On Sunday, July 16, 2023, at 5:18 PM, Matt Mahoney wrote:
> The result is helpful by giving one more reason why quantum computing is not 
> the path to AGI. Quantum computing is often misunderstood as computing an 
> exponential set of paths in parallel, when for most purposes it is actually 
> weaker than classical computing.  Leveraging the power of quantum computing 
> depends on arranging the computation so that the components of the unit 
> vector reinforce for a subset of the qubits, like in computing the quantum 
> Fourier transform for Shor's or Grover's algorithms for cracking crypto. But 
> it doesn't solve NP complete problems in polynomial time or anything like 
> that. The brain is not a quantum computer. Neural networks, and learning in 
> general, are not time reversible.

You don’t think the many-paths simultaneity can be leveraged to find short 
algorithmic paths and/or circuits better than classical?

If you look at quantum photosynthesis theory photons are used, and by mimicking 
that algorithmic paths would need to be represented in molecules then excited 
by light absorption into superposition states… but how efficient is 
representing algorithmic complexity in molecules such that the many paths are 
exposed to be transited? It’s almost like the computation would already need to 
be performed in the molecular pathway expression… unless the chemistry was 
arranged in various pre-chaotic states to broaden the array of paths.

But yes there is debate still on the photosynthesis:
https://pubs.acs.org/doi/10.1021/acs.jpclett.2c00538

John     
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