To me it often if feels like South American countries themselves are stuck in an eternal pendulum of electing corrupt left-wing populists after corrupt right-wing populists and swinging back again.
That's representative democracy. There's not really any practical ways to delegate power without enabling corruption, so corruption is more or less inevitable without radical levels of transparency and public oversight.
No, you aren't the only one, however I know from my uncle who used to do this that it will most likely mean back-breaking work or paid measly (sometimes both), hardly enough to feed a family.
But it's a funny image of usually quiet forests now crawling with former software devs looking for a new purpose.
The least they could do, after ruthlessly bombarding my employer's servers with requests, ignoring the robots.txt, scraping everything, and incurring significant Google Maps costs for us in the process.
I have heard that this is called the Benjamin Franklin effect, and it appears to be an inversion of the principle of reciprocity coined by Robert Cialdini.
Reading this thread makes me wonder if I'm the only one who really tried to learn to juggle, only to fail even after a whole month of brute-forcing it, while my partner at the time, who started at my suggestion, managed it after 30 minutes! That was 15 years ago...
People have tried to suss this out on the ML subreddit, and it is confusing. Most of the worst messages from Tay were just people discovering a "repeat after me: __" function, so it's hard just to figure out which Tay messages to consider as responses of the model.
There seems to have been interest in a model which would pick up language and style of its conversations (not actually learning information or looking up facts). If you haven't trained an LSTM model before - you could train on Shakespeare's plays and get out ye olde English in a screenplay format, but from line to line there was no consistency in plot, characters, entrances and exits, etc. in a way which you'd expect after GPT-2. Twitter would be good for keeping a short-form conversation. So I believe Tay and the Watson that appeared on Jeopardy are more from this 'classical NLP' thinking and not proto-LLMs, if that makes sense.
