Tootfinder

They tell me that Open AI have solved four hundred previously open maths problems this week.
The news media, and even the mathematicians, seem quite credulous about it.
No way to know how many of those will really stand up in the end. Lots of proofs turn out not to be really proofs coz they have a mistake, and AI is quite good at discovering mistakes as well as now apparently discovering maths.
Some of them are counter-examples that prove the conjecture is false and those are gonna be good at last. Machines can check it.
Some have other types of mechanical machine-checkable proof, which is interesting in that we can all believe the checker-machine: coz it's deterministic and understandable.
We can't trust the machine that isn't deterministic or understandable as much though.
GPT says these things are true. Now maths people have to check, because OpenAI staff aren't expert mathematicians either, mostly.
Some of the 400 proofs will fall, I'm sure.
How many tokens will be spent before machines find the flaws that are surely still there? How many tokens until you decide to stop?
But if a machine can prove a thing to itself, but not explain it to any person, is it really doing maths? Even if it's correct more often than people are? Or is doing maths more about making meat understand a thing?
🤔
I'm sure I can't tell if the proofs are true or not. No point me reading them. Mostly won't even understand the question. The boundary of my meager meat-mind's maths-understanding was around barely-degree level.
Can the academic discipline continue as one which is devoted mostly to trying to understand the output of a machine writing about maths, which is mostly right but nobody can really tell without an entire academic discipline trying to check.
In other words, mathematicians now also face a spam problem familiar to many github project leads.
#ai #maths