Everybody knows what eating the seed corn means.

There is no seed corn analog in mathematics.

Since the fashion that mathematics is problem solving there are lots of farmers ploughing their own field, that I concede.

Mathematics is fine and will be fine in the future.

Concrete example: Navier-Stokes. I don't make any claims about the truth of the announcement of the proof. But for the sake of the argument le't just suppose we know now that there is a smooth solution with smooth boundary and initial data which blows out in finite time.

Navier-Stokes is the simplest among evolution problems for continuum media, because it has maximal material symmetry (that's the mathematical meaning of a fluid).

If this is solved then go to a harder one, Coulomb friction. As a real life phenomenon, friction is very interesting to explore and mathematically is much harder than NS.

So it is not like we will ever be left without things to think about.

Oh, you want another? The present AIs are things made of mathematics. I would like to understand as a mathematician how and why they can beat human problem solvers?

Is that because mathematics is in some precise, interesting sense, more "computable" than it seems?

Misaligned are the present academic merit system hand in hand with financial interests of academic publishing industry.

The system will be exploited and there will be an inflation of problem solving articles produced with AI. Nobodies will be more productive than 10 Fields medal recipients, each year.

So of course that the ones at the top of this system are scared.

This is a social problem of the present system, not a problem of mathematics.

Mathematicians will do mathematics and politicians will do politics, what's new?

I always used guest non login accounts.

As a mathematician I was able to check two plagiates (by humans) with even such primitive means.

But I have to mention that some things irk me in this conversation about math or science and AI.

First, I see lots of attribution and other related problems, with certain impact for the researcher proffesion.

But I don't see the most natural question: wouldn't you like to know the answer to _open-problem_ ?

I mean, is research now only about publishing and solving famous problems?

From this point of view I think the links from this recent post are depressing

https://terrytao.wordpress.com/2026/09/10/crowdsourcing-a-li...

Second, I think very relevant that the original meaning of "encyclopedia" is "recurrent education".

So I arrived to think that the present and future forms of AI in mathematics and sciences should be seen as modern day encyclopedic efforts.

Once we pass over the flurry of solving famous open problems (and wouldn't you like to know?) the next natural step is an audit of the ehole corpus of mathematics and sciences accumulated until now.

And then pass further on a saner basis and damn about problem solvers and unhappy publishers and management.