Robot brains? Can't make 'em, can't sell 'em

Why dopes still beat boffins

Bridging the IT gap between rising business demands and ageing tools

Calling engineer Einstein!

So the tinkerers can't do the math, and the boffins can't tinker. To break that logjam we need an Einstein of engineering. He would be part hacker, part statistician: a special blend  of mathematical genius, programmer, and tinkerer.

And hopefully a businessman too.

Unique among technologies, robotics faces an insidious competition: live human beings. Almost every other revolutionary technology - steam engines, air travel, telephones, computers - accelerated crazily as it became better and better at doing what no human being could do, so even the earliest prototypes offered commercial benefits and attracted customers, reinvestment, and iterative improvement. The earliest trains, while expensive, nevertheless moved faster than horses: and that was enough to unleash the investment.  But robotic brainpower is different, because it competes with human brainpower; the "robotish-ness" is precisely what humans are better at. The dumbest human still sees, hears, and grasps better than the most expensive robot.

A similar chicken-and-egg predicament long stymied solar energy: large-scale investment made little economic sense while oil, coal, and hydro power were  much cheaper.  Solar ultimately succeeded in niche markets where it didn't compete with the mains;  autonomous robotics, likewise, needs a business application with no hope of human intervention.

Perhaps some applications are on the way.  The long-term goal of Stanford Professor Sebastian Thrun, designer of a prize-winning robot car, is a self-driving car which will save humans the trouble of keeping their own eyes glued to the road for hours a day. Such robot chauffeurs would form a great business, but they are still at least a decade off. While today, they are possible only because the technology is specifically tuned to the narrow task of road-driving with lasers, radar, GPS, and other purpose-built sensors. A robot chauffeur would not have a robot brain.

One high-profile businessman is working on real robot brains: Jeff Hawkins, founder of Palm Computing, hopes his new venture Numenta Inc will spur a business based on automatic, self-learning systems.  His system isn't robotic yet, but he champions a modular software architecture and generic API templates for coders and customers, so even if the initial algorithm sputters, it could be iteratively improved without redesigning all the infrastructure.

Such interfaces are the best news in an otherwise stagnant field. Toymaker Lego is in cahoots with Microsoft, vacuum-maker iRobot is creating an open robotics platform,  and the general trend is for standard drivers, modular programming modules, and interlocking parts. Once the algorithms are equally modularized, perhaps a new generation of mini-Einsteins will build a prototype or discover a business application  that others can imitate and improve upon. Then we might finally have real robots in place of promised ones. ®

Bill Softky has written a neat utility for Excel power users called FlowSheet: it turns cryptic formulae like "SUM(A4:A7)/D5" into pretty, intuitive diagrams. It's free, for now. Check it out.

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