5 ms·

So much effort wasted based on trying to derive fundamental meaning from coincident attributes of our brains' neurological implementation of abstract concepts.

• 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.