To put it real lightly, it's a real stretch to make any kind of analogy between the human brain does work and the way that semiconductor based processors do wor

To put it real lightly, it's a real stretch to make any kind of analogy between the human brain does work and the way that semiconductor based processors do work. The author's reference to Stephan Wolfram's idea of universality (developed in a prior essay) seems unfortunate: >“The key unifying idea that has allowed me to formulate the Principle of Computational Equivalence is a simple but immensely powerful one: that all processes, whether they are produced by human effort or occur spontaneously in nature, can be viewed as computations.” To borrow a metaphor from a recent HN thread about an eponymous paper called "How to recognize AI snake oil" [1], there's an "incomplete and crude but useful breakdown" on you can apply towards AI problems: genuine and useful progress in perception, imperfect but improving work in automating judgment, and fundamentally dubious attempts to predict social outcomes. Let's think about where the idea of a theory of mind based on computational complexity to determine "smartness" lands -- it's certainly not stimulus detection, it's certainly not automating judgment, but it is about predicting or modeling social outcomes. I would say that this application Wolfram's idea is fundamentally dubious. Because of this, it's hard for me to say that the premise, argument or conclusion of this essay is anything but fundamentally dubious. To at least leave a useful suggestion: this essay is missing an adequate definition and exploration of what "smart" is, why it's a facet of human nature and history, and what issues the concept causes. To the author, I'd recommend starting off by building a better foundation there before jumping to conclusions that are hard to take seriously. [1] https://news.ycombinator.com/item?id=21577156 https://news.ycombinator.com/item?id=21577156