Pop pop!
Magnitude!
I’ve spent time with an AI laptop the past couple of weeks and ‘overinflated’ seems a generous description of where end user AI is today.
The fact that is is from LA Times shows that it’s still significant though
I just want computer parts to stop being so expensive. Remember when gaming was cheap? Pepperidge farm remembers. You used to be able to build a relatively high end pc for less than the average dogshit Walmart laptop.
To be honest right now is a relatively good time to build a PC, except for the GPU, which is heavily overpriced. I think if you are content with last gen AMD, this can also be turned to somewhat acceptable levels.
The more you bAI
But the trillion dollar valued Nvidia…
Maybe we can have normal priced graphics cards again.
I’m tired of people pretending £600 is a reasonable price to pay for a mid range GPU.
Nvidia is diversified in AI, though. Disregarding LLM, it’s likely that other AI methodologies will depend even more on their tech or similar.
I think they’re going to be bankrupt within 5 years. They have way too much invested in this bubble.
NVIDIA uses of AI technology aren’t going to pop, things like DLSS are here to stay. The value of the company and their sales are inflated by the bubble, but the core technology of NVIDIA is applicable way beyond the chat bot hype.
Bubbles don’t mean there’s no underlying value. The dot com bubble didn’t take down the internet.
$2.5T currently to be exact
I’m not sure, these companies are building data centers with so many gpus that they have to be geo located with respect to the power grid because if it were all done in one place it would take the grid down.
And they are just building more.
But the company doesn’t have the money. Stock value means investor valuation, not company funds.
Once a company goes public for the very first time, it’s getting money into its account, but from then on forward, that’s just investors speculating and hoping on a nice return when they sell again.
Of course there should be some correlation between the company’s profitability and the stock price, so ideally they do have quite some money, but in an investment craze like this, the correlation is far from 1:1. So whether they can still afford to build the data centers remains to be seen.
They’re not building them for themselves, they’re selling GPU time and SuperPods. Their valuation is because there’s STILL a lineup a mile long for their flagship GPUs. I get that people think AI is a fad, and it’s public form may be, but there’s thousands of GPU powered projects going on behind closed doors that are going to consume whatever GPUs get made for a long time.
Their valuation is because there’s STILL a lineup a mile long for their flagship GPUs.
Genuinely curious, how do you know where the valuation, any valuation, come from?
This is an interesting story, and it might be factually true, but as far as I know unless someone has actually asked the biggest investor WHY they did bet on a stock, nobody why a valuation is what it is. We might have guesses, and they might even be correct, but they also change.
I mentioned it few times here before but my bet is yes, what you did mention BUT also because the same investors do not know where else do put their money yet and thus simply can’t jump boats. They are stuck there and it might again be become they initially though the demand was high with nobody else could fulfill it, but I believe that’s not correct anymore.
but I believe that’s not correct anymore.
Why do you believe that? As far as I understand, other HW exists…but no SW to run on it…
Right, and I mentioned CUDA earlier as one of the reason of their success, so it’s definitely something important. Clients might be interested in e.g Google TPU, startups like Etched, Tenstorrent, Groq, Cerebras Systems or heck even design their own but are probably limited by their current stack relying on CUDA. I imagine though that if backlog do keep on existing there will be abstraction libraries, at least for the most popular ones e.g TensorFlow, JAX or PyTorch, simply because the cost of waiting is too high.
Anyway what I meant isn’t about hardware or software but rather ROI, namely when Goldman Sachs and others issue analyst report saying that the promise itself isn’t up to par with actual usage for paying customers.
Well, I’m no stockologist, but I believe when your company has a perpetual sales backlog with a 15-year head start on your competition, that should lead to a pretty high valuation.
Yeah, someone else commented with their financials and they look really good, so while I certainly agree that they are overvalued because we are in an AI training bubble, I don’t see it popping for a few years, especially given that they are selling the shovels. every big player in the space is set on orders of magnitude of additional compute for the next 2 years or more. It doesn’t matter if the company they sold gpus to fails if they already sold them. Something big that unexpected would have to happen to upset that trajectory right now and I don’t see it because companies are in the exploratory stage of ai tech so no one knows what doesn’t work until they get the computer they need. I could be wrong, but that’s what I see as a watcher of ai news channels on YouTube.
The co founder of open AI just got a billion dollars for his new 3 month old AI start up. They are going to spend that money on talent and compute. X just announced a data center with 100,000 gpus for grok2 and plans to build the largest in the world I think? But that’s Elon, so grains of salt and all that are required there. Nvidia are working with robotics companies to make AI that can train robots virtually to do a task and in the real world a robot will succeed first try. No more Boston dynamics abuse compilation videos. Right now agentic ai workflow is supposed to be the next step, so there will be overseer ai algorithms to develop and train.
All that is to say there is a ton of work that requires compute for the next few years.
{Opinion here} – I feel like a lot of people are seeing grifters and a wobbly gpt4o launch and calling the game too soon. It takes time to deliver the next product when it’s a new invention in its infancy and the training parameters are scaling nearly logarithmically from gen to gen.
I’m sure the structuring of payment for the compute devices isn’t as simple as my purchase of a gaming GPU from microcenter, but Nvidia are still financially sound. I could see a lot of companies suffering from this long term but nvidia will be The player in AI compute, whatever that looks like, so they are going to bounce back and be fine.
It’s like the least popular opinion I have here on Lemmy, but I assure you, this is the begining.
Yes, we’ll see a dotcom style bust. But it’s not like the world today wasn’t literally invented in that time. Do you remember where image generation was 3 years ago? It was a complete joke compared to a year ago, and today, fuck no one here would know.
When code generation goes through that same cycle, you can put out an idea in plain language, and get back code that just “does” it.
I have no idea what that means for the future of my humanity.
I agree with you but not for the reason you think.
I think the golden age of ML is right around the corner, but it won’t be AGI.
It would be image recognition and video upscaling, you know, the boring stuff that is not game changing but possibly useful.
I feel the same about the code generation stuff. What I really want is a tool that suggests better variable names.
you can put out an idea in plain language, and get back code that just “does” it
No you can’t. Simplifying it grossly:
They can’t do the most low-level, dumbest detail, splitting hairs, “there’s no spoon”, “this is just correct no matter how much you blabber in the opposite direction, this is just wrong no matter how much you blabber to support it” kind of solutions.
And that happens to be main requirement that makes a task worth software developer’s time.
We need software developers to write computer programs, because “a general idea” even in a formalized language is not sufficient, you need to address details of actual reality. That is the bottleneck.
That technology widens the passage in the places which were not the bottleneck in the first place.
I think you live in a nonsense world. I literally use it everyday and yes, sometimes it’s shit and it’s bad at anything that even requires a modicum of creativity. But 90% of shit doesn’t require a modicum of creativity. And my point isn’t about where we’re at, it’s about how far the same tech progressed on another domain adjacent task in three years.
Lemmy has a “dismiss AI” fetish and does so at its own peril.
Are you a software developer? Or a hardware engineer? EDIT: Or anyone credible in evaluating my nonsense world against yours?
Machine learning scientist.
That explains your optimism. Code generation is at a stage where it slaps together Stack Overflow answers and code ripped off from GitHub for you. While that is quite effective to get at least a crappy programmer to cobble together something that barely works, it is a far cry from having just anyone put out an idea in plain language and getting back code that just does it. A programmer is still needed in the loop.
I’m sure I don’t have to explain to you that AI development over the decades has often reached plateaus where the approach needed to be significantly changed in order for progress to be made, but it could certainly be the case where LLMs (at least as they are developed now) aren’t enough to accomplish what you describe.
So close, but not there.
OK, you’ll know that I’m right when you somewhat expand your expertise to neighboring areas. Should happen naturally.
Thank fucking god.
I got sick of the overhyped tech bros pumping AI into everything with no understanding of it…
But then I got way more sick of everyone else thinking they’re clowning on AI when in reality they’re just demonstrating an equal sized misunderstanding of the technology in a snarky pessimistic format.
Too much optimism and hype may lead to the premature use of technologies that are not ready for prime time.
— Daron Acemoglu, MIT
Preach!
Hopefully this means the haters will shut up and we can get on with using it for useful stuff
You’re no no longer using the term Luddite on us! Character development!
Oh you’re a luddite, you’re also a hater and about as intractable and strupid as a trump supporter. You can be many crappy things at once!
FMO is the best explanation of this psychosis and then of course denial by people who became heavily invested in it. Stuff like LLMs or ConvNets (and the likes) can already be used to do some pretty amazing stuff that we could not do a decade ago. I am also not against exploring and pushing the boundaries, but when you explore a boundary while pretending like you have already crossed it, that is how you get bubbles. And this again all boils down to appeasing some cancerous billionaire shareholders so they funnel down some money to your pockets.
there is really no need shit rainbows and puke glitter all over it
I’m now picturing the unicorn from the Squatty Potty commercial, with violent diarrhea and vomiting.
Stuff like LLMs or ConvNets (and the likes) can already be used to do some pretty amazing stuff that we could not do a decade ago, there is really no need to shit rainbows and puke glitter all over it.
I’m shitting rainbows and puking glitter on a daily basis BUT it’s not against AI as a field, it’s not against AI research, rather it’s against :
- catastrophism and fear, even eschatology, used as a marketing tactic
- open systems and research that become close
- trying to lock a market with legislation
- people who use a model, especially a model they don’t even have e.g using a proprietary API, and claim they are an AI startup
- C-levels decision that anything now must include AI
- claims that this or that skill is soon to be replaced by AI with actually no proof of it
- meaningless test results with grand claim like “passing the bar exam” used as marketing tactics
- claims that it scales, it “just needs more data”, not for .1% improvement but for radical change, e.g emergent learning
- for-profit (different from public research) scrapping datasets without paying back anything to actual creators
- ignoring or lying about non renewable resource consumption for both training and inference
- relying on “free” or loss leader strategies to dominate a market
- promoting to be doing the work for the good of humanity then signing exclusive partnership with a corporation already fined for monopoly practices
I’m sure I’m forgetting a few but basically none of those criticism are technical. None of those criticism is about the current progress made. Rather, they are about business practices.
The stock market is not based on income. It’s based entirely on speculation.
Since then, shares of the maker the high-grade computer chips that AI laboratories use to power the development of their chatbots and other products have come down by more than 22%.
June 18th: $136 August 4th: $100 August 18th: $130 again now: $103 (still above 8/4)
It’s almost like hype generates volatility. I don’t think any of this is indicative of a “leaking” bubble. Just tech journalists conjuring up clicks.
Also bubbles don’t “leak”.
Also bubbles don’t “leak”.
I mean, sometimes they kinda do? They either pop or slowly deflate, I’d say slow deflation could be argued to be caused by a leak.
We taking about bubbles or are we talking about balloons? Maybe we should change to using the word balloon instead, since these economic ‘bubbles’ can also deflate slowly.
Good point, not sure that economists are human enough to take sense into account, but I think we should try and make it a thing.
I’ve never seen a bubble deflate, but I digress.
Its all vibes and manipulation
The broader market did the same thing
https://finance.yahoo.com/quote/SPY/
$560 to $510 to $560 to $540
So why did $NVDA have larger swings? It has to do with the concept called beta. High beta stocks go up faster when the market is up and go down lower when the market is done. Basically high variance risky investments.
Why did the market have these swings? Because of uncertainty about future interest rates. Interest rates not only matter vis-a-vis business loans but affect the interest-free rate for investors.
When investors invest into the stock market, they want to get back the risk free rate (how much they get from treasuries) + the risk premium (how much stocks outperform bonds long term)
If the risks of the stock market are the same, but the payoff of the treasuries changes, then you need a high return from stocks. To get a higher return you can only accept a lower price,
This is why stocks are down, NVDA is still making plenty of money in AI
A.I., Assumed Intelligence
More like PISS, a Plagiarized Information Synthesis System
Well, they also kept telling investors all they need to simulate a human brain was to simulate the amount of neurons in a human brain…
The stupidly rich loved that, because they want computer backups for “immortality”. And they’d dump billions of dollars into making that happen
About two months ago tho, we found out that the brain uses microtubules in the brain to put tryptophan into super position, and it can maintain that for like a crazy amount of time, like longer than we can do in a lab.
The only argument against a quantum component for human consciousness, was people thought there was no way to have even just get regular quantum entanglement in a human brain.
We’ll be lucky to be able to simulate that stuff in 50 years, but it’s probably going to be even longer.
Every billionaire who wanted to “live forever” this way, just got aged out. So they’ll throw their money somewhere else now.
I used to follow the Penrose stuff and was pretty excited about QM as an explanation of consciousness. If this is the kind of work they’re reaching at though. This is pretty sad. It’s not even anything. Sometimes you need to go with your gut, and my gut is telling me that if this is all the QM people have, consciousness is probably best explained by complexity.
https://ask.metafilter.com/380238/Is-this-paper-on-quantum-propeties-of-the-brain-bad-science-or-not
Completely off topic from ai, but got me curious about brain quantum and found this discussion. Either way, AI still sucks shit and is just a shortcut for stealing.
That’s a social media comment from some Ask Yahoo knockoff…
Like, this isn’t something no one is talking about, you don’t have to solely learn about that from unpopular social media sites (including my comment).
I don’t usually like linking videos, but I’m feeling like that might work better here
https://www.youtube.com/watch?v=xa2Kpkksf3k
But that PBS video gives a really good background and then talks about the recent discovery.
some Ask Yahoo knockoff…
AskMeFi predated Yahoo Answers by several years (and is several orders of magnitude better than it ever was).
And that linked accounts last comment was advocating for Biden to stage a pre-emptive coup before this election…
https://www.metafilter.com/activity/306302/comments/mefi/
It doesn’t matter if it was created before Ask Yahoo or if it’s older.
It’s random people making random social media comments, sometimes stupid people make the rare comment that sounds like they know what they’re talking about. And I already agreed no one had to take my word on it either.
But that PBS video does a really fucking good job explaining it.
Cuz if I can’t explain to you why a random social media comment isn’t a good source, I’m sure as shit not going to be able to explain anything like Penrose’s theory on consciousness to you.
It doesn’t matter if it was created before Ask Yahoo or if it’s older.
It does if you’re calling it a “knockoff” of a lower-quality site that was created years later, which was what I was responding to.
Great.
So the social media site is older than I thought, and the person who made the comment on that site is a lot stupider than it seemed.
Like, Facebooks been around for about 20 years. Would you take a link to a Facebook comment over PBS?
My man, I said nothing about the science or the validity of that comment, just that it’s wrong to call Ask MetaFilter “some Ask Yahoo knockoff”. If you want to get het up about an argument I never made, you do you.
