Stephen Wolfram

But in this kind of computational world, there is a very definite definition of does it understand, which is could it be turned into this symbolic computational thing from which you can compute all kinds of consequences?

And that's the sense in which one has sort of a target for the understanding of natural language.

And that's kind of our goal is to have as much as possible about the world that can be computed in a reasonable way, so to speak, be able to be sort of captured by this kind of computational language.

That's kind of the goal.

And I think for us humans, the main thing that's important is as we formalize what we're talking about, it gives us a way of kind of building a structure where we can sort of build this tower of consequences of things.

If we're just saying, well, let's talk about it in natural language, it doesn't really give us some hard foundation that lets us build step-by-step to work something out.

It's like what happens in math.

If we were just vaguely talking about math, but didn't have the full structure of math and all that kind of thing, we wouldn't be able to build this big tower of consequences.

In a sense, what we're trying to do with the whole computational language effort is

is to make a formalism for describing the world that makes it possible to kind of build this tower of consequences.

Well, so Wolfram Alpha, what it does, its kind of front end is turning natural language into computational language.

Yeah, right.

And it turns into, you know, what's the distance between, you know, Chicago and London or something?

Yeah.

And that will turn into, you know, geodistance of entity, city, you know, et cetera, et cetera, et cetera.

Each one of those things is very well defined.

We know, you know, given that it's the entity, city, Chicago, et cetera, et cetera, et cetera, you know, Illinois, United States, you know, we know the geolocation of that.

We know its population.

We know all kinds of things about it, which we have, you know, curated that data to be able to know that with some degree of certainty, so to speak.

And then...