Row 10451

Row ID: 10451 | Dataset Entry | Axioma AXP Content Repository

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What problem are you actually trying to solve? Your question is confusing. It's like asking for an academic paper comparing the lubrication performance of motor oil versus ice cream. Published research on such a question is going to be scarce because it's not a question that comes up in practical situations.

Current quantum computers are a long way from being able to run even a small support vector machine. Even in a fictional future world where the hardware constraints disappear, it's deeply unclear that SVMs would be a useful quantum algorithm because they're specifically designed to help classical computers deal with classification problems. There's almost certainly a better quantum algorithm (again, assuming away hardware constraints) to solve the same problem set. On current quantum simulators, running non-trivial SVMs would probably take millions of times longer than just running its classical version, because they're doing a bunch of work to take a classical algorithm into quantum land and back again.

Quantum computers aren't magical accelerators to classical workloads. They work very differently. As far as current science tells us, there is no useful comparison between running the same algorithm on both classical and quantum. They require different algorithms.

FieldValue
text What problem are you actually trying to solve? Your question is confusing. It's like asking for an academic paper comparing the lubrication performance of motor oil versus ice cream. Published research on such a question is going to be scarce because it's not a question that comes up in practical situations. Current quantum computers are a long way from being able to run even a small support vector machine. Even in a fictional future world where the hardware constraints disappear, it's deeply u…
label r/quantumcomputing
dataType comment
communityName r/QuantumComputing
datetime 2024-05-20
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Raw Record

{
  "text": "What problem are you actually trying to solve? Your question is confusing. It's like asking for an academic paper comparing the lubrication performance of motor oil versus ice cream. Published research on such a question is going to be scarce because it's not a question that comes up in practical situations.\n\nCurrent quantum computers are a long way from being able to run even a small support vector machine. Even in a fictional future world where the hardware constraints disappear, it's deeply unclear that SVMs would be a useful quantum algorithm because they're specifically designed to help classical computers deal with classification problems. There's almost certainly a better quantum algorithm (again, assuming away hardware constraints) to solve the same problem set. On current quantum simulators, running non-trivial SVMs would probably take millions of times longer than just running its classical version, because they're doing a bunch of work to take a classical algorithm into quantum land and back again.\n\nQuantum computers aren't magical accelerators to classical workloads. They work very differently. As far as current science tells us, there is no useful comparison between running the same algorithm on both classical and quantum. They require different algorithms.",
  "label": "r/quantumcomputing",
  "dataType": "comment",
  "communityName": "r/QuantumComputing",
  "datetime": "2024-05-20",
  "username_encoded": "Z0FBQUFBQm5Lakw1aGVzdnpJRU5qbkhWSGV0dVdHOFR0Z1VZU05rcjgzUkhHXzVtZ1QyMXZkdm5Bc2V2Qk0yTkU1bDZGdk9pS1dKaFk5dTh1emNDWWo0TkpqYms3cTFhblE9PQ==",
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