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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

#671

Post by solomatov »

aspenmartin wrote: post #647
solomatov wrote: post #613

Earlier quoted context omitted.

>For coding you always want to go with the best model in the category, not something that would be the best model if we went 1 year back which GLM 5.1 is, and I'm saying that as a big fan of GLM cause I run a translation site where GLM is good enough for the price. Currently, the difference is substantial, but what happens if capabilities saturate?

Then the house of cards comes crumbling down, but there is so much evidence to point to this not happening that it requires a bit of a theory for how that may happen

> but there is so much evidence to point to this not happening

Could you explain this?

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

#672

Post by lmm »

golem14 wrote: post #324
Tuna-Fish wrote: post #248

Earlier quoted context omitted.

Why on earth would AI labs be bragging about how little the product they sell actually costs them to make? You don't want to do anything that reduces it's perceived value to the user, that might make them less willing to pay for it. Also, inference costs are bound to go way down with more optimized architectures. GPUs are fundamentally not great at inference. No platform where the weights are streamed from a large po…

Why would any company brag about their margins ? Yet they do, to attract investors.

Growing companies don't brag about their margins, they brag about their growth and revenue. Margin talk is for when you're a mature company squeezing out every bit of profitability you can - if anything it would be a negative sign to be worrying about your margins when you're supposed to still be growing and innovating.

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

#674

Post by neuronexmachina »

materielle wrote: post #211
whatshisface wrote: post #173

Earlier quoted context omitted.

Here are a few thoughts: - The publicly available information about how inference costs compare to training costs is conflicted. EEs involved in datacenters talk about power usage spikes during training runs as if they were a major factor in the designs, but academic papers discussing cost-optimal scaling confidently treat inference-time compute as a major factor. - On the side of the balance indicating that training…

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…

> If AI labs saw a lot of potential there, they'd surely be bragging about it non-stop?

Google seems to pretty regularly post about how their TPU and algorithm advancements have been decreasing energy costs for both inference and training.

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

#675

Post by lmm »

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…

> it turned out that people claimed they were going to watch films 10-12 hours a day, every day of the week. Impossible.

And what happened? How many hours per day/week are people spending watching now?

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

#676

Post by bakies »

ex-aws-dude wrote: post #376
peder wrote: post #102

Earlier quoted context omitted.

> I don't see the business model working. Same. It's a nightmare from a Porter's Five Forces perspective. There will be a ton of businesses competing in this space, and there will be something of a moat due to how capital intensive the business can be, but there will still basically be infinite competitors. Great for consumers.

Well in reality AWS will just host one of them and most companies will use that Like how snapchat kind of fell off because the feature could just be a subset of instagram It seems like it would just become a commodity like EC2

Snapchat is huge and growing

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

#677

Post by supern0va »

overgard wrote: post #485
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…

Ed actually provides sources and goes into an incredible amount of detail as to how he came to his conclusions. The average AI booster just goes "I totally built ten businesses off vibe coding but I can't tell you anything because it's a SECRET!". And the mainstream tech media is so in the pocket of big tech and AI corporations that they might as well just publish their PR emails at this point. Yeah, I'll listen to E…

Ed actually seems to make some really serious errors in his work. Tim Lee called out a particularly egregious one here, though it's one of many: https://x.com/binarybits/status/2050562429709377986

That said, I really mean it when I say that I don't actually think Ed is a good choice for the anti-AI movement. I think an actual opposition is useful, but he ain't it.

I really recommend you read the Wired profile if you haven't yet and form your own opinion: https://www.wired.com/story/ai-pr-ed-zitron-profile/

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

#678

Post by majormajor »

simplyluke wrote: post #366
doug_durham wrote: post #356

Earlier quoted context omitted.

Open source models that you can run locally are much more than 3 to 6 months behind. 6 months was the November inflection for Claude. No open source model is as good as Claude Opus 4.6.

> that you can run locally That's doing a lot of work here. The future I see isn't most companies buying hundreds of thousands in hardware to run models, it's them adding a line item to their AWS bill. Inference costs on the larger hosted open source models are dramatically lower than the frontier labs API pricing.

Buying "hundreds of thousands in hardware" sounds like a lot but many companies - especially software companies - already do that if they have 100+ employees.

Running software in the cloud gives you certain reliability and scaling advantages that would be very hard to replicate locally. Running some code agents in the cloud vs local hardware, if the local hardware gets "good enough," breaks the other way - offline usage, alone, would be hugely valuable to many people and companies.

It'd be very interesting to see where various players would decide to make a call "local is good enough" though. Buying the hardware isn't a small bet, if it's not something that ends up as part of your standard computer.

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

#680

Post by raincole »

The article is at least one year too late. Claude Code has been the product-market fit. It's so obvious retrospectively that questioning it at this point would be very silly.

The problem is not whether they have PMF (they do) but how they're going to compete against on-prem and Chinese providers.

Having PMF != printing money forever.

The author claim:

> That’s $2,180.16 worth of tokens for $200

No matter what it means, rebuild the same thing you built with these $2,000 tokens with DeepSeek Pro V4 and let's see if Claude has a chance to survive.

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