I found the opening quote of this article to be intriguing, especially since it was from a 1992 research lab:

“One year of research in neural networks is sufficient to believe in God.” The writing on the wall of John Hopfield’s lab at Caltech made no sense to me in 1992. Three decades later, and after years of building large language models, I see its sense if one replaces sufficiency with necessity: understanding neural networks as we teach them today requires believing in an immanent entity.

Blog title: Solomonic learning: Large language models and the art of induction

Dark times for science when such quotes are thrown as legitimate.

The article is extremely technical and doesn't really explain the quote other than acknowledging that there are stuff we don't understand yet.

And really, a person will never grasp machine learning and AI as long as they keep drawing unbased parallels to humans and machines.