so these crazy prices i hear about being implemented (like at github) should actually be at least 10x higher?
10x higher to break even :)
Nice try, I ain’t gonna pay anyway
It’s gonna come crashing down pretty soon. It’s gonna hurt all of us. It won’t hurt the people responsible nearly enough.
pretty soon
people have been saying that for some time though
The bubble will pop, I think a lot of people are just baffled by how big it’s getting.
The thing is this really depends on the speed of some financial events, not some technical failing.
Notably, if OpenAI has to cancel any of their commitments to buy hardware because they find they have neither the money nor can secure even more debt to cover, that event would potentially cause the bubble to pop, even for hypothetical companies that may have been more responsible and might have a viable business approach. Those commitments are coming up, and a lot of analysis struggles to see how they will fund those commitments.
The thing with this bubble is that the investors don’t get the nuance and will flee at signs of trouble in any of OpenAI, Anthropic, or a handful of others, and Altman’s leadership has made trouble at OpenAI very likely, but the investors don’t believe it and won’t believe it’s unique to OpenAI, even if it would be.
Only because the hype has lasted longer than expected. Now that IPOs have been filed, the AI companies (Anthropic, OpenAI) released statements about slowing down to protect us. They’re setting the stage for lower growth. But I think you should invest every penny you have into “SpaceXMegaTwitterSuperCarAI”.
I wonder how much they spend for every $0 I pay them.
$1000 I would guess. They are just burning money at this point.
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I mean, this is no different than Walmart making prices low until other businesses die out and then raising them.
It is no different than police shoving all the homeless people and drug addicts into one area of town to crash the property prices, and then evicting them once developers buy everything for cheap.
They’re purposely operating at a loss in the expectation that they can get ingrained into a ton of workflows, and then gouge everyone absolutely to death while also worsening the quality of the service to make it cheaper for them to run.
If it weren’t so horrible for the environment, I’d kind of like it, because all the dumbass executives that are signing up for this are going to get exactly what they deserve. You’d think they’d recognize a scheme when they see one.
Now, I’m no MBA, but that seems like a bad business plan…
I can’t imagine paying for AI when the open source tools have made it so easy to set up a model locally.
Don’t be daft. The vast majority of people don’t have the knowledge or resources to set that up locally.
You’re right if we’re talking about the entire population of Earth. With these local models though, other people have already done all the hard stuff. Anyone with an RTX card and just a minimum level of patience can get going.
Minimum for local models is 12gb imo. There are several “rtx” cards that have 8gb. Also, why nvidia? AMD works well too. My previous point stands, still. If you don’t already have the hw, buying a pc today is very expensive. I don’t know if you go out much but it ain’t pretty out there. People arrn’t precisely swimming in cash.
Also, patience isn’t the only requirement. Keep in mind that some people struggle to even install a program.
Easy to set up, but still needs a 15k $ graphics card and electricity bill. The price you pay openai/anthropic is much cheaper than that for that quality of model.
Sure, you can setup a small model on a consumer graphics card, but the output will be considerably worse and the processing speed considerably lower.
For 240€/year you got a subscription to anthropic which will happily ingest a whole repository and process it in about one minute. No matter what latest model GPU you installed on your computer, you won’t be able to do that.
Sure, this guy was able to run a 26B model on an old CPU: https://point.free/blog/gemma-4-on-a-2016-xeon/
But that was not easy at all and the speed you get is definitely not the same as the one provided for a very cheap price.
If you were paying the real price it would be 2 grand a year though. And in 5 years that 15k graphics card will be $200 and sip on electricity by comparison.
A100 is 6 years old and is now sold at over 10k $. If you were paying a higher price it could be cheaper to buy the card, since the prices are low that is not the case.
Currently nearly 5 year old used graphics cards are being sold for their initial price. Not sure how much they’ll get cheaper…
There is a middle ground. Crypto farmers have transitioned into running AI workloads for money. There are things sort of like folding@home but you can let people use your GPU and you earn tokens which are used to buy compute or sold to people who want to buy compute on the network. So you can setup a bigass open source model for private on demand use it’s still not cheap but a lot closer to reality for a lot of people than a 15k initial purchase.
Good thing all the companies leaning hard on AI 10 X’d their profits… Wait…
Trust me bro we’re so close to profitability bro, just need this IPO to secure funding one last time bro then we’ll be profitable bro I swear.
What is the actual “cost” after they buy the hardware, is that $1000 really pure power usage cost?
I’m curious as well. My knowledge is probably quite outdated, but from what I understood the training part is what’s expensive and then querying the model is pretty cheap. Is it still true (or was it ever) that the generated answers on search engines are cheaper to generate than the actual search results?
I find that hard to believe, I recently had to uninstall co-pilot after it weaseled its way into my search bar. Its not an exageration to say that my PC literally ran cyberpunk 2077 with pathtracting better than it ran the fucking windows search bar with co-pilot.
It is sorta. Training is orders of magnitudes more intensive than inference, but we infer billions of times within a model generation.
that’s the $84,000 question. They’re filling datacenters with the fastest possible equipment and need it to be 10x faster, That hardware is dinosaur fodder a year after they install it.
AI Bubble burst coming sooner?
Oh come on bubble, why won’t you crash already?
That’s not good business
