Abstraction is a compression algorithm for a computationally bounded agent, I don’t see how it is related to a “goal”, except insofar as a goal is just another abstraction, and they all have to work together for the agent to have a reasonable level of fidelity of the internal map of the world.
Yes, abstraction is compression, but real-world abstractions (like trees, birds, etc.) are very lossy forms of compression. When performing lossy compression, you need to ask yourself what information you value.
When compressing images, for example, humans usually don’t care about the values of the least-significant bits, so you can round all 8-bit RGB intensity values down to the nearest even number and save yourself 3 bits per pixel in exchange for a negligible degradation in subjective image quality. Humans not caring about the least-significant bit is useful information about your goal, which is to compress an image for someone to look at.
I think it’s not a coincidence that the high-order bits are the ones that are preserved by more physical processes. Like, if you take two photos of the same thing, the high order bits are more likely to be the same than the low order bits. Or if you take a photo of a picture on a screen or printed out. Or if you dye two pieces of fabric in the same vat.
I’m not saying you couldn’t get an agent that cared about the low-order bits and not the high-order bits, and if you did have such an agent maybe it would find abstractions that we wouldn’t. But I don’t think I’m being parochial when I say that would be a really weird agent.
The argument given by the OP seems valid to me … that is the reason to believe that abstractions relate to goals.
Goals are not abstractions in the sense of compressions if an existing territory. When Kennedy asserted a goal to put a man on the moon, he was not representing something that was already true
Abstraction is a compression algorithm for a computationally bounded agent, I don’t see how it is related to a “goal”, except insofar as a goal is just another abstraction, and they all have to work together for the agent to have a reasonable level of fidelity of the internal map of the world.
Yes, abstraction is compression, but real-world abstractions (like trees, birds, etc.) are very lossy forms of compression. When performing lossy compression, you need to ask yourself what information you value.
When compressing images, for example, humans usually don’t care about the values of the least-significant bits, so you can round all 8-bit RGB intensity values down to the nearest even number and save yourself 3 bits per pixel in exchange for a negligible degradation in subjective image quality. Humans not caring about the least-significant bit is useful information about your goal, which is to compress an image for someone to look at.
I think it’s not a coincidence that the high-order bits are the ones that are preserved by more physical processes. Like, if you take two photos of the same thing, the high order bits are more likely to be the same than the low order bits. Or if you take a photo of a picture on a screen or printed out. Or if you dye two pieces of fabric in the same vat.
I’m not saying you couldn’t get an agent that cared about the low-order bits and not the high-order bits, and if you did have such an agent maybe it would find abstractions that we wouldn’t. But I don’t think I’m being parochial when I say that would be a really weird agent.
The argument given by the OP seems valid to me … that is the reason to believe that abstractions relate to goals.
Goals are not abstractions in the sense of compressions if an existing territory. When Kennedy asserted a goal to put a man on the moon, he was not representing something that was already true