I think dust theory is wrong in the most permissive sense: there are physical constraints on what computations (and abstractions) can be like. The most obvious one is “things that are not in each others lightcone can’t interact” and interaction is necessary for computation (setting aside acausal trades and stuff, which I think are still causal in a relevant sense, but don’t want to get into rn). But there are also things like: information degrades over distance (roughly the number of interactions, i.e., telephone theorem) and so you’d expect “large” computations to take a certain shape, i.e., to have a structure which supports this long-range communication such as e.g., wires.
More than that, though, I think if you disrespect the natural ordering of the environment you end up paying thermodynamic costs. Like, if you take the spectrum of visible light, ordered from ~400 to 800 nm and you just randomly pick wavelengths and assign them to colors arbitrarily (e.g., “red” is wavelengths 505, 780, 402, etc.), then you have to pay more cost to encode the color. Because, imo, the whole point of abstractions is that they’re strategically imprecise. I don’t have to model the exact wavelengths of the color red, it’s whatever is in the range ~600-800, and I can rely on averages to encode that well enough. But if red is wavelengths 505, 780, 402, etc., now averages won’t help, and I need to make more precise measurements. Precision is costly: it uses more bits, and bits have physical cost (e.g., Landauer’s limit).
I guess you could argue that someone else might go and see the light spectrum differently, i.e., what looks like wavelengths 505 vs 780 to us looks like wavelengths 505 vs 506 to them? But without a particular reason to think so it seems like a general purpose counterargument to me. You could always say that someone would see it differently—but why would they?
A footnote to information degrades over distance that you might be interested in:
Usually long-range correlations are small (‘information degrades over distance’), both over distance and scale. But not always. In very special situations long-range correlations can be large both over distance and over scale. I.e. the proverbial butterfly wingclap that causes a hurricane at the other side of the world.
in solid-state physics, condensed matter and a number of other fields people are interested in phase transitions. During phase transitions long-range correlations can become very large.
There is some fancy math going under monickers like ‘conformal field theory, virasoro algebra’ iirc. I know nothing about this but @Daniel Murfet might be able to say more.
I think dust theory is wrong in the most permissive sense: there are physical constraints on what computations (and abstractions) can be like. The most obvious one is “things that are not in each others lightcone can’t interact” and interaction is necessary for computation (setting aside acausal trades and stuff, which I think are still causal in a relevant sense, but don’t want to get into rn). But there are also things like: information degrades over distance (roughly the number of interactions, i.e., telephone theorem) and so you’d expect “large” computations to take a certain shape, i.e., to have a structure which supports this long-range communication such as e.g., wires.
More than that, though, I think if you disrespect the natural ordering of the environment you end up paying thermodynamic costs. Like, if you take the spectrum of visible light, ordered from ~400 to 800 nm and you just randomly pick wavelengths and assign them to colors arbitrarily (e.g., “red” is wavelengths 505, 780, 402, etc.), then you have to pay more cost to encode the color. Because, imo, the whole point of abstractions is that they’re strategically imprecise. I don’t have to model the exact wavelengths of the color red, it’s whatever is in the range ~600-800, and I can rely on averages to encode that well enough. But if red is wavelengths 505, 780, 402, etc., now averages won’t help, and I need to make more precise measurements. Precision is costly: it uses more bits, and bits have physical cost (e.g., Landauer’s limit).
I guess you could argue that someone else might go and see the light spectrum differently, i.e., what looks like wavelengths 505 vs 780 to us looks like wavelengths 505 vs 506 to them? But without a particular reason to think so it seems like a general purpose counterargument to me. You could always say that someone would see it differently—but why would they?
A footnote to information degrades over distance that you might be interested in:
Usually long-range correlations are small (‘information degrades over distance’), both over distance and scale. But not always. In very special situations long-range correlations can be large both over distance and over scale. I.e. the proverbial butterfly wingclap that causes a hurricane at the other side of the world.
in solid-state physics, condensed matter and a number of other fields people are interested in phase transitions. During phase transitions long-range correlations can become very large.
There is some fancy math going under monickers like ‘conformal field theory, virasoro algebra’ iirc. I know nothing about this but @Daniel Murfet might be able to say more.
see also: https://en.wikipedia.org/wiki/Self-organized_criticality, sandpiles