Stephen Wolfram
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But it's worth understanding kind of how that's working.
I mean, it's kind of like if it was going to say, you know, the cat sat on thee, what's the next word?
Okay, so how does it figure out the next word?
Well, it's seen a trillion words written on the internet.
And it's seen, the cat sat on the floor, the cat sat on the sofa, the cat sat on the whatever.
So its minimal thing to do is just say, let's look at what we saw on the internet.
We saw 10,000 examples of the cat sat on the.
What was the most probable next word?
Let's just pick that out and say that's the next word.
And that's kind of what it, at some level, is trying to do.
Now, the problem is there isn't enough text on the internet to, if you have a reasonable length of prompt, that specific prompt will never have occurred on the internet.
And as you kind of go further, there just won't be a place where you could have trained
where you could just work out probabilities from what was already there.
Like if you say 2 plus 2, there'll be a zillion examples of 2 plus 2 equaling 4, and a very small number of examples of 2 plus 2 equals 5, and so on.
And you can pretty much know what's going to happen.
So then the question is, well, if you can't just work out from examples what's going to happen, just know probabilistic from examples what's going to happen, you have to have a model.
And this kind of an idea, this idea of making models of things is an idea that really, I don't know, I think Galileo probably was one of the first people who sort of worked this out.
I mean, it's kind of like, you know, I think I gave an example of that, the book I wrote about Chachi Biti, where it's kind of like, you know, Galileo was dropping cannonballs off the different floors of the Tower of Pisa.
And it's like, okay, you drop a cannonball off this floor, you drop a cannonball off this floor.
You miss floor five or something for whatever reason, but you know the time it took the cannonball to fall to the ground from floors one, two, three, four, six, seven, eight, for example.