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Entire animal nervous systems, hormonal signals and interconnection plasticity included, may become simulable in coming decades, as imaging instrumentation and computational resources rapidly improve. Such simulations will greatly accelerate neurobiological understanding, but I think not rapidly enough to win the race. Valentino Braitenberg, who analyses small nervous systems and has designed artificial ones, notes the rule of "downhill synthesis and uphill analysis" -- it is usually easier to compose a circuit with certain behaviors than to describe how an existing circuit manages to achieve them. Meager understanding and thus means to modify designs, the cost of simulating at a very fine grain and ethical hurdles as simulations approach human-scale will slow the applications of neural simulations. But robot toys following in Aibo's pawprints should be interesting!

No human-scale intelligence (as far as we know) ever developed from conscious reasoning down, nor from simulations of neural processes, and we really don't know how hard doing either may be. But the third approach is familiar ground.

Multicellular animals with cells specialized for signaling emerged in the Cambrian explosion a half-billion years ago. In a game of evolutionary one-upmanship (there's always room at the top!) maximum nervous system masses doubled about every 15 million years, from fractional micrograms then to several kilograms now (with several abrupt retreats, often followed by accelerated redevelopment, when catastrophic events eliminated the largest animals).

Our gadgets, too, are growing exponentially more complex, but 10 million times as fast: human foresight and culture enables bigger, quicker steps than blind Darwinian evolution. The power of new personal computers has doubled annually since the mid 1990s. The "edge operator" estimate makes today's PCs comparable only to milligram nervous systems, as of insects or the smallest vertebrates (eg. the 1 cm dwarf goby fish), but humanlike power is just thirty years away. A sufficiently vigorous development with well-chosen selection criteria should be able to incrementally mold that growing power in stages analogous to those of vertebrate mental evolution. I believe a certain kind of robot industry will do this very naturally. No great intellectual leaps should be required: when insight fails, Darwinian trial and error will suffice -- each ancestor along the lineage from tiny first vertebrates to ourselves became such by being a survivor in its time, and similarly ongoing commercial viability will select intermediate robot minds.