Decoding Encoders: How Neural Networks 'Map' Reality

I want to delve into some more technical interpretations in the future about monosemanticity, the curse of dimensionality, and so on. Although I worried that some parts might be too abstract to understand easily for non-technical people, so I wrote a quick intro to ML and encoders as a stepping stone to those topics.

Its purpose is not necessarily to give you a full technical explanation but more of an intuition about how they work and what they do.

Thought it might be helpful to some people here as well who are just getting into ML; hope it helps!