GPT-3 uses sequences to 'predict' what word comes next.

You could probably train it to predict the weather by training it with a database of sequences of weather events and it should output the most likely to happen next based on past reference.

This principle should in theory work for everything as long as your database accurately describes the events in an understandable sequence of text.

This is what I’m getting at: could we start extremely simple, and scale up from there until we have a future prediction tool

Of course. Kind of naive question. It is one of their main uses. What will the user click next, what will the weather do, how will nuclear fusion behave, how will the stock market move, will the car in front of you brake, etc.

Not the same as actually predicting the future calling it a prediction is marketing

If you're thinking going towards capabilities even remotely approaching Laplace's daemon ( even just for tiny chunks of the universe like the weather of city x ) then sadly ( or not ? ) that kind of assurance is way too computationally expensive and requires datasets no one can assemble.

However, a lot weaker variants may be possible, for that I don't know enough.

SPOILER

>!That said, in the tv show Devs they got it to work, lol.!<

literally all examples I gave predict the future