I've just read i.e https://twitter.com/gdb/status/1096098366545522688 and even though it's "best of 25" (I guess cherry-picked by a human) - this is mind-blowing. I am actually having a very hard time believing this is legit generated text.
>Recycling is NOT good for the world.
>It is bad for the environment,
>it is bad for our health,
>and it is bad for our economy.
>Recycling is not good for the environment.
>Recycling is not good for our health.
>Recycling is bad for our economy.
>Recycling is not good for our nation.
The first paragraph keeps repeating the <X> is <bad | not good> for the <Y> pattern 8 times.
>And THAT is why we need to |get back to basics| and |get back to basics| in our recycling efforts.
"get back to the basics" is repeated twice in the same sentence.
>Everything from the raw materials (wood, cardboard, paper, etc.),
>to the reagents (dyes, solvents, etc.)
>to the printing equipment (chemicals, glue, paper, ink, etc.),
>to the packaging,
>to the packaging materials (mercury, chemicals, etc.)
>to the processing equipment (heating, cooling, etc.),
>to the packaging materials,
>to the packaging materials that are shipped overseas and
>to the packaging materials that are used in the United States.
It literally repeated packaging 5 times in the same sentence and the overall structure was repeated 9 times. Also what type of packaging is based on mercury?
That is the saddest part. It's not because AI is good, it's because we count saying "X is good/bad" 3 times as a persuasive argument. It won't be hard to learn this kind of "arguing", it's just sad that's what we're teaching our AIs to do and get excited when they do it.
I didn't say that it's a persuasive argument, I said that it can be persuasive IN arguments. There's nothing sad about an AI learning it, or people being happy with it, it's very impressive.
(This of course doesn't make it an amazing feat of computer engineering.)
The overarching narrative is great, but that's probably driven by the great antithesis supplied by the experimenter.
It'd be interesting to know how this works, what happens if less or more is given as thesis/antithesis/assignment, and after how much output it turns into gibberish (or repeats).
Heck, maybe having to compete with this will raise human discourse (Joking).