I have always been interested in bounding problems. My life's passion thus far has been finding the edges, limits, and forms of things in domains of increasing abstraction. I have worked on and studied, in no particular order: reinforcement-learning systems, both continuous and discrete, with a particular interest in classical actor-critic research (world models optional!); metaprogramming, especially C++26's reflection paradigm and the future code-generation patterns it may enable; and stochastic processes, particularly actor models of markets.

I am interested in collaboration, though I am constrained in the scope of what I can contractually undertake. I am especially drawn to collaborations that make room for rigorous questions, clear interfaces, and ideas pursued all the way to their edges.

“There is a line somewhere in Wozzeck that translates out to, roughly, ‘The world is awful.’ Yes, I said to myself as I shot across the Bay Bridge not giving a fuck how fast I drove, that sums it up. That is high art: ‘The world is awful.’ That says it all. This is what we pay composers and painters and the great writers to do: tell us this; from figuring this out, they earn a living. What a masterful, incisive insight. What penetrating intelligence. A rat in a drain ditch could tell you the same thing, were it able to talk. If rats could talk, I’d do anything they said.”

Philip K. Dick, The Transmigration of Timothy Archer

writing

raodreamer: deep & broad model imagination

Contrary to popular belief, machines can dream. For many years, the technologies around you have been improved by machines that imagine paths into the future and learn to act based on this imagination.

a million emergent rosarchs

A SAT-based forcing algorithm using some simple adjacency rules. My hope was to maximise emergent complexity without using templates or an underlying layout. I noticed that a few of the results spontaneously resemble rosarch blotches in quite a beautiful manner.