Some report burning through their whole monthly "AI credit" allotment in a single day.
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Give me a source of how training costs decreases 10x YoY that's NOT from a private company.Everyone on earth is pricing in 10x YoY cost decreases, and even using a model 6 months behind frontier (minimax) yields even greater savings than that, so it’s truly insane to see people not aggressively leaning into the curve.
Once a model, or a software program, is open source, and people start using the software and creating forks, I never seen the software program "fade away". At worst it just goes on archive.orgBy no one sharing them online anymore?
But they will be able to go "somewhere else", just not necessarily a blue-chip or premium service. Whether that ultimately winds up suiting their purposes will vary from user to user, and from budget to budget. I looked at the Hugging Face site yesterday and there are a LOT of choices for LLMs out there.Prices are going to go up everywhere - and keep going up - so users that think "going somewhere else" is an option are in for a surprise.
Doesn't mean the technology is going away. But people aren't going to use these things as readily as they do now once the massive subsidies go away.
I do have to point out that you not being aware of it doesn't mean it has never happened.Once a model, or a software program, is open source, and people start using the software and creating forks, I never seen the software program "fade away". At worst it just goes on archive.org
If I'm understanding @Madestjohn correctly, he's worried that the free model clearing houses will be pushed offline by the big houses in order to force people to subscribe to their UBB hell products.Have you ever been to Hugging Face? You can find the original OSS-20b model at https://huggingface.co/openai/gpt-oss-20b . Because it's free and open source, people take the model, and create their own versions of it.
I have never seen an active open source project that was pulled off line like that. Can you provide a link to one?
Yeah.That's nothing really new though. Ed Zitron calls them business idiots (though I think he got that term from somewhere else). The business world is filled with them. Especially at larger companies where size and momentum can paper over a lot of incompetence.
The fact it took so long for phone providers to switch to an unlimited amount of texts, despite the fact it never actually cost, as much as they charged their customers for a single text SMS was never originally designed for text messaging. There were actual costs to sending text messages on the older networks.The technology used for SMS/ text messaging is completely differently, and prices can be reduced. I can not see how pricing can be reduced for complex LLM usage. Can you explain how cost can be lowered using actual examples with sources?
Plumbers and electricians will support the economy.The issue still stands. If all the meat bags are unemployed then there are no customers to buy whatever widgets companies produce. Worse still the level of benefits governments now need to pay all the unemployed can't be covered by PAYE and the like so company tax will need to rise to support all the unemployed. Companies will be paying a huge tax bill to support meatbags they do not employ and will have no customers as the meatbags are too poor to buy their stuff.
Looks a somewhat sub optimal situation tbh
No. They are running on insane, eye watering, jumping off skyscrapers level of loss. And best thing? The costs scale. The more users the higher the costs per user.The million (billion? trillion???) dollar question is how much does it actually cost to run these models. I think companies like Anthropic and OpenAI earn a big profit on customers who pay per token. I'm looking forward to their IPOs so that I can see how their finances really look like.
"please downvote this into oblivion"Everyone seems to be focusing on raw scaling and yeah, with current transformer architectures maybe we have hit a wall in terms of data and horsepower. But scaling is not the only way technologies improve and I don’t believe we’re already at the end of improvement, that what’s been achieved in the last ~5 years is the end of AI development.
But I’m not going to continue discussion only for my posts to be hidden simply due to being unpopular so whatevs, believe what you will.
(please downvote this into oblivion too as I only want those of you who would do so to read it)
Hugging Face is VC-backed to the tune of several hundred million dollars as well as an undisclosed amount from Amazon and Meta. It’s revenue is in the tens of millions of dollars i.e. it’s incredibly unprofitable. Model weights run from tens to hundreds of gigabytes per download. Serving that amount of data is expensive. Some guy with a patreon isn’t going to be able to host these models if the big boys decide they don’t want to share any more.But they will be able to go "somewhere else", just not necessarily a blue-chip or premium service. Whether that ultimately winds up suiting their purposes will vary from user to user, and from budget to budget. I looked at the Hugging Face site yesterday and there are a LOT of choices for LLMs out there.
Have you used a Chatbot Frontend like Jan or GPT4All before (or went directly to Hugging Face)? If you haven't, check it out, and then go to the models section. People take the open source models, and since they are open source, modify them.I wouldn't be surprised if the free models don't migrate in a similar way. And if that's the case, I definitely won't be surprised if "guerilla" model training becomes a thing.
What about GitHub? What about Archive.org?Some guy with a patreon isn’t going to be able to host these models if the big boys decide they don’t want to share any more.
The transition from mostly-expensive to mostly-unlimited texting was a while ago, though. This “reverse” thing is just the modern startup model. Everything is sold at a loss initially to get network effects and hype. It’s really weird, it seems like an huge chunk of the tech sector orbits around this “anti-competitive pricing as a service.”The fact it took so long for phone providers to switch to an unlimited amount of texts, despite the fact it never actually cost, as much as they charged their customers for a single text SMS was never originally designed for text messaging. There were actual costs to sending text messages on the older networks.
With AI it seems we had the reverse happen, the real costs were hidden to us, and were first given the "unlimited' option only to discover that paying per text message is the future.
I'm here to learn. Can you please provide an example of an open source program, that's been forked, and used by at least 100K people, that was fully shut down and can't be downloaded from another site?I do have to point out that you not being aware of it doesn't mean it has never happened.
So, the AI providers. Because without cheap tokens, there aren't customers.I really don't think this is a sign of a bubble popping. (Well, not for the AI providers, but maybe some businesses that depended on cheap tokens.)
There's a ton of demand at a highly subsidized price. There's no evidence that demand will continue at the actual price.It shows that there is actually a ton of demand for AI workloads
You mean the ones actually using it., enough that they can afford to fire their worst customers.
Will they? Because the only way this works for the AI companies is that the people left, who are paying, don't use it.The ones who are left will be getting actual value for their money.
And that's why they shouldn't be allowed to be built.I thought they were going to have to make like those bitcoin miners in Texas who make money by not mining. These massive datacenters could hold the power grid, water supplies, and the climate hostage for cash.
Complaining about down votes is the surest way to farm down votes.Everyone seems to be focusing on raw scaling and yeah, with current transformer architectures maybe we have hit a wall in terms of data and horsepower. But scaling is not the only way technologies improve and I don’t believe we’re already at the end of improvement, that what’s been achieved in the last ~5 years is the end of AI development.
But I’m not going to continue discussion only for my posts to be hidden simply due to being unpopular so whatevs, believe what you will.
(please downvote this into oblivion too as I only want those of you who would do so to read it)
One of the main differences between OpenAI et.al and Nintendo is that Nintendo never made a software program that was under an open source license. For example, Super Mario Brothers is close source, and the code and copyright is completely owned by Nintendo. OpenAI's GPT-OSS-20b model is under Apache 2.0 license, allowing ANYONE to share, modify, distribute, and sellI wouldn't be surprised if the free models don't migrate in a similar way. And if that's the case, I definitely won't be surprised if "guerilla" model training becomes a thing.
I worked at Motorola in the early 90s. I still remember my phone plan - $0.11 a minute. That was it. There was no SMS in the early days.This reminds me of the pricing scheme of SMS/text messaging in the nascent cell-phone days.
No. Stop fucking handwaving this away, and be specific about how it's going to get better. 3DTV was a hot technology, and tell me how that's gotten better in the past few years?It's just the way fundamental technologies go. I would rather ask what could stop it.
Where are they going to get that from?I have no crystal ball but more data
Where are those going to be put?, more and faster training and inference hardware and techniques
Like what, exactly?new types of models and architectures
Again, there is literally nothing inherent about this stuff that says it has to keep getting better.There are millions of people using it and thinking about how to make it better. It will get better.
They are not. They have been around for quite some time. Stop using that excuse.In tech time LLMs are brand new, we're just scratching the surface.
What purpose are people using LLMs?a two-year old LLM is no practical use to anyone.
That chance never existed, based on the way these things work.Right at the start of the AI coding “revolution” there was a sliver of a chance that LLMs could be taught to write optimised machine code and unlock the wasted potential of everyone’s existing hardware, with all of the attendant gains in UX and energy saving.
Instead, we have a bunch of ludicrously expensive server racks churning out tens of thousands of lines per day of plagiarised javascript.
Again with the handwaving. You have an almost religious faith that someone will rescue you. It is just as likely that there is no way this technology gets to a state where it's cost effective.Everyone seems to be focusing on raw scaling and yeah, with current transformer architectures maybe we have hit a wall in terms of data and horsepower. But scaling is not the only way technologies improve and I don’t believe we’re already at the end of improvement, that what’s been achieved in the last ~5 years is the end of AI development.
But I’m not going to continue discussion only for my posts to be hidden simply due to being unpopular so whatevs, believe what you will.
(please downvote this into oblivion too as I only want those of you who would do so to read it)
I'm here to learn. I provide links to why I think how I think. If what you're saying is true, those links should be easy to find.But I’m not going to continue discussion only for my posts to be hidden simply due to being unpopular so whatevs, believe what you will.
I actually wonder if this is Microsoft's way of throwing a wrench into the IPOs or trying to get a cheaper price for itself.God forbid people realize the cost of the thing they've been using. This was, of course, inevitable.
All that VC / hyperscaler money that had been getting burnt on customer acquisition and experimenting was going to demand ROI at some point.. and that point is now.
2026: The year the AI bill came due.
It turns out you can't run a massive cash burn hopes-and-dreams machine forever without consequences. It's no small coincidence that that OpenAI / Anthropic are rushing to IPO before the costs catch up with everyone waking up to the real costs of the LLMs.
How does this website pump the AI hype train?and outlets like this have been ignoring them and relentlessly pumping the AI hype train
This.One of the main differences between OpenAI et.al and Nintendo is that Nintendo never made a software program that was under an open source license. For example, Super Mario Brothers is close source, and the code and copyright is completely owned by Nintendo. OpenAI's GPT-OSS-20b model is under Apache 2.0 license, allowing ANYONE to share, modify, distribute, and sellO) the software.
So OpenAI can pull GPT-OSS-20b (and other models) off from Hugging Face, but if Github or Archive.org or a random website wants to host it, they have no legal standing to stop it.
There are have been a bunch of positive or uncritical AI articles and at least a couple of the authors here are a least somewhat AI enthusiasts. But they've also hosted a ton of AI critical articles, so I'd say they are at most neutral? There certainly is not an AI overlord in the management team demanding more AI positive articles to "relentlessly" hype it up.How does this website pump the AI hype train?
that kind of subsidized customer acquisition may soon give way to Copilot-style usage-based pricing across the industry
Best reply of the whole bunch! Well played sir! Well Played! You win post of the day!One person can do the work of three people, for the cost of four! By Grabthar's Hammer, what a savings.
Exactly! Let's say the worst thing happens and the AI companies pull the models from Hugging Face, and send threatening letters to GitHub, Archive.org, et.al. There are peer-to-peer websitesDoom: Eternal is bigger than any of the models I run. And it’s illegal to distribute on top of that. And still, I have the sneaking suspicion I could find a cracked copy if I really wanted to.
I never seen agents that were able to do work. Please provide a source of agents that can do work, correctly, and a more efficient method can't be used.Before there were no agents doing actual work, and now there are.