[bloody_bocker]

> When people who can’t think logically design large systems, those systems become incomprehensible. And we start thinking of them as biological systems. And since biological systems are too complex to understand, it seems perfectly natural that computer programs should be too complex to understand.

For some time I've been drawing parallels between ML/AI and how biology "solves problems" - evolution. And I also am bit disappointed by the fact the future might lead us in a different direction than mathematical elegance of solving problems.

[MBCook]

I really loved that quote in the article. It’s such an excellent description of the “computer voodoo“ users come up with to explain what is, to them, unexplainable about computers.

You’re right though, we’re basically there with AI/ML aren’t we. I mean I guess we know why it does the things it does in general, but the specific “reasoning“ on any single question is pretty much unanswerable.

[l33tbro]

Are you able to share what these parallels are that you've drawn? I've always thought them to be slightly different processes.

[bloody_bocker]

Evolution: optimization done by selection, result is the DNA, that does amazing (we can't match that with traditional programming) things but it's bloody hard to decipher.

Neural network: created via training, does amazing things but (this is the area my knowledge is too small) it's bloody hard to decipher why is it doing the thing it does.

"Traditional" programming: you can (as in article) explain it down to the single most basic unit.