5 ms·

A recommendation is in the domain of subjectivity, meaning that there is no consensus on the correctness... so, even if the algorithm is faster, its usefulness

by b0gb 1y ago

A recommendation is in the domain of subjectivity, meaning that there is no consensus on the correctness... so, even if the algorithm is faster, its usefulness shouldn't be superior to a random pick based on some matching criteria... which is already as fast as it can be

snapcaster 1y ago
>superior to a random pick based on some matching criteria... this is a recommendation right? hard to understand your point here
- b0gb 1y ago
  my point is, the quantum part isn't (/wasn't) necessary in the first place...
  - ylow 1y ago
    The actual problem that is being solved here is well defined mathematically and is matrix completion via low rank matrix factorization. And using a sampling approach for it. (I have not read the paper in its entirety, just skimmed the intro a bit). It is called "recommendation system" largely due to some history around some of its common appplications (Netflix challenge). But this is not addressing the subjective recommendation problem, but a very particular instantiation of it.
    - b0gb 1y ago
      Yes, I get that..., my issue was with its application (a movie recommendation)... the idea itself isn't qualified for the quantum realm...
      - lo_zamoyski 1y ago
        I don't see how this follows. Besides, "subjectivity" concerns the subject, "objectivity" the object. The former is a matter of how an object is received by the observer, and so all perception is subjective in that sense; it can't be otherwise. But the subject can become an object of another subject. We can infer with varying certainty what someone is more or less likely to enjoy based on our knowledge of what they like.
        b0gb 1y ago
        As long as you accept subjectivity, you must also accept that logical inference isn't really useful... because the observer can add rules at any given time - without any logical constraint - thus preferences aren't deterministic... so a random option is as good as it can be.
      - ylow 1y ago
        The application, method and algorithm needs to be separated. The application is movie recommendation. One of the methods which works pretty well for this is low rank matrix completion. There are several algorithms for this method, one of which is quantum.
throwaway81523 1y ago
It's a theoretical result. There was a problem believed to take exponential time on a classical computer but polynomial time on a quantum computer. It turns out to be solvable in polynomial time on both types of computer, removing the quantum exponential speedup. Whether one polynomial was bigger or smaller than the other wasn't of much interest, as I understand it. The surprise was just that both are polynomials.
superfrank 1y ago
You're mixing up two things here. It doesn't really matter if the recommendation algorithm is good or not. The advancement isn't that we now have a better recommendation algorithm, it's that we thought that there was a problem that was impossible to solve with current computers and was being used as example of a problem that only quantum computing could solve and we've now learned that that isn't the case.

by b0gb 1y ago

snapcaster 1y ago

>superior to a random pick based on some matching criteria... this is a recommendation right? hard to understand your point here

b0gb 1y ago
my point is, the quantum part isn't (/wasn't) necessary in the first place...
- ylow 1y ago
  The actual problem that is being solved here is well defined mathematically and is matrix completion via low rank matrix factorization. And using a sampling approach for it. (I have not read the paper in its entirety, just skimmed the intro a bit). It is called "recommendation system" largely due to some history around some of its common appplications (Netflix challenge). But this is not addressing the subjective recommendation problem, but a very particular instantiation of it.
  - b0gb 1y ago
    Yes, I get that..., my issue was with its application (a movie recommendation)... the idea itself isn't qualified for the quantum realm...
    - lo_zamoyski 1y ago
      I don't see how this follows. Besides, "subjectivity" concerns the subject, "objectivity" the object. The former is a matter of how an object is received by the observer, and so all perception is subjective in that sense; it can't be otherwise. But the subject can become an object of another subject. We can infer with varying certainty what someone is more or less likely to enjoy based on our knowledge of what they like.
      - b0gb 1y ago
        As long as you accept subjectivity, you must also accept that logical inference isn't really useful... because the observer can add rules at any given time - without any logical constraint - thus preferences aren't deterministic... so a random option is as good as it can be.
    - ylow 1y ago
      The application, method and algorithm needs to be separated. The application is movie recommendation. One of the methods which works pretty well for this is low rank matrix completion. There are several algorithms for this method, one of which is quantum.

throwaway81523 1y ago

It's a theoretical result. There was a problem believed to take exponential time on a classical computer but polynomial time on a quantum computer. It turns out to be solvable in polynomial time on both types of computer, removing the quantum exponential speedup. Whether one polynomial was bigger or smaller than the other wasn't of much interest, as I understand it. The surprise was just that both are polynomials.

superfrank 1y ago

You're mixing up two things here. It doesn't really matter if the recommendation algorithm is good or not. The advancement isn't that we now have a better recommendation algorithm, it's that we thought that there was a problem that was impossible to solve with current computers and was being used as example of a problem that only quantum computing could solve and we've now learned that that isn't the case.