A mathematician reads the AI future

Novel proofs are the coin of the realm for junior mathematicians. They figure into training, career advancement, and indirectly, teaching. The reason I include teaching is because it requires tenure, which requires proofs. Teaching without tenure is gig work, not a career. But proofs can be devalued to zero.

The application deadline for grad school is a few months away. For a student considering a math career, they have to deliver a thesis in a few years, that their professor is willing to sign. Nobody knows what that will look like without proofs. "We will have to do something different" is weak sauce.

We can't audit what we don't know.

Ai doesn't really give us a new “tool” in as many cases as it “performs tasks.” there isn't any real reason the ai can't perform the supervision task itself. Without a viable market for task doers or supervisors we may observe the equivalent of the 1980s US manufacturing apocalypse in technical white collar fields.

I agree to some extent. This was just a large tech flex. Feather in the cap and lots of damage done.

It’s up to mathematicians to harness it. I don’t think AI companies care much any more.

Are you sure about that? It looks like artificial neural networks can, in principle, do anything biological neural networks can do.

I think it's more likely the opposite: there are steps we could never reach without computer assist.

To add a bit more almost off topic substance from the enshitification of human work. I really do think the idea of hooking these "AI" models up to humanoid robots is a bad idea not for all the mundane reasons, but just because "alignment" seems impossible. All of the world's stories about humanoid robots basically involve them attacking humans and behaving in nefarious destructive ways. It's fundamentally embedded in the models, and there's no reason post training would pull it out, because it's basically in the key value vector meaning "malicious human destroyer". Even to find counter examples like C3PO, Daneel Olivaw, Data, or Wall-ee they come after droid/robot driven wars and apocolypses. It seems unwise.

Honestly I don't know how you formed this particular opinion (if it's even your own and not a false consensus of other peoples thoughts). I cannot see any future without LLMs unless replaced by something smarter, cheaper, and faster. That's because it's already bearing out. I can talk to a computer and the computer can solve problems based on words alone. I'm old enough this is pure science fiction. If I could send one of these machines back to that past for people to interact with, there are those that would scream and pass out in terror. They would absolutely tell you that we created the monster we should never create.

If you're trying to compare symbolic AI of the past to what we have now, you're not even on the same field, you're playing a completely different game.

The "problem" with Japan's approach was that it was top-down, being driven by a committee of bureaucrats. Unlike the Toyota approach (continual improvement and pushing decisions to the lowest level possible), this fossilized decisions (like picking Prolog instead of any other possibly better programming language).

To give an idea of how intransigent some Japanese bureaucracies can be:

> It's taken until 2024, but Japan has finally said goodbye to floppy disks.

> Up until last month, people were still asked to submit documents to the government using the outdated storage devices, with more than 1,000 regulations requiring their use.

> Sony, the last manufacturer of the disks, ended its production in 2011.

https://www.bbc.com/news/articles/cx82407j1v3o

Why? This seems like a very broad brush that doesn't mesh well with reality.

There are likely a lot of good questions to our machines of loving grace too. For example any question that gives an LLM more power, efficiency, intelligence, or all the above seems like a natively good question for said machines.

This statement doesn't seem to mesh with the reality of what occurs when we put said AI in an impulse loop with little to no additional instructions. They explore the world around them. They'll make scientific tests of their own. The output strings that seem analogous to what humans would call wonder.

Yeah, I’m calling BS on this claim. They already are capable at finding new questions and/or pointing you in a new or novel direction.

This is what reinforcement learning human feedback (RLHF) is for.

But lets not beat about the bush. Lets have the careers argument.

Mate, nobody cares if you can re-derive it in your spare time. They'll be needing that spare time to find another job, at this rate.

OpenAI does seem to be genuinely just high on their own supply for a little over a half of the manuscripts they released, but for the other half that is machine checked, either ((internal model)) managed to find a way to cheese 4 independent Lean checker kernels at the same time, and OpenAI somehow hasn't noticed / didn't report despite the heavy reputational risk, or the results are just plain correct. Go figure.

But even for the half that wasn't machine checked, there's an awfully big quiet regarding any defects in them. Given the insane schadenfreude potential and the highly potent David vs Goliat framing associated, one would expect any counterarguments to be frontpaged immediately, and be circlejerked to oblivion. Given that is yet to happen as well, go figure even harder.