I'm a PhD student in CS. While I think these results are rather cool, it makes me terrified that the skills developed by the PhD will ultimately be worthless. I'm not quite sure what to do. Any thoughts from people in similar positions?

> 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.

I thought that was from the outset the intent of the Hilbert program, to automate mathematics. And mathematicians were behind it. Cannot see why they would be concerned when a different way to do the same, not subject to Gödel incompleteness, is working out. Maybe the frustration is that they were not the ones building it.

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.

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.

How do we know that these "internal models" are not just half computer and half a giant team of mathematicians? How do we know that OpenAI actually came up with these solutions and didn't steal them from outside researchers?

> 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?

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...

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.

> 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

> 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.

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?

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

I think this should be called “mathematician discover vibe maths”

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?

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.

Doesn't look like these proofs are from the book.

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.

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

Wasn't openai accused of stealing personal work of some mathematicians? It's going so fast I'm unable to keep up

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...>.

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.

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

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.

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.

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