Speaker unverified: belief

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…Yes. Because I guess for you, reading your work, you said that if know, if we wanted to create AGI, it would be something that looked like a scientist. Because you know, if we frame it at the right level, a scientist can generate hypotheses, and you know, they're they're an agent. They can act in the world. You know, they're embedded in in environment. So you're framed at a at a sort of sufficient level of embedding that you can actually capture the dynamics of the system. And and in that respect, I'd say it is an agent. And it has this principle of compression. And actually, maybe you can contrast it to active inference. Because that's quite similar. It's about this agent that balances energy and entropy. So sort of like predictive control and simplicity in some so called natural way. How is that different from ICSI? 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.…

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