Got a source?

I'm not OP, but I'm guessing he could be referring to something like this talk? https://www.youtube.com/watch?v=LrVi9LHP8Bk

I'm honestly not sure otherwise.

I think OP is talking about ML and matrix (array) multiplication to learn the right weights in a neural network.

This is a lecture series, not new research, but one of the main takeaways is if you want good performance on modern machines, you had better be using arrays: https://youtube.com/playlist?list=PLHxtyCq_WDLXFAEA-lYoRNQIe...

Surely it’s the interesting things built on top of the arrays?

Are you talking about Vector DB's?

Also ECS / columnar data?

When skirt lengths change and we observe no measurable change in human anatomy, that's fashion and to follow fashion is "hip".

When the computing platform changes and you have to start paying attention to L-level caches and counting your bytes (so you can do you big compute in memory), and use n cores, and then arrays are adopted, that is not fashion; so not "hip", rather modern.

Isn't everything since the Renaissance considered modern?

touche. Exactly so, just like how every political system going forward will be "democratic". /g

Interesting and similar here is that there are a bunch of algorithms from days of yore that made sense with performance back then, but these days where the CPU absolutely doesn't care whether it's comparing a single byte or 32 bytes at once this can shift some algorithms towards much simpler ones. E.g. for substring searches this page is rather interesting: http://0x80.pl/articles/simd-strfind.html which posits that some of the older algorithms were built with the assumption that comparing parts of memory is more expensive than a table lookup, which is in many cases no longer true.