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Comment by stared

4 hours ago

The whole title is a buzzword cluster, until proven otherwise.

Which tasks, in particular, does it do better? Not as in "it could do them better", but actually there are benchmarks. If they are, they are buried beneath marketing; if not - well, we have our answer.

What is "thinks like nature"? Spin systems, are no more (or less) nature than transistors.

That said, I am all for exploring various systems for computation and simulation - I think there is a lot to discover.

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stared

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ngriffiths  3 hours ago

Yeah, I mean it's obviously meant to be a marketing pitch but it's not a very good one.

> The hardest computational problems are not waiting for faster chips – they are waiting for machines that compute in a fundamentally different way.

Surely they don't actually believe that, right? Like you say the benefits must be limited to specific shapes of problems (not all of "the hardest" ones), and the whole history of computing is about how faster chips is an excellent answer to difficult computational problems.

  • gobdovan  2 hours ago

    > and the whole history of computing is about how faster chips is an excellent answer to difficult computational problems.

    I don't really disagree, and I am definitely not taking their marketing pitch seriously. Yet, you could look at the same computation history and interpret it as an economically constrained hill-climbing around an idea that was simple enough to work reliably (von Neumann architecture) and that worked and scaled so well that we were rarely forced or desperate enough to move conceptually far away from it.

    Sufficiently general digital computers can simulate other computational models, so I think 'faster' is ultimately the end game, but for some classes of computation, as you also noted, we may need to go for analog hardware, (maybe) quantum devices, optical interconnects, and so on.

    Bret Victor has a talk about this, more or less: [0]

    [0] https://www.youtube.com/watch?v=8pTEmbeENF4