Building intelligent machines by this route is like slowly flooding puddles to make pools. Existing robot control and perception programs seem muddy puddles because they compete in areas of deepest human and animal expertise. Reasoning programs, though equally shallow, comparatively shine by efficiently performing tasks humans do awkwardly and animals not at all. But if we keep pouring, the puddles will surely become deeper. That may not be true for reasoning programs: can pools be filled surface down?

Many of our sensory, spatial and intellectual abilities evolved to deal with a mobile lifestyle: an animal on the move confronts a relentless stream of novel opportunities and dangers. Other skills arose to meet the challenges of cooperation and competition in social groups. Elsewhere I've outlined a plan for commercial robot development that provides similar challenges. It will require a large, vigorous industry to search for analogous solutions. Today the industry is tiny. Advanced robots have insectlike mentalities, besting human labor only rarely, in exceptionally repetitive or dangerous work. But I expect a mass market to emerge this decade. The first widely usable products will be guidance systems for industrial transport and cleaning machines that three-dimensionally map and competently navigate unfamiliar spaces, and can be quickly taught new routes by ordinary workers. I have been developing programs that do this. They need about a billion calculations per second, like the brainpower of a guppy! Industrial machines will be followed by mass-marketed utility robots for homes. The first may be a small, very autonomous robot vacuum cleaner that maps a residence, plans its own routes and schedules, keeps itself charged and empties its dustbag when necessary into a larger container. Larger machines with manipulator arms and the ability to perform several different tasks may follow, culminating eventually in human-scale "universal" robots that can run application programs for most simple chores. Their 10-billion-calculation-per-second lizard-scale minds would execute application programs with reptilian inflexibility.

This path to machine intelligence, incremental, reactive, opportunistic and market-driven, does not require a long-range map, but has one in our own evolution. In the decades following the first universal robots, I expect a second generation with mammallike brainpower and cognitive ability. They will have a conditioned learning mechanism, and steer among alternative paths in their application programs on the basis of past experience, gradually adapting to their special circumstances. A third generation will think like small primates and maintain physical, cultural and psychological models of their world to mentally rehearse and optimize tasks before physically performing them. A fourth, humanlike, generation will abstract and reason from the world model. I expect the reasoning systems will be adopted from the traditional AI approach maligned earlier in this essay. The puddles will have reached the ripples.

Robotics should become the largest industry on the planet early in this evolution, eclipsing the information industry. The latter achieved its exalted status by automating marginal tasks we used to call paperwork. Robotics will automate everything else!