It's never the case that even close to all the cells in the visual cortex are being used. It's always a tiny fraction of that.This is also true of any individual transistor in a processor. An ALU contains hardware to perform many operations, but at most performs one per cycle. You can increase utilization through parallelism and pipelining, but you pay for it with more synchronization and control hardware that only switches on to resolve conflicts. And nowadays, half of all the transistors in a CPU are part of a cache (every cycle, you need a word or two, but get the whole block). You can't conclude that they're not making a contribution to output from the fact that they're often inactive.
No, I think we just haven't figured out what to do, not that we're limited by computational resources.
Based on what evidence? We know that the brain is hugely complex. We know it can sort through hugely complex problem spaces at least some of the time. Doesn't it seem like wishful thinking to assume both that the brain is really inefficient and that most of the problems it solves actually have simple hueristic solutions?
I'll step up and take ownership of the end result of this argument: If what you say is true and understanding is all we lack, why have these problems proved so stubborn?