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I think Anthropic and OpenAI have found product-market fit

simonwillison.net

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Re: I think Anthropic and OpenAI have found product-market fit

#441

Post by j-bos »

alexpotato wrote: post #377
trjordan wrote: post #11

They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. That's a _huge_ shift. Most people…

I was in college in the late 1990s/early 2000s and I distinctly remember an econometrics professor state the following: "As cable TV and Pay Per View came out, there were studies done about how many movies people would watch if given unlimited access to films. The results were bandied about as proof that we should build out all this infrastructure to support this line of business. When the data was further analyzed b…

But isn't it wonderful that they did?

Re: I think Anthropic and OpenAI have found product-market fit

#442

Post by disiplus »

FuriouslyAdrift wrote: post #246
trjordan wrote: post #11

They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. That's a _huge_ shift. Most people…

I work for a tiny little company ($150MM annual rev with 9% net) and we are already looking at dropping $100k on hardware to run local models because, for us, they're "good enough." Our estimated spend for AIaaS would exceed that cost in less than a year. In a few years, there will be hardware capable of running frontier models good enough for most things at accessible prices for even tiny companies.

same, but you need more then 100k of hw to run something like kimi k2.6 for a bigger team. on the other hand there is a ds4 flash that you can run on a macbook with 128gb ram. an that one is perfectly usable for a lot of tasks.

https://github.com/antirez/ds4

Re: I think Anthropic and OpenAI have found product-market fit

#443

Post by thesz »

whatshisface wrote: post #227
materielle wrote: post #211

Earlier quoted context omitted.

I'm about to leave a shallow comment, but I am a bit skeptical of the supposed drop in inference costs. If AI labs saw a lot of potential there, they'd surely be bragging about it non-stop? So the fact that publicly available information is conflicted is probably a sign that at the very least, the numbers aren't amazing. Yes I know there's no evidence and this is lazy reasoning. But there's probably a bit of truth to…

Inference has traditionally been far less expensive than training. One public example is the fact that hobbyists can run StableDiffusion ($600k training costs[1]) on their personal computers. Speaking to your point, inference being dramatically less costly than training would not be seen as a delta from the norm. The model of providing inference for anything near the operational costs (like a utility would), would th…

The difference between training and inference is 1) one have to keep intermediate results for backward pass in training and 2) computation for training double because of the backward pass.

Training is also done over batches, which increase memory requirements by several orders of magnitude. This is why training needs costly compute.

One of the ways out of this unfortunate situation is to use something like Stochastic Average Gradient Descent [1]. Examples there are mostly concerned with regularized logistic regression, which makes problem more or less convex. Neural networks are inherently non-convex. Still, maybe some ideas from there can be utilized in the context of neural networks, like use of estimated Lipshitz constant to derive curvature and appropriate learning step.

  [1] https://www.cs.ubc.ca/~schmidtm/Courses/540-W19/L12.pdf

Re: I think Anthropic and OpenAI have found product-market fit

#444

Post by aspenmartin »

hansmayer wrote: post #325
supern0va wrote: post #278

Earlier quoted context omitted.

>according to Ed Zitron So, unsourced vibes from a shady guy whose entire empire is built on being against AI? I genuinely don't know how folks can continuously buy into anything he has to say after that Wired piece. The credibility there is seriously lacking. Please, continue to be skeptical of the labs. But people need to stop talking about this dude as if he's the Holy Grail of the anti-AI movement. It's going to…

> So, unsourced vibes from a shady guy whose entire empire is built on being against AI? Actually he provides sources when he analyses stuff and imho much better than the usual corporate "Sam Altman says we should ask ChatGPT how to raise babies" crap. Also, I don't know many 'shady' guys who have built entire "empires", nor does he seem to actually have an empire. Usually being shady means you are kind of unknown an…

[dead]

Re: I think Anthropic and OpenAI have found product-market fit

#445

Post by cmiles8 »

Article doesn’t mention on-prem and on device models. Almost guaranteed that there are a range of killer enhancements on these fronts waiting to drop until IPOs get closer to inflict maximum chaos on the valuation games.

While the big guys will argue they’re worth trillions expect others to drop chaos booms showing their NPV may be effectively zero.

Re: I think Anthropic and OpenAI have found product-market fit

#446

Post by altruios »

NitpickLawyer wrote: post #58
altruios wrote: post #42

Earlier quoted context omitted.

> If I had been paying API pricing it would have been $2,180.16 The point being made above is that API pricing is calculated... somehow... seemingly arbitrarily. Possibly untethered to the infrastructure costs entirely: which would be the basis of any 'value', however that holds the labor theory of value, which isn't accurate either. So how do you accurately price these tokens at all (other than through price-discove…

> So how do you accurately price these tokens at all Like anything else in the economy: at the point where enough customers can pay you, and not enough will go to the cheaper competition.

> at the point where enough customers can pay you

> (other than through price-discovery: which is slow, messy and fuzzy)

I notice a distinct lack of reading or comprehension (from everyone around me now, not just this comment) which worries me. I worry if LLM's are to blame. No one reads anymore...

Re: I think Anthropic and OpenAI have found product-market fit

#447

Post by thesparks »

trjordan wrote: post #11

They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. That's a _huge_ shift. Most people…

Those are rookie numbers. We are going to blow past $1t per year in spending in no time. As a developer for 29 years, I couldn't go back to coding by hand. For better or worse, AI will be woven into the fabric of life in no time.

Re: I think Anthropic and OpenAI have found product-market fit

#448

Post by conradkay »

pzo wrote: post #181

> If you are a heavy user of coding agents these plans are a fantastic deal. I just ran the ccusage tool on my laptop to get an estimate of how much I would have spent if I were to pay for API tokens in the past 30 days and got You think this is fantastic deal only because they use similar like tricks where they inflate the price and tell you something supposed to cost $1000 but they have this today promo for $100. I…

GPT 5.5 is maybe 4x the size of v4 pro, hard to compare price since cache hit is basically free with Deepseek, but 40x cheaper (with their 75% off) seems about right.

So ballpark same price per parameter as Simon.

Re: I think Anthropic and OpenAI have found product-market fit

#449

Post by asdff »

roncesvalles wrote: post #226
cogman10 wrote: post #167

Earlier quoted context omitted.

This is the same argument that has been historically made for outsourcing developers. Get 20 more devs for the cost of 1 dev in the US. I suspect that AI will fail to pan out to the same extent for the same reason why outsourcing hasn't fully panned out (even though every company tries it after getting big enough). The problems that will come up will be and always have been ongoing maintenance. AI is great at writing…

Outsourcing of knowledge workers didn't work out because at large enough scales, the geographic arbitrage disappeared. Companies mostly always got what they paid for. The determinant of success was only whether the task needed American-tier labor or could make do with sub-American quality labor.

Outsourcing of knowledge workers is still ramping up. The issue in the past was the skills were few and far between internationally. Facilities were also not built. That has changed now in a lot of fields. New campuses have been built in places like Bangalore and Hyderabad, even Singapore. The skills are there now, the training is decent, and you can see that the hiring is going on for very skilled titles in these cities. It is a different animal than just 10 years ago in this.

Re: I think Anthropic and OpenAI have found product-market fit

#450

Post by [deleted] »

FuriouslyAdrift wrote: post #246
trjordan wrote: post #11

They've got, ballpark, $5t to $10t to make back in the next 5 years, or the hardware buildouts will start getting written down. This means we're going to need $1t+ per year in spending, per year, on tokens. 200m knowledge workers in the world, 30m developers. We're talking about a world where you need 5% of every knowledge workers salary to go into tokens. 20% if you're a developer. That's a _huge_ shift. Most people…

I work for a tiny little company ($150MM annual rev with 9% net) and we are already looking at dropping $100k on hardware to run local models because, for us, they're "good enough." Our estimated spend for AIaaS would exceed that cost in less than a year. In a few years, there will be hardware capable of running frontier models good enough for most things at accessible prices for even tiny companies.

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