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One of the most influential philosophical concepts for me from the last decade was from this very blog called “Nebulosity”. It just speaks to the nature of real

One of the most influential philosophical concepts for me from the last decade was from this very blog called “Nebulosity”. It just speaks to the nature of reality that is misinterpreted with overlays of meaning. - ‘Nebulosity’ refers to the insubstantial, amorphous, non-separable, transient, ambiguous nature of meaningness. From a distance, clouds can look solid; close-up they are mere fog, which can even be so thin it becomes invisible when you enter it. Clouds often have vague boundaries and no particular shape. It can be impossible to say where one cloud ends and another begins; whether two bits of cloud are connected or not; or to count the number of clouds in a section of the sky. If you watch a cloud for a few minutes, it may change shape and size, or evaporate into nothing. But it is impossible to find an exact moment at which it ceases to exist. It can be impossible to say even whether there is a cloud in a particular place, or not. [from] https://meaningness.com/nebulosity https://meaningness.com/nebulosity

aidenn0 6y ago
Maybe I'm missing a subtlety of your meaning here (how appropriate) but I know that philosophers have discussed such things for centuries; e.g. 2 grains of sand is not a pile, 1000 grains is, but where is the transition?
- dragonwriter 6y ago
  Fuzzy logic in the broad sense (not necessarily the logic of the Zadeh operators, for instance) seems to provide the best answer: there is no crisp transition; membership is real-valued, not binary.
  - deleted 6y ago
    [deleted]
- skybrian 6y ago
  Most of it isn't new, but David Chapman is better at explaining nebulosity and putting it into perspective than anyone I know, so I recommend reading more of his stuff.
- FeepingCreature 6y ago
  So much effort wasted based on trying to derive fundamental meaning from coincident attributes of our brains' neurological implementation of abstract concepts. "The transition is wherever your 'pile' classifier neuron fires."
  - wizzwizz4 6y ago
    I think that's a little too reductionist – in that I'm not sure that there is one neuron responsible for pile classification in that way. But as a metaphor, it's a very good sentiment.
    - FeepingCreature 6y ago
      Right, yeah. Not saying this is literally an actual single neuron, but the point holds.
  - aidenn0 6y ago
    I think you are selling at least some of the philosophers short. What is a pile and isn't a pile is not entirely subjective (i.e. we all agree that 1 grain of sand is not a pile), nor is it entirely objective (in the sense that different people will probably draw the line at different places). On top of that, the transition even for a single individual is not abrupt. Understanding and dissecting these sorts of ambiguities with something as inoffensive as piles of sand can be useful for better understanding disagreement that stems from ambiguity when things are more contentious.
    - FeepingCreature 6y ago
      Yeah but those properties are exactly what you would expect from imitation learned fuzzy neuronal classifiers. As such, they have no deeper meaning than saying "does the fact that the deep learning model thinks this traffic cone is a penguin reveal to us a deep truth about traffic cones and penguins?" No.. It just used some shortcut feature that's not universally applicable. Just like us. The heap classifier works to tell that obvious heaps are heaps. It works to tell that single items are not heaps. In between, there is no meaning but noise.
Dylan16807 6y ago
I agree with most of that. But if you're measuring at least a small distance from yourself, it's pretty easy to say if any cloud exists or not in a particular area. It's like asking whether you have any grains of sand. Much easier than asking if you have enough to make a pile.
oehtXRwMkIs 6y ago
This is just the problem of the many. Not sure where the blog author is getting "nebulosity" from.
- ceilingcorner 6y ago
  Unintentionally rediscovering ancient philosophical problems is a favorite pastime of bloggers.
  - oehtXRwMkIs 6y ago
    It was introduced by Unger in 1980. You're probably thinking about the Sorites paradox which is related but not the same.

aidenn0 6y ago

Maybe I'm missing a subtlety of your meaning here (how appropriate) but I know that philosophers have discussed such things for centuries; e.g. 2 grains of sand is not a pile, 1000 grains is, but where is the transition?

dragonwriter 6y ago
Fuzzy logic in the broad sense (not necessarily the logic of the Zadeh operators, for instance) seems to provide the best answer: there is no crisp transition; membership is real-valued, not binary.
- deleted 6y ago
  [deleted]
skybrian 6y ago
Most of it isn't new, but David Chapman is better at explaining nebulosity and putting it into perspective than anyone I know, so I recommend reading more of his stuff.
FeepingCreature 6y ago
So much effort wasted based on trying to derive fundamental meaning from coincident attributes of our brains' neurological implementation of abstract concepts. "The transition is wherever your 'pile' classifier neuron fires."
- wizzwizz4 6y ago
  I think that's a little too reductionist – in that I'm not sure that there is one neuron responsible for pile classification in that way. But as a metaphor, it's a very good sentiment.
  - FeepingCreature 6y ago
    Right, yeah. Not saying this is literally an actual single neuron, but the point holds.
- aidenn0 6y ago
  I think you are selling at least some of the philosophers short. What is a pile and isn't a pile is not entirely subjective (i.e. we all agree that 1 grain of sand is not a pile), nor is it entirely objective (in the sense that different people will probably draw the line at different places). On top of that, the transition even for a single individual is not abrupt. Understanding and dissecting these sorts of ambiguities with something as inoffensive as piles of sand can be useful for better understanding disagreement that stems from ambiguity when things are more contentious.
  - FeepingCreature 6y ago
    Yeah but those properties are exactly what you would expect from imitation learned fuzzy neuronal classifiers. As such, they have no deeper meaning than saying "does the fact that the deep learning model thinks this traffic cone is a penguin reveal to us a deep truth about traffic cones and penguins?" No.. It just used some shortcut feature that's not universally applicable. Just like us. The heap classifier works to tell that obvious heaps are heaps. It works to tell that single items are not heaps. In between, there is no meaning but noise.

Dylan16807 6y ago

I agree with most of that. But if you're measuring at least a small distance from yourself, it's pretty easy to say if any cloud exists or not in a particular area. It's like asking whether you have any grains of sand. Much easier than asking if you have enough to make a pile.

oehtXRwMkIs 6y ago

This is just the problem of the many. Not sure where the blog author is getting "nebulosity" from.

ceilingcorner 6y ago
Unintentionally rediscovering ancient philosophical problems is a favorite pastime of bloggers.
- oehtXRwMkIs 6y ago
  It was introduced by Unger in 1980. You're probably thinking about the Sorites paradox which is related but not the same.