Clearly the idea is strong, but have some downsides. One of them is piracy. Designers, architects and manufacturers are likely to face the problem currently faced by music industry. Fluid Forms makes an argument in a similar line and I did as well – in a short article on design and piracy from 2008. The problem however is best captured in an abstract of “Napster Fabbing”, Marshall Burns’ and James Howison’s presentation from 2001 quoted by Ponoko blog:

“If record companies had a fit over Napster, wait ’til manufacturers find out you can download Rolex.fab or Ferrari.fab and make them yourself.”

Clearly these problems will demand a new approach. However they do open new possibilities as well. Particularly the possibility of peer production of objects and, with time, of spaces as well. It’s easy to guess that the name of this blog is derived from this notion. Companies allowing it’s customers to customize their products on-line will have to adapt first since they are the ones most likely to suffer from eventual fraud. They are less immune for two reasons:

- their products are expressed entirely in a form of a code and the code is available online.

- their products are manufactured using CAM – technologies available not only to large-scale manufacturers but to private people as well.

It means that mass customization practitioners will soon have to figure out a new business model in which a product code is shared and open-sourced to some extend. When that happens the phrase “open-source design” will gain a new meaning – one similar to meaning of “open-source” in computer science community.

Last question is how far away are we from being able to manufacture “Rolex.fab” or “Ferrari.fab” using additive digital manufacturing techniques at home? Recently published report: “Road Map for Additive Fabrication: Identyfing of Freeform Processing” might be a good start for looking for an answer (I have found it via Replicator blog. It seems that the development in additive manufacturing technology takes place on an increasingly high pace and a new multi-material 3d printer from Objet proves that.

Google is really good with providing you with a list of websites which contain the answer to your query. Wolfram’s approach is different though. Instead of the website providing the answer his aim is to provide you with the answer itself. When you type in Poland’s GDP or rule 110 to Wolfram|Alpha it produces accurate result and there is no need to go anywhere else on the web. Google directs you to Wikipedia’s page as a first result in case of CA rule and gives you the number in case of GDP, but not accompanied by any additional data. Yet when you try terms which are slightly more vague, say “mass customization”, Google produces accurate findings (mass-customization.de on 2nd place), while Wolfram|Alpha get’s confused.

This is understandable since Wolfram|Alpha is not a tool to browse the web, but a tool to browse knowledge. To say it in the words of it’s developers, it’s a tool for new kind of knowledge based computing. It’s creators say that it is not a search engine (sorry for the misleading title), but a computational knowledge engine which aims to provide you with accurate answer to a query about any kind of a fact. For every query Wolfram|Alpha computes the answer composed out of information from numerous sources. List of those sources is available next to the answer in most of the cases.

Whether this can be called artificial intelligence able to “understand the meaning” of it’s users’ queries is a question somewhat outside of my scope of interest. What’s really interesting for me is the amalgam of algorithms behind it (the number of algorithms and models harnessed exceeds 50 000 already).

I have learned about Wolfram Alfa thanks to Edwin Bendyk’s article in Polish weekly magazine Polityka.