This is the first entry in the series Abstract Interpretation for Engineers - a collection of bite-size posts explaining the theory and practicalities of Abstract Interpretation.

As culture accelerates and fragments under the pressure of technological progress, we increasingly outsource meaning-making to machines - risking a collapse of narrative plurality and a convergence toward machine-mediated monoculture.

If you're working on a Ghidra plugin that performs some non-trivial program analysis you might be interested in unit testing your algorithms, this article is a collection of notes on set those up.

In this article I'm trying to clarify what constitutes superintelligence and push back against the idea of it being "beyond our reasoning".

In this article we start from a simple and inefficient algorithm that calculates population count a.k.a. Hamming weight, and then iteratively arrive at one of the efficient implementations that's in common use today.