mcharity@ATHENA.MIT.EDU (08/27/88)
From: mcharity@ATHENA.MIT.EDU Date: Fri, 26 Aug 88 16:25 EDT To: ailist@ai.ai.mit.edu Subject: Rates of change In a previous article, John Nagle writes: >... Look at Marc >Raibert's papers. He's doing very significant work on legged locomotion. >Progress is slow; ... >Along the way >are endless struggles with hydraulics, pneumatics, gyros, real-time control >systems, and mechanical linkages. (I spent the summer of '87 overhauling >an electrohydraulic robot, and I'm now designing a robot vehicle. I can >sympathise.) >... It's depressing to think that it might take >a century to work up to a human-level AI from the bottom. Ants by 2000, >mice by 2020 doesn't sound like an unrealistic schedule for the medium term, >and it gives an idea of what might be a realistic rate of progress. > I think it's going to be a long haul. But then, so was physics. >So was chemistry. For that matter, so was electrical engineering. We >can but push onward. Maybe someone will find the Philosopher's Stone. >If not, we will get there the hard way. Eventually. Continued use of a bottom-up experimental approach to AI need not demand continued use of the current experimental MEDIUM which so constrains the rate of change. While today one may be better off working directly with mechanical systems, rather than with computational simulations of mechanical systems, it is unclear that this will be the case in 5 or 10 years. If a summer's overhaul could be a week's hacking, you have an order of magnitude acceleration. If your tools develop similarly, the _rate_ of change is sharply exponential. Science, like engineering, is limited by the feedback lags of its development cycles. Many (most?) of these lags are in information handling. Considering our increasing competence, are current challenges so much vaster than past as to require similar periods of calendar time? Mitchell Charity