On the computability of universal rapid-prototyping

The new issue of Seed magazine (No. 25) has an article on machines that can make a copy of themselves. Well, actually, they can only make all the parts (other than batteries) that are needed to make a copy of themselves. That's not half-bad either. A machine that's cheap (and for which the materials are cheap!) and that can make all the parts for a copy of itself -- that's a big step towards universal availability of rapid-prototyping. And that may very well lead to something like personal factories, by analogy with personal computers and a similarly revolutionary idea.

By the way, in addition to RepRap mentioned in Seed, Technocrati and tens of other online sources (presumably because the project is affiliated with Google?), Fab@Home and its inventor Evan Malone (then at Cornell) have been pursuing universal rapid-prototyping at least since 2006.

The very idea raises questions about the interplay of the computational and the physical. If you can readily manufacture articulated, controllable things in your home, how do you then make them do useful things? As of now, fabbers (for that is what we shall call these nifty machines) don't make computer chips or electronics as part of the process. But people are working on it, and it doesn't defy the imagination to consider building (programmable?) circuits directly into the fabricated parts. Ah. So many things to ask from a computational perspective. Here's one: what is the computational class of circuits built by a fabber? Meaning: what class of problems can these circuits compute? What about any physically realizable fabber? There's a research project in there, yours for free.

More on all that later.