The Mathocalypse

matt3210

Agents basically did statistically guided brutforcing. There is no value in what they produced because it lead to no understanding of anything and most likely will hurt the field IMO

nostrademons

As a side note, you can tell this wasn't written by an AI by the first sentence: > mommy, I heard you got cooked! I heard that a robot solved the math problem you worked on for your whole career! OOF! My 8yo talks exactly like that. I could totally imagine him saying this, the same way, at the dining room table. I asked ChatGPT "pretend you're an 8/9 year old today. how would you insult your mom about having her job be replaced by an AI?", and the responses it offered were: > “Mom, AI took your job because apparently even robots were like, ‘Yeah… we can do this better.’” > “Mom, congratulations! You got replaced by a computer. Even Siri has a job now and you don’t!” > “Mom, AI took your job? Dang. I guess even a robot looked at your work and said, ‘I got this.’” > “Don’t worry, Mom. You can still be useful… like teaching the AI how to make my lunch.” All of these seem to have a vaguely Millennial flavor, aside from being pretty awkward and mechanical roasts. Trust the children and linguistic drift to be the best AI detector.

GMoromisato

I liked the metaphor of a climber teleported to the top of a fog shrouded mountain. And I agree that now that the teleporter exists, we need to use it to reach more peaks and explore. There's no going back to a world where AI doesn't exist.

tkdb

C'mon. Mathpocalypse. Things are hard enough already.

TMWNN

Quoting DCKP < https://news.ycombinator.com/item?id=49989738 >: >I have had this conversation with my PhD students yesterday. I am 100% sure that all of their problems can be solved by publicly-available models now (I solved a case of one myself as a test, it took 15 minutes). So the challenge for them is to see how much they can accomplish in their allotted period, and still pass a defence on at the end of it all. The PhD defence is going to become all about a test of understanding, not a test of quantity of publication. Also, Ted Chiang's 2000 short story "Catching crumbs from the table" < https://np.reddit.com/r/singularity/comments/1wzu5gf/this_mi... >.

PowerElectronix

What's with all the "AI just proved that this or that isn't O(n (log (n))^2) but akshually O(n (log (n))^1.99999)"?? I guess it deserves respect as progress, but it just rubs me the wrong way. Like the machine did the absolute minimum to beat the previous mark.

zkmon

The irony. Something that is born out of a science, eats up that science.

ks2048

> It feels like something written by someone who’s on psychedelics. So much unclear and doesn’t make sense. Lots of name dropping of previous work without discussing why it can be used despite impossibility results > Basically the paper is so horribly written that it’s impossible to read it without AI help That's interesting and haven't seen this in all the coverage of this event. It sounds horrible to wade through - like trying to understand someone else's messy code that still produces the correct output.

12376-1287

Guy is misrepresenting AGMAI, talking about the Simons Institute (AI boosters), Quanta (AI boosting magazine from the Simons Foundation), Scoot Alexander (!) and Steven Pinker (!). The he puts up preemptive straw man arguments against doomers. His blog has become a joke.

mlh496

Imagine if a team of mathematicians from OpenAI had gone on a university tour, gave demos of how powerful their models were for math research, and then gave mathematicians access to the model. Empower others rather than drop 700+ discoveries on GitHub that were made using a model only they have access to. People might feel differently about AI if they were a part of the changes rather than being a helpless spectator.

an0malous

> But it also appears that no human has understood just about any of these proofs yet Has anyone verified any of the proofs produced by OpenAI or is everyone just assuming that it just be true because the Lean code checks out? Couldn’t the Lean code just be formulated incorrectly?

daoboy

For those well suited through intelligence and demeanor to pursue a career in mathematics, what problems do these people reorient towards after this?

adverbly

Feels good to hear honesty and humanity from Scott having decided to watch Terminator 2 with his kids on after such a monumental release. Emotions can be funny.

OutOfHere

The obvious answer is to have mathematicians use AI to: 1. Help understand, check, and explain the results. 2. Write new works explaining or refuting the new approaches and results in more lucid language. 3. Advance the field further. I don't know why this is not obvious. Each step is intended to support human understanding, not to replace it. Any mathematicians who don't do these will be left behind, and if none do it, the field of human mathematics itself will become obsolete. All I am hearing so far is excuses.

yewenjie

> Experience has shown that, even now, there will still be people explaining in patronizing tones why none of this is real and none of it counts. If such people were capable of being impressed by anything that happens in the empirical world, of updating on anything, they would’ve already been impressed and already updated several years ago, long before things had reached the point of an actual Mathocalypse. ^^ half of the comments on this thread

geraneum

> my 9-year-old son was taunting my wife… “mommy, I heard you got cooked! I heard that a robot solved the math problem you worked on for your whole career! OOF!” Usually 9 year olds imitate adults when they regurgitate such words in these circumstances. What a sad state of affairs.

softwaredoug

Aren’t there dozens of proofs of the Pythagorean theorem? The goal isn’t to just “prove” but create something well written and intuitive to the average practitioner. And by gaining a deeper understanding we can ask better questions.

ajjenkins

The line about “understanding the aliens” reminds me of Ted Chiang’s short story The Evolution of Human Science (2000). Highly recommend reading it. Very prescient for something written 26 years ago. https://gwern.net/doc/fiction/science-fiction/2000-chiang.pd...

meander_water

Can someone who understands maths more than me explain why it could only solve 372/8000 problems? What was it about the other problems that made them unsolvable? Was it just a time constraint, or are they just harder problems?

whatshisface

I'll bite: none of this is real until I have learned something. OK, I am now listening. Does anyone want to make it real?