Just because the lowest level of computation occurs in a 'mix of hardware and software' does not mean that all the important abstractions don't run at a higher level.
And indeed, some evolutionary arguments about complex systems suppose that higher level structure is likely: its easier, evolutionarily, to build systems from many levels of subcomponent, rather than from the lowest level component.
Maybe with memristors we'll be able to simulate the particular high level process that occurs in the human brain faster. But unless we know what to simulate, that doesn't solve the hard problem. The game changer will be when we know what to simulate/run; after that we can work on finding a computational substrate (which may be memristors) that is optimised for it.
I agree with the gist of your response. I think we just disagree on the semantics of software in this case. Software being "instructions" that control the operation of hardware doesn't apply to a biological brain because the instructions are a combination of the state of each neuron and the connections each neuron makes with its neighbors, which themselves change over time. There may be higher level abstractions that can exist independent of a neural network as its basis, but I wouldn't label that the software in the case of a biological brain.
Even if there are higher level abstractions yet to be discovered, neural nets can open the door to them by allowing us to create more life-like simulations and then run experiments on it. I can imagine this is rather difficult in an actual biological entity.
Just because the lowest level of computation occurs in a 'mix of hardware and software' does not mean that all the important abstractions don't run at a higher level.
And indeed, some evolutionary arguments about complex systems suppose that higher level structure is likely: its easier, evolutionarily, to build systems from many levels of subcomponent, rather than from the lowest level component.
Maybe with memristors we'll be able to simulate the particular high level process that occurs in the human brain faster. But unless we know what to simulate, that doesn't solve the hard problem. The game changer will be when we know what to simulate/run; after that we can work on finding a computational substrate (which may be memristors) that is optimised for it.