> An alarming number of people don't understand that LLMs work via purely stochastic processes ...

I've been studying AI for 20 years. What really needs to be added to this statement is:

"An alarming number of people don't understand that LLMs work via purely stochastic processes - and so does human thinking. People do NOT arrive at the same conclusion if merely the weather's different. Worse: with human thinking not only do most people not think this is real, a subset of people will actively fight the idea. Of course, depending on the weather"

The same person is not going to give you three different answers within span of minutes. Especially when nothing fundamentally has changed. People might or might not update their views depending on their biases.

What's even worse, different humans have different weights.

If you train two different LLMs and replace what data they "see" in batch n, that doesn't affect the data they see in batch n+1, or any further batches. In LLMs, you can introduce "noise" into the training process, but that noise doesn't really compound.

Humans learn from experience, not from data, and their experiences at age n shape what experiences they seek (and hence train on) at age n+1. A small amount of "noise" injected into their "training", let's say hearing a group of friends discuss a movie while their identical tween goes to the bathroom, can compound into them watching that movie, which can compound into them forming an identity around that genre, and so on, until they're two completely different people, trained on completely different "data mixtures".

We expect computers to be consistent on the other hand. A calculator will always give you the same answer unless some chip gets struck by a particle. LLMs are on computers and should be fairly consistent too.

Test retest reliability is a thing in psychometrics.

a studied example is sampling judicial decisions before lunch and after lunch. judges are more lenient on a full stomach.