Archive for Project
June 24, 2008 at 9:33 am · Filed under Project, Uncategorized
For no particular reason, I present the following.
I have just registered the domain “uncannyvalleyfarms.com”
I am soliciting proposals and discussion regarding the creation of a suitable entity or institution, perhaps merely a design, to accompany this little kernel of ambiguity I discovered before my caffeine kicked in.
Friends, colleagues, utter fucking strangers: Please contact me (here, mainly, in comments) with design proposals for logos, the web site, the product line. Whatever.
All proposals will be released immediately under the least stringent Creative Commons licensing—the Public Domain Dedication—with no restrictions on reuse whatsoever. No intellectual property will be protected or kept secret, at all, in the course of this project. Your email, your comments, your drawings; you send it to me, and I will assume that you have agreed to the terms of this license.
And in one year (24 June, 2009), the domain registration for uncannyvalleyfarms.com will not be renewed. In the meantime, what should be done with it? It’s parked, for now.
June 21, 2008 at 7:21 am · Filed under Project, Uncategorized
Seem to have survived the first day (actually a mere 6pm–11pm) of Startup Weekend Ann Arbor.
So far it’s been falling together surprisingly well. Somewhere between 80 and 90 people arrived, sat and pitched on the order of thirty ideas for projects, companies, ill-formed ideas, work-for-hire “help my pre-existing venture” and the like, and managed collectively to organize into about a dozen teams.
No voting, no formal processes, no points or markets.
No goddamned boss.
And (Cf. below) no coordinator of facilitator to speak of.
People talking to one another can do work.
People sitting in rows of chairs cannot do work. They are delayed from doing work. You cannot productively help people by sitting them in rows of chairs and talking to all of them at once. Not in this situation, which is innovating. Creating real stuff.
If you haven’t been paying attention for 25 years, you might view this as a “support” for the principle of emergence and self-organized community-building in large groups with diffuse shared goals and values.
There were a number of naysayers and explicit skeptics in the traditional business development community. Fuck ‘em. I don’t honestly care what they think about the relative merits of their “traditional” process—golf or other sports, diligent application of chinos and polo shirts, sitting in innumerable audiences to be told What Works for Your Brand!!1!, pleading and pitching and being falsely upbeat to VC and angels who are stupider than you can imagine for merely “liking the cut of your jib”. Don’t care about the whole stultified time-tested pile of crap that these folks assume is necessary and universally applicable.
I don’t care because I don’t want economic development. All that ritualized crap is how you build and support economic development institutions themselves, not companies. Not new people. Not small people. Not the long tail of economics.
Because that’s what this is. We—small businesses, startups, independents—taken as a whole we’re more than all the large-scale corporations combined. Maybe not in revenue, but that’s a hedge until I see the numbers. But in terms of work and knowledge and agility, we win.
Don’t care what those people in the big Old world think. That’s not a slangy lyric missing its pronoun, it’s a fucking imperative. Stop caring about what those people think. Stop golfing. Stop going to dawn breakfasts to rub shoulders with people who just got lucky and think being rich is proof of their acumen. Stop going to seminars. Stop asking.
Better you ask 100 random people for help—at the same time they’re asking you—than ask one Professional for Expensive Advice.
The success (so far) of SWA2 is especially noteworthy because it’s come entirely out of Ann Arbor. This event, the community and energy and all the practicalities addressed already, these aren’t some testament to the great minds from the Startup Weekend Brand. The Startup Weekend company (as such) has suffered a sad series of disappointments and restructurings over the last few months, and as a result the fellow now sitting at the helm is cut adrift. On his own. Untrained, untried, but earnest and in his way diligent. He’s a good kid; he can go far if he adapts and thinks and participates. He needs to learn about Open Space instead of doing a half-assed job reinventing it from stupid mistakes; about what “facilitating” and “leaving things open” actually means to a mob of strangers. But he may—and his “company” may, just barely—survive encounters with people meaner than we are.
To be honest, I hope he does. Then the things he could learn and pass along would have some value. You want legacies, after all. People learning and talking, that’s the only real legacy the world allows us.
But in this case, it’s 100% us. This is 100% pure-D home-grown Ann Arbor effort, innovative results, community and experience brought to bear on a “nontraditional” thing that “shouldn’t” work. Just like all the rest of the open-access, emergent communitarian events.
We make this happen. We’re not the medium, we’re not the raw material, we didn’t get molded or shaped. We did it to ourselves.
This is life. Life is bootstrapping, not asking for permission or molded out of clay. Life is interaction and horizontal conversations and ecologies of reinvention, not respect paid and traditions long held. Life isn’t rebellion or competition, it’s simply ignoring filled niches and hierarchies and seeking or creating new ones. It’s parallelism, and concurrency, and nobody watching from the top of the pyramid in the center.
So this here, this nasty confusing roil of ignorance, is life. In both senses. Not just symbolic, but a prescription. It’s how we can live, in this crapped-up old region of ours in this crapped-up old nation of ours, with not much to do with our resources, and so little money left on hand.
This is life. Life isn’t progress, it isn’t about amphibians crawling up and getting lungs and standing up and starting to type on computers. It isn’t any of those myths you rely on.
It’s just dynamics. How things interact with one another.
Figure out, in these times of trouble, what the other things are. The other ways, so time-tested and “reliable”. By comparison to what I’m calling “life”. Right? Know what I mean, eh? This is me winking, wagging my finger with my mouth hanging open.
Life, here. What’s that other thing?
Now pick.
May 30, 2008 at 9:19 pm · Filed under Project, Tidbits of nanohistory
More in a bit. Slow going, because the book is rather fragile (still in the publisher’s wraps, not bound.
How should I actually present the book online?
And can anybody read the handwriting? Here’s a bigger version.
May 5, 2008 at 1:37 pm · Filed under Project
Crossposted at Not An Employee blog
What: Ann Arbor Coworking “town hall” meeting
Coworking is any long-term arrangement in which independent professionals can work in the same space, whether full- or part-time. You may have seen mention on CNN.com, in the New York Times, or local media.
We’re trying to gauge interest in developing a permanent dedicated coworking space in downtown Ann Arbor. This might include shared office space, meeting and training space, a private cafe, a “makers’ den” for electronic and other fabrication projects. Any or all of those. The space might be run by a private concern, a nonprofit organization, or an ad hoc collaboration. It might be a membership organization, a business of its own, or a cooperative. Or something else.
Let’s explore what it might be, and why you might want to participate.
Where: Ann Arbor District Library Freespace, 3rd floor, Downtown Ann Arbor library building
When: Monday, May 19, 7-8:30pm
The meeting space is reserved from 5pm through 8:30pm, but we will officially begin proceedings at 7pm. If enough interest is generated, we may run two 90-minute rounds of discussion. Please let us know if you’re coming.
Who: Organized by Not An Employee, LLC
Space in the Library conference room is limited to 32 people. If more want to attend and discuss the prospects for coworking, we will try to arrange a second session, and extend discussion after the meeting at one of the other local meeting venues.
Please let us know if you’d like to attend. You may want to use the free service at Upcoming.org to coordinate.
April 29, 2008 at 11:29 pm · Filed under Project, Tidbits of nanohistory
Because history is for sale on eBay, and nobody knows what’s in a “rough old book, good condition for its age”.
Tonight, while thinking diligently about how best to share these all in a new format, scanned this old tome:
Seems pretty dry, eh? History ≣ dry.
Why is this of any interest at all? Because people like Thomas S. Grimké were in attendance, and they thought some weird things that are still holding sway over American education to this day. Here’s Grimké’s preface to his address:
April 28, 2008 at 11:40 pm · Filed under Project
Somewhat zoomable scan of a bookseller’s catalog I have on hand here. If you regularly visit the blog, you may need to force-reload the page in your browser to get the little pieces to line up correctly. I had to have the sitewide CSS to get this to work here.
I’m trying to spec out a browsable, legible interface for scanned books with some complex page structure. You’d want to zoom in to read the images, but not lose the relational block structure; you’d want to be able to read the text somehow. A lot of the things I have in mind are encyclopedic, may have 10000, 20000 entries per volume. Be nice to break those apart individually, like blog entries.
But the big goal here is that the original page structure needs to be visible, but zoomable. I know I could do some stuff with PDFs, or with JPEG2000, or with some neat Flash crap… but you draw your pages with the software you have, not with the software you wish you had.
April 2, 2008 at 11:32 pm · Filed under Project
Cross-posted to the Nudge blog
There are really three basic genetic programming algorithms I like to use out of the box. One’s stupid, one’s (almost) standard, and one’s pretty fancy and effective.
Start with one nugget of assumption: Every search algorithm should be multi-objective. Period. No exceptions. You do a single-objective search on any real-world problem, you’re either lazy or a liar. The end, no exceptions. I don’t care if you’re an Operations Research guru or a lone stock trader looking to make a buck, no problem is single-objective.
So when I say “better” in any context, I am talking about Pareto domination, or if you’re an economist kinda girl, “relative Pareto efficiency”. Say you have two alternatives, A and B, and you’re deciding between them on the basis of two minimization objectives, w1 and w2. A is dominated by B if w1(B)<w1(A), and w2(B)<w2(A). B is dominated by A if w1(A)<w1(B), and w2(A)<w2(B). Neither one dominates the other unless it is strictly better on all comparisons. Otherwise, A and B are nondominated by one another; they can’t be differentiated in a meaningful way without saying which objective is “more important”.
You want to survive a car crash, or do you want to drive really really fast? Which is better? So, get that into your head. There is never one objective. Never.
Let’s make sure we understand why there are always multiple objectives in GP runs. You want accuracy, right? But you also want parsimony. You’re evolving models, solutions to problems, functions, structures. Things can get hairy very quickly in a runaway evolutionary world: programs can get superstitious, they can inherit weird cultish quirks, like learning to use “Cosine(0)” or Sqrt(Sqrt(Sqrt(Sqrt(Sqrt(8.9912)))) instead of “1″, if some forgotten ancestor happened to find that first and passed it on as Big Math Juju. So as God of Your Little Engineering Problem trust me: you honestly want to reach down out of the clouds and say, “Hey, guys, chill. Remember, we use our human-readable voice when we model, OK? Two commandments here: accurate, and succinct.”
So there’s an intrinsic reason right there why you want to minimize model error and model complexity. At least two objectives. Always.
Because there’s always a less efficient way to solve any problem without sacrificing accuracy.
Anyway, those search algorithms.
“Stupid” is random search:
- Create a random program, and evaluate it
- Create a new random program, and evaluate that
- Throw away the one that’s dominated, or the newer one if neither is dominated
- Go to 2
Seem so ridiculous it’s not worth considering? Not really. It’s essentially the worst you could possibly do, knowing nothing about your search problem. So if nothing else, it provides a useful baseline, as well as a nice test of your randomization methods, evaluator timing, and other infrastructure that almost any search algorithm will share with this dumb-as-a-sack-of-hammers approach.
Plus: Easy to explain? Damn straight. Always run random search on your problem, with your representation, full-fledged evaluation, and data collection system in place.
“(Almost) standard”? Steady-state Pareto tournament selection works for me for a number of reasons, at least as a first approach:
- Create a population of, oh I don’t know, 500 random programs
- Select a tournament of maybe, ummm, 10? yeah 10 programs from the population, uniformly at random, and evaluate them
- Identify the nondominated “best” programs among them, and the dominated not-so-best ones, and split them into two groups
- If there are no dominated ones, pick one of the “best” pool at random and demote it out of spite. If there’s only one “best” program, it’s lonely, and inbreeding is bad, so promote one of the lesser ones out of pity.
- Replace all the programs in the not-so-best pool with offspring of the nondominated “best” pool
- Pick two parents, with replacement, from the nondominated set
- Use one-point crossover to make offspring
- Mutate the babies slightly, here and there, to taste
- go to 2
OK, I confess. This is standard in almost no ways whatsoever. It’s a “standard” toolkit for me, sure, but it’s a pretty far cry from Koza’s classic lockstep population-based methods, the kind everybody and their brother has copied wholesale. I like it anyway: it gives rapid feedback on progress, it’s kindof elitist (except for that “spite” step), it saves a lot of search time by limiting expensive multiobjective comparisons to relatively small pools, it works with fitness caching. It’s not perfect, but I already linked to the NFL Wikipedia page, so what are you, so dumb you can’t read? Nothing’s perfect.
Fancy and effective? I really like the ParetoGP method from Mark Kotanchek and Guido Smits (and their colleagues):
- Create an Archive of 500 random programs
- Create a Population of 500 random programs
- Create a container for the Next Generation (an empty list; hold onto that)
- Select a tournament of 20 Archive programs with uniform probability, and evaluate them, and forget about the dominated ones. Just make a list of the nondominated ones from the Archive tournament.
- Select a tournament of 20 Population programs with uniform probability, and evaluate them, and forget about the dominated ones. Just keep the subset of nondominated ones from the Population tournament.
- For each Population tournament winner you got from step 5, pick an Archive tournament winner you kept from step 4, at random. Cross them over to create an offspring, maybe with some mutation if you must.
- Stick the baby into the Next Generation. If you have 500 programs in the Next Generation, replace the Population with it and go to 3. If you’ve run out of tournament winners before filling the Next Generation, just go to 4. If you choose to attack the Orc, turn to page 88.
- You’re going to be wondering when you stop cycling the Next Generations back into the Population, aren’t you? Oh, I dunno. Pick a number. Say “10″. Go on, say it. There: do it ten times. Or more. Or less. Whatever; it’ll work.
- Aha! But then: once you’ve done your ten renewals of the Population (what Kotanchek and such call a “cascade”), you’re not done. Oh, no, boyo. You get your butt up there and you start the whole thing, all over again at step 2. That’s right. Another cascade, from another new, random Population, and another ten generations or so. But—but—before you do, take the final Population, the best best best of that cascade you just finished, and you stick it into the Archive. Add it to the programs that were already there, and take the time to trim the Archive back down to 500 programs. You can do a full-fledged 1000-wise Pareto tournament if you have the time, or you could do some other cunning selection method if you want. Often I tend to do something quick and dirty, like just picking tournaments of 20 and culling all the dominated ones until the Archive size drops back down to 500. So, anyway, you were going back to Step 2 to run another cascade.
- Do that until you’re bored.
Now this is a close approximation of the ParetoGP algorithm described in a number of papers by Mark Kotanchek, Guido Smits and Katya Vladislavleva. It’s a broadly customizable framework, and if it seems like a lot of extra work compared with the “simpler” GP algorithms described above… well, that may be true. I like it very much because it exposes exploitation (via the Archive) and exploration (via the Population) as almost separable processes. You feel like things are getting stuck, let the Population grow a bit and do more random restarting and exploratory search for weird alternatives; you feel like things are getting too wild, you do fewer, shorter cascades and keep a bigger Archive, really nail down the variations on the already-discovered themes you’ve collected there. Play around, fiddle the knobs, see what you get.
And that’s the point, of course. There is no “best” search algorithm. Don’t make me link to that paper again.
You have to pay attention. You have to bring to bear a vast combinatorial armamentarium. You have to keep a seven-drawer toolbox in the virtual garage, with a hundred different wrenches in it, and then look at your problem and listen to your algorithm purring along, and reach into a drawer without looking and find just the right tool, and give that algorithm a little tightening here, a little shimmy there, grind a bit off the edge, take it apart and put it together again slightly better. With grease.
See, it’s not about solving your problem as fast as possible. It’s about watching it improve, and having the sense to see it improving. About having the tools on hand and the experience under your hat so you can intervene in a reasonable and effective way.
So, yes: there are other ways. None are best.
March 17, 2008 at 5:24 pm · Filed under Project
First more-or-less complete shell images of the new house have appeared. First post on project blog for our Nudge genetic programming thing has appeared. And many thanks for all the supportive voices we’ve heard in comments online and met at SXSWi regarding our (still intentionally) vague effort at Not An Employee.
February 29, 2008 at 5:34 pm · Filed under Project
One of the reasons it’s been relatively quiet here in the last few months is that I’ve been working on several projects. Not secret, as such; just the opposite in fact. But one doesn’t want to subject the world to half-formed notions.
The first real project went out the door today:
With Laura Fisher, Barbara Tozier, and Brian Kerr, we’ve made… something. We’ll see what it is, what it becomes.
Like many things these days, many things I’ve got my fingers in, many of the buttons I push, it may sound like a joke. It is; it was. And it’s not.
Who are you? And who do you serve?
Just what is it that you do?
May 22, 2007 at 8:41 pm · Filed under Project
Barbara points out that I’m perhaps over-generalizing in my earlier rant on conformity in academia, and that also perhaps I’ve elided the actual point.
If I were to sum up my concern, it’s the paucity of varieties of work in academic and industrial research. Not a cry about the monotony of personae or approaches, nor any worry about social activism.
But the…well the fact of monopoly. You get right down to it, there is exactly one life-course for a scientist. Or a historian. Or an engineer. You’re either merely an Amateur, or you’re on The Track.
You can tell those in The Track. I see them on the street, in this college town, and I know immediately what they do from the way they dress. Nine times out of ten, I can pick the campus they’re from (artsy, engineery, undregraddy, &c). Barbara thinks this might be different in other parts of the country or world, and might be different in the West especially. I don’t know; that might be a dilution effect, merely caused by mingling with laymen in big cities, or the practical necessity of Not Wearing Black in the Desert that makes professionals in Albuquerque look a bit more like paleontologists.
At any rate, what worries me is that the social and cultural norms that dictate appearance must also dictate worldview, worklife, options. I’m worried about the heretics.
The Academy really is the sort of monopoly that ended badly, back in the days of the Reformation.
And my question is not whether it exists. My question is: What will happen when it starts to break down?
Which it will. And soon.
May 21, 2007 at 11:19 pm · Filed under Project
As with the other project sketches this is something that I plan on taking up myself, but am posting a running account here as practice for real-time project-blogging. Readers are encouraged to follow along themselves if they get interested or bored or inspired or whatever.
This is an exploration. Don’t know if it will work. It’s intended to be an approach for creating algorithmic images, or for artifying pre-existing images. There are innumerable variations, but I’ve decided on a simple one to try first, just to see if the outcome is anything like what I expect.
I’ve been thinking about this one, on and off, for about ten years. A few years ago somebody recommended I look at the Image Analogies project at NYU, which is really cool if you haven’t seen it. That’s related, but what I had in mind for this was something less practical. Through the years I’ve dabbled in Mathematica a bit and done it wrong, and played in R with neural implementations. All unsatisfactory. But I had an insight a few days back that clarifies it and makes it much more attainable.
And I was thinking of using it in the blog redesign, if it does what I suspect it will. cron jobs, of course.
I’ll sketch the project now, and then report the results of a planning session and all the iterations as I actually make my moves. I expect it wouldn’t take more than a few hours if I were hacking it; I don’t intend to hack it. I intend to do it with unit and acceptance tests, if I can convince myself unit testing is feasible in Mathematica or R or wherever I work it through. Maybe I’ll do it in Ruby or Python, for the testing.
I’ll also add diagrams as I work on it. Right now I’m just going to jot it down. Admittedly, as a project involving bitmaps and some geometry, diagrams would help. And so they will. Just not tonight.
In a nutshell: The project will take an image or set of images as exemplars. It will create a database of scaled color pyramids from the exemplar(s). A color pyramid of scale n with origin at pixel (i,j) is composed of a tuple of four “center” colors, and a tuple of eight “edge” colors. The four “center” colors are the average colors of the four n×n squares of pixels starting at (i,j), (i+n,j), (i,j+n), and (i+n,j+n), respectively—NW, NE, SW, and SE in that order. The eight “edge” colors are the equivalent averages, but for squares 2n×2n on a side, surrounding the four center squares, in the order NW, N, NE, E, SE, S, SW, W.
Now if (i,j) is too close to an edge of the image, clearly some of these square regions will overlap or lie outside the proper dimensions of the picture. We’ll assume that there’s a solid background color, defaulting to white, out there. So a pyramid (of any scale) with origin in the upper leftmost pixel of the image will have its NW, N, NE, SW, and W edge squares lying entirely outside the image, and composed entirely of the background color.
So a pyramid of scale 1 contains four one-pixel squares in the center, and eight 2×2 pixel squares on the edges. The center colors are the colors of those four pixels; the edge colors are the averages of the four pixels in each of the eight larger squares.
Like I said: diagrams will help. Just not now.
Anyway, to preprocess an exemplar image, we’ll be generating a database of all possible pyramids (where every center square contains only image data) of scale 1, 2, 4, 8, 16 and 32 (6×6, 12×12, 24×24, 48×48, 96×96 and 192×192 and pixels, respectively). Just keep a list, maintaining repeated samples if there are any.
I’m thinking a scan of text. Something black-and-white, to begin with at least.
Got the data? OK. Now create and train a Kohonen SOM from each scale’s samples based only on the four center colors. Ignore the nine edge colors for the training period; just cluster the pyramid data at each scale on the basis of the four center features.
All trained up? OK. Now for each pyramid in the dataset, assign it an index value based on the cell of the Kohonen network where it ended up being placed. Some unique identifier so that when a pattern is matched to the trained network on the basis of its four center colors, we can obtain the entire set of training patterns that map to that same cell.
Now we have an image [de]generator: I can specify the center colors of an arbitrary pyramid of some scale. We can look it up by finding the cell of the correct Kohonen network that’s the closest Euclidean match. We can then query the database and obtain a list of exemplar pyramids that match that same cell, and pick one of those at random.
Let’s grab a new image. Something unlike the exemplar, or maybe one just like it. Don’t care. Call this the active image.
Pick a random position in the active image, and a scale. Measure the colors of the pyramid in the active image at that scale, refer to the appropriate trained Kohonen network, and have the database spit out a related pyramid from the exemplars. Now change the colors of the pixels in all the edge squares of the pyramid, in the active image, so that they are closer to the colors in the sampled exemplar pyramid. Average them, weight them, whatever.
So for example if we’ve selected pixel (88,100) of the active image, at scale 2, the edge region that will be changed will span all 144 pixels from (84,96) to (95,107). All but the center 16 pixels of that square will become more like some pyramid in the database.
If a pyramid of a chosen scale and position overlaps the boundary, just imagine the surrounding pixels are fixed at the background color.
Iterate by picking a new pixel and scale. Not sure with what probabilities, but probably some kind of weight over the set of scales. Keep going until things get interesting.
The point, of course, is that the pyramids from the exemplar won’t exactly match the traits of the active image, and that it should get kindof munged up, or even surreal, as pyramids are replaced. One might consider applying pyramids from a scanned text page to a landscape; pyramids from a Dutch master’s still life to a snapshot; pyramids from a Persian rug to one’s cat picture.
We’ll see how it works out.
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