Rob Wiblin

But we think that current models, which don't have this structure where there's verified claims that they're predicting, we think that they nonetheless represent truth internally because that's useful to the thing that they're doing.

But in this case, it doesn't work that way.

So what we could do instead is we'll put in a whole bunch of verified facts in like maths and computer science and I guess the hard sciences.

And then in like areas like geopolitics and psychology, maybe there'll be like very few verified things, but at least it has the concept of like, here's like verified things versus statements.

And then it will port that across.

And I guess it will assign credibility to different sources.

It will learn to like have some sense of who's truthful versus not.

And then like-

try to generalize out of distribution into these other areas.

So I could see it, so imagining a model where we've trained on lots of verified facts in hard sciences where we feel we're on stronger terrain.

And I guess it learns it wants parsimony, it wants like good sources, it wants coherence.

I could see that generalizing well out of distribution to other areas like psychology, or I could see it completely falling apart.

Do we have a sense of whether it would generalize well to other areas?

You said that you think the scientists at AI actually might be more capable because it's more trained on actually understanding the truth.

I guess I'm a little bit skeptical of that because it seems like if that were true, the companies would be more invested in this approach.

That'd be just like throwing more money at it, having more people work on it.

Do you think they're just making a mistake there?

So there's a sense in which for one of the leading companies, Anthropic OpenAI, it's not very attractive to make a bet on this, to divert 20% of your staff onto this, because if it's a bust, then you would fall behind basically your main competitor.

For a company that's currently way behind, that feels like it's losing on the dominant paradigm, there's a certain attraction to making a bet on something very different, because it could suddenly leapfrog you ahead if it turns out that it's a massive success.

Do you think there's any chance of convincing one of the