lalitmaganti
10 hours ago
I suggest also reading Kevin Buzzard's blog post which was just posted: https://xenaproject.wordpress.com/2026/09/04/flt-anthropic-h...
Provides great context on this accomplishment, what it means but also doesn't mean.
dang
8 hours ago
Thanks! I've added that link to the toptext.
I'd really like to make it the top link (and relegate https://www.anthropic.com/research/formalizing-fermats-last-... to the toptext) since HN has been tracking the work of https://news.ycombinator.com/user?id=kevinbuzzard for a long time and we're big fans. But I guess that would be overkill.
faitswulff
9 hours ago
I’m not very good at mathematics, but it seems like Kevin should take his girlfriend on trips more often for the good of all mathematicians.
aquafox
9 hours ago
We should start a gofundme to send him 2 months to a remote tribe in the Amazon. Chances are, we see the Riemann hypothesis and twin prime conjecture proven. ;)
BeetleB
9 hours ago
"I was given £1M to run my project over 5 years; Anthropic took only 11 days but I do wonder if they spent more money…"
Gives you an idea of the scale...
sebzim4500
9 hours ago
It sounds plausible they spent more, given the output tokens (6 billion of them) would cost $300k at API prices and presumably there will have been many more input tokens than output tokens.
_aavaa_
8 hours ago
Unlikely, api pricing includes a healthy profit margin (as near as we can tell from the outside) which they wouldn’t charge themselves.
musictubes
22 minutes ago
And which they could not charge anyone for. Unless these were extra resources that would otherwise go unused it cost them the amount they could have charged for them. Normally I would expect most businesses to make reasonable tradeoffs when it comes to how to allocate resources. I’m not convinced that any of the AI providers should be given that benefit of the doubt.
mbesto
8 hours ago
> healthy profit margin (as near as we can tell from the outside)
Ugh we still don't know if this is true and it's nearly impossible to calculate without a full understanding of the real CAPEX cycle. Stop spreading these rumors until we know for sure.
bryanlarsen
7 hours ago
SemiAnalysis estimates their profit margin to be 70%. To be losing money on inference implies that their costs are almost 4X higher than SemiAnalysis has calculated. That's not credible.
p-e-w
5 hours ago
I don’t see how they could credibly estimate inference costs without knowing the model size.
FuckButtons
5 hours ago
But we do have a reasonable estimate of model size.
alch-
8 hours ago
I don't think Anthropic is turning a profit ;)
_aavaa_
8 hours ago
Whether on net they turn a profit as company overall is neither here nor there.. My point is that they are selling API tokens at a profit (or if being pedantic, then at a price higher than the cost to serve them ignoring research costs). And that that price is got a healthy margin which they don't charge themselves.
irthomasthomas
8 hours ago
Because of the ongoing training costs. They are certainly making a healthy profit margin on inference.
Philip-J-Fry
7 hours ago
Never really a sound argument.
It's like having new solar panels installed every week. Sure you're "profitable" on the $0.20/kWh you're selling your "free" energy at when you ignore the cost of the solar panels you're buying every week.
dist-epoch
8 hours ago
Neither did Amazon for it's first 25 years ;)
btilly
5 hours ago
Amazon didn't make a profit because they were reinvesting money into starting new lines of business.
Basically there was a choice between taking the money, and growing. They chose growth.
chpatrick
5 hours ago
As opposed to...?
caughtinthought
8 hours ago
I think you're missing the point of the comment you responded to, lol.
CaptWorld
8 hours ago
Regardless the profit margin as a talking point seems to be bad as AI as a tech might never be reversed whether anthropic failed or succeeded. Indeed it's imperative we subsidize AI companies and tech to make them explore more solutions to scientific problems which has a downstream effect on human flourishing.
oblio
7 hours ago
Or we could invest in a ton of other non AI related research we're underinvesting in.
CaptWorld
7 hours ago
Like? I feel breakthroughs that can be found via AI might help us more in the long term where even previously non AI fields can be helped by AI. So you have specific non AI research in mind that we're underinvesting in? Because the USA is already spending crazy anyway for healthcare and I don't feel like funding is the issue but better incentives, reforms etc
fyredge
3 hours ago
Like funding education. Let's build up human intelligence instead, they seem to have made great breakthroughs in every single field!
The US doesn't pay too much to healthcare, they pay too much to health insurance. Too much for too little value
CaptWorld
31 minutes ago
But US also spends too much on education as well. The issue doesn't seem to be funding but the educational reform like in mississippi, where they increased student performance without increasing their budget too much. That's why you see bad k12 educational outcomes compared to the budget spent in blue states. It's all about efficiency. Give AIa chance in few years as I feel it can make great strides.. it's hard to imagine that chatgpt released in 2022 and look at the progress in just few years as it just changed software engineering field entirely.. i expect similar kinda progress where of course humans will still be making breakthroughs but it'll be accelerated with the help of AI.
Spending on health insurance is spending on health care.. Americans want free healthcare but no tax bump so health insurance is a compromise.. when even just ACA was passed and premiums increased, democrats got destroyed at midterms so Americans might be living in la la land.
2muchcoffeeman
6 hours ago
The token price seems like a poor measure.
Building the LLM that could do this work in 11 days cost multi billions.
The economics probably only make sense if LLMs prove to be a benefit to almost everyone in a way we can all accept.
Otherwise this cost a lot more than we’d otherwise pay. It was incredibly fast though. But we all know: cost, speed, quality. Pick two.
iterateoften
5 hours ago
How many previous attempts with other models failed or on other problems. Perhaps this is $300k out of $100M or $1B of total budget just breadth first searching theorems in math and all the failed attempts conveniently don't get mentioned.
UltraSane
6 hours ago
I burned $70 on fable 5.1 Max in about 2 hours. I suggest never using fable 5.1 on higher than High reasoning unless someone else is paying for it.
paulpauper
4 hours ago
Yeah, "major conjecture proved" with unlimited token budget bankrolled by trillion dollar firm.
blondie9x
6 hours ago
"I was given £1M to run my project over 5 years; Anthropic took only 11 days but I do wonder if they spent more money…"