Alternatively we could try to implement the brain's function at much larger than edge-detector grain. The solution space expands and with it the difficulty of finding globally efficient algorithms, but their computational requirements decrease. Perhaps programs implementing humanlike intelligence in a highly abstract way are possible on existing computers, as AI traditionalists imagine. Perhaps, as they also imagine, devising such programs requires lifetimes of work by world-class geniuses.

But it may not be so easy. The most efficient programs exhibiting human intelligence might exceed the power and memory of present PCs manyfold, and devising them might be superhumanly difficult. We don't know: the pool is extremely murky below the ripples, and has not been fathomed.

(Very powerful optimizing compilers could conceivably blur grain sizes by transforming neuron-level brain simulation programs into super-efficient code that preserves input-output behavior but resembles traditional AI programs. Such compilers would surely need superhuman mental power (they would be singlehandedly solving the AI problem, after all), but perhaps of a relatively simple, idiot-savant, kind.)

Puddles

Each approach to matching human performance is interesting intellectually and has immediate pragmatic benefits. Reasoning programs outperform humans at important tasks, and many already earn their keep. Neural modeling is of great biological interest, and may have medical uses. Efficient perception programs are somewhat interesting to biologists, and useful in automating factory processes and data entry.

But by which will succeed first? The answer is surely a combination of all those techniques and others, but I believe the perception route, currently an underdog, will play the largest role.

Reasoning-type programs are superb for consciously explicable tasks, but become unwieldy when applied to deeper processes. In part this is simply because the tasks deep in the subconscious murk elude observation. But also, the deeper processes are quantitatively different. A few bits of problem data ripple across the conscious surface, but billions of noisy neural signals seethe below. Reasoning programs will become more powerful and useful in coming decades, but I think comprehensive verbal common sense, let alone sensory understanding, will continue to elude them.