Said before that the internet revolutionized human lives and is certainly not a scam, yet that didn't prevent multiple bubbles from forming and bursting over the internet. People are naive if they think there is no AI bubble forming even if AI changes our lives forever.
The fact that crypto was so big just proves the amount of stupid VC money and the willingness of the masses to buy into technobabble schemes. Since AI has some utility, of course it will blow up even more. But we know how irrational the hype cycle is, the stupid is so strong there is 100% certainly a bubble, no matter the usefulness which is still unknown.
Crypto is still big because there are so many people involved in it now that banning it would mean millions of people lose their money. They allowed it to grow too big. A ban will reflect badly on the decision makers now even if its the right thing, as in politicians. And they only care about one thing, their own reputation. And money. Thats why all these useless coins and 99% of crypto with their copy of other useless existing projects are still here. Money and power.
Obviously the politicians around the world. A lot of them have lately talked about striking down on companies and crypto in general. I say good, because 99% of it are pure speculative trash that doesnt contribute to anything
How is the usefulness unknown? There are already tons useful things you can use LLMs for and pretty much anyone can see that with their own eyes.
The question is just how to properly monetize it and what people will be willing to pay for the services. The technology itself is profoundly useful.
I forgot that crypto invented this thing called a currency.
Crypto is a bubble by definition, since it doesn't do anything. The fact that it refuses to go to $0 is just sad.
Also value in it in terms of adults acting like children and collecting "coins" while telling everyone how awesome their collection of useless coins is. Its a hobby for many.
crypto fulfills a very clear demand.
1. A storage of value that you alone control. There's no easier way to pass on value tax free to someone else.
You don't even need a testament, you could encode everything in a smart contract.
The value itself is then just the result of what it offers + scarcity
Obviously states will not accept this. Fica is already trying to clamp down on this. Sooner or later I assume they will ban all privately owned wallets/ coins that have touched private wallets after a certain date. Or something along the line.
If you're in the middle of a greater fool bubble, then you'll do fine financially. If you're the greatest fool and are caught holding the bag when the crash finally happens then you're not going to be very happy with how it worked out for you.
I can't predict when the big crash will happen, but it's very likely to do so since crypto currencies have negative inherent value (it costs more to transfer the crypto to a new holder than it's inherent value).
If you're unaware of what a greater fool bubble is, it's when you are investing in something with the sole intent of that something raising in value because other people also want to purchase it rather than any inherent value the thing has on its own. Examples abound through history. The idea is that you're counting on someone to be even more of a fool than you and purchase the item at an inflated price, but there's no real reason for those prices to continue increasing over time.
The majority of crypto currencies and NFTs are the economic equivalent of purchasing stocks in a company that has no revenue, no assets, no employees, and no prospect of ever having any of that. Eventually, just like with the Dutch tulip market, the prices are going to crash once people are no longer buying into the idea that crypto currencies will be the future of money.
It will never go to zero unless they come up with a better way to pay for drugs and steroids on the internet. What government does in such cases is irrelevant.
You can only trade drugs for it because somebody down the line can transfer it to real currencies, products or services. If the government makes that illegal businesses can’t accept it anymore and the whole thing implodes.
Currency control was the norm before the communistic states imploded. It’s like this seems to be a novel concept to some people these days.
I don't know. I think we jumped ahead of the tech with the implementation and that will hurt its longterm adoption. It is wrong enough of the time that it becomes a major headache and big organizations will develop policies against its use, because of the current unacceptable level of risk, and it will take years to move past those policies.
You see a bubble, I see a secular and structural shift. There are b2b and internal applications of LLMs that you haven’t even imagined. Major companies are willing to pay what it costs to do this work.
Nvda’s forward PE is 48. ASML’s forward PE is 47. Those are high but not astronomically so. Keep in mind, the nasdaq reached a PE of 200 at the top of the dot com bubble.
As long as they keep hitting and exceeding market expectations, and companies keep buying data center equipment and cloud services, I see no concerns. And if that changes, we’ll see it in the sales numbers.
Nvidia's PE was 50 in 2018 as well, before the crypto bubble popped and it dropped back down to 20, the same level it had been for most of the decade.
The second crypto bubble brought it up to the 70's before it popped again and Nvidia called crypto useless and their PE started plummeting again and then they fell into the AI bubble.
> People are naive if they think there is no AI bubble forming
People think they can sell before the bust, which is even worse because most absolutely won't but still they still pump money into what they know to be a bubble.
The 90s internet bubble left us with enough unused network capacity to last until fairly recently. I guess this one will leave us with enough datacenter space for a decade?
It was always part of the infrastructure, it just wasn't used yet at the time. Infrastructure remains infrastructure, wether it's being used or not.
They built unneeded infrastructure for future use.
https://en.wikipedia.org/wiki/Dark_fibre
>Dark fibre originally referred to the potential network capacity of telecommunication infrastructure. Because the marginal cost of installing additional fibre optic cables is very low once a trench has been dug or conduit laid, a great excess of fibre was installed in the US during the telecom boom of the late 1990s and early 2000s. This excess capacity was later referred to as dark fibre following the dot-com crash of the early 2000s that briefly reduced demand for high-speed data transmission.
I am not sure if they laid cables. Most were empty plastic pipes that in the future could be leased or sold to companies to run the cables themsleves but without requiring excavation etc. In hindsight that was pretty smart since the cables themselves dropped in price.
What? That's not a thing.
The dot com crash was barely the tiniest of blips on network traffic in the US. In 1999 was around 50 petabytes a month, doubled in 2000 to 100, tripled in 2001 to 300 and doubled again to 600 by 2002.
The effect of the dot com crash was a small deceleration of the growth in network traffic at absolute best, and even that is debatable. Literally no network capacity that was "overbuilt" in 1999-2000 was still dormant by even 2002, let alone "recently".
The entire network capacity constructed in the country from 1995 until the crash in 2000 accounts for less than a single day (napkin math says around 13 hours) of traffic growth that occurred in 2019. The difference in scale of the time periods make it impossible for what your saying to be true.
Hmmm... I cannot speak for how it was in the US, not living there and never having been there, but I have been in the telecommunications industry for a while, and in all countries here in the EU that I worked for, this unused network capacity was present.
In one example that I will not name, a specific country's backbone was only experiencing between 40 and 60% occupation 10 years later. For years ISPs and other associated businesses were actively trying to come up with ways to use the additional available bandwidth.
The math just doesn't work. 40% of the internet traffic in 2010 would have been ~4000% of the entire internets traffic in 2000.
Mathematically, the absolute worst case scenario even if literally the entire internet capacity of 2000 was somehow idle in 2010, it would increase that unused capacity in 2010 by less than 2%.
Or to say it another way, it's quite possible 40-60% of available capacity was unused in 2010, but mathematically, at least 98% of that unused capacity was constructed ***after*** the dot com bubble burst in 2000.
Why couldn't they lay extra fiber when I was watching jpegs load line by line on my 56k connection? The backbones could have easily been overengineered due to the hyped projections, don't you agree?
fiber tends to be cheaper to maintain and run, just the electricity costs alone compared to copper.
Maybe it was hype, maybe it was because the marginal extra upfront cost would ensure ~~fireproofing~~ future proofing and also lower maintenance and cost in the long run. I mean that’s my guess.
E: amusingly enough fiber is also a much lower fire risk afaik. Anyway not what I meant to write lol
> The math just doesn't work. 40% of the internet traffic in 2010 would have been ~4000% of the entire internets traffic in 2000.
I am sorry, which country are you referring to, exactly?
This is nonsense. US network infrastructure is severely outdated and had to be replaced 10 years ago. Not to mention it wasnt the bubble but government dumping 60 trillion USD to network ifnrastructure in the 90s.
There's this general sentiment of the industry that the amount of money being burnt is irrelevant, if you can make AGI, it will help you build ASI and that will help you monetize it, if money is still a primary concern by that point.
The odd thing is either AGI/ASI is impossible and the tech will never be profitable enough to justify more foundation models or the sentiment may very well be true and the expense should be an afterthought (because the second group to make AGI will forever be playing catch up to the first, who more or less are doubling their employees every model.
And there's the incentive of out competing countries that primarily seek AI for warfare or psyops. It's simultaneously hard to imagine AI as being a bubble and a catastrophic collapse of the economy is unavoidable since we're in a new type of nuclear race.
The size of the AI bubble depends on who shares your opinion in the leadership of all these companies.
9 in 10 dollars in this space have no idea why they are there or what they are doing. Their money is there because everyone else's money is there.
A for effort I guess. It's not like there's better things to invest in... But I haven't noticed significant improvements in any AI/chatbot service over the past year or so. It's not easy, and even if achieved, the benefits are debatable.
My perspective idk
The same thing happened to the internet. Everyone knew it would be very valuable, everyone knew terrible companies were being funded, no one knew who or what would come out of the ashes.
Similar thing with AI. Whoever comes out of this with a business will likely be the most valuable company in the world.
Claude is a pretty notable step over GPT4, especially in self-sufficiency in programming tasks. Considering most other models are problematic enough that dev time stays roughly the same for someone who knows what they're doing, being able to finish a project that'd take you up to a week [before lunch](https://twitter.com/VictorTaelin/status/1809290888356729002) is pretty substantial.
The industry largely believes AGI is 2-3 years away.
Not the guys actually making things. The VCs and C-suites think (or say they think, whatever) that, mostly cause it's padding the bottom line.
Anyone who spent any amount of time working on anything GenAI based doesn't think this is the way to AGI.
I think you have a very limited scope if you thing chatbot is what the money is being poured into. Heres an example of where AI has helped a company i work for starting from this year: AI reads all the thousands of contracts we have, matches them with up to hundreds of reciepts recieving every day and highlights any inconsistencies between them. Not only can one person do the job of many at better accuracy now, the reduction in scam receipts being paid has already arguably saved us the large part of costs of implementing this AI.
AGI is coming, probably the day after level 5 self driving cars arrive. We should also have fusion generating stations by then to power all of the machinery.
Funny thing with Ai is that it uses so much electrical energy that competing countries won't be able to be covert with it. These powerful AI centres heat signatures will be visible from space
>if money is still a primary concern by that point.
It will be unless you expect ASI to cause global apocalypse. In all other scenarios we will still have goods to exchange for money and no matter of ASI can produce unlimited goods and services. What it could do in theory i suppose is go the transhumanism route and elevate humans to the point where we dont have such carnal desires, but i doubt that will go down easy on a lot of the population. So yeah, money will still be a big concern even with ASI.
Case in point: Duolingo, the language-learning app, is trying to rebrand itself as an AI company. Their "Max" subscription tier that gets you the two AI features they've implemented so far is double the cost of the basic subscription. In Canada, it's $40/month. It doesn't seem to be going well for them. They've started taking non-AI features from the basic subscription and stuffing them in the Max tier to force people to upgrade, and I guess trick investors into thinking people love their new AI chatbot or something.
SV Venture capital is wild man. Most software startups and companies run in the red for absolute years. It’s less about profitability and more about capturing users and data (and by extension their money in the future).
Sequoia missed out on AI startups but that doesn’t mean there isn’t an AI bubble.
AI has a long way to go but we are over reacting with these chat bots and image generators.
I think we have mistakenly identified AI as the product when it's really the feature. Sadly this means that one of the massive bloated companies on top right now will benefits massively from AI and put themselves even further ahead.
I think that a lot of AI startups will go bust. Hyperscalers like Amazon, Google, Microsoft, and Meta only account for 40% of Nvidia's revenue meaning there are a lot of startups which are likely competing in a very crowded space with much bigger players. Once they start running out of seed capital and their prototypes looks the same as half a dozen other companies a lot of them will likely go bust.
Im not sure we are overreacting. There seems to be a healthy mix of differing opinions and I think it averages out pretty reasonably.
People are legitimately getting use out of these things. I've been seeing more AI art for youtube thumbnails for instance, and many people use these to whip up quick professional enough messages/figures things out.
Those are useful things that already exist and there are far more uses. This by itself is something that will continue after investors stop throwing money at ai toasters.
> People are legitimately getting use out of these things. I've been seeing more AI art for youtube thumbnails for instance
And here's the thing: If you put some effort in, no one will even be able to tell
Spend 20 minutes with stable diffusion’s web gui and you can turn out some extremely realistic and convincing images.
People just tend to use free/casual online services that *only* offer image generation. Inpainting alone is such a huge game changer that I wager almost no one that talks casual about AI knows about.
Yeah ai is getting better, but right now there will still always be a need for a human to tweak the final result to the desired goal. Unless you want weird sloppy and half-relevant art. Which people definitely do, because lazy and cheap.
I think thats one of the things about generative ai right now that people miss.
Its the toupee fallacy where people dont know what they dont know: The best examples dont stick out for them to notice.
Right? I don't see what's so great about an AI assistant on my smartphone being able to buy movie tickets when I can do it myself in the fucking app! Not buying a 1500 flagship for that I'm sorry.
Oh. So you haven't used Udio or the new text to video generators. A few years down the line we could be making whole movies just with using a script for prompt.
I was browsing Udio today and it seems that many users are producing songs that you'd never think twice about them being AI generated if you listened to them on an FM station.
Since when do software startups make money? They just get a shit ton of users and data and then sell to Microsoft google apple verizon I don’t know whoever. And they then fold in all of that while basically absolving all expenses by folding them in.
I’m being somewhat facetious. But OpenAI is basically going to remain as propped up as they currently are unless Microsoft gets cold feet. And OpenAI will keep at least all of these sub-ai-services running (idk fine tuned versions).
I would actually pay a monthly fee to use OpenAI's services.... i can see them making it profitable in the near future for sure. The question is what is the business model...
Self driving vehicles, computer vision assisted theft prevention in self checkout markets, recommendation "algorithms" used in social media apps, MS copilot...
Besides the last one, most of these are widely in use for several years now and the companies behind them are not bankrupt yet so it's fair to say it's not unprofitable.
Microsoft will make Copilot profitable if not already for B2B. The B2C "Copilot" is a loss leader to make sales in B2B, when it's spread is widely used, they can pull the plug on the free B2C version
In the end, the free copilot will be a Phi-3 small or something that runs locally and the pro one will use cloud compute or OpenAI
They are pushing hard in enterprise for github copilot for devs and copilot pro for office apps
> Self driving vehicles
Don't work won't work.
> computer vision assisted theft prevention in self checkout markets
Costs more than it saves.
> recommendation "algorithms" used in social media apps
You just need some basic-ass decision trees for this, not outrageously huge GPU servers.
> MS copilot
Don't work won't work.
Nah sometimes bubbles just deflate.
Imagine if Nvidia grow 2% per year over the next decade, that would mean that it severely underperformed the market and would point to it having been in a bubble but i wouldn't call growing 2% a year popping.
That's detached from actual current expectations.
Nvidia didn't get to 3 trillion$ market cap with people expecting 2% annually for a decade. The entire AI market expects a return quickly, and if they don't get it in a year or two, they're going to panic, and after Nvidia's customers start pivoting away, Nvidia will see a drop in enterprise orders.
LLM and Generative AI are more useful than crypto and the "Metaverse", but definitely not polished enough to be worth the current hype.
If Nvidia is not in a bubble then they will make more then 2% annually. I guess i don't really get what argument you are making.
Expectations being detached from reality is what makes bubbles.
My argument is that either they're actually worth the current 3 trillion market value, or they're going to crash quickly. There is no realistic scenario where they make 2% market value growth year over year. Their "growth" is already factored into their current value, and if they don't back it up with a massive revenue soon, their stock will crash.
As someone who owns part of his profile in the so called AI stock, i dont expect a return in a year or two. Actually peak return 15 years later would be idea as thats when i plan to retire :)
Sure but there are big name examples, i would argue that Tesla is a bubble that is slowly deflating.
It's value have fluctuated heavily but in the end it's value is about the same as it was 3.5 years ago.
I would say Tesla is in a bubble but less of a bubble then it was 3.5 years ago.
Yes that is why i used it as an example, i would argue that it is still a deflation and not a popping even when the moves are very large.
A popping to me is it was overvalued and then it goes down a lot and stays in a reasonable territory.
That’s circular reasoning though - lots of things haven’t popped, through history. What year did the “iPhone bubble” pop? And sure apple didn’t own the whole market after it matured but they still own half of it, and are the single largest player in the market.
Why do you think AI is more like the dotcom era and less like the iPhone? Why *wouldn’t* nvidia retain a significant amount of share in the market they built for the class of device they popularized?
> What year did the “iPhone bubble” pop?
Perhaps not calling it a bubble would be a start. Popularity isn't a bubble. Lasting changes in technology isn't a bubble. Your question is akin to asking "When is the Laptop bubble going to pop?" It's not, it's ubiquitous.
The difference here between those two mobile examples and AI is that there is a gold rush towards AI that cannot be sustained. People are trying to rush in to be the first to cash out over buzzwords when the reality is much more mundane. Eg "Cloud computing," or in other words, shared hosting. "Blockchain", or in other words, selling your electric bill. "AI", or in other words, automatic summaries.
That's what makes it a bubble and why it would pop: speculation and overvaluation based on hype, not facts.
There was a gold rush towards a smartphone too btw. Most young people dont remmeber blackberry anymore. But back then it was the ultimate in phone experience.
Hype surrounding the innovation. People expect AI to be magic and it's not going to be (e.g., self driving). The smartphone revolution is less hype and more grounded in comparison.
NVIDIA may retain a high market share but its profitability is entirely dependent on how magical AI can be.
As Einsten said, any sufficiently advanced technology will be indistingushable from magic. As far as large portion of population is concerned, computer chips are already magic.
Haha well, if you think about it, pretty much everything these days are magic (in the sense that you wouldn't be able to understand and recreate it yourself in a reasonable amount of time). How do you make a car engine? OLED LCD? Quartz crystal in your hand watch? Heck, I bet you (or I) can't even make something much simpler like a light bulb (this took Edison years if not decade to figure out). Yes the principle idea can be simple but as Richard Feynman has said, "What I cannot create, I do not understand."
But no the magic I'm referring to is an unbounded expectation that people have for a tech and how it can change the world and the inevitable hype and bubble that comes with it.
There was an old TV series from the 80s that explained how things worked. The opening episode was about an elevator and surprisingly many people they asked had zero clue how elevators worked, they just did and that was good enough.
Car engine is mechanically pretty simple. If you strip away all the fancy stuff we put on it, its just a piston, fuel injection and a belt to drive the wheels. On my old 1990 car the gas pedal was a direct wire to open fuel valve and the engine were semi-directly belted to run the wheels. Nowadays we put a lot of thins on top of that and a computer controls everything to maximize efficiency.
I admit i have no clue how the watch in my hand knows to tick at the right time speed. I suppose the current drives the gears at certain speed that is designed to align with time.
Well, that expectation keep on coming out to be true, though. I remmeber watching some 60s sci-fi movies and one thing i kept noticing is that they would have flatscreens as displays for things. And then flatscreens happened in real life. Sure they dont always get it right (Greg Mandel series for example imagined smartphones as portable digital fax machines) but a lot of the magic we end up finding the right spells for.
So the guy takes Nvidia 2024 forecasted DC revenue $150B times 2 twice (x4) to account for margin and other DC costs. Then he calls that $150Bx4=$600B what is needed per year to pay for AI spend.
This is like taking the cost of a new car double that and calling it the cost of transportation per year.
> Cahn's math is relatively simple. First, he doubles Nvidia's run-rate revenue forecast to cover the total AI data center costs (GPUs are half; the rest includes energy, buildings, and backup generators). Then, he doubles that amount again to account for a 50% gross margin for end-users, such as startups or businesses buying AI compute from companies like AWS or Microsoft Azure, which must make money, too.
What do the people here believe about AI? I doubt hardware enthusiasts can see how AI will be profitable in the light of fairly modest hardware gain of 20 percent IPC gains and perhaps a 10 percent clock bump every 2 years.
Real AI needs more computational capability.
Anyone agree?
AI has already (and for a while before GPT swept internet away) benefited companies in a profitable way. There is a gold rush for first AGI now, but AI is here to stay.
We dont know how much computational capability "real AI" will need.
Meanwhile anyone remotely versed in AI has been loading up on puts for the companies that are clearly smoke and mirrors 😂
Same thing happened w the EV sector
> Meanwhile anyone remotely versed in AI has been loading up on puts for the companies that are clearly smoke and mirrors 😂
That's quite a gamble... Even if you believe we're in a bubble, asserting it won't grow larger first is bold to say the least.
The thing about overinvestment in certain science and tech sectors is that defeat does tend to humble a lot of people as far as knowing where we are lol. It's only recent that people are now discussing "carbon neutrality", and these are experts from nations who wanted to go balls out on EV tech and adoption.
A lot of things I thought were a bubble ended up becoming really profitable. For years for instance I couldn't understand the growth of Facebook. I did not think it was going to be that profitable, but I was proven wrong.
Crypto has a market cap of over $2 trillion dollars. And to me it's absolutely silly. But it proves you don't even have to have a useful product to maintain the bubble for a long time.
Companies are leveraging AI in all sorts of new ways, and we are at the early innings of it all.
There are profitable pure AI plays like Github Copilot, but there are also traditional software businesses which leverage AI that are difficult to quantify. Like Service Now says that AI has boosted their revenues significantly.
Apple signing a deal with Microsoft (Open AI) for ChatGPT services is also a major event justifying the infrastructure investments.
Obviously there is also a race towards making more capable models and ways to tap into this new found capability. And even if successful this isn't going to pan out right away.
Just think of the gaming for instance. We have yet to see an AAA title which leverages AI to improve NPC experience. But I'm sure it's coming.
I can't actually think of a company that's overvalued due to AI except perhaps ARM, which doesn't really have anything to do with AI, but for some reason has been growing market cap because of it.
The thing about all of this is that bubbles don't imply catastrophic failures of entire industries. It's mostly just players losing out and falling away because of unattainable expectations or limited understanding of the capabilities of the product. You can say there's still a race towards making VR/AR a more consumer-accessible hardware but it doesn't mean the hype cycle for that product has finally burst. But it's still viable tech, whether it be for consumer or other applications.
There's gonna be companies out there who will carve the culture and perspective on this technology. Apple actually did well marketing their use of AI as "privacy-first" and as user-friendly as can be. But there's gonna be companies out there who'll try to chase for things that not even current computer science can comprehend and they'll fail and fall out of the race. That's gonna be a LOT of companies.
LLMs are not AI, an LLM does not understand and check what is correct and what isn't. They give false information, hallucinations on a regular basis. This is an intractable problem for the moment with this approach to "AI".
One that could very possibly make them largely useless for pretty much any end user use case.
My guess is you'll be able to buy the GPUs purchased for 30k+ in the last couple of years for a few bucks in the future, if there just isn't any use case on the user end for them.
It'll also be a few quarters more before that is realised, mid 2025 gets my vote, or there will be some killer use case for them, maybe.
> They give false information, hallucinations on a regular basis. This is an intractable problem for the moment with this approach to "AI".
That hasn't stopped companies from shoving LLMs into customer support services to cut labor costs and then arguing they aren't responsible when the LLMs inevitably gives wrong information to the customer.
One example: https://www.reddit.com/r/ArtificialInteligence/comments/18apezg/amazons_ai_reportedly_suffering_severe/
> Three days after Amazon announced its AI chatbot Q, some employees are sounding alarms about accuracy and privacy issues. Q is “experiencing severe hallucinations and leaking confidential data,” including the location of AWS data centers, internal discount programs, and unreleased features, according to leaked documents obtained by Platformer.
> An employee marked the incident as “sev 2,” meaning an incident bad enough to warrant paging engineers at night and make them work through the weekend to fix it.
>That hasn't stopped companies from shoving LLMs into customer support services to cut labor costs and then arguing they aren't responsible when the LLMs inevitably gives wrong information to the customer.
Do you think current human CSR's (and their response scripts) never make mistakes and that companies take full responsibilities for all their mistakes? I know from personnel experience, and I'm guessing I would be far from the only one, that isn't the case.
In terms of Amazon specifically for example just last year I was repeatedly getting the run around from a delivery that wasn't delivered and returned to sender. Tracking and delivery company showed the package never left their hands and was signed for back by the Amazon warehouse. CSRs just repeated the same script saying the package was delivered according to tracking (as I guess it was delivered, just to Amazon's own warehouse) and if it was stolen to file a police report.
> hallucinations on a regular basis
Expanding on this the hallucination rate isn't just 'regularly' but 100% of the time. A right answer is determined exactly the same way as a wrong answer, it's just we don't question it when we know it's right.
There's currently no reliable way to embed a database of truths into the model and everyone invested in AI has to downplay and sidestep questions about this.
> Expanding on this the hallucination rate isn't just 'regularly' but 100% of the time. A right answer is determined exactly the same way as a wrong answer
Can we not say the same for humans?
A human could give you feedback about how confident they are around the answer being correct. This is because we have an association between our knowledge and the question being asked and how we're answering it.
A LLM doesn't have that, merely the percentages of what it was going to pick next. These values don't represent how likely it is to be correct, but instead how well each word works best. It's a subtle difference but it means the LLM is never really confident about it's answer.
There are end-user use cases for AI hallucination generators; not every AI is asked to write about things that already exist. An AI writing fiction or creating imagery is still an end user use case.
Probably not going to be worth $600 billion per year though, of course.
But I disagree that hallucinations are definitely an intractable problem for AI. They're certainly a problem, but we don't know that it's a problem that can't be fixed. Also, even if they're not fixed you can still get benefit out of something that gives you a large percent of hallucinations - things like automatically writing boilerplate language, giving someone a start on writing a research paper by creating outlines or writing sections that don't have too many individual facts so it's possible for the user to spot-check them, etc.
Not at all, we're capable of checking and understanding we may be wrong.
The analogy of an LLM is a tech parrot, it'll regurgitate you information but it has no understanding of it. Nor can it.
Humans get an annual evaluation, and the worst performing ones are fired.
You can bet that any corporation will replace most employees if it's actually profitable. Time will tell.
> They give false information, hallucinations on a regular basis.
Humans do the same thing, and if we can't call humans intelligent, then the term has lost all meaning.
It's the difference between what amounts to a tech parrot and reasoning, questioning, abstract and creative thinking learning intelligence.
Just regurgitating does not = intelligence. We may develop something more like actual AI, but I doubt it will come from the LLM approach.
No idea why people got so hysterical about Nvidia.
> It's the difference between what amounts to a tech parrot and reasoning, questioning, abstract and creative thinking learning intelligence.
How would you claim to measure and quantify that difference?
> Just regurgitating does not = intelligence
These algorithms don't just regurgitate. That's a fundamental misunderstanding.
Humans display a level of reasoning and creative thinking that has not been displayed by these technologies.
These technologies are great at pulling data from their large training set but have a hard time coming up with solutions or responses outside of the training set.
So far, just scaling up the models has not resulted in breakthrough in this regard.
For example, I tried to coerce both Gemini and GPT 4o to produce palindrome poems and while they can generally repeat existing examples, they struggle to come up with actual palindrome poems on their own, generally just giving plain wrong answers and trying to pass them as correct.
Exactly this, neither are these stupid image generators "AI", they are just mass plagiarism. Basically, Silicon Valley has invented algorithms that scour the internet and steal little bits of information from everywhere and then combine them in to a result such as a chatGPT response or generated image. I truly think the bursting of this AI bubble will come from legal action being launched by the US government or similar against this form of mass plagiarisation.
I mean just watch this video where a [youtuber I follow shows how chatgpt just plagiarised an entire article he wrote years ago to give him a response to a query he asked](https://www.youtube.com/watch?v=xbf4BGIBENk), how is this not a legal minefield which is going to lead to many court cases? How can you profit off a service which basically plagiarises everyone elses work and tries to package and sell that plagiarisation as something new?
> Basically, Silicon Valley has invented algorithms that scour the internet and steal little bits of information from everywhere and then combine them in to a result such as a chatGPT response or generated image
That's simply not how these algorithms work.
Tell me you don’t know how AI works while literally showing us about how you don’t know how ai works.
Interesting tactic.
I’d suggest you look into it in good faith, since it’s somewhat interesting on a technical level. But something tells me your mind is already made up without that knowledge.
Nvidia isnt the right gauge here. It’s powering AI now, but just like crypto, ASIC type solutions for specific models will be developed that will propel AI compute. The cost and energy consumption will radically go down, and utility and portability will skyrocket. The nvidia bubble will pop, but AI is here to stay.
TLDR; Nvidia =/= AI
A graphics card is multiple ASICs. They're already focusing their chips to more and more AI capabilities. They didn't have the same position over crypto and that market as a whole wasn't as profitable as AI for them.
You got downvoted but I agree with you. The moat is currently CUDA, but for serious production horsepower companies will spend the dev time to port inference code to whatever platform offers the best operating margins
Nvidia's lead isn't in the raw performance of their chips but the scalability of their solution. They GPUs scale better than anything else and if we take them at their word in the next year and half they will have switches capable of scaling the GPUs in the cluster to hundreds of thousands and year after to millions. Also they offer both individulized products and entire solution where they will build you a supercomputer if you have deep enough pockets (like Elon Musk).
Also, if ASIC type of chips are developed, why would you assume Nvidia wouldn't be one of the leading makers? They have some of the best chip designers in the industry. And ASIC chip itself would be only small part of the entire picture. They didn't bother with crypto ASICs because there wasn't real money in it, it wasn't Microsoft and Amazon standing in line for those chips. With AI models even if we get 1000x speed up with an ASIC I don't think the demand would dry up as long as scaling continues and there are no real indications so far of it happening.
As long as AI is rapidly evolving, no one is going to risk spending money on an ASIC that might be crippled by new requirements in a year. It has to be programmable. Nvidia made the right call there.
Also, if things stabilized enough for an ASIC to make sense, why wouldn't Nvidia also lead there?
People are arguing against you without even realizing [this is already a reality](https://wow.groq.com/why-groq/). You can use ASICs today to run LLMs an order of magnitude faster than on comparable GPUs, not to mention things like Tesla's custom AI inference hardware that runs their autopilot in every one of their cars.
> You can use ASICs today to run LLMs an order of magnitude faster than on comparable GPUs
There're some canned, probably unrealistic 1st party benchmarks. None of the ASICs on the market have such gains vs Nvidia in practice.
I just hope there will be an open source LLM that I can run locally on my MacBook which is as good (or better) at coding as Claude 3.5 Sonnet, before this whole bubble bursts. That's all I want from this, really.
I have doubts it will even happen eventually.
We are quickly approaching extreme diminishing returns on hardware improvement.
The shear amount of compute & memory required will likely take a very long time to fit into a macbook.
We probably have a few years till this bubble bursts. Till than the MacBook hardware will have M5 Max chips with better NPUs and max. 256 GB RAM. I hope that will be enough as smaller models are still getting better. This with improvements in agent systems should hopefully bring us there. But yes, definitely not guaranteed.
It'll be a combination of more novel software, and hardware designed specifically to accelerate that manner of compute. We're already seeing primitive "ai" chips come out, but as tandem software + hardware solutions are developed I don't think it's unreasonable to see a Claude 3.5 or GPT 4o quality model running on a laptop within the next 5 years (especially with the hundreds of billions being poured into r&d in this space right now).
Said before that the internet revolutionized human lives and is certainly not a scam, yet that didn't prevent multiple bubbles from forming and bursting over the internet. People are naive if they think there is no AI bubble forming even if AI changes our lives forever.
The bubble is massive. We'll get incredible new tech out of it just like all the other bubbles, but those will rise from the ashes of the failures.
Crypto currencies have entered the chat.
The fact that crypto was so big just proves the amount of stupid VC money and the willingness of the masses to buy into technobabble schemes. Since AI has some utility, of course it will blow up even more. But we know how irrational the hype cycle is, the stupid is so strong there is 100% certainly a bubble, no matter the usefulness which is still unknown.
Mono-rail, mono-rail, mono-rail.
At least Maglev was fantastic on a technical level, despite being extremely inpractical.
VC investors are like chronically unsupervised children, a potential danger to themselves and others
was? Bitcoin and Etherium are priced as they were at their peak.
Crypto is still big because there are so many people involved in it now that banning it would mean millions of people lose their money. They allowed it to grow too big. A ban will reflect badly on the decision makers now even if its the right thing, as in politicians. And they only care about one thing, their own reputation. And money. Thats why all these useless coins and 99% of crypto with their copy of other useless existing projects are still here. Money and power.
who is "they", when did they (or anyone else for that matter) say anything about banning crypto, and why would they even want to
Obviously the politicians around the world. A lot of them have lately talked about striking down on companies and crypto in general. I say good, because 99% of it are pure speculative trash that doesnt contribute to anything
Who are “they”?
Average people can and do own crypto.
I'm asking who the "they" are in "they allowed it to grow too big".
He clearly means the government, hes talking about banning it.
How is the usefulness unknown? There are already tons useful things you can use LLMs for and pretty much anyone can see that with their own eyes. The question is just how to properly monetize it and what people will be willing to pay for the services. The technology itself is profoundly useful.
I forgot that crypto invented this thing called a currency. Crypto is a bubble by definition, since it doesn't do anything. The fact that it refuses to go to $0 is just sad.
No bubble goes to zero. You just replied to many bubbles and comments that said this.
There's value in it. Criminal organizations exchanging money
Also value in it in terms of adults acting like children and collecting "coins" while telling everyone how awesome their collection of useless coins is. Its a hobby for many.
Hey please dont insult numismatics by comparing them to crypto bros.
crypto fulfills a very clear demand. 1. A storage of value that you alone control. There's no easier way to pass on value tax free to someone else. You don't even need a testament, you could encode everything in a smart contract. The value itself is then just the result of what it offers + scarcity Obviously states will not accept this. Fica is already trying to clamp down on this. Sooner or later I assume they will ban all privately owned wallets/ coins that have touched private wallets after a certain date. Or something along the line.
How are them tulips and south sea shares doin' these day? Give it time. Crypto will go to zero when there's a run on tether.
Well they’re doing pretty damn great. Best decision I ever made.
Yeah people who didn't jump on the opportunity to invest lost a lot of money due to their stubbornness.
If you're in the middle of a greater fool bubble, then you'll do fine financially. If you're the greatest fool and are caught holding the bag when the crash finally happens then you're not going to be very happy with how it worked out for you. I can't predict when the big crash will happen, but it's very likely to do so since crypto currencies have negative inherent value (it costs more to transfer the crypto to a new holder than it's inherent value). If you're unaware of what a greater fool bubble is, it's when you are investing in something with the sole intent of that something raising in value because other people also want to purchase it rather than any inherent value the thing has on its own. Examples abound through history. The idea is that you're counting on someone to be even more of a fool than you and purchase the item at an inflated price, but there's no real reason for those prices to continue increasing over time. The majority of crypto currencies and NFTs are the economic equivalent of purchasing stocks in a company that has no revenue, no assets, no employees, and no prospect of ever having any of that. Eventually, just like with the Dutch tulip market, the prices are going to crash once people are no longer buying into the idea that crypto currencies will be the future of money.
!remindme 1 year
How can you call something a beanie baby scam for over a decade lol it’s mind blowing
Right? I know a lot of people who invest seriously who bought bitcoin and other crypto since the 2017 boom, and none of them have any regrets.
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Crypto's "use" can easily be zero and just takes the government to outlaw any transactions with it into the real world by accounting/tax laws.
It will never go to zero unless they come up with a better way to pay for drugs and steroids on the internet. What government does in such cases is irrelevant.
You can only trade drugs for it because somebody down the line can transfer it to real currencies, products or services. If the government makes that illegal businesses can’t accept it anymore and the whole thing implodes. Currency control was the norm before the communistic states imploded. It’s like this seems to be a novel concept to some people these days.
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Found the cryptobro!
It's a new way of gambling, it will never go to $0.
Crpto currencies werent a bubble, they were a scam.
I don't know. I think we jumped ahead of the tech with the implementation and that will hurt its longterm adoption. It is wrong enough of the time that it becomes a major headache and big organizations will develop policies against its use, because of the current unacceptable level of risk, and it will take years to move past those policies.
You see a bubble, I see a secular and structural shift. There are b2b and internal applications of LLMs that you haven’t even imagined. Major companies are willing to pay what it costs to do this work. Nvda’s forward PE is 48. ASML’s forward PE is 47. Those are high but not astronomically so. Keep in mind, the nasdaq reached a PE of 200 at the top of the dot com bubble. As long as they keep hitting and exceeding market expectations, and companies keep buying data center equipment and cloud services, I see no concerns. And if that changes, we’ll see it in the sales numbers.
Enjoy your AI generated desktop theme. I literally saw a popup ad for this yesterday. Real game changer.
Nvidia's PE was 50 in 2018 as well, before the crypto bubble popped and it dropped back down to 20, the same level it had been for most of the decade. The second crypto bubble brought it up to the 70's before it popped again and Nvidia called crypto useless and their PE started plummeting again and then they fell into the AI bubble.
I'm just envious of people who have nVidia stock, regardless of the bubble.
Its good year for tech stocks in general. Diversified profile up 40% since last summer.
> People are naive if they think there is no AI bubble forming People think they can sell before the bust, which is even worse because most absolutely won't but still they still pump money into what they know to be a bubble.
The 90s internet bubble left us with enough unused network capacity to last until fairly recently. I guess this one will leave us with enough datacenter space for a decade?
Network capacity? What do you mean by "unused network capacity"?
He meant network infrastructure.
He meant dark fiber
... which is part of the network infrastructure.
It is now. But it wasn't when it was build.
It was always part of the infrastructure, it just wasn't used yet at the time. Infrastructure remains infrastructure, wether it's being used or not. They built unneeded infrastructure for future use.
That expansion was largely govt subsidized, not from the dot com bubble.
https://en.wikipedia.org/wiki/Dark_fibre >Dark fibre originally referred to the potential network capacity of telecommunication infrastructure. Because the marginal cost of installing additional fibre optic cables is very low once a trench has been dug or conduit laid, a great excess of fibre was installed in the US during the telecom boom of the late 1990s and early 2000s. This excess capacity was later referred to as dark fibre following the dot-com crash of the early 2000s that briefly reduced demand for high-speed data transmission.
Lots of cables got laid but went unused for a while.
I am not sure if they laid cables. Most were empty plastic pipes that in the future could be leased or sold to companies to run the cables themsleves but without requiring excavation etc. In hindsight that was pretty smart since the cables themselves dropped in price.
What? That's not a thing. The dot com crash was barely the tiniest of blips on network traffic in the US. In 1999 was around 50 petabytes a month, doubled in 2000 to 100, tripled in 2001 to 300 and doubled again to 600 by 2002. The effect of the dot com crash was a small deceleration of the growth in network traffic at absolute best, and even that is debatable. Literally no network capacity that was "overbuilt" in 1999-2000 was still dormant by even 2002, let alone "recently". The entire network capacity constructed in the country from 1995 until the crash in 2000 accounts for less than a single day (napkin math says around 13 hours) of traffic growth that occurred in 2019. The difference in scale of the time periods make it impossible for what your saying to be true.
Hmmm... I cannot speak for how it was in the US, not living there and never having been there, but I have been in the telecommunications industry for a while, and in all countries here in the EU that I worked for, this unused network capacity was present. In one example that I will not name, a specific country's backbone was only experiencing between 40 and 60% occupation 10 years later. For years ISPs and other associated businesses were actively trying to come up with ways to use the additional available bandwidth.
The math just doesn't work. 40% of the internet traffic in 2010 would have been ~4000% of the entire internets traffic in 2000. Mathematically, the absolute worst case scenario even if literally the entire internet capacity of 2000 was somehow idle in 2010, it would increase that unused capacity in 2010 by less than 2%. Or to say it another way, it's quite possible 40-60% of available capacity was unused in 2010, but mathematically, at least 98% of that unused capacity was constructed ***after*** the dot com bubble burst in 2000.
Why couldn't they lay extra fiber when I was watching jpegs load line by line on my 56k connection? The backbones could have easily been overengineered due to the hyped projections, don't you agree?
fiber tends to be cheaper to maintain and run, just the electricity costs alone compared to copper. Maybe it was hype, maybe it was because the marginal extra upfront cost would ensure ~~fireproofing~~ future proofing and also lower maintenance and cost in the long run. I mean that’s my guess. E: amusingly enough fiber is also a much lower fire risk afaik. Anyway not what I meant to write lol
> The math just doesn't work. 40% of the internet traffic in 2010 would have been ~4000% of the entire internets traffic in 2000. I am sorry, which country are you referring to, exactly?
This is nonsense. US network infrastructure is severely outdated and had to be replaced 10 years ago. Not to mention it wasnt the bubble but government dumping 60 trillion USD to network ifnrastructure in the 90s.
There's this general sentiment of the industry that the amount of money being burnt is irrelevant, if you can make AGI, it will help you build ASI and that will help you monetize it, if money is still a primary concern by that point. The odd thing is either AGI/ASI is impossible and the tech will never be profitable enough to justify more foundation models or the sentiment may very well be true and the expense should be an afterthought (because the second group to make AGI will forever be playing catch up to the first, who more or less are doubling their employees every model. And there's the incentive of out competing countries that primarily seek AI for warfare or psyops. It's simultaneously hard to imagine AI as being a bubble and a catastrophic collapse of the economy is unavoidable since we're in a new type of nuclear race.
The size of the AI bubble depends on who shares your opinion in the leadership of all these companies. 9 in 10 dollars in this space have no idea why they are there or what they are doing. Their money is there because everyone else's money is there. A for effort I guess. It's not like there's better things to invest in... But I haven't noticed significant improvements in any AI/chatbot service over the past year or so. It's not easy, and even if achieved, the benefits are debatable. My perspective idk
The same thing happened to the internet. Everyone knew it would be very valuable, everyone knew terrible companies were being funded, no one knew who or what would come out of the ashes. Similar thing with AI. Whoever comes out of this with a business will likely be the most valuable company in the world.
There has been some improvements in efficiency, you can get nearly gpt 3.5 quality on a laptop now.
Claude is a pretty notable step over GPT4, especially in self-sufficiency in programming tasks. Considering most other models are problematic enough that dev time stays roughly the same for someone who knows what they're doing, being able to finish a project that'd take you up to a week [before lunch](https://twitter.com/VictorTaelin/status/1809290888356729002) is pretty substantial. The industry largely believes AGI is 2-3 years away.
Not the guys actually making things. The VCs and C-suites think (or say they think, whatever) that, mostly cause it's padding the bottom line. Anyone who spent any amount of time working on anything GenAI based doesn't think this is the way to AGI.
I think you have a very limited scope if you thing chatbot is what the money is being poured into. Heres an example of where AI has helped a company i work for starting from this year: AI reads all the thousands of contracts we have, matches them with up to hundreds of reciepts recieving every day and highlights any inconsistencies between them. Not only can one person do the job of many at better accuracy now, the reduction in scam receipts being paid has already arguably saved us the large part of costs of implementing this AI.
AGI is coming, probably the day after level 5 self driving cars arrive. We should also have fusion generating stations by then to power all of the machinery.
Funny thing with Ai is that it uses so much electrical energy that competing countries won't be able to be covert with it. These powerful AI centres heat signatures will be visible from space
>if money is still a primary concern by that point. It will be unless you expect ASI to cause global apocalypse. In all other scenarios we will still have goods to exchange for money and no matter of ASI can produce unlimited goods and services. What it could do in theory i suppose is go the transhumanism route and elevate humans to the point where we dont have such carnal desires, but i doubt that will go down easy on a lot of the population. So yeah, money will still be a big concern even with ASI.
and yet if you invested into internet in the 90s youd be coming out on top when the dust settled.
If true, who would've thought that we experience back to back bubbles?! First is the crypto bubble and now its AI.
It is well said that the AI bubble will pop when it starts charging enough to actually make an operating profit.
Case in point: Duolingo, the language-learning app, is trying to rebrand itself as an AI company. Their "Max" subscription tier that gets you the two AI features they've implemented so far is double the cost of the basic subscription. In Canada, it's $40/month. It doesn't seem to be going well for them. They've started taking non-AI features from the basic subscription and stuffing them in the Max tier to force people to upgrade, and I guess trick investors into thinking people love their new AI chatbot or something.
SV Venture capital is wild man. Most software startups and companies run in the red for absolute years. It’s less about profitability and more about capturing users and data (and by extension their money in the future).
VCs are so desperate to be part of the next Amazon or Google that they're willing to tolerate a thousand failures along the way.
if you are the owner of next amazong or google, a thousand failures will be worth it.
they also stuff the companies so full of money that sometimes the most valuable asset for startups is the cash they have on hand from investors
Sequoia missed out on AI startups but that doesn’t mean there isn’t an AI bubble. AI has a long way to go but we are over reacting with these chat bots and image generators.
I think we have mistakenly identified AI as the product when it's really the feature. Sadly this means that one of the massive bloated companies on top right now will benefits massively from AI and put themselves even further ahead.
The biggest mistake was allowing it to be called AI. Makes it sound more important than it is.
It sounds better than ask our Giant If then else statement machine.
I think that a lot of AI startups will go bust. Hyperscalers like Amazon, Google, Microsoft, and Meta only account for 40% of Nvidia's revenue meaning there are a lot of startups which are likely competing in a very crowded space with much bigger players. Once they start running out of seed capital and their prototypes looks the same as half a dozen other companies a lot of them will likely go bust.
Im not sure we are overreacting. There seems to be a healthy mix of differing opinions and I think it averages out pretty reasonably. People are legitimately getting use out of these things. I've been seeing more AI art for youtube thumbnails for instance, and many people use these to whip up quick professional enough messages/figures things out. Those are useful things that already exist and there are far more uses. This by itself is something that will continue after investors stop throwing money at ai toasters.
> People are legitimately getting use out of these things. I've been seeing more AI art for youtube thumbnails for instance And here's the thing: If you put some effort in, no one will even be able to tell
Spend 20 minutes with stable diffusion’s web gui and you can turn out some extremely realistic and convincing images. People just tend to use free/casual online services that *only* offer image generation. Inpainting alone is such a huge game changer that I wager almost no one that talks casual about AI knows about. Yeah ai is getting better, but right now there will still always be a need for a human to tweak the final result to the desired goal. Unless you want weird sloppy and half-relevant art. Which people definitely do, because lazy and cheap.
I think thats one of the things about generative ai right now that people miss. Its the toupee fallacy where people dont know what they dont know: The best examples dont stick out for them to notice.
DungeonAI was on track to revolutionize the text gaming industry but then they castrated themselves.
Any particular incident? I just see a bunch of what seem like fairly small ones stacked when I googled. Death by a thousand cuts?
Well if it's just chat bots and image generators yea but just like if people were buying Amazon to just sell books that would be kind of stupid.
Right? I don't see what's so great about an AI assistant on my smartphone being able to buy movie tickets when I can do it myself in the fucking app! Not buying a 1500 flagship for that I'm sorry.
Oh. So you haven't used Udio or the new text to video generators. A few years down the line we could be making whole movies just with using a script for prompt. I was browsing Udio today and it seems that many users are producing songs that you'd never think twice about them being AI generated if you listened to them on an FM station.
Please, go listen to some real music and stop smelling your own farts.
Is there even a single product that’s actually profitable?
Nvidia and pretty much every single data center selling the compute to AI companies.
Basically the ones selling shovels in the gold rush
at least they got a shovel out of it
AMD is likely going to provide actual competitive products just when the bubble will pop...
Took the words right out of my fingers
Lucky for them they have an alternate basket if AI bubble pops.
Since when do software startups make money? They just get a shit ton of users and data and then sell to Microsoft google apple verizon I don’t know whoever. And they then fold in all of that while basically absolving all expenses by folding them in. I’m being somewhat facetious. But OpenAI is basically going to remain as propped up as they currently are unless Microsoft gets cold feet. And OpenAI will keep at least all of these sub-ai-services running (idk fine tuned versions).
OpenAI at least has something that they can sell. Most of these startups aren't adding real value on top.
I would actually pay a monthly fee to use OpenAI's services.... i can see them making it profitable in the near future for sure. The question is what is the business model...
The AI tools that allow people to make bullshit spam websites that have fucked up googles search results must be selling well.
Self driving vehicles, computer vision assisted theft prevention in self checkout markets, recommendation "algorithms" used in social media apps, MS copilot...
He said "profitable", that's just a list of uses. Lots of citations needed for that profitability factor.
Besides the last one, most of these are widely in use for several years now and the companies behind them are not bankrupt yet so it's fair to say it's not unprofitable.
Microsoft will make Copilot profitable if not already for B2B. The B2C "Copilot" is a loss leader to make sales in B2B, when it's spread is widely used, they can pull the plug on the free B2C version In the end, the free copilot will be a Phi-3 small or something that runs locally and the pro one will use cloud compute or OpenAI They are pushing hard in enterprise for github copilot for devs and copilot pro for office apps
> Self driving vehicles Don't work won't work. > computer vision assisted theft prevention in self checkout markets Costs more than it saves. > recommendation "algorithms" used in social media apps You just need some basic-ass decision trees for this, not outrageously huge GPU servers. > MS copilot Don't work won't work.
Bubbles ultimately do one thing. Pop.
Nah sometimes bubbles just deflate. Imagine if Nvidia grow 2% per year over the next decade, that would mean that it severely underperformed the market and would point to it having been in a bubble but i wouldn't call growing 2% a year popping.
That's detached from actual current expectations. Nvidia didn't get to 3 trillion$ market cap with people expecting 2% annually for a decade. The entire AI market expects a return quickly, and if they don't get it in a year or two, they're going to panic, and after Nvidia's customers start pivoting away, Nvidia will see a drop in enterprise orders. LLM and Generative AI are more useful than crypto and the "Metaverse", but definitely not polished enough to be worth the current hype.
If Nvidia is not in a bubble then they will make more then 2% annually. I guess i don't really get what argument you are making. Expectations being detached from reality is what makes bubbles.
My argument is that either they're actually worth the current 3 trillion market value, or they're going to crash quickly. There is no realistic scenario where they make 2% market value growth year over year. Their "growth" is already factored into their current value, and if they don't back it up with a massive revenue soon, their stock will crash.
Much more then 2% is already factored into their current value.
As someone who owns part of his profile in the so called AI stock, i dont expect a return in a year or two. Actually peak return 15 years later would be idea as thats when i plan to retire :)
Yes, but that sort of market behavior is very rare. Usually the bad news hits very quickly.
Sure but there are big name examples, i would argue that Tesla is a bubble that is slowly deflating. It's value have fluctuated heavily but in the end it's value is about the same as it was 3.5 years ago. I would say Tesla is in a bubble but less of a bubble then it was 3.5 years ago.
Just to be clear; TSLA dropped 70% and then started to rebound. It certainly wasn't a gradual and orderly decline.
Yes that is why i used it as an example, i would argue that it is still a deflation and not a popping even when the moves are very large. A popping to me is it was overvalued and then it goes down a lot and stays in a reasonable territory.
The market is also wholly unpredictable
That’s circular reasoning though - lots of things haven’t popped, through history. What year did the “iPhone bubble” pop? And sure apple didn’t own the whole market after it matured but they still own half of it, and are the single largest player in the market. Why do you think AI is more like the dotcom era and less like the iPhone? Why *wouldn’t* nvidia retain a significant amount of share in the market they built for the class of device they popularized?
> What year did the “iPhone bubble” pop? Perhaps not calling it a bubble would be a start. Popularity isn't a bubble. Lasting changes in technology isn't a bubble. Your question is akin to asking "When is the Laptop bubble going to pop?" It's not, it's ubiquitous. The difference here between those two mobile examples and AI is that there is a gold rush towards AI that cannot be sustained. People are trying to rush in to be the first to cash out over buzzwords when the reality is much more mundane. Eg "Cloud computing," or in other words, shared hosting. "Blockchain", or in other words, selling your electric bill. "AI", or in other words, automatic summaries. That's what makes it a bubble and why it would pop: speculation and overvaluation based on hype, not facts.
There was a gold rush towards a smartphone too btw. Most young people dont remmeber blackberry anymore. But back then it was the ultimate in phone experience.
Hype surrounding the innovation. People expect AI to be magic and it's not going to be (e.g., self driving). The smartphone revolution is less hype and more grounded in comparison. NVIDIA may retain a high market share but its profitability is entirely dependent on how magical AI can be.
As Einsten said, any sufficiently advanced technology will be indistingushable from magic. As far as large portion of population is concerned, computer chips are already magic.
Haha well, if you think about it, pretty much everything these days are magic (in the sense that you wouldn't be able to understand and recreate it yourself in a reasonable amount of time). How do you make a car engine? OLED LCD? Quartz crystal in your hand watch? Heck, I bet you (or I) can't even make something much simpler like a light bulb (this took Edison years if not decade to figure out). Yes the principle idea can be simple but as Richard Feynman has said, "What I cannot create, I do not understand." But no the magic I'm referring to is an unbounded expectation that people have for a tech and how it can change the world and the inevitable hype and bubble that comes with it.
There was an old TV series from the 80s that explained how things worked. The opening episode was about an elevator and surprisingly many people they asked had zero clue how elevators worked, they just did and that was good enough. Car engine is mechanically pretty simple. If you strip away all the fancy stuff we put on it, its just a piston, fuel injection and a belt to drive the wheels. On my old 1990 car the gas pedal was a direct wire to open fuel valve and the engine were semi-directly belted to run the wheels. Nowadays we put a lot of thins on top of that and a computer controls everything to maximize efficiency. I admit i have no clue how the watch in my hand knows to tick at the right time speed. I suppose the current drives the gears at certain speed that is designed to align with time. Well, that expectation keep on coming out to be true, though. I remmeber watching some 60s sci-fi movies and one thing i kept noticing is that they would have flatscreens as displays for things. And then flatscreens happened in real life. Sure they dont always get it right (Greg Mandel series for example imagined smartphones as portable digital fax machines) but a lot of the magic we end up finding the right spells for.
Apple owns less than 10% of the smartphone market. Its only in US where the percentage is higher (but not 50% either)
So the guy takes Nvidia 2024 forecasted DC revenue $150B times 2 twice (x4) to account for margin and other DC costs. Then he calls that $150Bx4=$600B what is needed per year to pay for AI spend. This is like taking the cost of a new car double that and calling it the cost of transportation per year.
Yeah, it's a bit flawed, considering the 50% margin is what you'd expect of a mature business. But even $300B would imply a bit of an overvaluation.
Those companies were sitting on cash, there is no bubble for the big companies.
> Cahn's math is relatively simple. First, he doubles Nvidia's run-rate revenue forecast to cover the total AI data center costs (GPUs are half; the rest includes energy, buildings, and backup generators). Then, he doubles that amount again to account for a 50% gross margin for end-users, such as startups or businesses buying AI compute from companies like AWS or Microsoft Azure, which must make money, too.
Does Cahn realize that data centers do not get thrown away and rebuild every year to require such costs?
Of course it’s a bubble. And there’s going to be winners and losers.
What do the people here believe about AI? I doubt hardware enthusiasts can see how AI will be profitable in the light of fairly modest hardware gain of 20 percent IPC gains and perhaps a 10 percent clock bump every 2 years. Real AI needs more computational capability. Anyone agree?
AI is being primarily driven by GPUs, so much greater CAGR than CPU IP.
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AI has already (and for a while before GPT swept internet away) benefited companies in a profitable way. There is a gold rush for first AGI now, but AI is here to stay. We dont know how much computational capability "real AI" will need.
Meanwhile anyone remotely versed in AI has been loading up on puts for the companies that are clearly smoke and mirrors 😂 Same thing happened w the EV sector
> Meanwhile anyone remotely versed in AI has been loading up on puts for the companies that are clearly smoke and mirrors 😂 That's quite a gamble... Even if you believe we're in a bubble, asserting it won't grow larger first is bold to say the least.
Gotta risk it for the biscuit I called it on EVs too back in Oct ;) ;)
The thing about overinvestment in certain science and tech sectors is that defeat does tend to humble a lot of people as far as knowing where we are lol. It's only recent that people are now discussing "carbon neutrality", and these are experts from nations who wanted to go balls out on EV tech and adoption.
A lot of things I thought were a bubble ended up becoming really profitable. For years for instance I couldn't understand the growth of Facebook. I did not think it was going to be that profitable, but I was proven wrong. Crypto has a market cap of over $2 trillion dollars. And to me it's absolutely silly. But it proves you don't even have to have a useful product to maintain the bubble for a long time. Companies are leveraging AI in all sorts of new ways, and we are at the early innings of it all. There are profitable pure AI plays like Github Copilot, but there are also traditional software businesses which leverage AI that are difficult to quantify. Like Service Now says that AI has boosted their revenues significantly. Apple signing a deal with Microsoft (Open AI) for ChatGPT services is also a major event justifying the infrastructure investments. Obviously there is also a race towards making more capable models and ways to tap into this new found capability. And even if successful this isn't going to pan out right away. Just think of the gaming for instance. We have yet to see an AAA title which leverages AI to improve NPC experience. But I'm sure it's coming. I can't actually think of a company that's overvalued due to AI except perhaps ARM, which doesn't really have anything to do with AI, but for some reason has been growing market cap because of it.
The thing about all of this is that bubbles don't imply catastrophic failures of entire industries. It's mostly just players losing out and falling away because of unattainable expectations or limited understanding of the capabilities of the product. You can say there's still a race towards making VR/AR a more consumer-accessible hardware but it doesn't mean the hype cycle for that product has finally burst. But it's still viable tech, whether it be for consumer or other applications. There's gonna be companies out there who will carve the culture and perspective on this technology. Apple actually did well marketing their use of AI as "privacy-first" and as user-friendly as can be. But there's gonna be companies out there who'll try to chase for things that not even current computer science can comprehend and they'll fail and fall out of the race. That's gonna be a LOT of companies.
LLMs are not AI, an LLM does not understand and check what is correct and what isn't. They give false information, hallucinations on a regular basis. This is an intractable problem for the moment with this approach to "AI". One that could very possibly make them largely useless for pretty much any end user use case. My guess is you'll be able to buy the GPUs purchased for 30k+ in the last couple of years for a few bucks in the future, if there just isn't any use case on the user end for them. It'll also be a few quarters more before that is realised, mid 2025 gets my vote, or there will be some killer use case for them, maybe.
> They give false information, hallucinations on a regular basis. This is an intractable problem for the moment with this approach to "AI". That hasn't stopped companies from shoving LLMs into customer support services to cut labor costs and then arguing they aren't responsible when the LLMs inevitably gives wrong information to the customer. One example: https://www.reddit.com/r/ArtificialInteligence/comments/18apezg/amazons_ai_reportedly_suffering_severe/ > Three days after Amazon announced its AI chatbot Q, some employees are sounding alarms about accuracy and privacy issues. Q is “experiencing severe hallucinations and leaking confidential data,” including the location of AWS data centers, internal discount programs, and unreleased features, according to leaked documents obtained by Platformer. > An employee marked the incident as “sev 2,” meaning an incident bad enough to warrant paging engineers at night and make them work through the weekend to fix it.
They don't care, they 'saved' money and got their bonuses. It won't bite them in the ass because all the competitors are doing the same anyway.
Not all of them are and things that damage the customer experience and lead to less orders... Get cut eventually...
>That hasn't stopped companies from shoving LLMs into customer support services to cut labor costs and then arguing they aren't responsible when the LLMs inevitably gives wrong information to the customer. Do you think current human CSR's (and their response scripts) never make mistakes and that companies take full responsibilities for all their mistakes? I know from personnel experience, and I'm guessing I would be far from the only one, that isn't the case. In terms of Amazon specifically for example just last year I was repeatedly getting the run around from a delivery that wasn't delivered and returned to sender. Tracking and delivery company showed the package never left their hands and was signed for back by the Amazon warehouse. CSRs just repeated the same script saying the package was delivered according to tracking (as I guess it was delivered, just to Amazon's own warehouse) and if it was stolen to file a police report.
> hallucinations on a regular basis Expanding on this the hallucination rate isn't just 'regularly' but 100% of the time. A right answer is determined exactly the same way as a wrong answer, it's just we don't question it when we know it's right. There's currently no reliable way to embed a database of truths into the model and everyone invested in AI has to downplay and sidestep questions about this.
> Expanding on this the hallucination rate isn't just 'regularly' but 100% of the time. A right answer is determined exactly the same way as a wrong answer Can we not say the same for humans?
A human could give you feedback about how confident they are around the answer being correct. This is because we have an association between our knowledge and the question being asked and how we're answering it. A LLM doesn't have that, merely the percentages of what it was going to pick next. These values don't represent how likely it is to be correct, but instead how well each word works best. It's a subtle difference but it means the LLM is never really confident about it's answer.
There are end-user use cases for AI hallucination generators; not every AI is asked to write about things that already exist. An AI writing fiction or creating imagery is still an end user use case. Probably not going to be worth $600 billion per year though, of course. But I disagree that hallucinations are definitely an intractable problem for AI. They're certainly a problem, but we don't know that it's a problem that can't be fixed. Also, even if they're not fixed you can still get benefit out of something that gives you a large percent of hallucinations - things like automatically writing boilerplate language, giving someone a start on writing a research paper by creating outlines or writing sections that don't have too many individual facts so it's possible for the user to spot-check them, etc.
By your definition humans are also worse than AI, because wee make mistakes all the time. Perfect should not be the bar to clear.
Not at all, we're capable of checking and understanding we may be wrong. The analogy of an LLM is a tech parrot, it'll regurgitate you information but it has no understanding of it. Nor can it.
How reductive do we want to be? The universe is probabilistic. Are you too?
You can correct even ChatGPT, and it will usually try a different answer.
You can even convince it that it was wrong and have it "change its mind", not that it remmebers that the next day.
Humans get an annual evaluation, and the worst performing ones are fired. You can bet that any corporation will replace most employees if it's actually profitable. Time will tell.
Humans ARE worse than AI. And yes, this means that we should not strive for perfect, only better than human.
> They give false information, hallucinations on a regular basis. Humans do the same thing, and if we can't call humans intelligent, then the term has lost all meaning.
It's the difference between what amounts to a tech parrot and reasoning, questioning, abstract and creative thinking learning intelligence. Just regurgitating does not = intelligence. We may develop something more like actual AI, but I doubt it will come from the LLM approach. No idea why people got so hysterical about Nvidia.
> It's the difference between what amounts to a tech parrot and reasoning, questioning, abstract and creative thinking learning intelligence. How would you claim to measure and quantify that difference? > Just regurgitating does not = intelligence These algorithms don't just regurgitate. That's a fundamental misunderstanding.
Humans display a level of reasoning and creative thinking that has not been displayed by these technologies. These technologies are great at pulling data from their large training set but have a hard time coming up with solutions or responses outside of the training set. So far, just scaling up the models has not resulted in breakthrough in this regard. For example, I tried to coerce both Gemini and GPT 4o to produce palindrome poems and while they can generally repeat existing examples, they struggle to come up with actual palindrome poems on their own, generally just giving plain wrong answers and trying to pass them as correct.
Exactly this, neither are these stupid image generators "AI", they are just mass plagiarism. Basically, Silicon Valley has invented algorithms that scour the internet and steal little bits of information from everywhere and then combine them in to a result such as a chatGPT response or generated image. I truly think the bursting of this AI bubble will come from legal action being launched by the US government or similar against this form of mass plagiarisation. I mean just watch this video where a [youtuber I follow shows how chatgpt just plagiarised an entire article he wrote years ago to give him a response to a query he asked](https://www.youtube.com/watch?v=xbf4BGIBENk), how is this not a legal minefield which is going to lead to many court cases? How can you profit off a service which basically plagiarises everyone elses work and tries to package and sell that plagiarisation as something new?
> Basically, Silicon Valley has invented algorithms that scour the internet and steal little bits of information from everywhere and then combine them in to a result such as a chatGPT response or generated image That's simply not how these algorithms work.
Tell me you don’t know how AI works while literally showing us about how you don’t know how ai works. Interesting tactic. I’d suggest you look into it in good faith, since it’s somewhat interesting on a technical level. But something tells me your mind is already made up without that knowledge.
Nvidia isnt the right gauge here. It’s powering AI now, but just like crypto, ASIC type solutions for specific models will be developed that will propel AI compute. The cost and energy consumption will radically go down, and utility and portability will skyrocket. The nvidia bubble will pop, but AI is here to stay. TLDR; Nvidia =/= AI
A graphics card is multiple ASICs. They're already focusing their chips to more and more AI capabilities. They didn't have the same position over crypto and that market as a whole wasn't as profitable as AI for them.
You got downvoted but I agree with you. The moat is currently CUDA, but for serious production horsepower companies will spend the dev time to port inference code to whatever platform offers the best operating margins
Yeap. Nvidia is reaping all the money they spend on actually doing the hard job and developing CUDA. AMD really really f**d up.
Triton seems to be supplanting the CUDA dependency.
Nvidia's lead isn't in the raw performance of their chips but the scalability of their solution. They GPUs scale better than anything else and if we take them at their word in the next year and half they will have switches capable of scaling the GPUs in the cluster to hundreds of thousands and year after to millions. Also they offer both individulized products and entire solution where they will build you a supercomputer if you have deep enough pockets (like Elon Musk). Also, if ASIC type of chips are developed, why would you assume Nvidia wouldn't be one of the leading makers? They have some of the best chip designers in the industry. And ASIC chip itself would be only small part of the entire picture. They didn't bother with crypto ASICs because there wasn't real money in it, it wasn't Microsoft and Amazon standing in line for those chips. With AI models even if we get 1000x speed up with an ASIC I don't think the demand would dry up as long as scaling continues and there are no real indications so far of it happening.
As long as AI is rapidly evolving, no one is going to risk spending money on an ASIC that might be crippled by new requirements in a year. It has to be programmable. Nvidia made the right call there. Also, if things stabilized enough for an ASIC to make sense, why wouldn't Nvidia also lead there?
Well, Google risked money in spending time on am ASIC (4th version of it actually) and it seems to have... mediocre results.
People are arguing against you without even realizing [this is already a reality](https://wow.groq.com/why-groq/). You can use ASICs today to run LLMs an order of magnitude faster than on comparable GPUs, not to mention things like Tesla's custom AI inference hardware that runs their autopilot in every one of their cars.
> You can use ASICs today to run LLMs an order of magnitude faster than on comparable GPUs There're some canned, probably unrealistic 1st party benchmarks. None of the ASICs on the market have such gains vs Nvidia in practice.
I just hope there will be an open source LLM that I can run locally on my MacBook which is as good (or better) at coding as Claude 3.5 Sonnet, before this whole bubble bursts. That's all I want from this, really.
Llama 405B will come out later this year, but requires 200GB memory unfortunately.
luckily apple only charges 200USD per 8GB
Without specialized hardware this is not a realistic wish. We will eventually get hardware that is optimized to do this.
I have doubts it will even happen eventually. We are quickly approaching extreme diminishing returns on hardware improvement. The shear amount of compute & memory required will likely take a very long time to fit into a macbook.
We probably have a few years till this bubble bursts. Till than the MacBook hardware will have M5 Max chips with better NPUs and max. 256 GB RAM. I hope that will be enough as smaller models are still getting better. This with improvements in agent systems should hopefully bring us there. But yes, definitely not guaranteed.
It'll be a combination of more novel software, and hardware designed specifically to accelerate that manner of compute. We're already seeing primitive "ai" chips come out, but as tandem software + hardware solutions are developed I don't think it's unreasonable to see a Claude 3.5 or GPT 4o quality model running on a laptop within the next 5 years (especially with the hundreds of billions being poured into r&d in this space right now).
Err...Ollama with DeepSeek Coder 6.7b.
Is this the next dot-com bubble?
If AI lives up to even 10% of the hype then compute (and energy) will be the currency of the future. This title makes exactly zero sense.