Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

AI is slowing down

wheresyoured.at

Post reply on HN
Print view View original

761–770 of 820 posts

Re: AI is slowing down

#761

Post by emil-lp »

simianwords wrote: post #710
emil-lp wrote: post #665

Earlier quoted context omitted.

Since you couldn't answer, I asked ChatGPT. It said: upfront investment: $3M to $6M. Customers should pay $25k per month. Checks out

I pasted everything you wrote and ChatGPT said >The "$25k per month" figure is almost certainly the result of ChatGPT making assumptions, not a fact derived from any known business model. https://chatgpt.com/share/6a28193b-6ec0-8333-a1af-d07e8d89ef... Your whole calculation is also ridiculous - I think you assumed what revenue per month is required to pay off hardware within a year? Why would I use hardware within a…

I reran the numbers, break even after four years. 10k users.

Minimum upfront: about $15M

Comfortable upfront: $20M–$25M

Monthly revenue needed: $900k–$1.5M

Required price per 10k individual customers: $99–$149/month

API-equivalent output price: usually $8–$20/M output tokens, unless utilization is very high.

Re: AI is slowing down

#762

Post by spmurrayzzz »

dofm wrote: post #264
spmurrayzzz wrote: post #82

Earlier quoted context omitted.

He has also consistently demonstrated, at least to me, that he doesn't really understand how inference works from a technical perspective, which weakens much of his core thesis for why there should be a collapse. I do value having some naysayers in the mix generally, because we do need balanced critique in what is otherwise a very frothy hype cycle. I just don't think he's making sound arguments, and that's even assu…

> That directly undermines his claim that providers always need to chase frontier intelligence in order to maintain current demand, utilization, and pricing curves. But does it also not mean that they will make less money given that there is already brutal competition for that lower tier from openrouter, Deepseek, Amazon, etc.? You can't on the one hand say "customers are beginning to understand they can spend less"…

> You can't on the one hand say "customers are beginning to understand they can spend less" and on the other hand suggest that this is good for forecasts of revenue.

Sure you can. Just because there is a non-zero amount of margin pressure from the lower tier inference providers does not imply that revenue forecasts ought to be poor. Jevon's Paradox gets oversold in this current cycle, but I do think it's a relevant lens to view this through given how much demand has outpaced capacity.

The argument is that customers learning to spend less per task can be good for the viability of the market (really the total demand) even if it is bad for naive revenue-per-token assumptions. If a workflow goes from economically stupid to economically viable because you route 80% of it to cheaper models and reserve frontier models for the hard cases, that can expand total usage and improve cost per useful outcome.

Re: AI is slowing down

#763

Post by ordinarily »

graphime wrote: post #719
ordinarily wrote: post #511

Earlier quoted context omitted.

Google literally invented the boat (transformers) to be fair.

> Google literally invented the boat (transformers) to be fair. Isn’t that more damming for Google? Invent the boat, don’t know how to use it, abandon it, then someone else comes along and steals your boat.

I think most of Google's deep research projects were done in the pursuit of pure science, not monetization or productization. In hindsight sure, it looks like they missed an opportunity. But not everything needs to be about money.

Re: AI is slowing down

#764

Post by butlike »

jorisw wrote: post #645
dgellow wrote: post #612

Earlier quoted context omitted.

Can we stop spreading the obvious bullshit that is space compute?

Care to at least refer to some sources why?

It's literally a deflection mechanism to the fact they want to build data centers all over the land by proposing a fantastical better way that simply won't work.

Re: AI is slowing down

#765

Post by emil-lp »

emil-lp wrote: post #761
simianwords wrote: post #710

Earlier quoted context omitted.

I pasted everything you wrote and ChatGPT said >The "$25k per month" figure is almost certainly the result of ChatGPT making assumptions, not a fact derived from any known business model. https://chatgpt.com/share/6a28193b-6ec0-8333-a1af-d07e8d89ef... Your whole calculation is also ridiculous - I think you assumed what revenue per month is required to pay off hardware within a year? Why would I use hardware within a…

I reran the numbers, break even after four years. 10k users. Minimum upfront: about $15M Comfortable upfront: $20M–$25M Monthly revenue needed: $900k–$1.5M Required price per 10k individual customers: $99–$149/month API-equivalent output price: usually $8–$20/M output tokens, unless utilization is very high.

[flagged]

Re: AI is slowing down

#766

Post by andrewflnr »

Aerolfos wrote: post #597
barrell wrote: post #539

Earlier quoted context omitted.

I do think Ed in intentionally ignorant of the capabilities of LLMs. But I also don't know that I would classify LLMs as 'wildly useful' for coding. Most productivity gains seem to be hallucinated, and while it's too early to make any claims on long term outcomes, there are plenty of studies indicating they might be even more negative. There are definitely use cases for LLMs in coding. And at times , they can be wild…

> I do think Ed in intentionally ignorant of the capabilities of LLMs. I think it's more complicated than that too. He's pretty well versed in the stated capabilities of LLMs. The fact that he isn't a deeply involved technical developer who knows the ins and outs and nuances of using LLM tools is the point , because the stated capabilities of LLMs are that they are trivial to use, extremely powerful, and getting so m…

One person's ignorance of something can never be evidence that it doesn't exist. It's far too easy to be willfully ignorant; no one can force you to abandon ignorance if you don't want to.

On the other hand, the hype of "Sam Altman and his like" being plainly exaggerated doesn't mean there's nothing at all behind it. It's plain to see there's something important about LLM capabilities. I don't even use them myself, as emotionally I find them entirely repugnant, and I can still see that.

We need to wait to get the whole story about LLMs, but we don't need to wait to confidently reject both extremes of opinion about them.

Re: AI is slowing down

#767

Post by spmurrayzzz »

beepbooptheory wrote: post #417
spmurrayzzz wrote: post #128

Earlier quoted context omitted.

There is a piece of this I agree with. That you do not need to be a deep technical expert to notice that a company is burning cash by overcommitting to capex, or relying on heroic revenue projections that may or may not come to pass. But that is not the full argument he is making. If the claim is that the labs will not be able to pay their creditors because inference is structurally incapable of becoming profitable,…

Doesn't this kinda imply its own smoke and mirrors though? Like if the name of the game with inference is already routing things around and caching so you can make money, why is the newest biggest model always the most important critical thing? How does this square with any of their press about it? Also wouldn't that just add more inference? Because you need to pre-judge every prompt to know where to route it? Also,…

I don't think its smoke and mirrors, though I do have plenty of gripes with how the labs market this product landscape generally speaking.

The newest biggest model can still matter even if you do not run every prompt through it. You'll always have some task where even small amounts of loss are unacceptable and thus you need to make sure frontier intelligence is used for it.

On the router point, yes, routing has some overhead. But the router does not need to run the biggest model to decide which model to use. We've been using tiny classifiers for recommendation engines for ages now, usually on CPU. If routing saves you from sending a large fraction of traffic to the expensive reasoning model, the routing overhead can easily be worth it.

> Also, if there is significant gains from caching, then like.. what are even doing here? Inputting something and then reading cached pieces of text based on their similarity to the input? Kinda like a search engine?

The caching I'm talking about is explicitly the attention/kv cache, so its not input similarity retrieval (that would be more like what you'd use in a RAG/IR system). Prompt caching is generally about reusing already-computed attention scores for repeated prompt prefixes. The idea being you don't recompute the same static system prompt, tool definitions, schemas, long shared context, or repeated boilerplate every time. In more sophisticated systems, you usually store multiple checkpoints so that a small prompt change doesn't result in all-or-nothing hit/miss scenario.

Re: AI is slowing down

#768

Post by 1attice »

dofm wrote: post #731
1attice wrote: post #708

Earlier quoted context omitted.

Think back. Has there ever been a time when you were both correct and angry? Would an angry Pythagoras' theorem be wrong, simply by virtue of his anger?

He was a bit bonkers anyway. But maybe: The square of the hypotenuse — you multiply it by its bleedin' self — is LITERALLY equal to the sum of the squares of the other two sides. Again. Multiply each of the other sides BY THEMSELVES, and then add them together. It's that bleedin' simple Jim Cramer could do it. That number is the same as the square of the hypotenuse, no matter what idiot CEOs think.

...and as horrible as that writing is, Pythagoras would have still been telling you a true thing.

So too, Zitron?

Re: AI is slowing down

#769

Post by morningsam »

crakhamster01 wrote: post #501
simonw wrote: post #132

Ed's argument for why "AI is slowing down" rests on company spending caps, in particular the Uber $1,500/engineer/tool cap. I interpret the exact same evidence in the opposite direction. A year ago the idea that a company would spend $1,500/month/employee on AI tooling felt absurd, what could people possible want to do with AI that would cost that much? Then coding agents (and, increasingly, general purpose agents) h…

I don't really understand how engineers at Uber are hitting $1500/month. Are they forced to pay API costs? My company provides employees with API keys and soft limits, but as soon as you approach ~$400/month they ask that you get a Claude/Codex Max subscription instead. Curious if it's not the same case at Uber.

>but as soon as you approach ~$400/month they ask that you get a Claude/Codex Max subscription instead

While this seems to be allowed because the current ToS don't seem to explicitly forbid it, I'd be surprised if this loophole stayed open for long... Why would they even distinguish between business and (much cheaper) individual plans if companies can work around it by telling employees to just pay for the latter themselves?

Re: AI is slowing down

#770

Post by simianwords »

emil-lp wrote: post #761
simianwords wrote: post #710

Earlier quoted context omitted.

I pasted everything you wrote and ChatGPT said >The "$25k per month" figure is almost certainly the result of ChatGPT making assumptions, not a fact derived from any known business model. https://chatgpt.com/share/6a28193b-6ec0-8333-a1af-d07e8d89ef... Your whole calculation is also ridiculous - I think you assumed what revenue per month is required to pay off hardware within a year? Why would I use hardware within a…

I reran the numbers, break even after four years. 10k users. Minimum upfront: about $15M Comfortable upfront: $20M–$25M Monthly revenue needed: $900k–$1.5M Required price per 10k individual customers: $99–$149/month API-equivalent output price: usually $8–$20/M output tokens, unless utilization is very high.

dawg -- what is your point? please write your statement clearly and we can discuss.
Post reply on HN