Tim Scarfe: belief

Transcript context

…Oh, I mean, they're very different formalisms. I would love to see someone try to do active inference ICSI. But it's just I guess active inference has a simplicity bias built into it. There's a regular but the focus is more on explaining something else. Also I think active inference is more Okay, so there's a whole bundle of ideas there. You've the free energy principle, you've got active inference, you've got all this stuff about Markov blankets and maintaining the border of an organism, and having an internal and external world. The targets are kind of different. I think that's fair. We have an agent, And the agent is doing prediction in the environment. And they can act and so on. And they are both, in some sense, I'd say, and active inference, trying to produce a simple model. Right? So there's this assumption or principle, if you like, that simplistic models, if they predict well, must be good. Yeah. Yeah. And this is a very popular, almost orthodox assumption to make, because Occam's razor does kind of work. But even as far back as 10 years ago, there were people pointing out that this assumption is based on, you know, what I mean, something like Solomonoff induction does it it performs reliably within within bounds based on the original assumptions. But once you put it in an interactive setting, like with ICSI, now you've got the subjective notion of complexity that the agent has, which is used for its version of simplicity because it's it's sort of perceiving the world through an interpreter. In the case of, actually, a universal Turing machine. But you can think of it as just just think of it as an instructionally, like a language. When say something in a language, how long it takes me to say it depends on the language I use. If I have some memetic single syllable word to describe a complicated concept, then the length of that concept is 1 in my language. And sort of my subjective world, that's fine. But if I have an external world that assesses complexity, in the case of IACSU, this is sort of like looking at leg hunter intelligence, which is sort of a measure of intelligence measuring the intelligence of an agent based on the complexity of the model it comes up with. It's got a different concept, a different sort of you know, it it the you can make these you can make it perform arbitrarily well or arbitrarily poorly by sort of shifting the goalposts of interpretation. You can make it so that if if I am to, you know well, yeah. You can essentially make simplicity completely disconnected from performance if you like. Not that that actually happens in reality. That's like it's not so cut and dried, but it's it's certainly not optimal, which is, I think, what a lot of people were hoping for with the original…

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