I recently had occasion to remember my proudest moment as a contender for national Poet Laureate. I know we’re not supposed to reveal such things, but enough time has passed that I think I can speak of the grave injustice that was served to me on a platter of shame. (It’s writing like that that got me onto the short list.)

It was in the late 1980s or early 1990s when I was working in the marketing department at Interleaf, the creator of the first fully WYSIWYG electronic publishing package. At that point, being WYSIWYG — “What you see is why you get” — was novel because it was damn hard to put text and graphics on the same page in real-time editing mode. Plus, Interleaf’s text and graphics editors were ahead of their time, providing near typeset quality text, and integrated raster and vector graphics, all elements adjusting their layout as you typed. And much more. It was truly amazing software, and included functionality — including an extension language — that has still not been fully matched.

I spent eight years there learning about technology, including tech that presaged the Web, and about tech businesses. It was a great experience.

Then one day as I sat in my office, a poem flowed from me as if I were a teapot and the keyboard was a cup. (Again with the great analogies!) It turned out to be the poem that brought me to the attention of the Federal Department of Poetry, and I present it to you as best I remember it:

FuzzyWuzzy the Bear

FuzzyWuzzy was a bear.
FuzzyWuzzy had no hair.
FuzzyWuzzy wore a fuzzy wig.
FuzzyWuzzy wasn’t WYSIWYG, was he?

Or possibly the bear’s name was WhizzyWhizzyWig. Or maybe just WhizzyWig. Either way, it is a reference back to Ovid’s immortal “FuzzyWuzzy,” which was later stolen from the commons by the CoolTime Kids, with the copyright assigned to “Music Sales Corporation” which is clearly a cover for SMERSH, as exposed in the 1963 James Bond movie, “1 800 Kars for Kruschev.”

But I digress.

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There’s a new version of Wordle called Semantle — not one that I “predicted” — that wants you to find the target word by looking not for a chain of spellings but a chain of semantics. For example, if you started with the word “child” you might get to the answer as follows:

1. Child
2. Play
3. game
4. Chess
5. Square
6. Circle
7. Donut
8. Homer

In short, you’re playing word associations except the associations can be very loose. It’s not like Twenty Questions where, once you get down a track (say “animals”), you’re narrowing the scope until there’s only one thing left. In Semantle, the associations can take a sudden turn in any of a thousand directions at any moment.

Which means it’s basically impossible to win.

It is, however, a good introduction to how machine learning “thinks” about words. Or at least one of the ways. Semantle is based on word2vec, which creates text embeddings derived from an analysis of some large — sometimes very very large — set of texts. Text embeddings map the statistical relationships among words based on their proximities in those texts.

In a typical example, word2vec may well figure out that “queen” and “king” are semantically close, which also might well let it figure out that “king” is to “prince” as “queen” is to “princess.”

But there are, of course, many ways that words can be related — different axes of similarity, different dimensions. Those are called “vectors” (as in “word2vec“). When playing Semantle, you’re looking for the vectors in which a word might be embedded. There are many, many of those, some stronger than others. For example, “king” and “queen” share a dimension, but so do “king” and “chess”, “king” and “bed size”, and “king” and “elvis.” Words branch off in many more ways than in Wordle.

For example, in my first game of Semantle, after 45 attempts to find a word that is even a little bit close to the answer, I found that “city” is vaguely related to it. But now I have to guess at the vector “city” and the target share. The target could be “village”, “busy”, “taxi”, “diverse”, “noisy”, “siege”, or a bazillion other words that tend to appear relatively close to “city” but that are related in different ways.

In fact, I did not stumble across the relevant vector. The answer was “newspaper.”

I think Semantle would be more fun if they started you with a word that was at some reasonable distance from the answer, rather than making you guess what a reasonable starting word might be. Otherwise, you can spend a long time — 45 tries to get “city” — just generating random words. But if we knew a starting word was, say, “foot”, we could start thinking of vectors that that word is on: measure, toe, body, shoe, soccer, etc. That might be fun, and would stretch our minds.

As it is, Semantle is a game the unplayability of which teaches us an important lesson.

And now I shall wait to hear from the many people who are actually able to solve Semantles. I hate you all with a white hot and completely unreasonable passion.[1]

[1] I’ve heard from people who are solving it. I no longer hate them.

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Planted four days ago.

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There’s Wordle for Jews: Jewdle. There’s Wordle for Star Wars enthusiasts: SWordle. And lord knows how many variants are now online or are being developed by anyone who knows how to edit a word list.

So let’s just get it over with. Here are upcoming versions, some of which probably already exist but I am too lazy to check.

Aordle: Wordle for cardiologists

Boardle: Wordle for millennials taking a break from playing Settlers of Catan

Boredle: Wordle for people playing Wordle

Cawdle: Wordle for crows

Chordle: Wordle rhythm guitarists

Clawdle: Wordle for manicurists

Cordle: Wordle for electricians

Coredle: Wordle for people taking Antarctic ice samples

Corridordle: Wordle for people hanging out in hallways

Crawdle: Wordle for eyes, ear, and throat doctors

Dawdle: Wordle for dillydallyers

Depordle: Wordle for ICE

Doordle: Wordle for doormen/doorpeople

Drawdle: Wordle for gunslingers

Eeyordle: Wordle for depressed people

Floordle: Wordle for linoleum salespeople

Flourdle: Wordle for bakers

Fordle: Wordle for F-150 owners

Fodordle: Wordle for travel advisors

Frodordle: Wordle for hairy-footed denizens of Middle Earth

Glowdle: Wordle for nuclear power plant employees

Growdle: Wordle for people who are cultivating marijuana for personal use

Hoardle: Wordle for hoarders

IOrdle: Wordle for computer engineers

Ignordle: Wordle for people who don’t do Wordle puzzles

Jordle: Wordle for kingdoms bordering Israel

KOrdle: Wordle for boxers

Lordle: Wordle for evangelical Christians

Majordle: Wordle for Army officers

Maordle: Wordle for Chinese Communists

Mayordle: Wordle for leaders of cities

Mayordle: Wordle for lovers of fatty white sandwich condiments

Minordle: Wordle for underrepresented populations

Mordordle: Wordle for the inhabitants of the Dark Kingdom of Middle Earth

Motordle: Wordle for car mechanics

Murdordle: Wordle for serial killers

Nordle: Wordle for Scandinavians

Nordle: Wordle for naysayers

Oordle: Wordle for the over-enthusiastic

Phylordle: Wordle for biological taxonomists

Poordle: Wordle for those who cannot afford a NY Times subscription to do a stupid word game

Pourdle: Wordle for sommeliers

Psuedordle: Wordle for people with imposter syndrome

Repordle: Wordle for journalists

Rappordle: Wordle for empathists

Rupordle: Wordle for the Murdochs

Rumordle: Wordle for gossips

Sawdle: Wordle for carpenters

Slaudle: Wordle for merciless mass killers

Sordle: Wordle for first-time horseback riders

Sprawdle: Wordle for suburban real estate developers

Strawdle: Wordle for scarecrows

Tordle: Wordle for turtle and turtle relatives

Thordle: Wordle for Asgardians

Vaulde: Wordle for gymnasts

Worldle: Wordle for geographers

XORdle: Wordle for machine language programmers

Yordle: Wordle for turtle monarchs

Zoordle: Wordle for imprisoned animals

Zorrordle: Wordle for fencers

The comments are open for your additions. (Note: Keep ’em unhurtful.)

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Notes for a post:

Plato said (Phaedrus, 265e) that we should “carve nature at its joints,” which assumes of course that nature has joints, i.e., that it comes divided in natural and (for the Greeks) rational ways. (“Rational” here means something like in ways that we can discover, and that divide up the things neatly, without overlap.)

For Aristotle, at least in the natural world those joints consist of the categories that make a thing what it is, and that make things knowable as those things.

To know a thing was to see how it’s different from other things, particularly (as per Aristotle) from other things that they share important similarities with: humans are the rational animals because we share essential properties with other animals, but are different from them in our rationality.

The overall order of the universe was knowable and formed a hierarchy (e.g. beings -> animals -> vertebrates -> upright -> rational) that makes the differences essential. It’s also quite efficient since anything clustered under a concept, no matter how many levels down, inherits the properties of the higher level concepts.

We no longer believe that there is a perfect, economical order of things. “We no longer believe that there is a single, perfect, economical order of things. ”We want to be able to categorize under many categories, to draw as many similarities and differences as we need for our current project. We see this in our general preference for search over browsing through hierarchies, the continued use of tags as a way of cutting across categories, and in the rise of knowledge graphs and high-dimensional language models that connect everything every way they can even if the connections are very weak.

Why do we care about weak connections? 1. Because they are still connections. 2. The Internet’s economy of abundance has disinclined us to throw out any information. 3. Our new technologies (esp. machine learning) can make hay (and sometimes errors) out of rich combinations of connections including those that are weak.

If Plato believed that to understand the world we need to divide it properly — carve it at its joints — knowledge graphs and machine learning assume that knowledge consists of joining things as many different ways as we can.

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I upgraded to a Pixel 6 because my Pixel 3’s charging plug no longer worked, the glass on the back was shattered, and battery life was down to 2-3 hours. I decided to splurge on the Pro version primarily because of its superior cameras.

But while I loved the photos the 3 takes, I’m wasn’t as happy with the 6 Pro. I don’t know enough about photography to be able to articulate why I liked the 3’s photo better, other than to say the colors and shadows were richer and deeper. The 6’s photos were clearer and more detailed, but I generally just liked the 3’s better.

Then I uploaded three sets of samples into this blog post and discovered that most of the differences were due to the displays on the two phones. Viewing them on my MacBook Pro, I think I probably like the Pixel 6 at least as much as the Pixel 3….except for the photo of the hand below.

Here are unedited photos from each so you can decide for yourself.

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I do not like writing about the death of friends because it feels foolish to the point of arrogance to pretend to capture what we’ve lost. But I want to talk about Chris, so I will, without pretense of capturing anything at all…

I met Chris Locke, aka Rageboy (RB) aka Kat Herding, in the late 1990s. I was writing a newsletter (“Journal of the Hyperlinked Organization”). He was writing a newsletter (“Entropy Gradient Reversals”). Doc Searls was writing a newsletter (“Reality 2.0”); I can’t find the newsletter, so here’s his blog.  Chris thought Doc and I would get along, so he introduced us. The three of us, along with Rick Levine, ended up co-writing The Cluetrain Manifesto, which did well enough to let me give myself permission to call myself a writer. The book changed my life, and much of its success was due to its voice which came straight from Chris. 

Chris was a prodigiously talented writer. Here’s a sample of Chris flapping his wings; it may not be the best way of introducing his writing style, but I honestly don’t know what would be. Doc and I figure that he wrote the sample a few months after he was diagnosed with emphysema.

He loved the Internet deeply because it seemed to be an epochal opportunity to break the oppressiveness of industrial capitalism. This in turn mattered to him because he yearned for the release of the creativity and goodness and connection that he was sure every pair of manacled hands was reaching for. (Yes, he and the rest of the Internet hippies like me were wrong about that in important ways. Long discussion for another day.)

Chris was a complicated person. An autodidact. Publicly abrasive and fearless, and sometimes reckless. Privately and personally kind and modest. Undisciplined in some of his writing — a strength as well as a weakness — but highly disciplined in important aspects of his private life. As a self-termed gonzo writer, he likely would have liked to have been Hunter S. Thompson if Thompson hadn’t already taken the job.

Chris was wonderful to hang out with in person, but the Internet friends that gathered around him were a truly intimate social group, supporting him through his long illness, especially it seems to me the women. He and I fell out of touch, to my shame and regret. Nevertheless, his insights about the positive social nature of the Internet were not entirely wrong, at least for him. And his fierce, unrelenting yawp against the dark industrial forces that grind up so many good souls is piercing, needed, and true.

Chris was a character, fully formed yet becoming, his flaws an integral part of his being. I love him, owe him, and miss him.

Twitter: @KatHerding  Facebook: @KatHerding

I just read Doc Searls’ superb post about Chris.

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As a non-observant Jew embedded in a Modern Orthodox family, here are my rules for when I say “Merry Christmas.”

To someone who wishes me a merry Christmas before or during Hanukkah, I reply, “And a happy Hanukkah to you.” If this counts as waging war on Christmas, I offer no apology.

For the week after Hanukkah, I tell known Jews “I hope you had a happy Hanukkah.”

After that, I say to another Jew, “Have a good holiday season” because there’s no getting around the fact that the Christian slow down of business for a few weeks is very pleasant, even for non-Christians. Perhaps especially for non-Christians.

To someone who has wished me happy holidays, I reciprocate with “And happy holidays to you.”

To someone who wishes me a merry Christmas after Hanukkah, I reply, “Have a happy holiday season,” hoping they take the “season” as rebuke even though no one ever seems to notice.

I have had these rules embossed on a small plastic tablet I carry with me. I plan on offering them for sale sometime around Passover/Easter.

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Our 3 year old was randomly typing on my wife’s Chromebook and somehow made all of the images go wonky. This includes all images displayed in the browser, the system’s wallpaper, and even the icons.

I could not find any mention of this problem anywhere on the Internet, apparently because I insisted on using the word “posterize” to describe the images’ condition. The rest of the world apparently calls this “inverted.” I have been calling inverted images posterized probably since the late 1980s. It has never before steered me wrong. But according to dictionaries and what Google Search has learned from the Internet, I’ve definitely been misusing it.

But first, the solution to the Chromebook problem. I learned this from Iain Tait (@iaintait) who responded to my tweet asking for help. He pointed to this article in Chrome Unboxed. Our granddaughter unwittingly put the Chromebook into “high contrast mode.” Clicking Ctrl+Search+H will undo the little devil’s mischief.

Now, back to how I went wrong.

Posterization apparently was coined in the 1950s to refer to the process of turning a color image into the sort of stylized image often used in posters. Gradations in color are flattened, colors are brightened, and so forth, until the image would have been acceptable to The Beatles in their late psychedelic phase. Inversion is a 1:1 clipping of colors so that the original looks like what I think a color negative of it would look like, but I’m probably wrong about that too.

Here’s an example using a photo of our post-Thanksgiving walk (CC-BY-SA-NC by me).

Original:

Posterized:

Inverted:

But the real point of this post is to let Google Search see a few more instances of posterize, posterized, and posterizing in the same sentence as image inversion and Google Chromebooks so that the next fool who confuses posterization and image inversion when faced with an image inverted by Chromebook will find at least one damn entry that clarifies a mistake that apparently no one else has ever made.

Posterize inverted images Chromebook. Posterize inverted images Chromebook. Posterize inverted images Chromebook. Posterize inverted images Chromebook.

(The transformations are by Pixelmator Pro.)

* * *

Isian has written a lovely post about how our paths crossed after many years.

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Aeon.co has posted an article I worked on for a couple of years. It’s only 2,200 words, but they were hard words to find because the ideas were, and are, hard for me. I have little sense of whether I got either the words or the ideas right.

The article argues, roughly, that the sorts of generalizations that machine learning models embody are very different from the sort of generalizations the West has taken as the truths that matter. ML’s generalizations often are tied to far more specific configurations of data and thus are often not understandable by us, and often cannot be applied to particular cases except by running the ML model.

This may be leading us to locate the really real not in the eternal (as the West has traditional done) but at least as much in the fleeting patterns of dust that result from everything affecting everything else all the time and everywhere.

Three notes:

1. Nigel Warburton, the philosophy editor at Aeon, was very helpful, as was Timo Hannay in talking through the ideas, and at about a dozen other people who read drafts. None of them agreed entirely with the article.

2. Aeon for some reason deleted a crucial footnote that said that my views do not necessarily represent the views of Google, while keeping the fact that I am a part time, temporary writer-in-residence there. To be clear: My reviews do not necessarily represent Google’s.

3. My original first title for it was “Dust Rising”, but then it became “Trains, Car Wrecks, and Machine Learning’s Ontology” which i still like although I admit it that “ontology” may not be as big a draw as I think it is.

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