But the trillion dollar valued Nvidia…
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.
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.
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.
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.
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.
$2.5T currently to be exact
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.
I highly doubt that. If the AI bubble pops, they’ll probably be worth a lot less relative to other tech companies, but hardly bankrupt. They still have a very strong GPU business, they probably have an agreement with Nintendo on the next Switch (like they did with the OG Switch), and they could probably repurpose the AI tech in a lot of different ways, not to mention various other projects where they package GPUs into SOCs.
It really depends on how much they’ve invested in building AI chips.
They don’t build the chips at all. They pay tsmc.
Sure, but their deliveries have also been incredibly large. I’d be surprised if they haven’t already made enough from previous sales to cover all existing and near-term investments into AI. The scale of the build-out by big cloud firms like Amazon, Google, and Microsoft has been absolutely incredible, and Nvidia’s only constraint has been making enough of them to sell. So even if support completely evaporates, I think they’ll be completely fine.
Fall in share price, yes.
Bankrupt, no. Their debt to Equity Ratio is 0.1455. They can pay off their $11.23 B debt with 2 months of revenue. They can certainly afford the interest payments.
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.
Wall Street has already milked “the pump” now they short it and put out articles like this
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!
Shitty useless pictures each costing kilowatt hours.
The pictures aren’t very good I’ll grant you that, but they definitely don’t require even one kWh per image, and besides that basically everything made with a computer costs power. We waste power on nonsense just fine without the help of LLMs or diffusion models.
No, no, and also no. Try again? Or cram your face into a blender? Either is good with me
Are you ok? Too long in the sun?
Bit tired (had to get up too early today) but otherwise okay, thanks. How’s your face? Blended to a fine paste yet?
I mean, machine learning and AI does have benefits especially in research in the medical field. The consumer AI products are just stupid though.
It’s help me learn coding, Spanish, and helped me build scripts of which I would never have been able to do by myself or with technical works alone.
If we’re talking specifically about the value I get out of what Gpt is right now, its priceless to me. Like my second, albeit braindead, systems administrator on my shoulder when I need something I don’t want to type out myself. And what ever mistakes it makes is within my abilities to repair on my own without fighting for it.
AI didn’t do that. It stole all the information for free on the internet from people who tried to help others and make money of it.
Have you ever used Google translate or apps that identify bugs/plants/songs? AI is used in products you most likely use every week.
You are also arguing for a closed garden system where companies like reddit and Getty get to dictate who can make models and at what price.
Individual are never getting a dime out of this. In a perfect world, governments would be fighting for copyleft licenses for anything using big data but every law being proposed is meant to create a soft monopoly owned by Microsoft and Google and kill open-source.
I can very much so assure you that chatGPT did all of those things for me.
“PIXAR DIDNT MAKE TOY STORY!! THE CHI ARTISTS DID!!!”
I know coding now to a degree. But when I mess something up I’m not going to post to a random forum somewhere to see if someone feels like looking at my problem, and then when they view the issue someone feels the need to include their non objective solution or answer. I don’t want conversation or to be told “see you CoULD do this yourself If you did this”
Like yea that’s cool…but my building just disconnected from the outside world and 1200 people are now expressing their concern, and me being told to just Google it, when my Juniper flipped a bit isnt going to cut it. And Andy in Montana just locked my post because"this question has been answered before" with no elaboration. And spice works has my exact issue but is closed because: problem solved. But they didn’t show their work.
How about this; when books first became widely adopted people bitched that the youth would get lazy. Then it was radio. Then it was television. Then it was the Internet. Then it was social media. Now it’s AI.
The race is always going. But you can stop when ever you feel uncomfortable. But the rest of the pack is going to keep moving to the finish line that never shows up. And new comers can join at any time.
_------------
For Spanish learning, I can now have full endless conversation with something and it never gets tired. It never stops being objective. Since the task is so simple it never fucks up or hallucinates. It never tells me it has other things to do. It never discourages our demeans when I get something wrong. Infact it even plays along with what ever speed or level of language I need it to, such as kindergarten level or elementary level. And all of this is supplemental to actually learning through other means. Try to get that consistency on reddit. Whether that be speed, integrity or volition.
Your suggestion works in 2015 when cleverbot was around or when siri was a creature comfort but it’s 10 years later.
Oh and all of what I mentioned is free - to me.
That would be absolutely amazing. How can we work out a community effort that is designed to teach, you some crowdsource tests maybe we can bring education to the masses for free…
That would indeed be great but completely unrelated to what I said so I suspect you may have answered the wrong person
Now I want the heaters to shut down so we can make some cool s*** too
I find it insane when “tech bros” and AI researchers at major tech companies try to justify the wasting of resources (like water and electricity) in order to achieve “AGI” or whatever the fuck that means in their wildest fantasies.
These companies have no accountability for the shit that they do and consistently ignore all the consequences their actions will cause for years down the road.
It’s research. Most of it never pans out, so a lot of it is “wasteful”. But if we didn’t experiment, we wouldn’t find the things that do work.
I don’t think I’ve heard a lot of actual research in the AI area not connected to machine learning (which may be just one component, not really necessary at that).
Most of the entire AI economy isn’t even research. It’s just grift. Slapping a label on ChatGPT and saying you’re an AI company. It’s hustlers trying to make a quick buck from easy venture capital money.
You can probably say the same about all fields, even those that have formal protections and regulations. That doesn’t mean that there aren’t people that have PhD’s in the field and are trying to improve it for the better.
Sure but typically that’s a small part of the field. With AI it’s a majority, that’s the difference.
No, it is the majority in every field.
Specialists are always in the minority, that is like part of their definition.
Is it really a grift when you are selling possible value to an investor who would make money from possible value?
As in, there is no lie, investors know it’s a gamble and are just looking for the gamble that everyone else bets on, not that it l would provide real value.
I would classify speculation as a form of grift. Someone gets left holding the bag.
I agree, but these researchers/scientists should be more mindful about the resources they use up in order to generate the computational power necessary to carry out their experiments. AI is good when it gets utilized to achieve a specific task, but funneling a lot of money and research towards general purpose AI just seems wasteful.
I mean general purpose AI doesn’t cap out at human intelligence, of which you could utilize to come up with ideas for better resource management.
Could also be a huge waste but the potential is there… potentially.
What’s funny is that we already have general intelligence in billions of brains. What tech bros what is a general intelligence slave.
Well put.
I’m sure plenty of people would be happy to be a personal assistant for searching, summarizing, and compiling information, as long as they were adequately paid for it.
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.
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.
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.
Too much optimism and hype may lead to the premature use of technologies that are not ready for prime time.
— Daron Acemoglu, MIT
Preach!
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.
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.
this is just wrong no matter how much you blabber to support it" kind of solutions.
When you put it like that, I might be a perfect fit in today’s world with the loudest voice wins landscape.
I regularly think and post conspiracy theory thoughts about why the “AI” is such a hype. And in line with them a certain kind of people seem to think that reality doesn’t matter, because those who control the present control the past and the future. That is, they think that controlling the discourse can replace controlling the reality. The issue with that is that whether a bomb is set, whether a boat is sea-worthy, whether a bridge will fall is not defined by discourse.
they’re pretty good, and the faults they have are improving steadily. I dont think we’re hitting a ceiling yet, and I shudder to think where they’ll be in 5 years.
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.
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.
First off, are you extrapolating the middle part of the sigmoid thinking it’s an exponential. Secondly, https://link.springer.com/content/pdf/10.1007/s11633-017-1093-8.pdf
Dismiss at your own peril is my mantra on this. I work primarily in machine vision and the things that people were writing on as impossible or “unique to humans” in the 90s and 2000s ended up falling rapidly, and that generation of opinion pieces are now safely stored in the round bin.
The same was true of agents for games like go and chess and dota. And now the same has been demonstrated to be coming true for languages.
And maybe that paper built in the right caveats about “human intelligence”. But that isn’t to say human intelligence can’t be surpassed by something distinctly inhuman.
The real issue is that previously there wasn’t a use case with enough viability to warrant the explosion of interest we’ve seen like with transformers.
But transformers are like, legit wild. It’s bigger than UNETs. It’s way bigger than ltsm.
So dismiss at your own peril.
But that isn’t to say human intelligence can’t be surpassed by something distinctly inhuman.
Tell me you haven’t read the paper without telling me you haven’t read the paper. The paper is about T2 vs. T3 systems, humans are just an example.
Yeah I skimmed a bit. I’m on like 4 hours of in flight sleep after like 24 hours of air ports and flying. If you really want me to address the points of the paper, I can, but I can also tell it doesn’t diminish my primary point: dismiss at your own peril.
dismiss at your own peril.
Oooo I’m scared. Just as much as I was scared of missing out on crypto or the last 10000 hype trains VCs rode into bankruptcy. I’m both too old and too much of an engineer for that BS especially when the answer to a technical argument, a fucking information-theoretical one on top of that, is “Dude, but consider FOMO”.
That said, I still wish you all the best in your scientific career in applied statistics. Stuff can be interesting and useful aside from AI BS. If OTOH you’re in that career path because AI BS and not a love for the maths… let’s just say that vacation doesn’t help against burnout. Switch tracks, instead, don’t do what you want but what you can.
Or do dive into AGI. But then actually read the paper, and understand why current approaches are nowhere near sufficient. We’re not talking about changes in architecture, we’re about architectures that change as a function of training and inference, that learn how to learn. Say goodbye to the VC cesspit, get tenure aka a day job, maybe in 50 years there’s going to be another sigmoid and you’ll have written one of the papers leading up to it because you actually addressed the fucking core problem.
I’ve written something vague in another place in this thread which seemed a good enough argument. But I didn’t expect that someone is going to link a literal scientific publication in the same very direction. Thank you, sometimes arguing in the Web is not a waste of time.
EDIT: Have finished reading it. Started thinking it was the same argument, in the middle got confused, in the end realized that yes, it’s the same argument, but explained well by a smarter person. A very cool article, and fully understandable for a random Lemming at that.
And I wouldn’t know where to start using it. My problems are often of the “integrate two badly documented company-internal APIs” variety. LLMs can’t do shit about that; they weren’t trained for it.
They’re nice for basic rote work but that’s often not what you deal with in a mature codebase.
Again, dismiss at your own peril.
Because “Integrate two badly documented APIs” is precisely the kind of tasks that even the current batch of LLMs actually crush.
And I’m not worried about being replaced by the current crop. I’m worried about future frameworks on technology like greyskull running 30, or 300, or 3000 uniquely trained LLMs and other transformers at once.
I’m with you. I’m a Senior software engineer and copilot/chatgpt have all but completely replaced me googling stuff, and replaced 90% of the time I’ve spent writing the code for simple tasks I want to automate. I’m regularly shocked at how often copilot will accurately auto complete whole methods for me. I’ve even had it generate a whole child class near perfectly, although this is likely primarily due to being very consistent with my naming.
At the very least it’s an extremely valuable tool that every programmer should get comfortable with. And the tech is just in it’s baby form. I’m glad I’m learning how to use it now instead of pooh-poohing it.
Ikr? It really seems like the dismissiveness is coming from people either not experienced with it, or just politically angry at its existence.
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.
It’s not about stages. It’s about the Achilles and tortoise problem.
There’s extrapolation inside the same level of abstraction as the data given and there’s extrapolation of new levels of abstraction.
But frankly far smarter people than me are working on all that. Maybe they’ll deliver.
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.
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.
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.
As I job-hunt, every job listed over the past year has been “AI-drive [something]” and I’m really hoping that trend subsides.
“This is an mid level position requiring at least 7 years experience developing LLMs.” -Every software engineer job out there.
Yeah, I’m a data engineer and I get that there’s a lot of potential in analytics with AI, but you don’t need to hire a data engineer with LLM experience for aggregating payroll data.
there’s a lot of potential in analytics with AI
I’d argue there is a lot of potential in any domain with basic numeracy. In pretty much any business or institution somebody with a spreadsheet might help a lot. That doesn’t necessarily require any Big Data or AI though.
Reminds me of when I read about a programmer getting turned down for a job because they didn’t have 5 years of experience with a language that they themselves had created 1 to 2 years prior.
That was cloud 7 years ago and blockchain 4
I’m more annoyed that Nvidia is looked at like some sort of brilliant strategist. It’s a GPU company that was lucky enough to be around when two new massive industries found an alternative use for graphics hardware.
They happened to be making pick axes in California right before some prospectors found gold.
And they don’t even really make pick axes, TSMC does. They just design them.
They didn’t just “happen to be around”. They created the entire ecosystem around machine learning while AMD just twiddled their thumbs. There is a reason why no one is buying AMD cards to run AI workloads.
I feel like for a long time, CUDA was a laser looking for a problem.
It’s just that the current (AI) problem might solve expensive employment issues.
It’s just that C-Suite/managers are pointing that laser at the creatives instead of the jobs whose task it is to accumulate easily digestible facts and produce a set of instructions. You know, like C-Suites and middle/upper managers do.
And NVidia have pushed CUDA so hard.AMD have ROCM, an open source cuda equivalent for amd.
But it’s kinda like Linux Vs windows. NVidia CUDA is just so damn prevalent.
I guess it was first. Cuda has wider compatibility with Nvidia cards than rocm with AMD cards.
The only way AMD can win is to show a performance boost for a power reduction and cheaper hardware. So many people are entrenched in NVidia, the cost to switching to rocm/amd is a huge gambleOne of the reasons being Nvidia forcing unethical vendor lock in through their licensing.
Go ahead and design a better pickaxe than them, we’ll wait…
Go ahead and design a better pickaxe than them, we’ll wait…
Same argument:
“He didn’t earn his wealth. He just won the lottery.”
“If it’s so easy, YOU go ahead and win the lottery then.”
My fucking god.
“Buying a lottery ticket, and designing the best GPUs, totally the same thing, amiriteguys?”
In the sense that it’s a matter of being in the right place at the right time, yes. Exactly the same thing. Opportunities aren’t equal - they disproportionately effect those who happen to be positioned to take advantage of them. If I’m giving away a free car right now to whoever comes by, and you’re not nearby, you’re shit out of luck. If AI didn’t HAPPEN to use massively multi-threaded computing, Nvidia would still be artificial scarcity-ing themselves to price gouging CoD players. The fact you don’t see it for whatever reason doesn’t make it wrong. NOBODY at Nvidia was there 5 years ago saying “Man, when this new technology hits we’re going to be rolling in it.” They stumbled into it by luck. They don’t get credit for forseeing some future use case. They got lucky. That luck got them first mover advantage. Intel had that too. Look how well it’s doing for them. Nvidia’s position over AMD in this space can be due to any number of factors… production capacity, driver flexibility, faster functioning on a particular vector operation, power efficiency… hell, even the relationship between the CEO of THEIR company and OpenAI. Maybe they just had their salespeople call first. Their market dominance likely has absolutely NOTHING to do with their GPU’s having better graphics performance, and to the extent they are, it’s by chance - they did NOT predict generative AI, and their graphics cards just HAPPEN to be better situated for SOME reason.
they did NOT predict generative AI, and their graphics cards just HAPPEN to be better situated for SOME reason.
This is the part that’s flawed. They have actively targeted neural network applications with hardware and driver support since 2012.
Yes, they got lucky in that generative AI turned out to be massively popular, and required massively parallel computing capabilities, but luck is one part opportunity and one part preparedness. The reason they were able to capitalize is because they had the best graphics cards on the market and then specifically targeted AI applications.
His engineers built it, he didn’t do anything there
They just design them.
It’s not trivial though. They also managed to lock dev with CUDA.
That being said I don’t think they were “just” lucky, I think they built their luck through practices the DoJ is currently investigating for potential abuse of monopoly.
Yeah CUDA, made a lot of this possible.
Once crypto mining was too hard nvidia needed a market beyond image modeling and college machine learning experiments.
Imo we should give credit where credit is due and I agree, not a genius, still my pick is a 4080 for a new gaming computer.
The tech bros had to find an excuse to use all the GPUs they got for crypto after they bled that dry
The tech bros had to find an excuse to use all the GPUs they got for crypto after they
bled that dryupgraded to proof-of-stake.I don’t see a similar upgrade for “AI”.
And I’m not a fan of BTC but $50,000+ doesn’t seem very dry to me.
No, it’s when people realized it’s a scam
If that’s the reason, I wouldn’t even be mad, that’s recycling right there.
I don’t think AI is ever going to completely disappear, but I think we’ve hit the barrier of usefulness for now.
The more you bAI
Welp, it was ‘fun’ while it lasted. Time for everyone to adjust their expectations to much more humble levels than what was promised and move on to the next sceme. After Metaverse, NFTs and ‘Don’t become a programmer, AI will steal your job literally next week!11’, I’m eager to see what they come up with next. And with eager I mean I’m tired. I’m really tired and hope the economy just takes a damn break from breaking things.
I just hope I can buy a graphics card without having to sell organs some time in the next two years.
Don’t count on it. It turns out that the sort of stuff that graphics cards do is good for lots of things, it was crypto, then AI and I’m sure whatever the next fad is will require a GPU to run huge calculations.
I’m sure whatever the next fad is will require a GPU to run huge calculations.
I also bet it will, cf my earlier comment on rendering farm and looking for what “recycles” old GPUs https://lemmy.world/comment/12221218 namely that it makes sense to prepare for it now and look for what comes next BASED on the current most popular architecture. It might not be the most efficient but probably will be the most economical.
AI is shit but imo we have been making amazing progress in computing power, just that we can’t really innovate atm, just more race to the bottom.
——
I thought capitalism bred innovation, did tech bros lied?
/s
I’d love an upgrade for my 2080 TI, really wish Nvidia didn’t piss off EVGA into leaving the GPU business…
If there is even a GPU being sold. It’s much more profitable for Nvidia to just make compute focused chips than upgrading their gaming lineup. GeForce will just get the compute chips rejects and laptop GPU for the lower end parts. After the AI bubble burst, maybe they’ll get back to their gaming roots.
My RX 580 has been working just fine since I bought it used. I’ve not been able to justify buying a new (used) one. If you have one that works, why not just stick with it until the market gets flooded with used ones?
move on to the next […] eager to see what they come up with next.
That’s a point I’m making in a lot of conversations lately : IMHO the bubble didn’t pop BECAUSE capital doesn’t know where to go next. Despite reports from big banks that there is a LOT of investment for not a lot of actual returns, people are still waiting on where to put that money next. Until there is such a place, they believe it’s still more beneficial to keep the bet on-going.
But if it doesn’t disrupt it isn’t worth it!
/s
I’m just praying people will fucking quit it with the worries that we’re about to get SKYNET or HAL when binary computing would inherently be incapable of recreating the fast pattern recognition required to replicate or outpace human intelligence.
Moore’s law is about similar computing power, which is a measure of hardware performance, not of the software you can run on it.
Unfortunately it’s part of the marketing, thanks OpenAI for that “Oh no… we can’t share GPT2, too dangerous” then… here it is. Definitely interesting then but now World shattering. Same for GPT3 … but through exclusive partnership with Microsoft, all closed, rinse and repeat for GPT4. It’s a scare tactic to lock what was initially open, both directly and closing the door behind them through regulation, at least trying to.
My only real hope out of this is that that copilot button on keyboards becomes the 486 turbo button of our time.
Meaning you unpress it, and computer gets 2x faster?
I was thinking pressing it turns everything to shit, but that works too. I’d also accept, completely misunderstood by future generations.
Well now I wanna hear more about the history of this mystical shit button
Back in those early days many applications didn’t have proper timing, they basically just ran as fast as they could. That was fine on an 8mhz cpu as you probably just wanted stuff to run as fast as I could (we weren’t listening to music or watching videos back then). When CPUs got faster (or it could be that it started running at a multiple of the base clock speed) then stuff was suddenly happening TOO fast. The turbo button was a way to slow down the clock speed by some amount to make legacy applications run how it was supposed to run.
Most turbo buttons never worked for that purpose, though, they were still way too fast Like, even ignoring other advances such as better IPC (or rather CPI back in those days) you don’t get to an 8MHz 8086 by halving the clock speed of a 50MHz 486. You get to 25MHz. And practically all games past that 8086 stuff was written with proper timing code because devs knew perfectly well that they’re writing for more than one CPU. Also there’s software to do the same job but more precisely and flexibly.
It probably worked fine for the original PC-AT or something when running PC-XT programs (how would I know our first family box was a 386) but after that it was pointless. Then it hung on for years, then it vanished.
Actually you pressed it and everything got 2x slower. Turbo was a stupid label for it.
I could be misremembering but I seem to recall the digits on the front of my 486 case changing from 25 to 33 when I pressed the button. That was the only difference I noticed though. Was the beige bastard lying to me?
Lying through its teeth.
There was a bunch of DOS software that runs too fast to be usable on later processors. Like a Rouge-like game where you fly across the map too fast to control. The Turbo button would bring it down to 8086 speeds so that stuff is usable.
Damn. Lol I kept that turbo button down all the time, thinking turbo = faster. TBF to myself it’s a reasonable mistake! Mind you, I think a lot of what slowed that machine was the hard drive. Faster than loading stuff from a cassette tape but only barely. You could switch the computer on and go make a sandwich while windows 3.1 loads.
Oh, yeah, a lot of people made that mistake. It was badly named.
That’s… the same thing.
Whops, I thought you were responding to the first child comment.
I’ve noticed people have been talking less and less about AI lately, particularly online and in the media, and absolutely nobody has been talking about it in real life.
The novelty has well and truly worn off, and most people are sick of hearing about it.
Yeah, now we are gonna get the reality of deep fakes; fun times.
It’s like 3D TVs, for a lot of consumer applications tbh
Oh fuck that’s right, that was a thing.
Goddamn
3D has been a thing every 15 years or so
3D TVs were a commercial fad once and I haven’t seen them in forever.
2016 may have been the end of them
Yes but 3D is always a thing periodically.
I used shutter glasses with two voodoo2 cards…
I used shutter glasses with the sega master system back in 87. They were rad af
The hype is still percolating, at least among the people I work with and at the companies of people I know. Microsoft pushing Copilot everywhere makes it inescapable to some extent in many environments, there’s people out there who have somehow only vaguely heard of ChatGPT and are now encountering LLMs for the first time at work and starting the hype cycle fresh.
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.
