It's not particularly surprising that if you:
(1) take a 300 line NN algorithm,
(2) throw a quarter of the world's GDP + all literature ever collected at using the algo to train a NN
(3) throw another quarter of the world's GDP at billions of teraflops for inference, and
(4) aim the resulting world's-largest-computer at marketing itself to investors, for instance by decoding ciphers from obscure medieval manuscripts,
that you could perform some pretty magical tricks. There are other feats humans have performed for less cost, like sending people to the moon, or landing a rocket vertically, or idk, curing Polio.
I'm not knocking the "miraculous" advance here. The unique thing about the solution which makes it particularly non-trivial and something that humans would struggle with was exactly what LLMs excel at: Diffing loads of texts against each other. But the 176k tokens at around $10 doesn't tell the story of the cost. It says a lot about the externalized cost and the amount of money flowing in to support the hardware. If they'd put a $100,000 bounty out to solve that cipher, I think the internet would've solved it in a couple days.
It's funny we're already at the "actually this isn't very impressive" stage when it was a little over a year ago when we were making fun of LLMs for not being able to add numbers.
IC production takes a vast amount of resources and wealth, and it's a known quantity (after all, we've been doing it for decades), but it's still impressive what modern fabs can achieve.
Afaik LLMs still can't add numbers. They've just had their system prompts updated to make them use a tool call for any arithmetic.
That does not reflect with testing I just did locally. When the option of writing and running scripts was available, Qwen3.8-flash did indeed prefer to just do a physics related calculation via code. But, with a fresh chat and tool access turned off, it did the work on its own and produced correct results. Each step was rounded similar to how a person working by hand might do things, but matched my own hand calculations perfectly.
I found this post hilarious exactly about this the other day:
First, it’s AI can’t multiply 4-digit numbers.
Then it’s AI can only, by brute force, get silver in the IMO with specialized systems.
Then it’s OK, well, now a general-purpose model can get gold, but it’s still just the IMO, it’s for high schoolers.
Then it’s OK, it can solve a few trivial Erdős problems, but only because nobody seriously tried them before, they were low-hanging fruit.
Then it’s OK, a lot of serious mathematicians tried this one, but the result was still obvious in hindsight, it just combined knowledge from a thought-to-be-unrelated field, if any human knew that, they would solve it.
And then to OK, but there are still Millennium Prize Problems.
Then OK well it's just Navier-Stokes wake me up when its the Riemann Hypothesis.
Then-
If AI does solve the Riemann it will be the watershed moment when the world realises what has happened.
The ability of the algorithm to absorb billions of dollars of training effort is itself the major breakthrough of the transformer architecture.
also fire is not particularly surprising, once discovered
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