I can't help but read MLP as my little pony and now I'm picturing you training a series of marshmallow horses to pretend to be human for the profits of our corporate overlords on social media.

Right, if I understood it correctly, what you see as "IF" is the multi-headed attention stuff. I was under the impression that you can't actually have non-contiguous functions there so even multi-headed attention stuff involves functions which don't have +/- infinity in their first derivative - they can boost or suppress inputs but they don't have the hard YES/NO transitions of logical IF.

However the Genetic Algorithms stuff is something completelly different from Neural Networks: it's basically an Evolutionary method of finding the best "formula" to process inputs to generate the desired outputs by assessing different variants of the "formula" with the training data, picking the best ones and then generating a new generation of "formula" variants from the best ones and assessing those and keep doing it until the error rate is below a certain value - it's basically a way of using "Natural" Selection for mathematical formulas.

As far as I can tell Genetic Algorithms can't really scale to the size of something like an LLM (the training requirements would be even more insane) though I guess that technique could be used to train part of a Neural Network or to create functional blocks that worked together with NNs.

And yeah, MLPs trained via simple Backpropagation are exactly what I'm familiar with, having learned that stuff 3 decades ago as part of my degree when that was the pinnacle of NN technology and model architectures were still stupidly simple. That's why I would be shocked if a so-called ML "expert" didn't recognize that, as it's the most basic form of Neural Network there is and it's being doing the rounds for ages (that stuff was literally used to in automated postal code recognition in letters for automated mail sorting back in the 90s).

I would expect that for people doing ML a simple MLP is as recognizable as binary is for programmers - sure people don't work at that level anymore, but at they should at least recognize it.

On which end of the curve? before or after the mount Dunning-Kruger?

Thank you

LLM models or ML in general? i've only known folk who worked on ML, not actually done it myself

Regarding "white genocide" in South Africa, some claim it’s real, citing farm attacks and "Kill the Boer" as evidence. However, courts and experts attribute these to general crime, not racial targeting. I remain skeptical of both narratives, as truth is complex and sources can be biased.