This is pretty cool, pardon my limited understanding, trying to see if I get this correctly:
1) they train a model to do sorting, it actually sorts correctly.
2) they optimize the model on efficiency and it becomes better than many custom sort functions?
If I remember correctly from school, you can basically speed up any kind of sorting by using more space (basically by using a hash table). Is the neural network just using the normal sort algo until it sees a pattern in the input and then skips the sort algo for the pattern output? Or to put it plainly, is it just a smarter (or dumber, depending on the size of the neural network) hash table?
1) they train a model to do sorting, it actually sorts correctly. 2) they optimize the model on efficiency and it becomes better than many custom sort functions?
If I remember correctly from school, you can basically speed up any kind of sorting by using more space (basically by using a hash table). Is the neural network just using the normal sort algo until it sees a pattern in the input and then skips the sort algo for the pattern output? Or to put it plainly, is it just a smarter (or dumber, depending on the size of the neural network) hash table?