Michael C Hogan

Agile Product Development & Innovation Strategy


Checkout the source code for the Apollo moon mission

Resharing a link I discovered through the Adafruit blog

The AGC’s source code is an excellent example of organising a large and complex codebase. Written in an assembly language, the code is impressively well-structured. Tasks are split into separate modules and routines for better maintainability, a practice that is even more vital in today’s complex software projects.



Hogan Test for AI

In order for a program to be considered intelligent the following questions must be answerable with a ‘yes’.

  • Is the output of the program passable as human work?
  • Can the program cite sources inline and create a bibliography of works cited?
  • Can the program explain the reasoning behind its conclusions?
  • Can the program respond “I don’t know” when it doesn’t know the answer to a question?
  • Can the program explain its limitations?
  • Can the program propose a conclusion that is not present in the training data used to create it?

Disclaimer: I’m an AI novice and may be completely wrong about the conclusions presented in this article. Over the past few years I’ve dabbled in machine learning. I’ve watched introductory videos explaining the underlying concepts, trained an R/C car to drive itself using computer vision, generated art, and experimented with ChatGPT.