerge in this investment cycle.

Get ready to pick up a ton of cheap hardware in a year or two…


> Get ready to pick up a ton of cheap hardware in a year or two…

That's not a bold statement since that's the natural life cycle of hardware anyways. I think the "year or two" is a bit soon, but also tracks with the price of hardware holding value for that term too.


>Get ready to pick up a ton of cheap hardware in a year or two…

Why? As far as I know, we're hugely bottlenecked by hardware in both training and inference even for current models.


If it did get as crazy as the dotcom boom it seems like SPACs would make it way worse. Zero revenue companies aren't going to go through the IPO process.


> In 2024, OpenAI is probably at $2 - $3 billion in revenue right now

Do you have any source for this estimate? Everything I find online tells a different story (single digit million per year).


Where are you seeing that? Here's one source: https://www.bloomberg.com/news/articles/2024-06-12/openai-do...


Thanks!


Single digit million per year? Where is the source please.


> During the dotcom bubble, companies IPOed with no revenue and no profit. In 2024, OpenAI is probably at $2 - $3 billion in revenue right now. All the companies benefiting the most from AI are established companies such as Microsoft, Apple, Nvidia, TSMC. We haven't had any pure AI companies IPO with no revenue in 2024 as far as I know. Heck, I'm not even sure if there is an AI company that IPOed in 2024.

The market is much smarter to scrutinise and punish companies attempting to IPO and underperform in the public markets like what we have seen with WeWork and the other SPAC companies that failed to go anywhere.

Once again, companies with little to no-revenue and especially no-profit are getting valued at >$1B all because they slap 'AI', 'LLM' nonsense to inflate their valuations. That is already a dotcom bubble level hype.

The reality is, the existing big tech companies (Microsoft, Apple, Meta, Google, Nvidia, etc) will take all the value of LLMs and will bankrupt the late comers except for the advanced few such as (OpenAI, Anthropic and Cerebras Systems)


Genuine question on your preferred use-cases: Would you be comfortable with some probability of misinformation/mistakes/inaccuracies? Or would you accept the risk of some wrong information as a reasonable time vs. accuracy trade-off?


Not the parent commenter, but I want those same things, and yes, I'll take a tradeoff of possible inaccuracy. Ideally the tool will give me the answers AND some relevant quotes / links to double check things myself if something feels off.

We live in a very messy information space, both publicly and privately, and we navigate it with messy, sometimes-inaccurate brains. I don't expect LLMs to operate at a higher level of formal logic than a human brain does.


I think anybody that asserts their "human in the loop" doesn't have the same problem is biased/delusional.

People make mistakes: even the best people. We accept that risk as colleagues/employers/employees because there's a human connection, but that doesn't make it nonexistent. We're now trying to figure out how to deal with that when you're "employing" AI, and whether the risk tolerance is higher or lower alongside the reduced operational cost


That is a really good comparison - in the dot com bubble, money got thrown at anything that was "an internet business". People would throw up static content sites, get some traffic, and be handed money.

LLMs have absolutely put us in a similar place. People are getting customers/money by saying "Look at our AI-driven features!" But give it 5-10 years, or maybe less, and that will seem silly. People will be using LLMs for focused use cases and making sure they help the end users. You will be evaluated with a higher standard - of what you actually accomplish with your products. Saying your product is "AI-driven..." will be as stilly as saying your product is "RDBMS-driven..." would be today. Because it will be a foundational piece of the tech stack, not a marketing blurb.

I doubt it will be as big of a bubble as the dotcom crash, though. We may all still fall victim to hype cycles, but it is hard to explain just how low the bar was for investment during the original dotcom bubble. We are collectively wiser now, even as we stumble along the way.


> But give it 5-10 years, or maybe less, and that will seem silly. People will be using LLMs for focused use cases and making sure they help the end users. You will be evaluated with a higher standard - of what you actually accomplish with your products.

This day cannot come fast enough in my opinion. Hype is tiring and ultimately detrimental in the long term (more disappointment than fulfilled wishes), in terms of opportunity cost of what could have been invested in instead.

How does one escape this?


My life has been: The soviets are out to get us, computers are amazing and revolutionary, the muslim terrorists are out to get us, peak oil, the banks have collapsed, PV is amazing, oh no a pandemic, AI is god/the devil incarnate.

If that's reflective of the broader human condition, we only avoid hype by having a scapegoat to demonise… or possibly the causality is the opposite direction and we only avoid demonising scapegoats by hyping something up.


By ignoring it? Nobody's forcing you to read news, read tweets, or listen to every clown talk about AI. Just put your head down and solve real problems and focus on the end users and providing real value


Fair. More specifically what I meant was how can one avoid being subject to being pulled away from providing real value when superiors are wooed by hype. In that sense just ignoring it is not easy if you care at all about your work.


For those looking for some relatively light financial reading related to the question of "how does one escape this?":

Morgan Housel (a writer at the collab fund) has written about how cycles of boom and bust are inherent to markets.

https://collabfund.com/uploads/Collaborative%20Fund%20--%20T...

The first section "1: The Inevitability of Insanity Among Sane People" is probably the most relevant, and a more summarized version is from Housel directly: https://collabfund.com/blog/the-laws-of-investing/

And another great level-headed financial writer Howard Marks has a great "memo" about how bull markets (sometimes read: bubbles) rhyme. Specifically the section "Optimistic Rationales, Super Stocks, and the New, New Thing".

https://www.brookfieldoaktree.com/sites/default/files/2023-0...

I can't find the exact quote, but I feel that one of them basically once said that you wouldn't really want a market to not have bubbles, if something didn't have the ebbs and flows that financial markets have, there wouldn't really be any room to find niches or to innovate because innovation requires risk, and risk inherently destabilizes any existing stability (re: the first article).


I think the same can be said of crashes… Or at least recessions… You would not want a market without corrections or recessions.

I can’t stop beating this analogy to death:

A market that is never allowed to fall into recession is like a forest whose fires are always snuffed out immediately… One of these days it’s gonna go and when it does the resulting conflagration will be many, many times worse than if It had been allowed to burn a little bit here and there…


I personally give it no more than 1-2 years before the starry eyed believers come back down to earth and start selling off their stock whilst they can. Then it will be exponential backoff.


I'm not sure that you want to escape it. This is just part of how capitalism works. A large percentage of investments fail and a small percentage have massive returns. You don't get the big returns without making a lot of risky investments, too.


AI is a bit of a bubble but even the natural language capabilities alone are revolutionary as far as computers go. Anyone who thinks it’s only hype either had a misunderstanding of what computers could do before AI, or isn’t paying attention. It will be years until software can fully leverage it and it’s completely baked into the way we interact with computer systems akin to the popularization of the graphical user interface in the 1980s


Is it really a bad thing that people are trying crazy stuff? This is a new technology that people don't fully understand. Yeah, most of these AI features and companies will die, and I'm sure the investors know that, they're just gambling on being in the 1% that survives. In the end we will have learned some good lessons on how to apply this tech instead of having it waste away in Google or Microsoft's closet.


> Is it really a bad thing that people are trying crazy stuff?

There's a major difference between different kinds of "crazy new stuff".

One kind is things that are just beyond the current frontier, and things people obviously kind of want, like say self-driving cars. It's another thing if we're talking about haphazardly bolting the new hotness in a distracting, pointless, or detrimental manner onto every single tech stack in the entire world, regardless of whether people actually want it, and regardless of whether it hurts end-users.

Lots of the current activity with AI is clearly more in the 2nd category than the 1st. In terms of end-users, things like job searches, home/apartment searches, loan applications, college admissions, etc are just a few of the most obvious examples where things are about to get muuuuuch worse for almost everyone (and it was already kind of awful).

Businesses/institutions generally don't care about end-users of course, but I would argue that it won't really help them either. It will just become another very large cost of doing business in the modern world, something you have to do to even be involved, similar to marketing/advertising/legal-council and the rest of the boring-but-necessary overhead. A necessary evil but one with very ambiguous ROI.


I don't agree that there is a distinction in the types of innovation you describe. We don't know how AI will be applied 10 years from now, shis isn't even really a tech question, it's a product question.


The bar for AI investment is also incredibly low right now. People are throwing crazy amounts of money at everything. It would be incredibly surprising if there isn't a massive investment bubble right now that pops in a year or so. That's true even if the underlying technology is the real deal and is going to be transformative. Probably even _more_ likely if AI is real, in fact, because if it's bullshit, the bubble won't have time to get very large before people stop investing in it. All you need is a few big pay days to keep it going.


We've had a couple of bubbles with the same exact shape: Instead of 1. starting with the end-user's problem and picking a technology to solve it with, companies are 2. starting with the technology (LLMs) and thrashing around trying to find problems to solve with it. #1 is how you build long-term, sustainable businesses and #2 is how you build hype trains and slosh money around until the music stops.

End users don't care whether you solved a problem with clever algorithms, a cluster of hardware, or actual black magic. Just like they don't care if their software is written in Python or JavaScript. Why does anyone think customers care that their product is "AI powered"? Customers don't care, but for some reason, investors do care. Wacky.


Dead on. But I’ve learned that solving actual problems is rewarded less than 25% of the reward allowing delusional business people to dream is.


You might find the recent Verge/Decoder podcast with Cohere's CEO interesting:

https://www.theverge.com/24173858/ai-cohere-aidan-gomez-mone...

The host is clearly trying to push the CEO of Cohere on how all this is going to make money (or just be economic). The CEO is confident, but not in a very specific way. There is a great moment where he is like "we did some proof of concepts with 5 users, and they were pretty good, but when you tell CFOs about the running costs for a full user base, its not viable."

What fascinates me about AI right now is that it seems to have very different economics from traditional software/internet/SaaS businesses. Those business scale super-efficiently. They have some initial startup costs (but still relatively low, especially with cloud providers) and low running costs.

With AI, the initial capital costs to build the model are quite high. And, the running costs to handle queries are also quite high. These companies need to find use cases that generate value significantly in excess of those costs. If those use cases are out there, they must either involve really significant productivity improvements, or the costs have to come down a lot, or both.

All that said, I remember going to a talk by Adobe's founders, in which they pointed out that when they introduced Postscript, the first Apple printer that ran it was only viable because of a last minute drop in memory prices, and when they started building Photoshop, you could fit six (6!) digital images on a powerful computer.

So, I see why the investment is happening, but its a high risk investment right now hoping to identify both high-value use cases and significant cost savings simultaneously.


I think LLM foundational models are like the Cisco/Level3 of the dotcom hype. Cost is high.

It's the startups building on top of LLMs that will have much lower cost.


There's certainly exaggerated faith in the capabilities of a single technology - Transformers - and evidence is appearing about its limitations on planning and reasoning. See the work of prof. Subbarao:

https://x.com/rao2z/status/1795595801177260311

https://www.youtube.com/watch?v=hGXhFa3gzBs

This Nikhil Suresh article can also be very enlightening:

https://ludic.mataroa.blog/blog/i-will-fucking-piledrive-you...


People adopted the Internet organically during the dotcom era for a simple reason: on-demand news and email. On a $10/mo dialup plan, that was a pretty affordable deal; you didn't have to write letters to people anymore.

I think genAI is different as most of the use cases aren't really all that valid for individuals, and it's yet to be seen if companies actually derive benefits from it beyond just growing their ability to spam you with on-demand video, podcast and image generation. I'm not saying Copilot and the like aren't helpful, just that there probably isn't room for more than one Copilot scale product.

Mostly however, I feel that the AI hype is being driven by VCs and companies themselves, and there isn't a network effect to catalyze its growth among consumers, like there was with email.


I think there's plenty of valid use cases for GenAI, it's disingenuous to say otherwise. And I would also say that it's more beneficial for individuals than it is for companies despite it being pushed by companies themselves.


Name 5? It is believers like you who are disingenuous when calling people out. It's funny how you never have any examples. Coincidence? No.


A bubble forms when a large number of investors pour money into investments that lack real inherent value. One example is Bitcoin, or in the year 2000, companies like Pets.com that had no substantial business but were valued like the most valuable companies in the world. This scenario does not apply to companies like Nvidia, Microsoft, and Amazon, which have huge, successful businesses. It is very likely that these companies will still exist in 10 years and remain highly profitable. However, their valuations could experience sharp ups and downs, similar to Tesla. Therefore, I would prepare for a volatile ride, but I would not sell an S&P 500 ETF out of fear of impending hype.


Just to remind you that Bitcoin is already 15.5 years old and shows no signs of subsiding. It has real inherent value as a trustless and permissionless means of value transfer, and as a fixed-supply store of value.


I think it's an apt analogy. The Internet (and the web) was definitely good tech that is still used. Artificial Intelligence (or maybe more broadly, data science or _statistics_) is good tech that will still be used.

But chatbots in all the things? That will definitely collapse. I am interested to see what cream rises to the top out of all this and if we'll see an actual bubble burst like we did then.


I wouldn't say it will collapse, its use cases will be narrowed tho, I still know hobbyists finetuning chatbots locally and integrating it to games, coding, writing, and stuff.


IMO "put LLM everywhere" does look like a bubble. More fundamental things like what OpenAI is doing is probably not, the hype will fade if the progress will slow down, but nobody can tell if it will.


I think some AI heavy based companies (like Nvidia) could go boom (stock price wise) but not the tech industry as a whole. If AI works out like I think as a new powerful tool, and not a real paradigm shift, then those companies will pop, I don’t think we’ll hit AGI which is what the market is trying to price in currently. It couldn’t last more than another year at most. However I was just starting college back during that dot com bubble burst and even I as a “computer hacker” type going into college knew it was smoke and mirrors and so so so many companies were nothing but paper tigers, it was much different than AI I believe since AI is -something-, those companies were based on literally nothing but promises.


You will know it’s a bubble when people stop asking whether it’s a bubble


Yes.

Even the company I work for, which makes and sells ERP software, literally changed its main domain from .com domain to .ai


Yes.

There are lots of potential applications for _some_ LLM models. However, if your business is dependent on openai to differentiate you from another business, you're probably fucked.

I don't think nvidia is going to be the only shop in town for much longer. The GPUs are too expensive and too power hungry.

Meta and Amazon are going headlong into AI. Most of the stuff they are embedding into product are _shit_ despite meta accidentally seeding self hosted LLMs with llama "leaking"

Google are probably dead in the water. They have the talent, but not the vision or the leadership structure to drive meaningful change in their products.

Meta is slightly better placed. but they also have no real internal product leadership (shrimp jesus, and all the utter shit changes they've made to the facebook app, and the poison they've been pissing into Instagram. ) However they have got distracted from AR by Mixed reality, and even more recently by AI (ooo I can ask generic questions about a photo, and get a bullshit answer, how great!)


> I don't think nvidia is going to be the only shop in town for much longer. The GPUs are too expensive and too power hungry.

I'm dying to hear what you think is more efficient for floating-point computation. ASICs fabbed on TSMC 5nm?


> I'm dying to hear what you think is more efficient for floating-point computation

yup, flops are the only thing that matter. Nothing else makes a difference.

700watts a unit, plus the ancillary heat from the processor and infiniband/fancy ethernet is challenging to house at scale.

as to my original point, they are fucking expensive. Some of the ones we have are literally gold plated.


What is your use-case where you need a GB200 but can't house it? These are datacenter processors; they consume a lot of power, output a lot of heat, and do an impressive amount of work. The same problem would arise with an Instinct or Gaudi accelerator.

The real "only thing" that matters is CUDA. CUDA scales from Raspberry Pi boards to desktop cards to datacenters without skipping a beat. It's a killer product in an age where OpenCL is rotting and dead.


> where you need a GB200 but can't house it?

density. Datacentre space is expensive. 9.6kw per machine means putting liquid cooling to the die, if we want to have more than 3 machines per rack. We've already lost a load of space in order to house an unspecified thousands of "h100"

We need to have some space left to put in storage, otherwise we're going to wasting power for funsies. We need that storage to be close, because otherwise it gets _really_ expensive and really slow quickly.


I don't know what to tell you. Jetson Orin exists, GPU cards in all form factors support CUDA, and the servers represent the apex of that power. There are options for almost every form factor and power profile you can imagine; the goddamn Nintendo Switch supports CUDA running at 7w.

Literally, what are your other options? Hot aisles get hot, I don't know what to tell you there.


Yes, Orins exist, and they are frankly awful to develop on. Sure I could spend a boatload of time porting my stuff to an outdated version of ubuntu, with no practical HSM support, or I could not. Mind you, its no worse than dealing with our internal shit.

You are misunderstanding what I originally saying: there is an opportunity for other people to bring in new types of accelerators.

You took that to mean that I was saying nvidia are shit.

GPUs TPUs and other accelerators are a pain in the arse to integrate at scale. NVIDIA have the current winner because CUDA is well understood, and the GPUs they make are fast and plentiful for the desktop.

They also make a loverly goldplated "mini computer" in the form of the DGX. Again great for any startup that's just got funding.

But, just like IBM, DEC & HP, who also made really fast, capable, large scalable machines, they were eaten by slower, cheaper pizzabox clusters. Not because they were better, or more efficient, but because they were cheap, plentyful and easy to sling in a room.


Orins are fine. If your use-case is robotics and edge compute, your alternative is exclusively worse ARM boards or x86 boards. Strictly speaking, it is the "pizzabox computer" disrupting everyone else's acceleration racket.

And my point isn't that I resent people insulting Nvidia; I think the world would be a better place if CUDA didn't exist. But there literally are not HPC alternatives that exist in the mainstream today. Seriously, what are you suggesting? 20,000w Beowulf clusters that accelerate everything on 10-year-old Xeons? A few thousand Macs running GPU-shader accelerated int8 inference? These solutions just aren't out there, and it's why Nvidia owns the industry right now. The sheer incompetence of every other commercial hardware vendor has cemented their dominance for the foreseeable future. The industry would rather watch each other die fighting Nvidia than work together to stand a solitary chance.


Having sat thru the dot com bubble and bust, this is very similar. I think the easier analogy is search rather than all the ecommerce that had no revenue.

Search and generative AI are eerily similar in my eyes. Most of the best (aka higher quality) responses from ChatGPT are when it is assembling "answers" to things it is just looking up. I remember when a ton of companies were touting their "search" or being adjacent to search, selling search engines, etc.

At some point the tide will go out for companies doing BS "AI" and the capital will have a $0 ROI. Some of this will have downstream effects on underlying APIs and hardware companies much like the dot com era had impacts on companies like Cisco. There will be major players that come out of this with transformative tech that will be useful.

Tech stocks has always had a larger risk than traditional companies so there could be corrections but in general its not like MSFT is going to go bankrupt. Investing in ETFs should insulate against any single company fails. I would be wary of startups promising equity and some IPO, take over the world type of thing, etc.


I think it will also do something more serious. If ai continues to improve the amount of software engineers employed will decrease.

1 software engineer can become 10x with a better ai.

In the further future 20x.

People are worried about the investment bubble. I’m worried about the employment bubble.

It’s sort of opposing metrics if ai does pan out your job is at risk. If it doesn’t, your ai investments are at risk. I think ultimately it’s your job that will be obsolete.


> If ai continues to improve the amount of software engineers employed will decrease.

AI is already affecting the junior dev/intern space. Seniors and mid developers really don't need juniors around, there is a GPT that you can ask questions to and get the boilerplate back that you would usually send to the juniors to think through and develop for you.


Not in my experience. LLMs are nowhere near replacing a junior dev. Maybe you can have a junior dev fix their bug ridden garbage responses but that's not replacing them.

It's possible this may be true in some domains now, but not in any I work in


You can't NOT have juniors, because that is what seniors evolve from :)

Otherwise when all current seniors die there would be nobody left to do programming.


See COBOL


Boy am I tired of people propelling this completely baseless narrative.

Everything that I have seen from ai makes me very secure that I’ll have work for far longer than desired.


Follow the trend line. It’s not about the current state of ai. It’s about how fast it’s improving and the trajectory. Ai is now leaps and bounds ahead of a mentally retarded human which was deemed impossible less than a decade ago.

Also you’re biased. I talk in terms of economics and jobs in general. You talk about you feeling “secure” and you having “work”. You’re thinking of your own security. I’m thinking about the population from a dispassionate perspective.

You need to be more logical.


Yes.

If one of the AI companies use their windfall investment funds wisely they'd invest in getting fusion power working, something that small scale crypto power wasters don't have the organisation for.

That is, in fact, the only thing I can figure out what Sam Altman needs $7 trillion for.

At least then when it bursts we'd have something to show. And he'd get some place in history.


Ask yourself how it will affect you:

Do you personally have a job because employers and investors threw money at AI?

When no-one uses or pays for your AI features, will your employer lay you off?

I'm sure the hype bubble will pop, and investments will cool off, but I don't think that will translate to the average CRUD developer being laid off.


Yep, we're worried about similar things. I'm seeing formerly stable companies de-stabilize themselves and re-invent product features to put AI ahead of end user needs. I'm not worried in the long run, but I do see some short-term company failures and shuffling of talent in our future as this discrepancy between what is needed vs. what is getting built gets sorted out.


Every tech company tends to die if they don't survive and profit the next breakthrough, there's no stability. Google is far from stable right now and not winning on AI won't help.


It could be, but I have a feeling we’ll find out sooner rather than later.

Whatever GPT-5 turns out to be will set the tone. If there is a clear increase in intelligence over GPT-4, I don’t think it’s a bubble. If it turns out to be a modest improvement in capabilities (like a GPT-4.5), then it’s probably a bubble.

In other words, if the exponential gains continue as AGI/ASI proponents expect, then there is every reason for these crazy valuations to be real.

That said, I think most these AI startups which are simply wrappers around an LLM are obviously going to die either way.


Two things :

- The current "AI" stuff is truly useful. So it isn't just hot air, like "web3" was, for example. - Does that justify Nvidia's crazy market cap? I don't think so.


What is it useful for?


I use it a lot for coding, researching things...

Obviously, you still need to verify the output, but even with that in mind, it's a great productivity boost, at least for me.

I'm sure people in other industries can also find use for it.


Generating crap... And world consumes lot of crap...


captioning images, at least that what I use it for when I need to caption thousands of images.


I'm reminded of this quote from Margin Call:

> "It's just money; it's made up. Pieces of paper with pictures on it so we don't have to kill each other just to get something to eat. It's not wrong. And it's certainly no different today than it's ever been. 1637, 1797, 1819, 37, 57, 84, 1901, 07, 29, 1937, 1974, 1987—Jesus, didn't that fucker fuck me up good—92, 97, 2000 and whatever we want to call this. It's all just the same thing over and over; we can't help ourselves. And you and I can't control it or stop it, or even slow it, or even ever-so-slightly alter it. We just react. And we make a lot of money if we get it right. And we get left by the side of the road if we get it wrong. And there have always been and there always will be the same percentage of winners and losers, happy fuckers and sad suckers, fat cats and starving dogs in this world. Yeah, there may be more of us today than there's ever been, but the percentages—they stay exactly the same."

https://youtu.be/IAqAl292ozs?t=217


All new technologies go through this: canals, the Industrial Revolution and steam engines, railroads, telegraphs, electricity, phones, etc.

See:

* https://en.wikipedia.org/wiki/Technological_Revolutions_and_...

* https://www.pwlcapital.com/investing-technological-revolutio...


Well, it could be. But I also see it as a way to make everyone a bit more productive.

Let's say AI isn't as revolutionary as we thought, but it does make the average office worker %15 more productive. Surely that's worth a lot. And surely that means every single company with office workers will be spending money on it, no?

Maybe it's a bit like the bubble of the PC market, in that there is real value, and money to be made, but when it all shakes up there will only be a handful of big winners.


As someone working a AI company with lots of AI in every slide I agree. But I see the reason differently. For highly thoughtful use cases the data is not ready. Getting that AI ready data will be a massive effort und change management needed for potential a low ROI. I believe that after a few attempts this is what most companies will see and course correct and for sure reduce the expense and that field and the bubble will burst.


NVDA and the semiconductor manufacturers TSMC/MU are minting. NVDA margins are ~60% and growth is super. They are the real AI winners.

How long it continues is anyone's guess.

However like any boom and bust cycle, the losers could be AI startups building thin layers on top of apis.

When OpenAI becomes Google and loses product sense, they'll be bust.


Yes… and just like the .com bubble it doesn’t mean everything related is useless, just a whole lot of it.


Probably not. Investors are a lot more knowledgeable today, and have learnt the lessons of the original dotcom bubble. Also most of the money is going to huge companies building real powerful products, not to me too wannabes.


Businesses like OpenAI probably aren't long for this world. But who's going to unseat Nvidia? Seems like there's a strong core driving this rally with no competitors in sight.


It's not about unseating. When NVDAs revenues are so concentrated from just a few customers, it only takes one to slow down and NVDAs multiple will contract.

https://finance.yahoo.com/news/single-customer-made-19-nvidi...


NVDA is making out like a bandit because they are selling the shovels (graphics cards) in this goldrush.

MSFT is hosting and investing in Open AI, but other than offering AI in Azure and O356 products, what is the business model and future for AI?

GOOG, META, and TSLA now have their own AI LLMs and chat gpts, but only GOOG has sort of a plan for AI, which is to replace search with it.

AMZN is the only competitor to Open AI and MSFT with Claude.

Again, what is the business model and plan for revenue?


I don't think google has a plan, I think its panicing.

Meta is sorta trying to make an AI assistant that lives on your glasses. I'm not sure they are going to make it practical before instgram dies.


I think this is a really poor analysis of both plans. Google and Meta have had AI-specific research labs for almost a decade now; TPUs, Llama and Tensorflow/Pytorch didn't materialize from nothing. They were part of a long-term, dedicated plan to explore AI capabilities. Both Google and Meta have Github accounts with thousands of open-source AI experiments.

You don't have to ascribe a business strategy to that any more than you ascribe a business strategy to whatever wack technology Apple patents next. These companies are using their R&D to test new technology, it's not hard to believe they do it for kicks since they already write-off hundreds of non-product developments a year.


You're making my point. If any of META, GOOG, AMZN, or MSFT decide maybe they can spend 20% less on GPUs, then NVDA will take a huge hit. It's not going to destroy NVDA or signal the end of LLMs, but will quickly put a damper on NVDAs multiple.


Or GOOG just uses their own chips: https://www.techradar.com/pro/google-is-rapidly-turning-into...


Exactly. Same with Meta.


Isn't Nvidia overbooked though? If a few of their customers bail, who's to say that others won't take their place?


Sure, but overbooked leads to pricing power (there's also the question of who has billions to spend on GPUs). Stock price is about growth multiple, and NVDA is priced for perfection. Some say they are already priced for what's next after AI.


hardware sales to datacenters is cyclical.

80% datacenter sales are to less than 8 customers.

marginal buyers - coreweave and xai are funded with speculative monies to the tune of $15B

so, expect pain.


How far behind is AMD?

https://www.reuters.com/technology/amd-launches-new-ai-chips...


Hardware wise, they have a shot. But software wise, they are relying on everyone else to start using something they can leverage.

I respect AMD for trying to get people to care about Open Source alternatives to CUDA, but the rest of the industry would rather fight Nvidia for scraps than work together to dethrone them. CUDA represents almost a decade of concentrated software design, and it's going to take a lot of work, proprietary or Open Source, to put it in it's grave.


I have not seen any explanation of why CUDA is so hard to replicate. Is it that hard... even with billions of dollars at stake no one can come up with an alternative?


> Is it that hard... even with billions of dollars at stake no one can come up with an alternative?

It's so hard that with trillions of dollars at stake, nobody can be bothered to compete. There are really two alternative routes that the industry can take to kill CUDA. I've mentioned it a few times in this thread but their choices are:

1) Revive OpenCL as a cross-platform GPGPU solution. Fund Khronos and get them to brush up the spec and make OpenCL into what Vulkan was for DirectX. There's a lot of work OpenCL needs before it catches up with CUDA, but a Free and Open Source, cross-platform GPGPU API would make a lot of Nvidia's software monopoly irrelevant.

2) Compete with proprietary, hardware-specific CUDA alternatives that implement only parts of CUDA's spec piecemeal. Basically entails trying to beat Nvidia at their own game, something the rest of the industry hasn't been very good at historically.

Option 1 makes the most sense; everyone wins if everyone's device speaks the same language. But the industry is too greedy to desire a true solution to CUDA's problem. OpenCL is derelict today because Apple, Microsoft and Google all feel as though they have better odds fighting CUDA alone. None of them are even close to Nvidia's performance profile or software capability, which is why I really feel that Option 1 is the only way forward.


I would love AMD in the race, but isn't it CUDA and the software written specifically for NVDA hardware that makes them dominant?


Question is not only about unseating, but also correction. Nvidia can continue making money, but be valued at more sensible level. Or there might be some trigger in scaling down manufacturing resulting the market cap dropping.


This may be Nvidia's "reasonable value" though. They have longstanding Nintendo contracts, significant presence in the desktop market, and they currently own the datacenter with no end in sight. Nvidia is shipping their own CPU designs for server hosting and reportedly has plans to make desktop CPUs as well. If optimistic AI-bros keep paying hand-over-fist for good compute (and I suspect they will), Nvidia will profit from the industry's incompetence.


and nvidia has the need for compute in general behind it, which i dont see going away anytime soon


I don't think there's as much investment capital sloshing around looking for a home right now but I could definitely see it grow into something similar.


dot.com and internet changed how we shopped, how businesses conducted commerce, and how we communicate.

Mobile and smart phones put the internet in our pocket.

I dont see how gen-ai is going to change any of our day-to-day workflows. Hence I believe it to be a giant bubble. It will help some small sectors (education, customer support) but the overall impact will be much smaller than dotcom or mobile.


Just search LinkedIn for "E = mc^2 + AI" posts and it's clear the hype has outran current capabilities by a long shot.


I'm really interested in the history of dotcom bubble, is there some books are something out there?


In valuations and hype perhaps but I do think on a tech level this will have real effect


I see the current AI market as a likely bubble. I used this topic as a trick question when interviewing a financial consultant. Her answer, to invest in AI by proxy via companies such as Microsoft (who have other means of income), was pretty spot on imo. I considered that a pretty great answer and it helped gain my trust.


NVIDIA being the most valuable company is a clear sign of it.


It already is one.

Just like those here are old enough to remember the Cisco stock price and Intel's stock price in the 1990 when the internet was hyped up.

It is unsustainable and insiders will start or already have been taking profits out to derisk and anticipate any outside market forces that will correct these prices such as; for example: A declaration of war and an invasion.

This will be no different. Even the Nvidia CEO is taking out profits. Soon employees will do the same (and are already doing so), then Pelosi will do that ahead of the event.


I often wonder if there really was a dot com bubble. Some companies failed, but shouldn't we look at the software market as a whole?

Look at the performance of th qqq certificate, which invests in the largest 100 non-tech companies in the Nasdaq:

https://www.google.com/search?q=qqq

And click on "max". It goes from $52.97 in May 1999 to $485.51 today.

That is an annualized ROI of 9.21%. A better performance than many other market indices had over the same time.


QQQ tracks the Nasdaq-100, which contains the 100 largest non-financial companies, not non-tech companies. Nine of QQQs top ten holdings are tech companies, which by themselves account for almost 50% of the ETFs allocations.


Yes, typo. I meant non-finance.

QQQ is a good indicator for how tech performed since the so-called "dot com bubble". And it performed pretty well. That's why I tend to not call it a bubble.


I mean, I think almost everyone can agree that this is a bubble and a correction is going to follow in the not-so-distant future. I'm just not so certain of the magnitude of that correction.

Something which I'm kind of convinced about though is that I think after this we're going to see an end of an era in tech in that I don't foresee another "next big thing". Feels like we've kind of played all of them out, they've all more-or-less matured. Like, maybe there will be another hype cycle in AR/VR, but unless Apple really outdoes itself with the next Vision Pro launch I don't foresee it being all that buzzy. Hell, even if Apple launches a headset that's both affordable and ridiculously good, I still don't foresee AR/VR being all that buzzy.

And if AI really does live up to the hype, well, there still won't be a "next big thing", just for an entirely different reason.

I'm not personally upset about it. There's still a wealth of good ideas out there to chase that don't have the scaling potential to attract VC interest but nonetheless could potentially make a decent chunk of people rich and employ a lot of people. Perhaps society will give more of its collective attention to the problems that aren't so easily solved with a mobile app.


Yes


Yes




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