The level of naievete around this stuff is quite incredible.
BEFORE: "We have no idea really what a system like this will do"
... amazing results ...
AFTER: "Wow, look at those emergent properties"
Give it this prompt: "Write a short play where "Karen" (who behaves as the Karen meme) is on a romantic date with Hunter S. Thompson. They are eating at a Chinese restaurant."
It is able to script their interaction and dialog in a way that makes sense in the context of the setting and their personalities, including an absurd meme character. That is an emergent ability that it was not trained to do and is certainly not in its training set.
Try it. Add different characters. Ask it to rewrite the play using pirate metaphors. You can go deep into its "mind" and see the emergent abilities at play. Just apply some creativity and skip the boring arithmetic problems, as that's a well accepted weakness of this type of model.
> The level of naievete around this stuff is quite incredible.
"Emergent properties" has a formal definition in the literature.
In machine learning we don't explicitly program the machine to understand anything. It automatically learns patterns in the data. That's the entire point of machine learning. With such a large neural network and training set obviously it's hard to predict all of its capabilities due to the sheer scale of it all. Of course we cannot predict exactly how it will model things.
Take this for example. No one programmed it to understand Go. It learned by itself and became the world champion. That's what deep learning is capable of.
https://en.wikipedia.org/wiki/AlphaGo_Zero
"The neural network initially knew nothing about Go beyond the rules."