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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

#991

Post by drumdance »

simplyluke wrote: post #305
FuriouslyAdrift wrote: post #246

Earlier quoted context omitted.

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.

Yeah, that's the part that just seems to be wildly under-discussed to me. If open source models are ~3-6 months behind SOTA, and ~opus4.6 capabilities are good-enough for product market fit, do the frontier labs have half a decade to catch up on their prior burn? AI cost ballooning faster than companies can afford is becoming a very common topic in my circles right now. The era of "I'll pay infinitely more for margin…

For give my naiveté, but who pays for the training of these models?

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

#992

Post by extraextra »

janalsncm wrote: post #471
vlovich123 wrote: post #405

Earlier quoted context omitted.

Small alternative potential future changes that alter this analysis: * At some point model capability reaches diminishing returns. Then inference >> training in the future but training >> inference now. It’s not a prisoner’s dilemma but a land grab to solidify market position and be one of the 2-3 firms left standing as dominant in the space. The model companies aren’t super sticky yet but they’re working on it. * ev…

The issue is that most tasks do not require frontier-level intelligence, but companies like OAI can really only profit off of the frontier. Capabilities from a year or two ago are so outdated that even OpenAI gives it away for free and there are many other models biting at their heels. In other words they are spending huge amounts of money to cash in on a depreciating asset. So one possible future is that frontier-le…

Once the land grab is over, the market will consolidate and the winners will absorb the losers. Then the few winners will be the only ones with real capital to train frontier models and will have true pricing power. Similar to how social media companies or the gig-economy benefits from network effects, AI companies will benefit from having the lion's share of paying customers (that also constantly feed in more data to train the models on).

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

#993

Post by extraextra »

stevenally wrote: post #649
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…

> If we don't even know the ratio between amortized capital expenses and operational costs, outside investor analysis is impossible. And yet we surely need this data for the IPO? Or are they relying on rule changes on the indexes to force ETFs to buy shares?

The IPOs are months away, potentially 6 months or more. We're in a volatile macro environment. AI companies have all the incentives to not create higher expectations regarding their financial situation a long time before the IPO. Obviously at IPO they will have to disclose their full financial situation.

The market is super hyped anyway for their IPOs. If they raise investors expectations now and things change until the IPO, investors will be disappointed. It's a lose-lose proposition.

The smart play for any company is to keep their cards close to their chest until close to the IPO time.

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

#994

Post by extraextra »

somewhereoutth wrote: post #597
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…

Yes the huge discrete stepwise training spend is critical. Maybe investors will realise that "the only winning move is not to play". And so we are left with (as was) frontier models getting more and more out of date as whoever their post bankruptcy custodians are tries to eek pennies on the dollar for inference on their decaying property. Perhaps along with local and/or highly specialized models still feeding on the…

Bankruptcies? The winners will gobble up the losers and the few remaining players will have pricing power. Don't be naive thinking that OpenAI or Anthropic can possibly go bankrupt. There will always be someone happy to buy them up for a nice price. Yes, the market will have to go through a consolidation phase though.

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

#995

Post by extraextra »

whatshisface wrote: post #173
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…

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…

Great points. - At the end of the day those are still private companies (albeit huge ones), so we can only speculate about the state of their private financial situation. Once they will decide it's the right time to IPO, they'll publish all their financials and we'll start to have a clearer picture. - Later, each company will slightly specialize and have a different go-to-market strategy, which will allow us to understand on a deeper level what works in the market and what doesn't (think about how Facebook, Instagram and TikTok are all huge universal social media platforms, but, each with a different target audience and different user base). - Finally, the market will go through a consolidation phase in which winners will gobble up the losers and then the incumbents will have a real moat (against new-comers) and real pricing power on their user base.

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

#996

Post by extraextra »

safety1st wrote: post #781
FuriouslyAdrift wrote: post #246

Earlier quoted context omitted.

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.

Yes 100% this. A lot of people keep talking about how OpenAI and Anthropic will need to raise their prices. What is less discussed is how they CAN'T raise their prices because competition exists, and sure it's not SOTA, but it's literally an order of magnitude cheaper in many cases and the drive to figure out how to make it work well enough is going on right now (and will only intensify when the SOTA models raise the…

I'd qualify your point that Anthropic and OpenAI can't raise prices, that is as of right now. Once the industry will go through a phase of consolidation and the bigger players will have some moat around their product, they'll have more pricing power.

Your last point is common sense in my opinion, I agree with it. At the end of the day most employees are (by definition) of average intelligence and most businesses are average in complexity. Thus, it is logical that average tools (AI models) should do the job for most people and most businesses.

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

#997

Post by kkarpkkarp »

whazor wrote: post #791
kkarpkkarp wrote: post #783

> I currently subscribe to the $100/month Max plan from Anthropic and the $100/month Pro plan from OpenAI. If you are a heavy user of coding agents these plans are a fantastic deal. Guys, what - in your opinion - does "heavy user" mean? I thought I am heavy user (I am using AI to code every day 8hr a day + side projects) but 20 USD/month Cursor plan is always enough. What should I be doing to extend my license to hig…

My agents are easily busy 30 min to a hour independently. Implementing their plan, building and running tests, verifying deployment, linting. So I switch between multiple agents. Each agent has its own branch and worktree.

could you give me example of task which takes 30 mins? out of curiosity.

at most I have a time to go make a tea for myself when I am waiting for agent to end the job.

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

#999

Post by disiplus »

FuriouslyAdrift wrote: post #979
disiplus wrote: post #442

Earlier quoted context omitted.

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

I think the quote came out to $107k. 4 AMD MI300A's. Around 60k tokens per second, 512GB of GPU memory. https://www.gigabyte.com/Enterprise/GPU-Server/G383-R80-AAP1

Which model are you running ?

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

#1000

Post by harrouet »

simonw wrote: post #854
harrouet wrote: post #813

Product-market fit, but what about customer retention? It is quite trivial to switch from using one model or another. Likewise, in a few years we'll have affordable laptops to run today's frontier models. What's their plan to let us keep subscribing?

Right now the main plan for that appears to be having those enterprise accounts commit for a year at a time.

One-year commitment won save their churn rate without vendor lock-in.

How about letting you maintain a vibe-coded repo only with access to the context that led to it ?

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