[jerf]

It is not clear to me that you realize that Solomonoff induction is a mathematical argument, not a practical algorithm. To run it at the level of generality necessary to discover the laws of physics is computationally infeasible. In fact, it's one of those cases where calling it "computationally infeasible" is an inadvertent understatement of the problem, because English doesn't have gradations for this level of difficulty. Merely a "singularity" doesn't help this problem; you need more computation than our physics appears to allow.

[ad510]

Yes, I know that Solomonoff induction is completely impractical for real life machine learning. My point was that if you can survive in the simulation to the point where you see either the 0 or the 1, we don't have any way even in theory (let alone in practice) to guess the probabilities of seeing a 0 or 1, unless you use some sort of learning algorithm. You can use any learning algorithm for this; it doesn't have to be Solomonoff induction.

[jerf]

But your argument seems to fundamentally rest on Solomonoff induction. Put any real algorithm in there, and now you need to ensure that 1. the biases of the algorithm encompass a hypothesis that matches the data and 2. the algorithm will be able to arrive at that hypothesis given a real data stream, and, ideally, a real amount of computation. Both of these are hard questions, in the strongest sense of the term.

And once you open that door, well, all you've really done is restate the fact that learning how the universe works seems to be really difficult.

[ad510]

OK, I see what you're saying now. In that case, can you think of a better way of predicting whether you see a 0 or 1 in that situation?

[jerf]

If I had an answer to that question, I probably wouldn't be putting it on HN. :) I'd be firing it at the market and making boodles of moolah.

[kordless]

I would note that "computation" is work done over time. Causality.

There may exist an alternate form of causality that isn't time bound, which may be exposed here over short periods of time. I would hesitate to judge it "computationally infeasible" until we know more. :)

[jerf]

I think it's important to distinguish arguments that hypothesize that our understanding of physics is fundamentally, deeply flawed, from arguments that are based on our current understanding of physics. I can't prove that our understanding of physics isn't deeply flawed and there isn't some source of infinite computation somehow available to us; for instance, one proposed explanation of the Fermi Paradox is that all civilizations escape to a physics/computation regime more congenial to civilization before colonizing the galaxy. But it's still important to know when we're engaging in flights of fancy vs. speculating based on what we know.

And given that the topic in question is plumbing the depths of physics in the first place, this is perhaps a notch more important than it might otherwise be. How would we discover that physics has an infinite/acausal computation mechanism if we first must use Solomonoff induction to discover that, when we can only afford to use Solomonoff induction to discover that if we harness that computation?

[kordless]

Well, there are things we know and things we will know. If we take the hypothetical "all knowing I", we assume it has zero security and all knowledge (wisdom). With individuals, we have high security (you can't know what I'm thinking) and low wisdom. So, knowledge plays a part in all this, as is evident of the result of causality. There's a sutra that deals with this concept as well.

I have a hypothesis that reality is backed by a blockchain data structure, which is why it's robust and fairly immutable. One might create a simple reality based on a blockchain data structure and then attempt to model causality/matrix rotations with that structure in such a way that the behavior of "gravity" noted in a gyroscope can be observed to not occur, given the nature of the scientific method. i.e. model rotations in a blockchain without generating gravity/precision and you've disproved my hypothesis.

The correlation with this test and reality would be allowing brief access to a "search" across all knowledge (which could be optimized behind the scenes) and then allow that knowledge to exist until the block is closed, at which point you are left with whatever gets closed in the block and the resulting forces that have to occur to rationalize the rotation. Rinse and repeat.

Probably doing a horrible job of explaining it. First time I've really written it down.