me at intel's 2010 sts talking about cuda and moore's law!
behind my hand is the then-canonical image showing the organization of memory on an nvidia gpu
(registers, caches, sram, dram, threads, warps, blocks, grids, etc.)
time flies!
in fact this field switch is a return to my "childhood" work --- in 2009, before i knew what a vector space was, i was writing cuda kernels for (medical) computer vision applications (see e.g. my first paper below)! that work was unprestigious then, so i concluded that i should work on more "serious" topics instead of trying to parallelize everything i could find. hint: prestige is stupid
[it is amusing to wonder what might have been had i remained on that track given how early that work was (i even had a side project in which i attempted to produce style-transferred language output through "gofai" methods, since i knew nothing about neural networks --- it failed)!! --- i conclude that i am glad i gave mathematics my full focus]
in any case my priority now is supporting safety work, though my interests lie in capabilities --- hence anthropic. if you are a mathematician interested in learning the core of the field, especially to either work on safety research or else support it as i am, please let me know! after all, though i was witness to terrible behaviour in the math community (it is large and full of humans :) ), i found the modal member of such to be exactly the kind of person who would have a positive (in my opinion) influence on this field's developments
my papers and such are below, and expect more (non-ai, naturally --- no secrets :) ) to come!
i also hope to throw together a quick video series for math experts trying to quickly learn the field's basics (again no chance of secrets of course :) ) --- but nothing below yet!
finally, and unrelated to anthropic, my dream with this technology has long been to finally make the journal system in mathematics obsolete (i stopped giving my solo works over to journals a year before graduate school --- the arXiv clearly suffices for mathematicians uninterested in politics or ranking others' work) by making formalization practical --- indeed even easy! (imagine a world where it is the norm to upload formalizations along with pdfs to the arXiv! or one where there is a new bourbaki-like push to formalize works like ega...!) whether that is a priority during these rapid developments is unclear, but if you have ideas related to this please let me know :)!
A vtk-based, CUDA-optimized non-parametric vessel detection method (with Alark Joshi, Dustin Scheinost, John Onofrey, Xiaoning Qian, and Xenios Papademetris). (My Intel STS project from high school.)
*: (I once thought I'd discovered a new and "purely analytic" proof of quadratic reciprocity. In fact the argument was known to Dirichlet! So I turned it into a little expository article. See the fun!! section for a non-expository version, which amounts to a few lines.)