The only reason OpenAI and Anthropic are making a loss is due to training new models to keep up with competition - not because the industry is flawed in terms of business model.
> The only reason OpenAI and Anthropic are making a loss is due to training new models to keep up with competition - not because the industry is flawed in terms of business model.
So in other words they are not profitable? Like you cant say they are profitable and then in the next sentence say they make a loss. That is not how profit works.
The point is that the model is already immensely profitable. There is no fundamental reason why AI isn't profitable. It already is.
Insane competition does not last forever. When chip manufacturing first started, there were dozens of companies that had fabs that made compute chips. Nowadays, only TSMC is viable. Samsung and Intel survived because of geopolitics.
> Is that not self evident by the insane revenue from frontier labs?
No...? Of course not?
Because revenue is only one side of the equation. Did you ever look at total cumulative OPEX and CAPEX, and how long it will take them to even just break even at current growth?
They're likely over $80b ARR by now. They'll be at $800b ARR next year at the same rate. Let's say their growth gets cut down to 3x instead of 10x - that's still $240b ARR by this time next year.
When you are growing so fast, you don't need to make a net profit. You just need to make sure your unit economics are good - which it seems like they are given reports that their gross margins are at 60-70%.
> They're likely over $80b ARR by now. They'll be at $800b ARR next year at the same rate.
And they will be 800 trilion ARR in a couple of years, following that same rate! 8 quadrillion by 2029!
> When you are growing so fast, you don't need to make a net profit. You just need to make sure your unit economics are good - which it seems like they are given reports that their gross margins are at 60-70%.
If their margins were anywhere near this good, they wouldn't need to raise so much money so often.
If you create a machine that turns 1 dollar into 3 dollars, you don't dillute your ownership of the machine, you use your fabulous profits to expand your machine's capabilities.
If their margins were anywhere near this good, they wouldn't need to raise so much money so often.
Why not? They are reinvesting into growth. There isn't a clear winner yet and Anthropic wants to make sure it is one of them. Taking a profit now while letting OpenAI take your marketshare and train better models is not very smart.
Or they bleed money like crazy, and their margins are pretty awful. Which is the correct answer.
Your $200 subscription is a major net loss for them. The vast majority that pays for that would cancel in a heartbeat the moment they had to pay API prices. Which may or may not be profitable, I am not entirely sure. But for the sake of argument, let's assume that it is.
Wihout insight on how much enterprise is paying, it is impossible to draw any conclusions. Unless you have any access to their contracts and are willing to share evidence? I find that highly unlikely.
People here throw around crazy numbers - the dude above was claiming they have some insane good margins, numberd that he took out of his ass.
The only evidence I have is that they are incredibly unprofitable, and they keep raising insane amounts of capital like crazy.
There was a leak sometime ago that they were EBITDA positive during a quarter where they didn't pay for part of their compute. And EBITDA is a cute metric to use when depreciation is actually very important to them, as a model from a year or so ago is nearly worthless.
serving models is very profitable (70%+) but the issue is you need to invest in training the next iteration. but so far all of anthropics models have been profitable fully loaded
the vast majority of the labs revenue is from enterprise api usage (theres public sources from the information and ramp). but the risk there is customer concentration, where most of the revenue comes from other tech companies and a chunk of it is from foreign labs distilling
so i am drawing a conclusion that the labs' business model is good, maybe not as great as boosters think it is. if they make real progress on the biosciences like drug discovery that could turn it into an amazing business
This is not evidence. This is random people speculating on Anthropic's margins without any real evidence.
Just because it is on some blog post, it does not make it true.
I wasted the time to read the first blog post. It considers 100% utilization over the course of years to calculate an estimation, and it did not consider depreciation for the model itself. That thing is extremely extensive to create, and after a relatively short amount of time is considered outdated.
Are we still calculated $200 subscription token spend based on their highly inflated API token cost and then concluding that they must be losing money on all $200 subscriptions?
Sure, there is revenue, and market valuation. Is there _profits_ in frontier models ?
What is the horizon for openai and anthropic to _make_ money ? Will they achieve that by charging more for frontier models, or investing slightly less in training frontier models, etc... ?
I've heard it before and believe it that one reason is because many of the developers are working on new maxed-out machines and network connections both at work and home, so they don't notice problems for older or cheaper ones and/or can't justify it to management.
Taxis in general are a working and proven business model. You could have been skeptical about the way they approached it but surprise surprise, you can make money providing taxi services. Less so with "AI", it's not proven at all that this can be made profitable in the near future.
The failures of past doomsayers are important to keep in mind. It’s hard to say “well, but we know things they didn’t know at the time, but this time that won’t happen.” I will observe, however, that Uber’s revenues come from consumers. Consumers are never going to be willing to spend enough on AI to justify OAI and Anthropic’s spending, even if a single company captured all of their demand. They recognized this and pivoted to software engineering and enterprise customers. These are much more sophisticated buyers than someone trying to catch a cab or get a burrito delivered, and more able to be patient or expend resources to find a better, cheaper provider.
It also bears mentioning that if any particular AI lab manages to survive and succeed in the way Uber has, there will be several multibillion dollar corporate gravestones behind it. In fact, I don’t even think that nobody can be the Uber of AI. I just think it can’t be OAI or Anthropic. The debt is too great and it’s priced under old assumptions.
I owned a Samsung NC10 which had a non-shitty keyboard as its outstanding feature. Was a nice little Linux machine I used a lot. Only bad thing, those Intel Atom N2xx CPUs are just awfully slow, even back then.
Today realistically I don't think it really makes that much sense to bother with those devices even for small home servers. You can e.g. get used thin clients for cheap which run circles around those old CPUs and support way more RAM while likely being as power efficient if not more. At the bare minimum I would avoid using any 32 bit x86 CPU for running anything modern, even Debian dropped official support for that architecture now.
> Netbooks didn’t need Microsoft’s help in dying. Nobody bought more than one of them, the experience was that bad.
If I remember correctly Microsoft put a limit on the HW specs for getting those cheap Windows copies while simultaneously making sure they all shipped with Windows which did not run that well on that low spec hardware. I think this is a huge part why this category died that quickly.
On the other hand there was also just general technological progress happening, "full size" notebooks were generally getting a lot more compact and lightweight so there was less need for that separate category.
> Proxmox is merely Debian with some fancy curtains.
It's part of the appeal that it is mostly just Debian under the hood. If I want to run containers I would also not see it as the best choice but it really shines in managing qemu VMs.
Proxmox upgrades make K8s appealing, and that's not easily done.
I've been on Incus with my homelab for a few months now, and couldn't be happier. Maybe I should make a post about it, but I don't have much to report. My biggest maintenance outage was forgetting to set WakeOnPower in the BIOS.
Edit: And yes, all I want to do is run containers. Nothing fancy, Nginx Proxy Manager suffices for networking, and Linstor/DRBD handles disk. I wanted to remove hyperscaling complexity, but keep immutability, and so far, life is good.
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