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by LikeBeans
557 days ago
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In simple terms, if I understand quantum computing, and please correct me if I'm wrong, the big benefit is parallel computing at a massive scale whereas classical computing is serial in nature. If yes likely both method are useful. But a very useful use case for quantum computing is AI training to create the models. Currently consumes a lot of GPUs but QC has nice chance to impact such a use case. Did I get it right? |
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The problem with this line of reasoning is that, even though a quantum system might have many possible states, we only observe a single one of those states at the time of measurement. If you could somehow prepare a quantum system such that it encoded the N equally-likely solutions to your classical problem, you would still need to rerun that experiment (on average) N times to get the correct answer.
Broadly speaking, quantum computing exploits the fact that states are entangled (and therefore correlated). By tweaking the circuit, you can make it so that incorrect solutions interfere destructively while the correct solution interferes constructively, making it more likely that you will measure the correct answer. (Of course this is all probabilistic, hence the need for quantum error correction.) But developing quantum algorithms is easier said than done, and there's no reason to think a priori that all classical problems can be recast in this manner.