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I am not a CEO and I hope this AI bubble bursts already.
That said, if I were a CEO using all possible tokens while they are heavily subsidized and tightening the purse when they get more expensive does not sound like the worst strategy to me. You get all your teams to build some expertise and (hopefully) get a sense of where the technology might have some ROI.
If only they had presented it this way (and not “AI therefore layoffs”) probably a lot of us would hate it much less now.
@sanitation，提到的‘我们创造了一个怪物’，确实反映了AI工具在初期应用中的预算挑战。很多公司在评估AI的效用和成本时，发现问题在于如何平衡创新和开支。有时候，小范围试点可以帮助更好地了解工具价值。我们总结了一些实际应用场景，更多细节在这里 https://cxgo.ai/l/WCe7FjK。
It will only get much worse.
So the the test of capitalism is whether any of the executives who pushed the AI roll out have gotten fired or had their bonuses slashed… My guess is none of them.
If this were actually about competition, then people would be punished for not paying attention to all of the naysayers who predicted this exact phenomenon. If accountability were a key feature, then corporations would have set up their bonus structure to look for 5-year or 10-year benefits from the AI push because of this exact issue.
Of course we haven’t seen that anywhere because AI was and always is a bubble and everybody knew it and the only goal was short-term profits for whoever can claw them out of the employees or the minor shareholders fingers.
This, plus if we had any kind of political will or intelligence (as a nation; meaning the USA) we’d force AI companies to pay their extenalities: treat and sanitize every drop of water they use, and build the infrastructure to bring it back to communities; pay for their electrical infrastructure in advance and pay their electricity bills to the tune of “nobody else’s bill goes up”; some kind of massive carbon capture tax for their use (this one might not be possible to actually do; it’s too much); and of course paying royalties and copyright violation fines.
As at least one AI CEO has said, if they had to pay for all the laws they’ve broken and resources they’ve stolen, all AI companies currently existing would go out of business. let’s say they didn’t: The cost per token would be quite high, and very few people would use it.
It runs on theft and planet-scale destruction.
It runs on theft and planet-scale destruction.
You could argue that this is the very nature of capitalism: theft because it always means owners extracting value from other people’s work, and ultimately planet-scale destruction because it depends on infinite growth while externalizing (not paying for) the true costs of its activity.
In that sense, AI companies are just a faster-growing strain of the global cancer that is capitalism.
Reasonable take, but the last part (“faster-growing”) is huge here. The sheer scale and multipliers on the bad things caused by AI are far beyond most (all?) previous technologies used by capitalists.
As at least one AI CEO has said, if they had to pay for all the laws they’ve broken and resources they’ve stolen, all AI companies currently existing would go out of business.
I find those terms acceptable.
What’s the most expensive thing one can do with AI and how do we do it on a mass scale to one company at at time?
I know a company that burned $100k in tokens after they they let like 50 worker bees using general AI for OCR, simply converting images and PDFs to text.
They didn’t bother to create a skill, or teach the AI how to reuse a shared script so every request resulted in it writing a new python project, pulling libraries, using a frontier model rather than offloading a dumb one etc.
Basically find a business process that happens often and let em at it inefficiently, it’ll happily chew through the budget.
Thats pretty much what people freaked out about llms doing at my work and all they use it for. I’m here like…we have had OCR for over 20 years.
People are duuumb.
There has been some serious leaps in terms of quality. It couldn’t read human writing or half the fonts for that matter like 5 years ago, let alone 20.
OCR libraries have undoubtedly improved but LLMs are using the same open source libraries and tools available to anyone… there’s few cases where sending the work through general models is worth it for text conversion. Employees just needed a front end to upload, run something like tesseract behind the scenes, and spit out the result. It’s an egregiously stupid use of resources.
have undoubtedly improved but LLMs are using the same open source libraries and tools available to anyone…
I read a surprising article on Lemmy just a week ago that explained that that is not how LLM’s do OCR. LLM’s convert images into tokens and then treat them like text input. I can’t see how it works but it does. It’s why they are better than classic OCR neural nets but at the trade off of enormously larger computation cost.
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Maybe 16k image/video upscaling of super low quality shitposts?
File sizes are going to be huge! 2K is already a lot to upload, couldn’t imagine 16K right now.
Just expend some more compute time on doing compression and we’ll get those filesize numbers to a workable level.
$ stat -c %s enhance.png 276773 $ convert enhance.png enhance.avif $ identify enhance.avif enhance.avif AVIF 1164x558 1164x558+0+0 8-bit sRGB 14391B 0.000u 0:00.000 $ stat -c %s enhance.avif 14391 $
zoom and enhance
$ identify enhance2x.avif enhance2x.avif AVIF 2328x1120 2328x1120+0+0 8-bit sRGB 32448B 0.010u 0:00.000 $ stat -c %s enhance2x.avif 32448 $
zoom and enhance
$ identify enhance4x.avif enhance4x.avif AVIF 4656x2232 4656x2232+0+0 8-bit sRGB 50758B 0.000u 0:00.000 $ stat -c %s enhance4x.avif 50758 $
Okay, that last one took 17 minutes to upscale on my GPU, so I’m not going further. But I’m using SD Ultimate Upscale, which is tile-based, so in theory that could be farmed out over a collection of GPUs and parallelized. Just need more compute hardware.
But as to filesize, that’s under 50kiB.
Whoah! Nice effort! Yeah a cluster could cut the time down a lot.
Burn your AI tokens and get promoted for using more AI!
I sadly don’t find the GitHub repo with the bash script anymore, but that thing seems to do the same thing
(Maybe I’ve misread though, I’m just going to sleep)Edit: ha! Found it!
https://github.com/dtnewman/burn-baby-burnhave it end to end build a fully featured web browser that works on Windows, MacOS, and Linux from scratch.
Thus transferring their money to openAI, Anthropic etc? How does that help?
They actually lose money as well, because they’re proving those tokens at below cost price.
It’s all going to Nvidia
those companies arent profitable either and they have same problems in which it costs them more to run their products than they are currently charging people to use it.
What do you mean by either? Walmart and Amazon make tens of billions in profit a year if not a quarter.
i thought we were talking about OpenAI, antrhropic, etc, not Walmart?
Did you read the title? It says to spend Walmart and Amazon’s money on AI. And you said “those companies aren’t profitable either” which would mean, using normal rules of English grammar, that “Walmart and Amazon aren’t profitable and OpenAI and Anthropic aren’t profitable either”. So what are you talking about? What does “either” mean?
ooh I see. my bad. erase the word either from my comment, it wasn’t necessary.
More companies with less money is better than a few companies with all the money.
Ultimately distributed power has to be more democratic, and centralized power has to be more fascistic.
That’s part of why governments having large distributed bureaucracies each with their own authority and independent ability to intervene is better than say; a single executive office/president controlling everything directly.
Distribution also leads to stability though (making it harder to challenge the status quo), so it’s a double edged sword.
“The public really didn’t like it when we shoved AI down their throats. Whats the solution?” “How bout a lil’ ‘artificial scarcity?’”
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