3 ms·

If a computer running a probabilistic calculation got it right 90% of the time, and the next one over running the same calculation on identical hardware got it

If a computer running a probabilistic calculation got it right 90% of the time, and the next one over running the same calculation on identical hardware got it right 10% of the time, there would be something wrong with the computer. This is not true with cells.

generalizations 2y ago
Your point only stands when the percentages are exaggerated. What if it were 99.99 vs 99.999? Let's not forget cosmic ray bitflips. Just because the two machines operate at different levels of probabalistic exactitiude, does not mean they are not both machines. Do you really think modern computers are fully deterministic at the lowest levels?
- roywiggins 2y ago
  Cells behaving randomly is a fundamental part of their ordinary operation. Computers are tractable because we've done our best to engineer out the randomness and, when we can't, layer on enough error correcting codes so we can mostly not think about it. But cells don't operate on such nicely bifurcated scales (small and random vs large and mostly predictable). If they did, the dream of cellular wiring diagrams allowing cells to be understood would be a lot more achievable.
  - generalizations 2y ago
    Your example of randomness upthread was brownian motion: I'm not surprised a transport mechanism relies on stochastic behaviors. To me, that looks comparable to electrons bouncing down a wire, or minimizing quantum tunneling effects between transistor layers - random at a very low level, but averages out to the behavior we need. Put guardrails at the extremes, so the random behavior stays within bounds, within a margin of error - that's just good engineering. Compare to loggers, floating trimmed trees down a river to the sawmill: the logs bouncing down the river are behaving in an entirely random manner, but it's within bounds and doesn't matter, because they'll still make it downstream where they get caught by another system. It's a "machine" with random behaviors. Maybe this (obligatory) xkcd illustrates my point: https://www.explainxkcd.com/wiki/index.php/2916:_Machine https://www.explainxkcd.com/wiki/index.php/2916:_Machine I get the impression that what this is coming down to is massive complexity rendering the machine incomprehensible - but again, that doesn't mean it isn't a machine.
    - roywiggins 2y ago
      If sending logs down a river is a machine, couldn't that make almost anything a machine? The river itself, for instance.
      - generalizations 2y ago
        Yes, it is a mechanical system that invokes stochastic processes within deterministic bounds to accomplish a specific, complex outcome. Given sufficient knowledge, it can be mapped and its functions defined. I believe that summarizes transistors, cells, and forest-to-sawmill machines.
        roywiggins 2y ago
        Doesn't that also describe, like, plate tectonics and tornadoes? Once you expand the definition of "machine" that far, what doesn't it reach?
        generalizations 2y ago
        Vortexes absolutely have their place in fluid dynamics and mechanical design. Modern shipbuilding depends on them. If we ever manage to attempt geoengineering at the largest scale, plate tectonics would probably also come into play. Which is to say, yes: it is a system composed of comprehensible systems, which makes it, itself, a comprehensible system. And that's the whole point here: given knowledge and time, we can tease out exactly how it works.
fluoridation 2y ago
Are you saying a, for example, muscle cell that produced 10% of the contracting power of its neighbor for the same sugar cost would be perfectly healthy?
- roywiggins 2y ago
  It's not that cells can't go awry, it's that perfectly healthy, otherwise identical, cells do not behave predictably to identical stimuli, even on average. That's their normal mode of existence. Some of those behaviors are pathological (eg cancer) but mostly they're not. Computers don't behave this way at all: you can be reliably sure that if two computers produce different results with the same input that one of them is wrong. If it's a stochastic algorithm at least the averages should be within a certain bound. You can't make the same conclusion with cells.
  - quonn 2y ago
    Yes you can and the comment you responded to illustrated this very well.
    - roywiggins 2y ago
      Which stochastic algorithms produce different distributions of results on different identical machines with the same inputs, but it's not considered a bug?
      - generalizations 2y ago
        > different identical machines with the same inputs > No two cells are identical, given that no two cells respond to a stimulus in the exact same way—even if they are genetically the same. That's just begging the question.

generalizations 2y ago

Your point only stands when the percentages are exaggerated. What if it were 99.99 vs 99.999? Let's not forget cosmic ray bitflips. Just because the two machines operate at different levels of probabalistic exactitiude, does not mean they are not both machines. Do you really think modern computers are fully deterministic at the lowest levels?

roywiggins 2y ago
Cells behaving randomly is a fundamental part of their ordinary operation. Computers are tractable because we've done our best to engineer out the randomness and, when we can't, layer on enough error correcting codes so we can mostly not think about it. But cells don't operate on such nicely bifurcated scales (small and random vs large and mostly predictable). If they did, the dream of cellular wiring diagrams allowing cells to be understood would be a lot more achievable.
- generalizations 2y ago
  Your example of randomness upthread was brownian motion: I'm not surprised a transport mechanism relies on stochastic behaviors. To me, that looks comparable to electrons bouncing down a wire, or minimizing quantum tunneling effects between transistor layers - random at a very low level, but averages out to the behavior we need. Put guardrails at the extremes, so the random behavior stays within bounds, within a margin of error - that's just good engineering. Compare to loggers, floating trimmed trees down a river to the sawmill: the logs bouncing down the river are behaving in an entirely random manner, but it's within bounds and doesn't matter, because they'll still make it downstream where they get caught by another system. It's a "machine" with random behaviors. Maybe this (obligatory) xkcd illustrates my point: https://www.explainxkcd.com/wiki/index.php/2916:_Machine https://www.explainxkcd.com/wiki/index.php/2916:_Machine I get the impression that what this is coming down to is massive complexity rendering the machine incomprehensible - but again, that doesn't mean it isn't a machine.
  - roywiggins 2y ago
    If sending logs down a river is a machine, couldn't that make almost anything a machine? The river itself, for instance.
    - generalizations 2y ago
      Yes, it is a mechanical system that invokes stochastic processes within deterministic bounds to accomplish a specific, complex outcome. Given sufficient knowledge, it can be mapped and its functions defined. I believe that summarizes transistors, cells, and forest-to-sawmill machines.
      - roywiggins 2y ago
        Doesn't that also describe, like, plate tectonics and tornadoes? Once you expand the definition of "machine" that far, what doesn't it reach?
        generalizations 2y ago
        Vortexes absolutely have their place in fluid dynamics and mechanical design. Modern shipbuilding depends on them. If we ever manage to attempt geoengineering at the largest scale, plate tectonics would probably also come into play. Which is to say, yes: it is a system composed of comprehensible systems, which makes it, itself, a comprehensible system. And that's the whole point here: given knowledge and time, we can tease out exactly how it works.

fluoridation 2y ago

Are you saying a, for example, muscle cell that produced 10% of the contracting power of its neighbor for the same sugar cost would be perfectly healthy?

roywiggins 2y ago
It's not that cells can't go awry, it's that perfectly healthy, otherwise identical, cells do not behave predictably to identical stimuli, even on average. That's their normal mode of existence. Some of those behaviors are pathological (eg cancer) but mostly they're not. Computers don't behave this way at all: you can be reliably sure that if two computers produce different results with the same input that one of them is wrong. If it's a stochastic algorithm at least the averages should be within a certain bound. You can't make the same conclusion with cells.
- quonn 2y ago
  Yes you can and the comment you responded to illustrated this very well.
  - roywiggins 2y ago
    Which stochastic algorithms produce different distributions of results on different identical machines with the same inputs, but it's not considered a bug?
    - generalizations 2y ago
      > different identical machines with the same inputs > No two cells are identical, given that no two cells respond to a stimulus in the exact same way—even if they are genetically the same. That's just begging the question.