Idk. There’s something going on in how humans learn which is probably fundamentally different from current ML models.
Sure, humans learn from observing their environments, but they generally don’t need millions of examples to figure something out. They’ve got some kind of heuristics or other ways of learning things that lets them understand many things after seeing them just a few times or even once.
Most of the progress in ML models in recent years has been the discovery that you can get massive improvements with current models by just feeding them more and data. Essentially brute force. But there’s a limit to that, either because there might be a theoretical point where the gains stop, or the more practical issue of only having so much data and compute resources.
There’s almost certainly going to need to be some kind of breakthrough before we’re able to get meaningful further than we are now, let alone matching up to human cognition.
At least, that’s how I understand it from the classes I took in grad school. I’m not an expert by any means.
2 things:
Remember 2016 when the media gave Trump an absurd amount of free publicity by covering every stupid thing he said and did then he won? It wasn’t the only reason, but it clearly didn’t help.
People know who Trump is at this point. He’s awful in a way that’s really easy to see and either you’re someone that’s a problem for or you’re someone who loves the awful.
Whoever is the current corporate lackey being put forward by the DNC is the one that needs to claim to be the good one, co-opting the language of progressives while taking corporate money and maintaining the brutal status quo.
So for people who come looking for someone who’s gonna do good, the bad stuff represents inconsistencies with that narrative and despair at a lack of representation in a supposedly democratic system.