As a former mathematician, I found research to be a very winding path. While that can be fun, I felt there's a lot of opportunity to train LLMs and ML models on the corpus of math papers, to try to make research more deliberate and less reliant on talking to the right person at the right time.
This is very much a work in progress but so far you can:
* Browse through similar papers
* Get recommendations for new papers and collaborators
* Chat with papers and ask questions to all the major reasoning models
* Have it come up with future paper ideas (along with references) giving a potential title or collaborators.
My focus very much is on the exploratory stages since that's where a lot of the time is spent, but I intend to integrate more tools for problem solving, writing, and computation.
I think you should have some "about us" section on your webpage if you want people to give their email addresses. I already get loads of spam that knows my email address belongs to someone with a PhD (though they are often shaky on the details). I looked at your site and there's no information about who is doing it and why.
That's fair, though there's not much to say since I'm building it out myself as a benefit corporation. I also have strict opt-out for any communications and a proper privacy policy.
I've also tried to keep as much as I can accessible without login, but I want to protect some of the more expensive features from being spammed.
No matter how original you think you are, it's almost always already been done. You think you found a new theorem and then you check some old pdf from 20+ years ago and it's already been done.
If you can pull it off, and the result is actually novel and not trivial, you can get a PhD. that is how hard it is.
The flipside of that is seeing hints of a result that would be really helpful. I still remember how excited I was to stumble on a book from 1931 (The Taylor Series by Dienes) since it had the only english-language proofs of some results by Szego and Polya that I felt could unblock my research. My hope is that this discovery problem can be largely solved.
This is also why I'm not as excited by the focus on pure reasoning and olympiad problem solving in the math and AI space. It's like the early career phase of trying to solve Collatz and Riemann but just repeating work from decades ago.
This is very much a work in progress but so far you can:
* Browse through similar papers
* Get recommendations for new papers and collaborators
* Chat with papers and ask questions to all the major reasoning models
* Have it come up with future paper ideas (along with references) giving a potential title or collaborators.
My focus very much is on the exploratory stages since that's where a lot of the time is spent, but I intend to integrate more tools for problem solving, writing, and computation.