[dead]
How the AI Bubble Bursts
311–320 of 557 posts
Re: How the AI Bubble Bursts
#312Earlier quoted context omitted.
Companies doing foundational models need to cover the cost of training which is much more expensive than training something like kimi.
>Companies doing foundational models need to cover the cost of training [...] But that's moving the goalposts? The original claim was on inference itself, not the whole company. > The cost to serve tokens is absolutely profitable today and that’s been true for at least a year.
But that's the same as thinking "This bar is selling a cocktail for $15. I could make it at home for 30 cents. They're making $14.7 dollars of profit per cocktail, the owner must be a millionaire now!"
Everything is profitable if you ignore the costs.
Re: How the AI Bubble Bursts
#313From the beginning of this I’ve wondered the same question: how do these companies justify spending such massive amounts now (and 3 or 4 years ago) when software and hardware efficiencies will bring down the cost dramatically fairly soon? They basically decided that scaling at any cost was the way to go. This only works as a strategy if efficiency can’t work, not if you simply haven’t tried. Otherwise, a few breakthr…
Because whoever wins the AI race (assuming they don't overshoot and trigger the hard takeoff scenario) becomes a living god. Everybody else becomes their slave, to be killed or exploited as they please. It's a risky gamble, but in the eyes of the participants the upside justifies it. If they don't go all in they're still exposed to all the downside risk but have no chance of winning. I don't expect hardware prices to…
Just to add some slight nuance but is an important distinction,
They aren't all necessarily racing to be "god", some are racing to make sure someone else is not "god".
If it weren't for Altman releasing ChatGPT, it's very likely that we would have markedly less powerful LLMs at our disposal right now. Deepmind and Anthropic were taking incredibly safe and conservative approaches towards transformers, but OAI broke the silent truce and forced a race.
Re: How the AI Bubble Bursts
#314Earlier quoted context omitted.
So these companies will be profitable if training stops? Is that even a real possibility?
The impetus to continue training at the pace they are is driven by the competition. So if the money starts drying up, then they’ll naturally slow down because they’ll have to figure out how to do more with less. I suspect that once the models hit a point of “good enough” for certain use cases companies will start putting R&D focus in other areas that may be less expensive. Like figuring out how to run more efficientl…
> So if the money starts drying up, then they’ll naturally slow down because they’ll have to figure out how to do more with less.
Meanwhile companies like Google will keep investing on training...
Anthropic's CEO has suggested all AI companies should slow down training but obviously this is only beneficial for companies that can't afford to keep training.
Re: How the AI Bubble Bursts
#315Earlier quoted context omitted.
> We create the very things that cause that to be the case! What happened in the 1970’s was the NeoLiberal shift and wasn’t caused by software.
That NeoLiberal shift did not take place in a vacuum. It was a product of the world around it. It absolutely was caused by tech. If we — those with the power to build the productivity creators — took a stand and said "we refuse to create tech for the interests of the few" it would have never happened. But, instead, we welcomed it and are responsible for it.
The corollary of “if we took a stand” is that Capital took a stand and collectively undid a lot of the gains of the post-WWII social democratic order.
So no. It wasn’t caused by tech beyond the uninteresting factors like modern society being complex and, of course, that tech developments influence things (pretty much all things).
Re: How the AI Bubble Bursts
#316Earlier quoted context omitted.
Jevons paradox only applies if demand hasnt already been saturated. The fact that public LLM usage is leveling off at a price of $0 and Jensen "we make the shovels in this gold rush" Huang is rather desperately claiming that you need to spend $250k/year in tokens to be taken seriously suggests that demand saturation may not be that far off. Whether Jevons' Paradox applies to software engineers I think is another open…
It is quite hard to imagine how the demand is saturated now. I think any company that uses a sliver of AI will happily increase their token consumption 100x if it's free.
Executive FOMO disease is being exploited by the model providers to push for maximal token usage even when it is pointless.
This includes encouraging people to set up elaborate multi model set ups (e.g. "gas town") for coding that do not meaningfully improve productivity but which certainly do cause token usage to explode.
It also includes encouraging execs to use token consumption as a proxy for productivity - almost akin to SLOC.
AI has a halo right now and the managerial class seem to be willing to forgive almost any failure because the promise is so enticing. We're at peak expectations right now. They will soon start to be less forgiving when the warts which are intrinsic to LLMs remain unsolved.
Re: How the AI Bubble Bursts
#317Earlier quoted context omitted.
I’m not disagreeing with you, but consumer RAM prices are lagging indicators. If commercial RAM prices are dropping then consumers will see those price drops last, especially given the fact that several consumer manufacturers turned to commercial only.
Is there a source that says commercial RAM prices are dropping? I was recently told (without a source, so I am not sure if it is true or not) that OpenAI never even bought any of the RAM they signed deals on last year, and that those deals were just letters of intent. So if prices are coming down I wouldn't be shocked but the economy is pretty well vibe coded these days so who even knows.
Well, all manufacturers of ram have publicly stated that they're sold out for 2026
RAM prices falling during 2026 is insanely unlikely unless AI crashes so hard it starts to actually kill companies. And not just any but big tech
I'm not seeing that in 2026. Maybe 2027 (I'd sincerely doubt that too, honestly), but definitely not within the next 9 months. Their runway is _way_ too large for things to spiral out of control within such a short period of time
Re: How the AI Bubble Bursts
#318Earlier quoted context omitted.
dotcom was maybe 100B a year focused on the US and mostly VCs. AI is perhaps 250B global VC (with more than half of ALL VCs concentrated in one sector) and another 800B+ from non-VC. These numbers are basically a guess but structurally we are set up for something much, much worse.
But unlike the dot com boom, demand for tokens has not let up and there is increasing demand. I don’t know where it falls, certainly companies don’t get or right and they either over or under build. With the current demand rate changes it’s hard to understand why you would stop building today.
Demands for tokens exists yes. On one side you have huge demand for the infinitely subsidized tokens so that people can post a "unique" illustration when posting on social media, along with the text itself even.
On the other end we have professionals happy to pay a subscription for heavier use, to build something in the hope to sell it.
I figured I don't believe in value when my dad explained to me his mate fired his team once he realised he could just pay 20 bucks for his Gemini account and run his business. I asked, do you call this value add? He said it must be, since he can produce the same output with no staff.
There is a confusion between profiting from a circumstance and value creation.
You create value if, say, you cure a disease. That it takes you an army of staff or extract maximum profit from it is just a feasibility formula.
That you make the cure more affordable is value creation.
That you cure the same disease but increase your profit doesn't create any value, except to yourself, for a while
Re: How the AI Bubble Bursts
#319Earlier quoted context omitted.
I created 5 websites this year and am working on 3 prototype games. For free. Without any knowledge of coding beforehand.
Value? There are millions of other wanna be engineers doing exactly the same, assuming demand will scale as much as the offer. What returns are you getting on those? Let me create 500 websites, deployed for free, I hand that over to you by end of day. Will you give me a cent per piece? If so, happy to do business with you.
The value is obviously to the people who will use this to replace engineers.
I would happily pay $200 a month for this. Luckily I dont need to, it's free.
Literally every game and website that I would have had to pay someone else to make I can now make myself. There's no value in that?
A year ago the best free LLM couldn't even give me a basic gridmap and collision. Now it can give me a full RCT style prototype & editor in 20 iterations.
I can only imagine what improvements we will have NEXT year!
Re: How the AI Bubble Bursts
#320Earlier quoted context omitted.
> The ads aren’t going into your paid plans (except maybe a highly discounted tier, depending on the market). The ads are a play to offer a free version. Having an ad-supported free tier isn’t new. Sounds like it is new for ChatGPT though. That's also how it started with TV and Youtube, first on the free tier then expanding to the paid ones.
YouTube, Spotify, and most video steamers have zero ads on paid tiers. I never see video ads.
Most services have now light premium-tiers, where they do show ads. And then there are the rats like Amazon, who just add them to the normal tiers, and offer an additional service to not show ads.