[michaelerule]

I think part of the mystery is that computers can copy binary information losslessly, ad infinitum. So they can move information as often as needed with (almost) no error. We don't think neurons are as reliable, and excessive copying is expected to degrade a memory/representation. It seems like this might work for discrete categorical representations, whose activation is essentially binary, but would gradually fail for anything analog/continuous.

[retrac]

If the computational hypothesis for minds and brains is true, and it is only conjecture though a tempting one, I can only see one way out. Analogies are a wicked thing to indulge in here. But bear with me.

If an engineer designs a computer that computes on encrypted information, from an observer's naive perspective, the entire contents of memory is rewritten with a random value for each step. Yet there is a mathematical relationship between those seemingly random bits and whatever is encoded. Even just using some error correction and non-deterministic parallel processing and it might look pretty much like noise if you don't have the decoder ring.

Something like that is the only explanation I can come up with. Information is stored at a level of abstraction in a structure that is maintained by being continuously re-encoded in the ephemeral computations at a lower level.

[michaelerule]

If I understood correctly, I think I agree with your loose analogy. I've tried combining some error correction with ongoing re-learning. It stabilizes things against drift, but not indefinitely. This is all in an extremely preliminary cartoon sketch of a model. https://www.biorxiv.org/content/10.1101/2021.03.08.433413v1....

[jakeogh]

Digital abstractions seem practically worthless when the hardware is not explicitly designed to suppress non binary behavior.

Perhaps analog FPGA's are interesting windows https://news.ycombinator.com/item?id=23432601

[kevin_thibedeau]

The Xilinx 6200 series could safely run randomized bitstreams without damaging itself. Genetic algorithms could be applied to create circuits that worked despite being riddled with what would normally be fatal design flaws.

[Barrin92]

Considering that mystifying presupposes that the function of the brain is to represent lossless or perfect memories in a static way, rather than say, maintain coherence or consensus across experiences. It's not clear at all that altering or evolving memory is bad for the system overall.

It might very well be a feature of this drift that old memories or information is gradually adapted. After all evolutionary speaking you wouldn't expect the brain to optimize for archiving but for making fitness optimizing decisions in the world.

[notahacker]

But human representations do degrade to the extent we forget detail, and also the information changes (sure, the odour might be the same and the experimental controls perfect, but an organism probably should change how they process it over time "new, unfamiliar odour", "smelt that yesterday"... "wonder if anything's happening related to that odour which emerged recently", "meh, background odour") so some of the information update is additive