Terence Tao

It's a great question.

We may not have enough.

The bottleneck is not math.

So there is a science like if there's competing hypotheses explaining the world, so you're in a simulation or the universe was created by a deity or whatever.

There's a branch of statistics called Bayesian probability, which can help you guide which of these outcomes is more possible.

You have to lay out all the possible scenarios that could be true, assign some prior probability to each being true.

And then take all the data that you have.

And there's a formula that allows you to take for every observation that you have, update.

So some data confirms some theories and makes their probability go up.

And some

some data makes some theories less likely and that probably goes down.

And in principle, if you are very if you could compute everything you could, you could end up with and say, Oh, now I'm 20% confident I'm in simulation or or 80% that the universe is real or whatever.

But the problem is that we don't know all the possible different

types of universes that could happen.

And we don't know what their prior probabilities are.

And there's just so many of them, we can't compute how many of them would replicate a world that looks like ours.

So while people attempt to do these calculations, there's just so many gaps and sort of implicit biases in how you choose which universes, you know, maybe some hypotheses you have implicitly set up to fail, or some that you're biased to make succeed.

Isn't that the argument?

Right.

So you could never rule out a hypothesis with 100% certainty, because whatever data you have collected could itself be faked, as you said.