Comment by doctoboggan
20 hours ago
Can anyone give a little more color on the nature of Erdos problems? Are these problems that many mathematicians have spend years tackling with no result? Or do some of the problems evade scrutiny and go un-attempted for most of the time?
EDIT: After reading a link someone else posted to Terrance Tao's wiki page, he has a paragraph that somewhat answers this question:
> Erdős problems vary widely in difficulty (by several orders of magnitude), with a core of very interesting, but extremely difficult problems at one end of the spectrum, and a "long tail" of under-explored problems at the other, many of which are "low hanging fruit" that are very suitable for being attacked by current AI tools. Unfortunately, it is hard to tell in advance which category a given problem falls into, short of an expert literature review. (However, if an Erdős problem is only stated once in the literature, and there is scant record of any followup work on the problem, this suggests that the problem may be of the second category.)
from here: https://github.com/teorth/erdosproblems/wiki/AI-contribution...
Erdos was an incredibly prolific mathematician, and one of his quirks is that he liked to collect open problems and state new open problems as a challenge to the field. Many of the problems he attached bounties to, from $5 to $10,000.
The problems are a pretty good metric for AI, because the easiest ones at least meet the bar of "a top mathematician didn't know how to solve this off the top of his head" and the hardest ones are major open problems. As AI progresses, we will see it slowly climb the difficulty ladder.
Don't feel bad for being out of the loop. The author and Tao did not care enough about erdos problem to realize the proof was published by erdos himself. So you never cared enough and neither did they. But they care about about screaming LLMs breakthrough on fediverse and twitter.
> Did not care enough about erdos...
This is bad faith. Erdos was an incredibly prolific mathematician, it is unreasonable to expect anyone to have memorized his entire output. Yet, Tao knows enough about Erdos to know which mathematical techniques he regularly used in his proofs.
From the forum thread about Erdos problem 281:
> I think neither the Birkhoff ergodic theorem nor the Hardy-Littlewood maximal inequality, some version of either was the key ingredient to unlock the problem, were in the regular toolkit of Erdos and Graham (I'm sure they were aware of these tools, but would not instinctively reach for them for this sort of problem). On the other hand, the aggregate machinery of covering congruences looks relevant (even though ultimately it turns out not to be), and was very much in the toolbox of these mathematicians, so they could have been misled into thinking this problem was more difficult than it actually was due to a mismatch of tools.
> I would assess this problem as safely within reach of a competent combinatorial ergodic theorist, though with some thought required to figure out exactly how to transfer the problem to an ergodic theory setting. But it seems the people who looked at this problem were primarily expert in probabilistic combinatorics and covering congruences, which turn out to not quite be the right qualifications to attack this problem.
Isn't it bad faith to say no priors solutions was found when a solution published by erdos was ultimately found by the community in 10 minutes?
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This Tao dude, does he get invited to a lot of AI conferences (accommodation included)?
He's the most prolific and famous modern mathematician. I'm pretty sure that even if he'd never touched AI, he would be invited to more conferences than he could ever attend.
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I know someone who organized a conference where he spoke (this was before the AI boom, probably around 2018 or so) and he got very good accommodations and also a very generous speaking fee.