> Aren't they losing money on the retail API pricing, too?
No, they aren't, and probably neither is anyone else offering API pricing. And Anthropic's API margins may be higher than anyone else.
For example, DeepSeek released numbers showing that R1 was served at approximately "a cost profit margin of 545%" (meaning 82% of revenue is profit), see my comment https://news.ycombinator.com/item?id=46663852
They're all looking for outside money because they're all looking for outside money, and so need to keep up with their competitors investments in training. It's a game of chicken. Once their ability to raise more abates, they'll slow down new training runs, and fund that out of inference margins instead, but the first one to be forced to do so will risk losing market share.
Ed Zitron made that claim (in particular here: [1]). In the same article he admits he not a programmer, and had to ask someone else to try out Claude Code and ccusage for him. He doesn't have any understanding of how LLMs or caching works. But he's prominent because he's received leaked financial details for Anthropic and OpenAI, eg [2]
Maybe I'm misreading it, but I don't see him saying it's just the cost of *inference* alone (which is the strawman that the article in the OP is arguing against). He says:
> this company is wilfully burning 200% to 3000% of each Pro or Max customer that interacts with Claude Code
There is of course this meme that "Anthropic would be profitable today if they stopped training new models and only focused on inference", but people on HN are smart enough to understand that this is not realistic due to model drift, and also due to comeptition from other models. So training is forever a part of the cost of doing business, until we have some fundamental changes in the underlying technology.
I can only interpret Ed Zitron as saying "the cost of doing business is 200% to 3000% of the price users are paying for their subscriptions", which sounds extremely plausible to me.
I'm surprised "faulty PSU" is not on GP's list of common problems. Almost every unstable computer I've ever experienced has been due to either a dying PSU (not an under-specced one) or dying power conversion capacitors on the motherboard.
There's a Polish electronics forum that's infamous because it's kind of actively hostile to them noobs. "Blacklisted power supply, closing thread." is a micro meme at this point.
Used to repair PCs in the mid 90s. Had guy come in with right mouse button not working suddenly. Replaced mouse. No go. Replaced motherboard, CPU, RAM, reinstalled Windows. No go. Changed the PSU. Right mouse button worked.
I concur. A lot of “flakey” issues can be traced to poor quality power supplies. That’s a component that doesn’t get any attention in spec sheets other than a max power rating and I think a lot of manufacturers skimp there. As long as the system boots up and runs for a few minutes, they ship it.
Definitely that too, particularly in 2nd-world countries. I remember having a difficult time with dirty power for some hardware products I was responsible for at one time, where the customers were in the Middle East nd Africa in the 1990s. We ended up having to have the PS manufacturer do a redesign to help compensate for dirty power. It can be done, but it costs a bit more.
>> People using Linux are probably putting Linux on old machines
Maybe for linux noobs. But i would suggest that most linux users are not noobs booting a disused pentium from a live CD. They are running linux on the same hardware as windows users. I would further suggest that as anyone installing a not-windows OS is more tech savvy than the average, that linux users actually take better care of thier machines. Linux users take pride in thier machines whereas the average windows user barely knows that computers have fans.
As any linux user for thier specifications and they will quote system reports and memory figues like Marisa Tomei discussing engine timings. Ask a random windows user and they will probably start with the name of the store that sold it.
Unix user for 35 years, Linux for 30+ years ... my case fan died during the summer of last year ... just took the side panel off and kept things running.
An exception to prove the rule. You fixed it yourself and are here proud of your machine.
I did basically the same thing recently when I built an AI rig. I tried to put it in a sever rack case but the fan noise was too much. So I ditched the rack and put in an open mining frame.
Which is kinda crazy to me, in light of how durable their business laptops have been in my experience. I’ve owned maybe 6 pc laptops in my career, and the only 2 that’ve survived that nearly 20 year space are both dells.
> Gemini 2.5 Pro's reasoning traces (before they nerfed them) were a good example. The deep technical analysis, and then the human-friendly version in the final output. But I found their reasoning more readable than the final output!
They were also sometimes more useful: you could see whether it reasoned its way to an answer, or used faulty reasoning, or if it was just contextual recall. Huge shame they replaced them with garbage (though a bit better now).
> the language is surprisingly offputting. I don't know if it got worse
I recently used Makie to create an interactive tool for inspecting nodes of a search graph (dragging, hiding, expanding edges, custom graph layout), with floating windows of data and buttons. Yes, it's great for interactive plots (you can keep using the REPL to manipulate the plot, no freezing), yes Observables and GridLayout are great, and I was very impressed with Makie's plotting abilities from making the basics easy to the extremely advanced, but no, it was the wrong tool. Makie doesn't really do floating windows (subplots), and I had to jump through hoops to create my own float system which uses GridLayout for the GUI widgets inside them. I did get it to all work nearly flawlessly in the end, but I should probably have used a Julia imGUI wrapper instead: near instant start time!
Yes. And I did port my GUI layer to CimGui.jl. The rest of it is pretty intertwined with Makie, didn't do that yet. The Makie version does look better than ImGui though.
> They pragmatically changed their views of safety just recently, so those values for which they would burn at the stake are very fluid.
Yes it was a pragmatic change, no it was not a change in their values. The commentary here on HN about Anthropic's RSP change was completely off the mark. They "think these changes are the right thing for reducing AI risk, both from Anthropic and from other companies if they make similar changes", as stated in this detailed discussion by Holden Karnofsky, who takes "significant responsibility for this change":
> I strongly think today’s environment does not fit the “prisoner’s dilemma” model. In today’s environment, I think there are companies not terribly far behind the frontier that would see any unilateral pause or slowdown as an opportunity rather than a warning.
> What I didn’t expect was that RSPs (at least in Anthropic’s case) would come to be seen as hard unilateral commitments (“escape clauses” notwithstanding) that would be very difficult to iterate on.
> Yes it was a pragmatic change, no it was not a change in their values. The commentary here on HN about Anthropic's RSP change was completely off the mark. They "think these changes are the right thing for reducing AI risk, both from Anthropic and from other companies if they make similar changes", as stated in this detailed discussion by Holden Karnofsky, who takes "significant responsibility for this change":
Can you imagine a world where Anthropic says "we are changing our RSP; we think this increases AI risk, but we want to make more money"?
The fact that they claim the new RSP reduces risk gives us approximately zero evidence that the new RSP reduces risk.
That misses my point: the evidence is the extensive argumentation provided for why it reduces risk. To quote Karnofsky:
> I wish people simply evaluated whether the changes seem good on the merits, without starting from a strong presumption that the mere fact of changes is either a bad thing or a fine thing. It should be hard to change good policies for bad reasons, not hard to change all policies for any reason.
I'd agree that this effect is probably mainly due to architectural parameters such as the number and dimensions of heads, and hidden dimension. But not so much the model size (number of parameters) or less training.
Saw something about Sonnet 4.6 having had a greatly increased amount of RL training over 4.5.
Agreed, and here's a real example from a tiny startup: Clickup's web app is too damn slow and bloated with features and UI, so we created emacs modes to access and edit Clickup workspaces (lists, kanban boards, docs, etc) via the API. Just some limited parts we care about. I was initially skeptical that it would work well or at all, but wow, it really has significantly improved the usefulness of Clickup by removing barriers.
Sure, depending on the particular product, having control and direct local access to the data would be desirable or deal breaker. But for this Clickup integration that's not so important to us (we can duplicate where necessary), while still using Clickup lets us use all the other features we can get via the web app.
No, they aren't, and probably neither is anyone else offering API pricing. And Anthropic's API margins may be higher than anyone else.
For example, DeepSeek released numbers showing that R1 was served at approximately "a cost profit margin of 545%" (meaning 82% of revenue is profit), see my comment https://news.ycombinator.com/item?id=46663852
reply