I have seen two worries recently:
1. People will publish so much frontier mathematics, humans won't be able to understand it all
2. Frontier mathematics will all be kept secret
Fortunately, these seem like they can't both happen at once.
1. People will publish so much frontier mathematics, humans won't be able to understand it all
2. Frontier mathematics will all be kept secret
Fortunately, these seem like they can't both happen at once.
The fact that we don't know why is a clue pointing at some area of math that we haven't discovered yet. The hope is always that it will uncover some hidden fertile valley that will lead to lots of new discoveries. But the proof of the conjecture itself, without understanding, is really not that valuable.
My point is that even if AI discovers many new truths, there's still plenty to do for the mathematical community, in dissecting it and building useful abstractions to understand it, abstractions that can be leveraged for further exploration and uncovering new questions.
That already happened before AI.
> 2. Frontier mathematics will all be kept secret
Gauss kept lots of frontier mathematics in his drawer. In the 20th centuries government spy agencies developed public key cryptography long before that was known to the public. To give just two examples.
It's not the end of the world.
And what do you care, if someone keeps frontier mathematics a secret, if you can ask DeepSeek version 10 in 2030 to prove the Riemann hypothesis for you?
About 4-6 years earlier, depending what you want to count, although the inventors may also have been less clear on its importance or applications compared to the later public inventors.
https://en.wikipedia.org/wiki/Public-key_cryptography#Classi...
I guess that's kind of a long time in computer technology terms.
Though it appears to have gained popularity from 2017-2021, it dipped in '22 and that's as far as ngram goes.
1. People will publish AI generated frontier math making it difficult to identify frontier mathematicians. 2. Trained frontier mathematicians will become scarce
" The National Security Agency is the largest employer of mathematicians in the U.S. "
https://www.scientificamerican.com/article/mathematicians-an...
There are very-very few cases where you need truly advanced math in finance. The problems that need solving are generally vastly more pedestrian.
You need to deal with terrible data quality, terrible formats, noise in every aspect of your work, disruptions, lack of standards, inability to generate new data (and repeat experiments), conflicting and often opaque incentives, technical problems ranging from shitty APIs to having to squeeze nanoseconds out of your network stack, etc.
These are all difficult problems, but they are crucially not frontier math problems (by and large).
Tell me you have no clue about quant finance without telling me you have no clue about quant finance.
You probably think it’s abstract topology and Ito calculus, when in reality it’s linear regression and PCA. If you’re lucky, maybe you’ll see a sigmoid function.
If someone in finance is using LLMs, it’s for marketing purposes (recruiting new grads or impressing investors). Jane Street and DE Shaw are notorious for this.
Nope.
Let me guess: you listened to The Man Who Solved the Market and think RenTech uses/used unpublished frontier mathematics to predict the market.
There are plenty of firms with both higher annual % returns (consistently over 15-20 years) and higher absolute $ returns than RenTech/Medallion fund, especially post-2010. And they’re not using “frontier mathematics”.
A lot of alpha comes from how well you know the VP at the exchange. Not math. Not tech. But good ol’ politics.
Don’t like a market participant? Tell the exchange to issue violations to that participant. Get them banned for a few months.
Fat fingered a trade with wrong price or quantity? The exchange can and does undo a trade after the fact. All in the name of “orderly markets”. Similar to when governments use “national security” as an excuse.
No, more like, some differential geometry and gauge theory. The topics that Jim Simons worked on.
Which makes total sense unlike the "too much frontier math" nonsense.
Which groups are those?
If you are good at it, end result is that minority can keep majority of the seats and power. So, as there are two parties, the groups are "likely to voted republicans" and "likely to vote democrats".
According to you, there is no discourse about politicians using gerrymandering to give themselves safer seats.