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Comment by ampdepolymerase | Hacker News Reader

You realize quantum computing is ultimately just a few linear algebra operations right? There is no more magic in it than conventional neural network based models. Standard ML ethical frameworks are more than sufficient.

Adding "quantum" simply means speed ups for a few specific types of operations. You are not going to get an AGI with the current state of the art in quantum computing.

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Are those quantum speed ups for neural nets even good?

More specifically, are they better than the ones from "neuromorphic" chips like Intel Loihi?

I suppose that’s the reason google made the investment- to find out.

I'm not an expert on either, but based on my one course in neural networks I took, they are basically a series of linear algebra equations.

>You realize quantum computing is ultimately just a few linear algebra operations right?

Quantum systems have wavefunctions though, which collapse to a state. And before collapse, these can interfere. The math of this involves way more than normal linear algebra. Especially when you consider the things we've simplified away -- e.g. how exactly the wave function collapses. (We just say it's 'abrupt' and kinda leave it there. But it's possible this has implications for quantum computing, once we think in quantum theory terms rather than CS.)

A significant part of quantum computation is just a sequence of unitary transformations, represented by matrices. So essentially just a series of big matrix multiplications. The nonlinearity is introduced in the measurement. You have to repeat the calculation several times to build up a probability distribution.

Wave functions are just another type of vectors. Measurement (and collapse) is just an application of matrix diagonalization. It has its complications and its own beauty, but it is indeed just fanciful linear algebra (I work professionally on this).

> Standard ML ethical frameworks are more than sufficient.

Agreed. All ethical frameworks should include Hindley-Miller type inference.

No. See for example the Grover search algorithm. You can use to find whether an item is inside a list in O(sqrt(n)).

I don't understand what you are saying. The parent comment said that quantum allows a few types of operations to get faster, and your response was "No," followed by a specific algorithm that is faster. Where do you disagree?

I think the point was it doesn't only speed up a small set of linear algebra calculations, but allows other, more complex, operations to be sped up as well.

How big does n need to be before the expected runtime is less than n/2? And at that n, what gate fidelity is necessary to ensure that the answer will usally be correct?

Slightly tangential but how significant is O(sqrt(n)) speed up? Fast algorithms are slightly faster but intractable algorithms are still intractable?

It makes memory, not compute, the limit.

It halves the exponent on the number of operations. 2^128 - reasonably secure by todays standards! 2^64 - horribly insecure.

(CAVEAT: where the speedup is applicable, which is often hard.)

2^64 is hardly horribly insecure. Its on the edge of what a gigantic compute cluster can do. So its not secure, but hardly horribly insecure. Especially even if you can get a quantum computter working, its not going to be on the same level of operations that a million dollars in AWS credits will get you. At least not for a very long time.

Besides,in most places where that is an issue, its trivial to switch to 256bit algorithms

> (CAVEAT: where the speedup is applicable, which is often hard.)

Grover's algorithm has pretty wide applicability. Its the exponential speed ups like shor's algorithm that have super limited applicability.

I think the point is it lowers security by a factor of 2 in the exponent. Going from 2^64 to 2^63 lowers the amount of time to bruteforce a key by half.

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