From: Anders Sandberg (nv91-asa@nada.kth.se)
Date: Fri Dec 27 1996 - 04:13:22 MST
On Thu, 26 Dec 1996, Eliezer Yudkowsky wrote:
> Think genetic programming. Current "populations" are in the 10^3-10^6
> range. With a 64-qubit QC, you could have a population of sixteen
> billion billion. Heck, with a 64-qubit QC, you could probably string
> instructions together completely at random and wind up with the most
> powerful solution immediately.
Interesting. However, I think it might be a bit trickier to implement GP
than that since you have to make the best solution appear when the
wavefunction collapses. I'll have to read more about the new algorithms,
I think.
Another fun application: optimal chess playing.
> As for quantum neural networks, it seems to me that the number of neurons
> simulated would simply equal 2^qubits or the amount of memory available
> - practically speaking, the amount of memory available.
Either you "quantum" over neurons, or you "quantum" over neural states.
In the first case, you can get a lot of neurons "for free", in the second
you can get quantum-weird neurons. Hmm, doing it over the synapses is a
fun idea, that might be really useful to do the weight-multiplying step,
and if they could be made to coalesce through a transfer function...
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