Thingiverse remix graph: visualizing the net of physical things

I recently became a happy owner of a Solidoodle 2 3D printer. This has been the start of a beautiful addiction, but more on the hardware hacking aspects in another post.

If you haven’t heard of it before, 3D printing refers to a family of manufacturing methods, originally developed for rapid prototyping, the first of which appeared almost three decades ago. Much like mainframe computers in the 1960s, professional 3D printers cost up to hundred thousands of dollars. Starting with the RepRap project a few years ago, home 3D printers are now becoming available, in the few hundred to a couple of thousand dollar price range.  For now, these are targeted mostly to tinkerers, much closer to an Altair or, at best, an Apple II, than a MacBook. Despite the hype that currently surrounds 3D printing, empowering average users to turn bits into atoms (and vice versa) will likely have profound effects, similar to those witnessed when content (music, news, books, etc) went digital, as Chris Anderson eloquently argues with his usual, captivating dramatic flair. Personally, I’m similarly excited about this as I was about “big data” (for lack of a better term) around 2006 and mobile around 2008, so I’ll take this as a good sign. :)

One of the key challenges, however, is finding things to print!  This is crucial for 3D printing to really take off. Learning CAD software and successfully designing 3D objects takes substantial, time, effort, and skill. Affordable 3D scanners (like the ones from MatterformCADscan, and Makerbot) are beginning to appear. However, the most common way to find things is via online sharing of designs. Thingiverse is the most popular online community for “thing” sharing. Thingiverse items are freely available (usually under Creative Commons licenses), but there is also commercial potential: companies like Shapeways offer both manufacturing (using industrial 3D printers and manual post-processing) and marketing services for “thing” designs.

I’ve become a huge fan of Thingiverse.  You can check out my own user profile to find things that I’ve designed myself, or things that I’ve virtually “collected” because I thought they were really cool or useful (or both). Thingiverse is run by MakerBot, which manufactures and sells 3D printers, and needs to help people find things to print. It’s a social networking site centered around “thing” designs. Consequently, the main entities are people (users) and things, and links/relationships revolve around people creating things, people liking things, people downloading and making things, people virtually collecting things, and so on. Other than people-thing relationships, links can also represent people following other people (a-la Twitter or Facebook), and things remixing other things (more on this soon). Each thing also has a number of associated files (polygon meshes for 3D printing, vector paths for lasercutting, original CAD files—anything that’s needed to make the thing).

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Adventures in fiberglassing: custom fabricated tweeter pods

[This project is more than a year old, but I never got around to posting anything earlier.]

I generally like to make things (I used to say “build” things, but that was misconstrued by some manager/academic types, who apparently have a very different definition of “to build”), whether it’s software, writing, or “hardware”.  I usually talk about the first, but I occasionally do the last (much to the dismay of my wife, who has nonetheless been very patient! :).  I also like to try new things–I probably care more about the process and experimentation, learning what’s possible and how to do it, that the final product (which is not to say that I don’t care about the final product at all, but it get’s boring pretty quickly for me). So, sometime last year I decided to upgrade my car speakers (I also Dynamat-ted all doors, but I didn’t take photos of that adventure; one tip, though:: make sure you sit down properly, because after crouching down on tiptoe for almost an entire day, I needed physiotherapy for my heel tendon :) —now my Subaru’s doors sound like a Mercedes when you shut them). However, the new tweeters were much larger than the factory-installed ones, so I took the opportunity (excuse?) to learn fiberglassing and make new tweeter pods.

Let me set the mood by starting with my outfit: I started with the one on the left, but after plenty of PVC dust, fiberglass dust, and acetone fumes, I upgraded to the one on the right. A proper respirator helps a lot, especially if you’re working indoors. And don’t skip the safety glasses (even if you’re wearing vision glasses, as I found out).  Always take the proper safety precautions.

outfit0 outfit

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Expectations of privacy

I have stopped worrying what can be inferred about me, because I’ve accepted the simple fact that, given enough time (data) and resources, anything can be inferred. Consider, as an example, “location privacy.”  A number of approaches rely on adaptively coarsening the detail of reported location (using all sorts of criteria to decide detail, from mobility patterns, to spatial query workload characteristics, etc).  For example, instead of revealing my exact location, I can reveal my location at a city-block level. In an area like NYC, this would conflate me with hundreds of other people that happen to be on the same block, but a block-level location is still accurate enough to be useful (e.g., for finding nearby shops and restaurants).  This might work if I’m reporting my location just once.  However, if I travel from home to work, then my trajectory over a few days, even at a city-block granularity, is likely sufficient to distinguish me from other people.  I could perhaps counter this by revealing my location at a city-level or state-level.  Then a few days worth of data might not be enough to identify me.  However, I often travel and data over a period of, say, a year, would likely be enough to identify me even if location detail is quite coarse.  Of course, I could take things to the extreme and just reveal that “I am on planet Earth”.  But that’s the same as not publishing my location, since this fact is true for everyone.

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The pesky cousin from Greece

I’m far from an expert in economics, politics, or history; quite the contrary.  Which is why I try to cast events in more familiar, anthropomorphic terms, and also why such analogies are dangerous. Caveat lector—now, let’s get on with the story.

There once was a large family, with many brothers, uncles, and cousins spread over many different places. Each of them led their own lives.  The extended family spanned all sorts of lifestyles, from successful businessmen, dignified and well-dressed, to smart but somewhat irresponsible bon viveurs.  They lived in many different places and they occasionally exchanged gifts and money, some more frequently than others (admittedly, this part is rather weak in its simplicity, but a single analogy can only be taken so far). But they were getting tired of running to Western Union, paying transaction fees, losing money on currency conversions due to volatility in exchange rates, and so on. Furthermore, some of the more powerful family members had gotten into nasty feuds (world wars).

So, under the leadership of some of the more powerful siblings (Germany and France) they thought: well, we have enough money to go down to an international bank and open a common family account in a solid currency, say, dollars (they in fact created their own currency and bank, perhaps to avoid associations with existing institutions, but it’s probably safe to say that they heavily mirrored those of one of the leading siblings).  Then it will be so much easier to do the same things much more efficiently.  The richer craftsmen and businessmen among them could send their stuff with less hassle and waste [e.g., paragraph seven], and the poorer ones could gain a bit by wisely using their portion of the funds and an occasional advance withdrawal.

The leading siblings knew how to keep their checkbooks balanced, and it seemed reasonable to assume that these methods were general enough and suitable for everyone.  So, after opening the family account with all of them as joint holders, they shook hands and simply agreed to use the money wisely, pretty much in the way that had worked well for the richer and more productive ones (stability and growth pact).  Once in a while they might briefly meet and agree on some further rules of how the money should be used, but basically each one of them went their way, living the life they always had, managing their portion of the family funds.  One of the more cynical siblings (England) was a bit skeptical about opening a family account while living their separate lives apart, so it chose to stay out, at least for a while.  Times were good for several years, but they didn’t last forever.

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Mobile OCR input: “Fully automatic” and reality

Recently I’ve been toying around with WordSnap OCR (project page, source code, app on Android Market), an app for OCR-based camera input on Android. In the process, I found out a few things about “smart” versus “fast”.

At least in data mining, “fully automatic” is an often unquestioned holy grail.  There are certainly several valid reasons for this, such as if you’re trying to scan huge collections of books such as this, or index images from your daily life like this.  In this case, you use all the available processing power to make as few errors as possible (i.e., maximize accuracy).

However, if the user is sitting right in front of your program, watching your algorithms and their output, things are a little different. No matter how smart your algorithm is, some errors will occur. This tends to annoy users. In that sense, actively involved users are a liability. However, they can also be an asset: since they’re sitting there anyway, waiting for results, you may as well get them really involved. If you have cheap but intelligent labor ready and willing, use it! The results will be better or, at the very least, no worse.  Also, users tend to remember the failures. So, even if end results were similar on average, allowing users to correct failures as early as possible will make them happier.

Instead of making algorithms as smart as possible, the goal now is to make them as fast as possible, so that they produce near-realtime results that don’t have to be perfect; they just shouldn’t be total garbage. When I started playing with the idea for WordSnap, I was thinking how to make the algorithms as smart as possible.  However, for the reasons above, I soon changed tactics.

The rest of this post describes some of the successful design decisions but,  more importantly, the failures in the balance between “automatic” and “realtime guidance”. The story begins with the following example image:

Original image

Incidentally, this image was the inspiration for WordSnap: I wanted to look up “inimical” but I was too lazy to type. Also, for the record, WordSnap uses camera preview frames, which are semi-planar YUV data at HVGA resolution (480×320). This image is a downsampled (512×384) full-resolution photograph taken with the G1 camera (2048×1536); most experiments here were performed before WordSnap existed in any usable form. Finally, I should point out that OCR isn’t really my area; what I describe below is based on common sense rather than knowledge of prior art, although just before writing this post I did try a quick review of the literature.

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My godfather is a Markov model

Before the memory is completely lost in the dust of time, I’d like to document how I ended up with this domain name. It all started last summer, when I decided to start a personal site. Of course, both my first and last names were already taken, even in TLDs I’d never heard of before.  But using my name would have been too easy anyway.  Challenge is good.

Politically-correct and totally un-sarcastic as I am, I originally wanted to go with some combination of “principled anarchy”.  Now, that was available! Apparently, nobody wanted to touch it with a ten foot pole, not even cybersquatters; which kind of gave me a hint.  Wouldn’t want to, say, end up in a three-letter-agency watchlist, at least not while in the US on H1B.  They might not share my sense of humor.

So, armed with online thesauri, dictionaries, the internet anagram server, and things like that, I set out on a name quest.  I don’t remember anymore what I tried; “coredump” (which, in case you didn’t know, has “code rump” as an anagram—still available, if you’re interested), “segfault”, “brainfart”, “farout”, and pretty much anything else I could think of: all taken.   Even these names as well as these are taken (thank god!).

At some point I was naïve enough to hope that a Tolkien name would be free.  No luck of course, anything semi-pronnounceable was taken.  You’d have to go as far as, say,  “gulduin” (which, by the way, means “magic river” in Elvish) to find something available. Good luck getting people to remember that!  Oh well, at least I had a reason to actually read some of the Silmarillion; if you’ve tried this and you’re not a religiously devoted Tolkien fan, you know what I’m talking about.

After the first week of searching, I think I even got temporarily banned from Yahoo! whois search. In desperation, I finally turned to one of many domain name generators.  I asked omniscient Google to give me one and, as always, it obliged.  By now I had decided that I wanted a name as free of any connotations as possible (say, like Google or Slashdot, not like Facebook or YouTube).  I went through things like “fractors”, “naphead”, “magnarchy”, “aniarchy”, “mallock”, “hexndex”, “squilt”, “terable”, and so on. It’s amazing how several weeks of searching in frustration temper one’s standards of quality. Anyway, one day “bitquill” popped up: neutral, inoffensive, bland, unusual, and a composite which is short and almost pronnounceable!  I couldn’t ask for much more, so I registered it.  

That, and “clusterhack”.  Sorry.  I couldn’t resist.

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Hello Android

After blabbering about Android, I decided to get my hands a little dirty and actually write some code. For various reasons, I won’t describe the app (it was a “weekend hack” anyway), but hopefully my first impressions will be clear even without a specific context. Read the rest of this entry »

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Back again…

Seoul

After coming back from Seoul, New York seemed even dinkier than the last time I returned from a trip. As I was boarding the plane at Incheon, I picked up a copy of the Wall Street Journal (Asian edition). I had enough time to read almost all of it, as KAL arrived into Narita early, but Continental was six hours late. It might as well have been called “The GM Journal”, since about two thirds of the stories were about GM and Chrysler, and how the US government is trying to save them from doom due to chronic mis-management and exorbitant legacy costs.  

My wife, who has a far more sensitive nose than me, jokes that the first thing you smell upon disembarking the plane is cigarette smoke in Greece, and garlic in Korea. Read the rest of this entry »

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