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My old AI professor used to say that every problem is a search problem. The issue is that to find solutions for useful problems you're often searching through

by kypro 2y ago

My old AI professor used to say that every problem is a search problem. The issue is that to find solutions for useful problems you're often searching through highly complex and often infinite solution spaces.

visarga 2y ago
For some problems validation is expensive. Like the particle collider or space telescope, or testing the COVID vaccine. It's actually validation that is the bottleneck in search not ideation.
pishpash 2y ago
There's no problem with search. The goal is to search most efficiently.
- deely3 2y ago
  You mean that by improving search we can solve any problem? What if solution field is infinite, even if we make search algo 10x100 more performant, solution field will still be infinite, no?
  - pishpash 2y ago
    Gradient descent is a search. Where does it say the search space has to be small?
shkkmo 2y ago
I would argue that no actually searchable solution space is really infinite (if only because infinite turing machines can't exist). Finite solution spaces can get more than large enough to be intractable.
- smokel 2y ago
  What about ℕ? Seems pretty infinite to me, unless with "actually" you mean finite in time and space, which would make your argument a tautology. Or am I missing something?
  - shkkmo 2y ago
    Searches happen in finite time an space and, more importantly, systems performing those searches have practical finite limits on parameters that determine size of the space within which that search can take place (such as available memory). Even within fairly modest finite limits, you can produce a solution space that cannot be significantly searched with the available finite matter and time available in the observable universe. Thus, the problem with using search isn't that solution spaces can be infinite, but that finite solution spaces can be unimaginably large.
  - lupire 2y ago
    Almost every "number" "in" N doesn't actually exist. In the search for numbers that exist, we will most likely only ever find a finite set of numbers before the Universe or humanity dies. ("Scare quotes")

by kypro 2y ago

visarga 2y ago

For some problems validation is expensive. Like the particle collider or space telescope, or testing the COVID vaccine. It's actually validation that is the bottleneck in search not ideation.

pishpash 2y ago

There's no problem with search. The goal is to search most efficiently.

deely3 2y ago
You mean that by improving search we can solve any problem? What if solution field is infinite, even if we make search algo 10x100 more performant, solution field will still be infinite, no?
- pishpash 2y ago
  Gradient descent is a search. Where does it say the search space has to be small?

shkkmo 2y ago

I would argue that no actually searchable solution space is really infinite (if only because infinite turing machines can't exist). Finite solution spaces can get more than large enough to be intractable.

smokel 2y ago
What about ℕ? Seems pretty infinite to me, unless with "actually" you mean finite in time and space, which would make your argument a tautology. Or am I missing something?
- shkkmo 2y ago
  Searches happen in finite time an space and, more importantly, systems performing those searches have practical finite limits on parameters that determine size of the space within which that search can take place (such as available memory). Even within fairly modest finite limits, you can produce a solution space that cannot be significantly searched with the available finite matter and time available in the observable universe. Thus, the problem with using search isn't that solution spaces can be infinite, but that finite solution spaces can be unimaginably large.
- lupire 2y ago
  Almost every "number" "in" N doesn't actually exist. In the search for numbers that exist, we will most likely only ever find a finite set of numbers before the Universe or humanity dies. ("Scare quotes")