I am 100% sure that some of the tweets I got back should be considered as "found"/"searched" instead of "generated". For example, I tried "bigdata", and one of the "generated" tweet is "Big data is like teenage sex: everyone is talking about it, but nobody really knows how to do it." and I believe this is not AI generated and is simply a copy of other human being's tweet.
It is said that GPT-3's parameter space is enough to encode/memorize nearly 1/3rd of it's training corpus[0] as pointed out by 'GIFtheory in another GPT-3 thread here on HN. It seems you're finding the effects of that.
Additionally I'm curious about the recursive effect of this over-fitting after more and more output from GPT-n is published on the internet and inevitably gets included in the training corpus for GPT-(n+m) as pointed out by 'jobigoud[1]. Especially as people start using GPT-like models to spam the internet. We may lack a ground-truth corpus in the future to label "human".
It would be a bit like how carbon dating or production of low background steel changed after 1945 due to nuclear testing.
Edit: actually, I think I saw this tweet: https://twitter.com/rantlab/status/1284849214653034497, and remember thinking "I bet this person just read the hn thread about low backround steel". It doesn't seem to have come up on hn other than that since the low background steel post.
There are probably already manipulation techniques in play where an actor 'plants' (or 'incept' if you will) a future post by posting a lot of things that will lead people to organically 'find' the subject they want to promote.
Someone please tell us the German word for that. There must be one. (Or maybe a French phrase.) ;-)
Clearly it wasn't as creative of an analogy as I originally thought. For myself, just a very small leap of logic after reading 'jobigoud's comment. Very surprised to see other people making it as well, and a good re-calibration for me!
1) The analogy has more symmetries between the left and right side of the analogy than most analogies, allowing people to arrive at it from many different perspectives.
2) A lack of options for the analogy - maybe there just aren't that many good examples with any real symmetries at all, so everyone who is inclined to create analogies is forced to the same one, which may or may not be particularly quality.
I'd hypothesize overall (1) will generally dominate (2) just because if an analogy is poor, I'd expect few people to come up with it even if it's the only possible analogy...it wouldn't pass the "impact"/"relevance" threshold needed to spend effort converting to a tangible form for communication.
I also think (2) may be a false mechanism given the incredible breadth of experiences everyone has. There might not be a lack for analogy targets for almost every conceivable topic.
Whereas (1) feels quite a bit more defensible overall.
That said, we're in a bubble here as 'tlarkworthy points out, so I wouldn't use this as an example.
Well, it's not close to that, but it's close enough to be amusing. Here are some questions it answered in Q&A:
https://tildes.net/~games/qmc/ai_dungeon_dragon_model_upgrad...
But I think for factual knowledge, it will need to be better about explaining where it got the information.
Seems like a case of overfitting.