AuthorTom Lee

In Ersilia, to establish the relationships that sustain the city’s life, the inhabitants stretch strings from the corners of the houses, white or black or gray of black-and-white according to whether they mark a relationship of blood, of trade, authority, agency. When the strings become so numerous that you can no longer pass among them, the inhabitants leave: the houses are dismantled; only the strings and their supports remain.

From a mountainside, camping within their household goods, Ersilia refugees look at the labyrinth of taut strings and poles that rise in the plain. That is the city of Ersilia still, and they are nothing.

They rebuild Ersilia elsewhere. They weave a similar pattern of strings which they would like to be more complex and at the same time more regular than the other. Then they abandon it and take themselves and their houses still farther away.

Then, when traveling in the territory of Ersilia, you come upon the ruins of the abandoned cities, without the walls which do not last, without the bones of the dead which the wind rolls away: spiderwebs of intricate relationships seeking a form.

(Previously)

I mostly like my Sonos system. The downsides: I had a controller die on me out of warranty; it’s a bit pricey; and it doesn’t have Airplay support. This last one, at least, turns out to be fixable, thanks to a few open source projects and the Raspberry Pi.

The ingredients:

• the Shairport project, for providing Airplay
• the SoCo project, for controlling the Sonos

This last one is important for making the Sonos start listening to its line-in when Airplay begins to be used.

Getting your Raspberry Pi on your wifi network is a bit of a pain. You’ll need to compile Shairport’s dependencies and install some modules from CPAN. SoCo’s setup.py doesn’t leave you with a working installation, but the codebase is fine if you use it directly.

With all the pieces in place, you just need a script like this to switch the Sonos:

import re, sys
from soco import SonosDiscovery, SoCo

if __name__ == '__main__':
main()

and then to start the Shairport daemon like so:

perl /home/pi/sonos-airplay/shairport.pl -d -w /home/pi/sonos-airplay/shairport.pid -l 100 --apname="Sonos" --play_prog="/home/pi/.virtualenvs/sonos/bin/python /home/pi/sonos-airplay/set_line_in.py bedroom"

This will call the set_line_in.py script every time a new Airplay client connects.

For good measure, here’s the /etc/init.d/shairport startup file I’m using:

#!/bin/sh
# /etc/init.d/shairport
PIUSER='pi'
case "$1" in
start)
/home/pi/sonos-airplay/start_shairport.sh
echo "Starting Shairport Server for $PIUSER "
;;
stop)
kill `cat /home/pi/sonos-airplay/shairport.pid`
echo "Shairport Server stopped"
;;
*)
echo "Usage: /etc/init.d/shairport {start|stop}"
exit 1
;;
esac
exit 0

It all works pretty well! The only real downside is the volume: Airplay’s pretty quiet. I should be able to automate the volume adjustment on the Sonos — SoCo exposes that functionality as well, and Shairport can call scripts upon client disconnect, too, to reset the volume. But I haven’t had a chance to write that yet.

Anyway, if folks start wandering in from Google and find this useful or desirable, let me know. I could probably make this all a bit more reusable without a ton of trouble (distributing a Raspberry Pi filesystem image might be the easiest thing, really).

UPDATE: Hmm. Subsequent investigation of the Sonos’s line-in level adjustment capabilities reveals that the SoCo portion of this might be unnecessary: there is indeed some capacity for adjusting amplification on the line-in. Better still, there’s some sort of line-in activity detection! I think I might stick with my script anyway: I have a Sonos unit on the porch that’s usually powered off; I’ll probably just adjust the script’s logic to pipe the line-in to it if it’s activated. Still, for most users the Shairport stuff should be sufficient.

I mean, yikes.

So look. I’m obviously no designer. And I agree that the pie charts in that blog post, which are clearly cherry-picked for maximum terribleness, are terrible.

But usually pie charts are fine. I’m not going to bother collecting examples that demonstrate this, because unless you’ve led an unusually brief or interesting life, you’ve seen thousands of them and understood them perfectly well.

But I realize this isn’t going to stop you. You have been to the Seminars. You have received the Texts. You have studied the words of the Prophet Tufte, and you have concluded that they demand jihad. I’m not going to convince you otherwise.

I’ll make my case anyway.

To me, pie charts are handy for conveying information about the relative components of a whole because they do so through visual cues of both area and angle. If you need to show the relative sizes of multiple wholes, you can do that by varying the pies’ size! Fun times, but I suppose it’s not for everyone.

But I would like to request that you not join the pie-haters I sometimes see advocating for donut graphs or treemaps as alternatives. These have all of the problems of pie charts, but they throw away one of the two visual cues. (Treemaps can be useful for expressing hierarchies, and donut graphs are useful for… er. Well. Sometimes you can put a number in the middle of them!)

If your graph is confusing, it’s probably a bad graph and you should try to make a different one. But let’s not pretend that there’s a Platonic Graph that we’re working toward just because some dweeb in an eye-tracking lab eked out a few milliseconds’ worth of statistical significance. Real graphs used for Science usually look like this (to be honest, even that red line is a bit decadent). It’s not great, but it gets the job done. Science is pretty much going fine despite a lot of shitty-looking graphs.

If you ask me (you haven’t) presenting information is about tradeoffs. I don’t really want to spend all day looking at things that are ugly, and that’s okay. Nicely designed graphs are pleasant! People like to look at them, which is important if you want people to look at your graphs. Even if you really think pies are inefficient, you’re kidding yourself if you think graphs are always purely made to shoot numerical truth into your readers’ brains (when was the last time you adjusted the stroke weight on an error bar?).

People have varying tastes. That’s a totally legitimate rationale for hating pie charts. And they’re not the best choice for everything. I’m on board with that, too.

(Building part of your self-conception around the fanatical endorsement of the work of the one widely-known name in information design is, I would suggest, a little sillier. But whatever floats your boat. I went through a big anime phase in college, for instance.)

Anyway: pie charts. All I really ask is that you please shut up about them.

My last laser-cut finger-joint project (and the electronics inside) was meant to be a time machine, an emergency device, a way to bend reality. Also, it was octagonal. These aims proved to be unrealistic. I did pull off the octagonal bit, but even that was a struggle.

Less fraught projects need enclosures, too, though, and I liked the technique. You can do some super-cool stuff with lasercut materials. Like 3D printing, it removes craftsmanship as an excuse for failing to instantiate the things you imagine.

But although laser-cut construction allows for much stronger and prettier materials than 3D printing, the process of translating from two dimensions to three is trickier than you might think. There are various considerations, from the variance of the width of the source material to the width of the path burned away by the laser (“kerf”). Accounting for these things in vector graphics editing programs can be quite tedious. It’s easy to make mistakes.

The right way to do this would probably be to write a plugin for Inkscape/Illustrator. But I’m more comfortable writing Python, so that’s what I did. I wrote up a support class that facilitates the creation of finger-joints, and which handles things like kerf automatically.

The output isn’t designed to be ready-to-print. You should plan to import it to a vector editor and do subsequent work. Here, for example, is the output of a simple script I used for my latest project:

And here’s the EPS I constructed from it and submitted to Ponoko:

Note the difference in the corners of the larger piece, in particular. Some editing is necessary. But the results are quite nice!

(ignore those laser scorch marks; I haven’t pulled the adhesive paper side off yet, but when I do and flip the sides, the outside should be relatively pristine)

I’ve published the code, and would love to see it expanded into a more general-purpose toolkit. Apologies for its hackiness/non-pythonicness. I assure you it’s much better than the first two drafts. This version does matrix math and everything!

As I began this book, I was disappointed. I had picked it up after reading The Idea Factory, the fascinating history of Bell Labs: Fortune’s Formula was mentioned glowingly in the acknowledgements. Bell Labs employees — including my favorite, Claude Shannon — taking a road trip to Vegas to use their reality-bending powers of analysis to defeat the casinos? Sign me up.

Digging in, the danger signs began accumulating. Poundstone’s prose is workmanlike at best. There are endless asides about the backgrounds of various mobsters tied to the gambling industry. And while Shannon’s trips to Vegas (to beat blackjack and roulette, it turns out) are exciting and ingenious, the man was smart enough to quit once his intellectual curiosity had been satisfied. This is no Bringing Down the House. Vegas fades from the scene by the book’s halfway point.

But this is where Poundstone’s project becomes clear. His language loosens, his transitions from explanation to narrative become more fluid, and he starts calling people dopes. He enters his element, and embarks on the effort that excites him. Poundstone is not just fleshing out a fun Bell Labs footnote; he’s telling a story about arbitrage and the modern finance industry.

In particular, he’s telling the history of the Kelly Criterion, an asset allocation formula — aka betting system — mathematically proven to maximize returns over the long run, given reinvestment of winnings and quantified odds. The story of the Kelly Criterion is interesting enough. Its foundations are rooted in Information Theory, the field Shannon singlehandedly invented, in part through the revelation that information works by reducing uncertainty — and what is a gambler’s edge if not a reduction in uncertainty? It’s also fascinating to learn that despite its mathematical soundness, the Kelly Criterion apparently remains a subject of fierce debate, largely rejected by economists, finance experts and business schools thanks to a combination of practical, intellectual and cultural reasons (that it was invented by information theorists, not economists, doesn’t help its cause).

But this book is about more than that. Poundstone mounts an implicit but still quite damning case against the modern finance industry. It’s not just the slight seediness of mathematical concepts invented for roulette translating smoothly to Wall Street; it’s the gangsters we were introduced to in the book’s opening chapters make the trip, too, swept along by a conscious legal strategy (going legit) into a new form of gambling. By the time a young prosecutor named Rudolph Giuliani discovers he can use RICO, a law designed for the mob, to go after titans of finance, the story has become a fascinating moebius strip of money and risk. Is it a coincidence that Ed Thorp, the man who taught the world how to count cards, is also the analytic mind behind one of the first and most successful hedge funds in history?

Thorp comes out of this book looking like a singular genius, and a probably-ethical one, to boot. I’m convinced, but some suspicion is warranted — Poundstone seems to have gotten a lot of help from him in putting this book together. Still, the man’s record of returns and lack of indictments speak for themselves.

Aside from the Kelly Criterion and Wall Street’s strange bedfellows, there are two important takeaways to be had here:

First, Poundstone does a number on the Efficient Market Hypothesis. I think he treats it fairly, explaining the views of its proponents, its intellectual heritage and the debates surrounding it with nuance — like Thorp, Paul Samuelson is portrayed as a brilliant and towering figure (I’m going to have to remember this trick of his — what an amazing dick move). The random walk is explained, as are investment strategies that can succeed despite the market’s unpredictability. Fees and common investor mistakes are acknowledged, and he allows no confusion about what a typical investor should do: buy an index fund and ignore anyone who tells you they can beat the market.

Still, by the end of the book it’s very hard not to conclude that a few ubermenschen walk among us — people like Thorp — who can consistently identify systemic pricing errors and develop ingenious ways to profit from them. The history of hedge fund tactics is explained, and of course it turns out to be built on these manipulations, from the warrant-based delta hedge to junk bonds to leveraged buyouts.

Before you ask: yes, Poundstone considers the survivor-bias argument at length. But I was still convinced that these techniques have worked — at least until they’re disclosed and the market begins pricing them in. EMH proponents tend to hand-wave toward this pricing-in happening with calculus-like instantaneity, but the actual history makes it clear that the process has sometimes taken months or years.

Second, and following from this, it’s hard to read Fortune’s Formula and not conclude that finance has evolved toward (and probably past) a point of uselessness — perhaps even destructiveness. Why does our society reward this kind of work? To provide better prices, they say, so that capital can be allocated more efficiently. The problem is that the process has no finish line. Arbitrage opportunities are discovered, profited from, and cease to exist; but Manhattan remains steadily expensive. So new arbitrage opportunities must be discovered or invented, via the sorts of exotic financial instruments that we’ve heard so much about these past years. But the low-hanging fruit is gone — the margins on these deals are tiny, so they have to be amplified through incredible amounts of leverage. The complexity of the system inevitably sometimes reaches a point where interdependencies aren’t fully realized — Poundstone makes this point by narrating the epic destruction of LTCM — and things blow up.

Fortune’s Formula was published in 2006. Poundstone doesn’t even need the Great Recession to make his point.

A few caveats. I’m not a great consumer of books about finance. I haven’t even read The Big Short. It’s very possible that these insights are less novel than they seemed to me.

But this book taught me quite a bit of history, more than a few financial concepts, and changed the way I think about investing/gambling/risk. I’m tempted to reread it, even if just to make sure I got the thrust of the early chapters right (if I’d known who Ed Thorp would become, I would’ve paid a bit more attention — I had heard the name before, but didn’t make the connection).

Highly recommended.

I’m not sure what to think of this one. Watts rattles off a ton of counterintuitive facts about human cognition, and they’re facts that I love and am fascinated by — this is what I spent my college years studying — but I can’t help but be irritated by his recitation of them.

A big part of this is his prose, which is pretentious and baroque. Three uses of “calcareous” in a single novel might not *sound* like a lot…

The mechanics of what’s going on are often difficult to track. This isn’t so much because of the alienness of the ideas on offer, like in Quantum Thief. It’s more that the language obscures what’s going on. It’s quite a contrast from Rendezvous with Rama, another first-contact-with-a-questionably-populated-alien-craft story. The action is overwritten, and hard to track.

Watts also gives himself too much credit for the quality of the ideas he’s offering. The motley crew of savants that he offers seem not-that-abnormal, to be honest. The idea that a mediating “jargonaut” is necessary to translate their bizarre utterances into baseline-human comprehensible intelligence seems implausible (even with some minor hand-waving about this being an edited account). His characterizations are fairly thin, too — in light of this, giving one character multiple personalities seems like a particularly poor decision.

The biggest problem may be how overeager he is to get to his ideas. There’s a distinct refusal to self-edit — the closing notes of the book mention that his other sci-fi series, Rifters is available in unabridged form on his website, and indicates some kind of disagreement with the publisher about the shorter form the printed edition took. Hmm. One can’t help but wonder if the ideas about the singularity, empathy, Searle’s Chinese Room, qualia zombies, evolution and vampires (sigh) should have been pared down, at least slightly (at the very least the vampires should have been tossed).

Still, I have to admit that the book picks up in its final third. Watts proves to have been building toward something, and it’s coherent and interesting. I’m not a huge fan of the consciousness-denying hypotheses that I associate with Dan Dennett and that Watts attributes to Thomas Metzinger. But they’re presented mostly coherently (though consciousness is given seriously short shrift by Watts, particularly its likely role in organizing concepts so as to make technology possible). I’m more of a mystic, or at least sufficiently guilt-riddled as to want to embrace panpsychism. But I will admit that he’s making an interesting argument, even if it is cobbled together from a truly wild hodge-podge of quite-tentative research and misstatements about electromagnetism.

A ton of people that I know love this book, and a ton more are intrigued by these philosophical questions. If you’re less bugged by the writing than I am, you might really like it. For me it was just okay, though it earns points for its ambition.

I just reread this thing for the who-knows-how-many-th time. It’s still quite funny! But it’s interesting to read it as an adult:

• The humor is a little harder to take than it used to be, having now been exposed to long years of amiable nerds gracelessly aping the Monty Python sensibility. Douglas Adams books are clearly another transmission vector for this tendency to tediously parrot (though Adams’ own execution, while inarguably derivative, is fluid and hilarious).
• It’s quite nihilistic, thought mirthfully so. I suspect this had a big influence on my own comedic preferences.
• It’s also pretty libertarian in its perspective, particularly the passage with the ruler of the universe (though I suppose that’s in the next book).
• It’s thin! Adams wasn’t kidding about stopping mid-stream.
• Ben’s right that The Restaurant at the End of the Universe is less satisfying, largely thanks to its repetition of jokes. I think things get quite a bit better further along, though, particularly in Adams’ treatment of the Golgafrinchans, which is considerably more humane than the uniformly acid tone of the first book.
• Last thought: Adams is of course mostly a humorist, but he’s underrated as a stylist. Magrathea is spooky and lonely. The primeval earth is calming and lovely. England is small and homey. This talent really shines through in his nonfiction book Last Chance to See, incidentally, which I recommend highly.

A really lovely history of Bell Labs and its incredible impact on the world. Gertner does a fantastic job of synthesizing existing historical accounts, while also unearthing his own wholly original findings through interviews and dives into the AT&T archives.

I found the book particularly interesting since my job is all about managing technical staff who are trying to identify worthwhile problems and new ways of looking at them. I don’t mean to compare our modest efforts to those of the people who invented the transistor, of course. But it was reassuring to have many of my engineer’s intuitions about what makes for successful research environments — adequate resources, plenty of freedom, good people, a focus on the questions themselves and a healthy tension between theory and application — validated by the management theories captured in this book.

It’s clear that Gertner has favorites among the cast of characters orbiting Bell Labs, but that’s okay; so do I. His charming and moving account of Claude Shannon is particularly affecting, I thought. And it’s hard to read this and not emerge a John Pierce fan. The treatment of Bill Shockley, by contrast, is relentlessly negative, though Gertner makes a strong case for this being wholly deserved.

My only other window into the Bell system is Tim Wu’s book, which is notably unmentioned here, despite being published more than a year earlier than The Idea Factory. I assume this has something to do with publication lead times, something to do with Wu’s book being an analysis that rehashes the same histories Gertner mined, and something to do with its less charitable perspective on AT&T and its monopolistic activities. Still, an interesting omission.

Anyway, this is highly recommended for anyone inspired by digital technology or information theory. I think this will finally nudge me into reading the Gleick book (as well as Fortune’s Formula, about Shannon’s efforts to beat Vegas and the stock market — that one, in particular sounds fantastic to me).

Beautifully written; this makes me want to read more Le Guin.

I wasn’t bowled over by the ideas on offer. In part this is probably because this book is an innovator; others have used sci-fi to examine gender in more radical ways since, which makes this feel slightly tame.

But I suspect that my reaction is also in part because I’m a man. The signature implication of Gethenian physiology is that things in their culture aren’t gendered. This mostly registered to me as bland ambiguity, but I can imagine that might have to do with my own gender being the default for so many things in my own culture (witness even Le Guin employing “he” as the pronoun used for ungendered characters).

But though I might have a blind spot when it comes to the novelty of the setting, I feel pretty confident in saying the plot is thin. It’s driven largely by politics, but those politics are presented through a veil of intentionally alien concepts (shifgrethor, for example) that prevent the reader from feeling excited, Wolf Hall-style, even when very little is actually happening.

Inscrutable political shuffling then gives way to some heroic questing, but with an extremely spare cast of characters. That’s fine for a Jack London story, but I’m not sure it works here — particularly since Le Guin shies away from making us uncomfortable with the Ai/Estraven dynamic’s final destination.

Basically: needed more kemmering.

Really interesting, and wins points for bothering with characterizations. I’m not sure how much sense it makes, though. In this world both food calories and fossil fuels have become massively more expensive (due to engineered plagues and depletion/climate change, respectively). But this leads to more of the energy economy being driven by food calories? Mastodons are not an efficient energy storage mechanism! Where are the solar panels and nukes and wind turbines and tidal power?

Aside from that I have three main complaints. First, the book’s climax feels disjointed and loses the winning human scale of earlier action — the characters who’ve been built up in earlier phases are left on the sidelines while the action moves through redshirts and cipherlike Thai generals. Second, the sexual exploitation of Emiko is porny in an unfortunate way. And third, Gibbons seems underutilized to the point where he’s mostly just a Dr. Moreau throwaway.

The setting is pretty cool, though, and the neocolonial stakes are extreme and awesome. This is like Atwood’s dystopic genomic imagination but played out through believable institutions.

I sort of fell off from my commitment to cross-post them here. Partly this is that I’ve slowed down; partly it’s that I’ve been reading a bunch of semi-trash thanks to being committed to two different sci-fi book clubs. Nevertheless, time to clear out the queue.

People seem ready to hate Google Glass!

Yesterday there was the Tumblr White Men Wearing Google Glass. This is not only slightly mystifying — a Google image search for “Google Glass” returns what seems like a pretty diverse collection of testers and models — but, speaking as a white man who aspires to wearing Google Glass (at least briefly), hard not to take a little bit personally. In fairness to the Tumblr’s author, Robert Scoble is a faintly ridiculous person, and adding “screaming” and “in the shower” certainly does not yield a net improvement in gravitas. This is, arguably, another fitful effort to delineate a gendered subtext to Glass, a project started when Sergey Brin stupidly described smartphone use as “emasculating” during a TED sales pitch. (I think the most plausible reading is that he intended the word to mean “disempowering” rather than “womanly”, but the charitableness of your reading may reasonably differ.)

This isn’t the only place where people are picking sides between Team Glass and Team Glass Is Stupid And Bad. Earlier today Wired published a truly awful essay by Marcus Wohlson predicting Glass’s failure for different (though still Scoble-related!) reasons. It begins by erecting a geek/nerd continuum best left to Joss Whedon fan boards, goes on to a question-begging explanation of Segway’s lack of success, and concludes by belittling Glass’s lack of coolness — as if coolness was an objective quality rather than something constructed collectively by people like the author himself. It’s a bit mind-boggling that anyone could so thoroughly fail to see the arbitrary nature of culture. (The best reply to the Wired piece is probably this great post by Bianca Bosker discussing the history of eyeglass adoption. But for a shortcut, the next time you see a world leader wearing a business suit, reflect on whether Europeans just happened to come up with the objectively awesomest formal attire.)

Watching people declare their tribal loyalties is fascinating and wearying. It’s not surprising behavior, exactly: this product launch is a big, SEO-worthy cultural event, and one wouldn’t want to be caught un-jaded. Certainly I don’t: I’ve cheerfully presented from a slide deck making dumb Dragonball Z jokes at Glass’s expense.

Nor should consumer tribalism be surprising to anyone who’s read John Gruber’s ongoing project to construct a theodicy of Apple, or anyone who has spoken to a teenager for thirty seconds. For people who don’t enjoy getting angry about sports or religion or nationalism or politics, consumer gadgets seem to fill the void.

Still, in this case I can’t help being irked by these reactions. I tend to emotionally align against new tech products (“that’s dumb/it’s been done”), so this might seem hypocritical.

But don’t you have to respect the ambition of Glass? This is the most daring project I’ve seen in ages. Not just automation of an existing system of transport/food delivery/coupons. Not a privatized homage to NASA triumphs of decades past.

Consider what a persistent connection to the network means. Already I find myself giving up on learning certain classes of information — why would I need to remember a friend’s address or a bus schedule or a business’s hours? Those parts of my mind now exist in my phone, and sure, the retrieval times are poor, but the integrity and capacity are excellent. Narrowing the latency of that interface further would be a profound change.

And that’s to say nothing of the implications of persistent enmeshment in the conversations and status competitions of social media. You can take your strange, geographyless social universe with you on the go! On your head (if not yet in it)! You will be fully in one place even less often than you are now. If Twitter is like telepathy, Google Glass strives to be like astral projection*.

I suspect that humans’ individual nervous and collective social systems aren’t currently capable of dealing with this. Either Glass will flop or we will. For what it’s worth, I think the former is pretty likely (battery or input bandwidth are where I’d place my bets) and, failing that, the latter is all but certain. But I don’t really know. I am certain, though, that Glass is a wildly ambitious transhumanist project, a crazed conceptual art piece being executed on a massive scale with, mystifyingly, real engineering and industrial muscle behind it.

I have no idea if it’ll succeed; I have no idea if I want it to succeed. But carping about its coolness is like complaining about the case color of the first A-bomb. To hell with that. Even the privacy argument about Glass strikes me as shallow.

The question is: what does Glass and its successors aim to turn us into? Is it something we want to become, or can become? And if it’s to fail, can it please, please be for reasons more profound than fashion or lack of 4G?

* ask me about my Doctor Strange-themed trend piece pitch!

UPDATE: This is also dumb!

Let’s find out. This interview elicits a number of quibbles from me.

[… Y]ou never had the technology of perfection that was as available and as cheap and as ubiquitous. You never had Google Glasses before, you never had self-driving cars, you never had doors that recognise who you are and let you in.

We still don’t have two of those things; declaring them “technologies of perfection” seems premature. Wikipedia says we’ve had the third technology for about four millennia.  I agree that connecting the system to Klout instead of  human-mediated systems of status-determination is annoying, but it seems like an incremental change.

If [Valley royalty with political ambitions] join the Democrats or the Republicans, then it would be very boring. If some of them decide to go and resurrect the democracy movement, then that would be very exciting to write about.

It was initially a bit gobsmacking to see a critic of Silicon Valley’s political naivete declare that an tech-led attempt to create a third party would be “very exciting to write about.” But perhaps he finds this exciting in the same sense that a hunter looks forward to a deer wandering into a meadow.

In America, you need to drive and you need to drive more and more

Vehicle miles traveled is declining, and the global trend is toward urbanization. But his point about the potential effect of self-driving cars on the commuting equilibrium is well-taken.

As drones get cheaper and 3D printers get cheaper, all that can be done in a very different manner. And there will be huge implications for mobility from 3D printers, which again some people don’t expect.

3D printers are mostly good for producing alternatives to injection-molded plastic and, to a lesser extent, ceramic and metal, in applications where price and the strength of the material are not important considerations. Looking around my desk, the items that could plausibly be produced by 3D printer — without an expert to assemble other pieces, at which point the automation rationale falls apart — include a coffee scoop, a pencil case, and a few collectible figurines. And I assure you that my desk is extremely messy.

Products like this are mostly imported and cost basically nothing, and consequently there’s not going to be a ton of capital available to build a huge same-day iPhone case-manufacturing infrastructure. Yes, Staples is going to offer in-store 3D printing, and yes, I am pretty excited about it for hobbyist reasons. But it’s going to be a niche. This technology will continue to have a growing impact on industrial design (where it’s been in use for decades), fabrication of bespoke objects like running shoes and medical implants, and might make some consumer goods slightly more feasibly repairable. But I think people are confusing “how super-cool is this technology?” with “how likely is this technology to change how we live and work?” Seriously, go give Thingiverse a good look. It’s lovely work, and some of it would be quite handy (albeit wildly expensive compared to existing injection-molded or stamped alternatives). But not that much of it.

Most useful objects are made of multiple materials, and 3D printing is not yet very good at that kind of fabrication. Perhaps it will grow to be! In the meantime, I suggest that optimists try pricing a pick-and-place machine, then imagine what it might cost to buy one that works in three dimensions. My next pair of sneakers could be 3D printed; parts of my next bicycle probably will be; my next kneecap certainly ought to be. But this is a tiny fraction of the manufactured world.

I have loved the Toynbee tiles for a while. They’re all over the east coast, and Philadelphia in particular. There’s something urgent and singular about them. I’d looked the phenomenon up on Wikipedia a few times, but what I found was always just a description of a mystery.

But it’s a mystery that turns out to be solved. My colleague Bob pointed me toward this documentary, which I watched tonight and really enjoyed. I won’t say it’s the most artfully composed film, but the story it tells is wonderful.

The underlying impetus is necessarily about mental illness, and as with every fascinating story in this vein, one is all but certain to find tragedy if the temptation to keep digging is indulged for too long. Luckily (though perhaps also callously) the film avoids this, while still convincingly explaining the Toynbee tile mystery.

Spoiler alert, I guess: one industrious stranger has been fixated, for decades, upon the idea that science will be able to deliver the afterlife that he feels God has promised but failed to deliver. Molecules will be traced to their historical source, and reassembled, and life will be renewed. On Jupiter.

It’s crazy, of course, but watching the movie’s subjects trace minute particles of information through decades, assembling them into a completely coherent whole–it’s a thing to behold, and makes the tiles’ thesis seem a little less nuts.

(Also worth noting: the extent to which this investigation is enabled by the internet has to give pause to anyone worried about our modern panopticon. The film doesn’t dwell on this point, but it’s absolutely clear that this mystery would have persisted–and perhaps never even been noticed–in the days before the net.)

I’m sympathetic to what Matt says here, but I think he misses the bigger value of Twitter snark: as long as journalists and experts use Twitter for social ends (whether by telling the best snarky joke or whatever) their participation in the medium will remain at least somewhat grounded.

The alternative is to make the professionalization of Twitter complete. I already have quite enough of that, thanks — I don’t need more of people pushing their day’s clips at me through pathetically thin news-hook framing in what amounts to a really shitty, lossy RSS reader. Who would want that? I know it’s fun when you’re the one staring at ChartBeat (I do it all the time!), but for the people on the other end of the equation it’s a drag, even if they don’t realize it.

The great thing about Twitter is that you can absorb the thinking of and even interact with people who have a huge amount of expertise, who might be inaccessible via other means. They’re steeped in whatever it is they work on constantly, and if you follow them you’ll start to understand their perspective and vocabulary. But that works best when they’re being honest. Honesty means direct, non-calculated, first-order interaction with the medium. And that won’t happen unless they’re able to satisfy human drives other than the need for clickthroughs, which to be honest seems like it might not have even been in Maslow’s hierarchy in the first draft.

I’m glad that Nick Beaudrot has figured out that he wants to interact with Twitter on a more limited basis, I wish him luck with his self-promotion-only strategy, and if I had been following him before now I would cease doing so immediately.

UPDATE: It occurs to me that I wrote something similar a few years ago. The framing’s different, but the upshot — that social network users attempting to avoid trivial content become a free rider problem — seems relevant.

The folks at the Sk/oll W/orld Forum were nice enough to let me write some rambling thoughts about “Big Data” for publication in, I’m guessing, a glossy brochure that will be flipped through if any of their event’s panels prove to be particularly tedious. I am grateful for the opportunity, and congratulate myself for not making any of the childish chewing tobacco jokes that were ripping through my mind during the process.

Normally I would sheepishly self-promote on Twitter and leave it at that. But it is maybe worth sharing how the editorial process went.  I originally wrote a piece that said, “You know, this stuff isn’t really new–the analysis of quantitative data and its application to social policy are at least a century old, and we probably shouldn’t expect any sudden home runs. But it is true that some new things are being measured lately, so who knows, we might figure some new stuff out.”

This was totally inverted, though, to emphasize the exciting new types of data and to minimize my yawning ho-hummery about the limits of technocratic governance. And it’s true that this inversion makes for a much more compelling piece! The editors I worked with did their jobs well (though I’ll admit I have no idea what the hed has to do with the piece).

But consider this datapoint when you read things about Big Data, or really any technology. Unless you achieve Morozovian levels of learnedness and vituperation, you’re not going to place anything that amounts to “Don’t Believe the Hype.”

…or one of them, anyway, was released today. You can find it here; or use this, a direct link to the PDF.

It really is unfinished — chapters end abruptly, discussions are alluded to that were clearly never written — and the whole thing is written (but not formatted) in Markdown. But it contains an extremely high percentage of Correct Opinions About The Web. Here’s one bit I particularly enjoyed about the Semantic Web (seemingly since relabeled as Linked Data, basically in order to escape this well-earned critique):

I have to say, however, the idea’s proponents do not escape culpability for these utopian perceptions. Many of them have gone around talking about the “Semantic Web” in which our computers would finally be capable of “machine understanding.” Such a framing (among other factors) has attracted refugees from the struggling world of artificial intelligence, who have taken it as another opportunity to promote their life’s work.

Instead of the “let’s just build something that works” attitude that made the Web (and the Internet) such a roaring success, they brought the formalizing mindset of mathematicians and the institutional structures of academics and defense contractors. They formed committees to form working groups to write drafts of ontologies that carefully listed (in 100-page Word documents) all possible things in the universe and the various properties they could have, and they spent hours in Talmudic debates over whether a washing machine was a kitchen appliance or a household cleaning device.

With them has come academic research and government grants and corporate R&D and the whole apparatus of people and institutions that scream “pipedream.” And instead of spending time building things, they’ve convinced people interested in these ideas that the first thing we need to do is write standards. (To engineers, this is absurd from the start—standards are things you write after you’ve got something working, not before!)

And so the “Semantic Web Activity” at the Worldwide Web Consortium (W3C) has spent its time writing standard upon standard: the Extensible Markup Language (XML), the Resource Description Framework (RDF), the Web Ontology Language (OWL), tools for Gleaning Resource Descriptions from Dialects of Languages (GRDDL), the Simple Protocol And RDF Query Language (SPARQL) (as created by the RDF Data Access Working Group (DAWG)).

Few have received any widespread use and those that have (XML) are uniformly scourges on the planet, offenses against hardworking programmers that have pushed out sensible formats (like JSON) in favor of overly-complicated hairballs with no basis in reality (I’m not done yet!—more on this in chapter 5).

Instead of getting existing systems to talk to each other and writing up the best practices,these self-appointed guarantors of the Semantic Web have spent their time creating their own little universe, complete with Semantic Web databases and programming languages. But databases and programming languages, while far from perfect, are largely solved problems. People already have their favorites, which have been tested and hacked to work in all sorts of unusual environments, and folks are not particularly inclined to learn a new one, especially for no good reason. It’s hard enough getting people to share data as it is, harder to get them to share it in a particular format, and completely impossible to get them to store it and manage it in a completely new system.

And yet this is what Semantic Webheads are spending their time on. It’s as if to get people to use the Web, they started writing a new operating system that had the Web built-in right at the core. Sure, we might end up there someday, but insisting that people do that from the start would have doomed the Web to obscurity from the beginning.

All of which has led “web engineers” (as this series’ title so cutely calls them) to tune out and go back to doing real work, not wanting to waste their time with things that don’t exist and, in all likelihood, never will. And it’s led many who have been working on the Semantic Web, in the vain hope of actually building a world where software can communicate, to burnout and tune out and find more productive avenues for their attentions.

Entertaining, brutal and accurate. Swartz does more or less succumb to the dream of the Semantic Web again in his conclusion. But who knows, maybe one day someone will deliver on it.

I picked up this handsome fellow in Texas:

I found him at Uncommon Objects, a really lovely and fun antique-y shop on Congress. They had a bunch of beautiful old radio stuff, but this was the only thing I walked away with. It’s a strange little piece — just a sheet metal enclosure for a voltmeter, probably from a test bench of some sort. Those two ports on the front were originally for connecting to the voltage being measures (though the internal wires connecting them to the meter had been snipped by the time I got to it).

It took a little work, but I’ve given this guy a brain:

That’s a wifi-enabled Raspberry Pi which can drive the VU meter. I also added a red and an amber LED (also controllable via the Pi).  I haven’t figured out what I want to measure just yet, but I’m sure something will come to me.

I’ve been trying to get a VU meter-driven project together for a while now, but between the software, hardware and enclosure, I was feeling a little overwhelmed. Having the enclosure taken care of made this a pleasant stepping stone.  Details/thoughts/tips:

Networking

• Linux wifi is a huge pain in the ass. Finding a card with a compatible chipset is your first major task. Lady Ada has helpfully identified a pretty cheap one and sells it here. I bought a slightly cheaper Monoprice card with my BeagleBone in mind, and it works fine with the Pi’s default Raspbian distro — no messing with firmware downloads or ‘nothin.
• Wifi cards suck up a lot of juice, and the Pi can’t supply very much over its USB ports. You might need a powered hub. The revision 2 Pi can power this adapter okay, but only if you boot with it in — plug it into a running system and the current draw will force a system reset.
• I hate messing with wpa_supplicant. The wicd package and its wicd-curses interface are your friends. But do not try to use them over SSH. The system flushes its routing when it sets up a new connection, and your SSH connection will get killed halfway through any connection to a wifi network, even if your SSH session started over ethernet. And then weird stuff will happen, like the wifi taking over the ethernet IP. It took me forever to figure out what was going on — I thought maybe the current draw of connecting to a network was bringing the system down. The moral turns out to be: use a keyboard and monitor until you’ve got a system that reliably boots and connects to the wireless network.
• I’ve got a simple Raspbian bootstrap script that updates things and sets up a Python environment. You might find it useful — though you’ll probably want to remove the part that gives my public key access to your system :-/

Hardware

• The meter was designed to measure a voltage range of 0-15V; delightfully, it still did this pretty well, despite being an antique! But the Raspberry Pi’s PWM only outputs a max of 3.3V. I had already bought a cheapo buck converter off of ebay before Timball reminded me that VU meters are basically just galvos, and use resistors to set their range. Here’s what the inside looks like:

  

  The resistor’s in the upper left. I dug out my old standby, reminded myself what a resistor network is, and added a trim potentiometer in parallel with the existing resistor (it’s the blue square on the far right of the second picture in this post). Through some careful tuning with a screwdriver I was able to make the arm sweep all the way to the 15 with just the weensy 3.3V of the maxed-out Pi. Hurrah!

• I also added a couple of status-indicator LEDs to the bottom of the meter. Their placement isn’t ideal, but you can see something when they’re on, at least. The meter wasn’t designed to accommodate them, so I had limited options.
• The LED holes and the entry point for the system’s power cable both required some Dremeling. Having sparks of hot metal showering your arm can be counted on to prompt some justified self-congratulation about wearing eye protection. Yeesh.

Software

• The wiringpi library and its Python bindings are designed to be pleasantly Arduino-like. Setup is  as easy as `sudo apt-get install -y python-dev && pip install wiringpi`. By default, you have to run your GPIO/PWM-manipulating scripts as root — there’s an alternate method available, but I couldn’t get the /sys/ GPIO interfaces to work properly in userland (though I didn’t try very hard). Ah well.
• Pay attention to the variability in pin names. wiringpi uses the pin numbers of the underlying microcontroller, not the numbers from the Pi connector. This table will help you translate between the two. Unless you’re doing something crazy, the Pi’s sole PWM comes out of GPIO1, which is “pin 1” to wiringpi and pin 18 on the Raspberry Pi connector.
• The software I wrote to run this thing is nothing special, though there is one convenience library you might enjoy: pwmcalibrate.py. Using a curses interface, it slowly steps down the PWM output from max to zero, recording the active PWM setting as you hit spacebar, which you should do as the needle crosses each step on the meter. This data is used to create a calibration file that can be easily reloaded, allowing you to set the meter by the desired display value without having to think about it much. It also does some simple linear interpolation if you ask for a value that’s between recorded calibration steps. I’m pretty pleased with how it performs, though the meter itself seems to display some performance variability at the low end of its range. Probably nothing to be done about this, given the age of the hardware. Oh, and it will slowly step down the PWM when making transitions, if you ask it to. This is worth doing if you don’t want the needle to bounce around a ton.

I think that’s it. Now I just need to hook it up to something worth measuring. Or Twitter, I guess.

It’s no fun to argue with the dead, but sometimes it can’t be helped. Or at least, I can’t help myself.

I’ve tried to limit how much I say about Aaron Swartz’s death, because I’m not sure I have much right to say anything. I only met the guy a couple of times, exchanged a couple of emails, replied to a few tweets. We were not friends, and I understand that I don’t deserve to grieve the loss of him the way his loved ones do. That would be distasteful and presumptuous of me.

But it is true that Aaron was part of an embarrassingly small pool of technologists that I revere — people toward whom I do not feel my usual, regrettable reflex toward rivalrous, Holden Caulfieldish pissiness. Instead, I was in awe of Aaron. I told the PACER story frequently, and I read his book reviews with disbelief. (I didn’t realize it at the time, but I suppose I must have begun my Goodreads book-reviewing habit as a way of emulating him.)

I didn’t know him well, but I sort of thought that someday I would, when (if!) I had done something that earned me the right. The fact that this will never happen is something that I suspect I haven’t fully grasped.

I’ve been reading a lot of his old stuff this week, and today that included the chapter he contributed to the book Open Government, which O’Reilly Media generously open-sourced as a memorial to Aaron. Entitled “When Is Transparency Useful?”, I think it could fairly count as one of the “high-profile, public denunciations” that Cory Doctorow mentioned in his remembrance of Aaron.

Aaron began work on a project supported by Sunlight, but he ultimately decided it was fruitless and abandoned it before completion. This was all before my time, but I know it resulted in some hurt feelings. I’m sorry things ended that way, because in this case I think Aaron got it wrong. He had good company, though: people like Lessig and Clay burned out on transparency, too.

I haven’t, and I don’t think I will. My understanding of how transparency works is different, I suspect (and probably different from that of my colleagues). It might be worth writing it down here, in advance of the next ally that loses faith.

So. Let’s say we’re running a school. The school has a cafeteria, which is largely unmonitored. In political theory we would call this a Hobbesian state of nature, but never mind that for now.

Within this cafeteria we have a bullying problem. Some kids make a regular practice of socking other kids in the gut and demanding their lunch money, which is then handed over. This is against the rules, of course, but enforcement is imperfect. Sometimes a teacher will be passing through and catch a bully in the act, or a victim will muster enough evidence and courage to tattle effectively. When that happens, detention is assigned to the bully. Along with anecdotal evidence, the number of detentions forms our sense both of the extent of the bullying problem and of how effectively we’re fighting it.

Eventually, repeated petitions from the members of the Audio-Visual Club convince us that this situation is intolerable, and we agree to install some surveillance cameras in the cafeteria. We can’t monitor every moment of footage, of course, but we make a concerted effort at the start, handing out tons of detention slips. Soon the bullies wise up, the on-camera punching stops, and the detention hall sits empty.

There are a lot of potential problems with this. Maybe the bullies have taken to waiting for the A.V. Club by the flagpole after school. Maybe they’re issuing verbal threats instead of physical ones. Maybe the invasion of student privacy that the cameras represent is a substantial harm that outweighs the reduction in bullying.

But it would be pretty silly to look at the empty detention hall and conclude that it means the cameras aren’t working. And it would be downright stupid if we gave in to disappointment because we find our lack of bullies to punish less emotionally satisfying than the pre-camera days.

Besides, even if the system isn’t perfect, it’s still probably harder for bullies to catch kids when they’re running past the flagpole instead of massed in the lunchroom. If the threats are now verbal, at least fewer people are getting punched.

You can argue that other reforms would be superior, and I might agree with you. Having the school sell lunch plans that eliminate the need for carrying cash, for instance, might make this entire problem disappear. But I do think that the cameras were a useful intervention, even if they fall short of “silver bullet” status.

Obviously it’s easy for me to concoct this story. But there’s evidence that this is how transparency actually works.

It’s deeply unsatisfying, I know! Believe me, I dream about our databases leading to corrupt politicians being marched off in handcuffs. It’d make for some great stories — I suspect grant officers would much rather hear about that stuff than about unmeasurable counterfactuals (“Why should we keep paying for these videotapes when they don’t show any bullying?”). If I’m honest, though, it’s probably a better idea to raise the costs of bad behavior so that it doesn’t happen as much, rather than trying to catch bad behavior after it happens.

Perhaps this isn’t enough to fix things. But it really can help.