Rob Wiblin

Whereas your models, they'll be primarily oriented towards figuring out what is true, how does the word work, and then they would learn to understand what people might say as a side effect of that incidentally.

Is that definitely true?

Because it seems like they don't buy into conspiracy theories that much currently.

They don't say that the world is flat just because many people, I don't know.

I feel like the discussion about this proposal last year got, I think, more focused on the mathematical, theoretical guarantees, discussion of the safety guarantee side.

And it feels like you're moving, and it seems like I feel like probably we should move towards a scrappy 80-20.

This is going to probably be safer.

We have good reasons to think it's better.

Let's just throw something out and see how it goes and work from there, iterate from there.

Yeah, you agree?

I think for many people who are less into AI or computer science, a concern that might immediately jump out at them about this entire proposal is the idea of we're going to build a database of things that we think are verified facts that are ground truth that we're going to be aiming at.

It's the kind of thing I feel would give people who are trained in the humanities a bit of a heart attack, the idea that we have some corpus of things that we're absolutely sure are true.

In some philosophies, there's nothing that we're really confident about, or at least in the areas that we're most interested in, things seem highly contested and uncertain.

Is that a big problem for the proposal, or is close enough is good enough?

If we mostly put in things that we're mostly confident about, then it approximates it and it can see through any errors in there, as long as it's not massively systematically biased in what you've put in as verified.

This is something I'm very sure about.

So could you train a scientist AI of this type with no verified claims in the database?

No.

You can't.

It has to have that.