Katherine Maher on The Truth

Wikipedia is about verifiable facts from reliable sources. For Wikipedia, arguing with "The Truth" is often not effective. Wikipedians don't argue "because it's true" but "because that's what's in this source".

It is painful and upsetting to see Katherine Maher so viciously and widely attacked on Twitter. Especially for a quote repeated out-of-context which restates one of the foundations of Wikipedia.

I have worked with Katherine. We were lucky to have her at Wikipedia, and NPR is lucky to have her now.

The quote - again, as said, taken out of the context that it stems from the way Wikipedia editors collaborate is: "Our reverence for the truth might be a distraction that's getting in the way of finding common ground and getting things done."

It is taken from this TED Talk by Katherine, which provides sufficient context for the quote.

Partial copyright for an AI generated work

Interesting development in US cases around copyright and AI: author Elisa Shupe asked for copyright registration on a book that was created with the help of generative AI. Shupe stated that not giving her registration would be disabilities discrimination, since she would not have been able to create her work otherwise. On appeal, her work was partially granted protection for the “selection, coordination, and arrangement of text generated by artificial intelligence”, without referral to the disability argument.

• Wired: How One Author Pushed the Limits of AI Copyright, by Kate Knibbs

Northern Arizona

Last week we had a wonderful trip through Northern Arizona.

Itinerary: starting in Phoenix going Northeast through Tonto National Forest towards Winslow. In Tonto, we met our first surprise, which would become a recurring pattern: whereas we expected Arizona in April to be hot, and we were prepared for hot, it had some really cold spells, and we were not prepared for cold. We started in the Sonoran Desert, surrounded by cacti and sun, but one and a half hours later in Tonto, we were driving through a veritable snow storm, but fortunately, just as it was getting worrisome, we crossed the ridge and started descending towards Winslow to the North.

The Colorado Plateau on the other side of the ridge was then pleasant and warm, and the next days we traveled through and visited the Petrified Forest, Monument Valley, Horseshoe Bend, Antelope Canyon, and more.

After that we headed for the Grand Canyon, but temperatures dropped so low, and we didn't have the right outfit for that, we stayed less than a day there, most of it huddled in the hotel room. Still, the views we got were just amazing, and throwing snowballs was an unexpected fun exercise.

Our last stop took us to Sedona, where we were again welcomed with amazing views. The rocks and formations all had in common that they dramatically changed with the movement of the sun, or with us moving around, and the views were always fresh.

Numbers: Our trip took us about 950 miles / 1500 kilometeres of driving, and I was happy that it was a good Jeep for this trip. The difference in altitude went from 1000 feet / 330 meters in Phoenix up to 8000 feet / 2400 meters driving through Coconino. Temperatures ranged from 86° F / 30° C to 20° F / -7° C.

What I learned again is how big this country is. And how beautiful.

Surprises: One thing that surprised me was how hidden the Canyons can be. Well, you can't hide Grand Canyon, but it is easy to pass by Antelope Canyon and not realizing it is there. Because it is just a cut in the plateau.

I also was surprised about how flat and wide the land is. I have mostly lived in areas where you had mountains or at least hills nearby, but the Colorado Plateau has large wide swaths of flat land. "Once the land was as plane as a pancake".

I mentioned the biggest surprise already, which was how cold it got.

Towns: it was astonishing to see the difference between, on the one side, a town such as Page or Sedona and on the other side Winslow. All three have a similar population, but Page and Sedona felt vigorous, lively, clean, whereas Winslow felt as if it was on the decline, deserted, struggling.

The hotel we stayed in in Winslow, La Posada, was a beautiful, weird, unique jewel that I hesitate to flat-out recommend, it is too unusual for that, but that I still enjoyed experiencing. It is clearly very different from any other hotel I ever stayed in, full of history, and embracing themes of both suicide and hope, respectfully trying to grow with the native population, and aiming to revive the city's old town, and it is difficult to really capture the vibe it was sending out.

For pictures, I am afraid I am pointing to my Facebook posts, which should be visible without login:

• Scottsdale
• Palo Verde tree
• Desert Botanical Garden, Phoenix
• Desert to snowstorm
• Winslow
• La Posada hotel
• Petrified forest
• Monument valley
• Horseshoe bend
• Antelope canyon
• Grand canyon
• Sedona

Crossing eight time zone borders in three hours

Hopi Nation is an enclave within Navajo Nation. Navajo Nation is located across three US states, Arizona, New Mexico, and Utah.

Arizona does not observe daylight saving time. Navajo Nation observes daylight saving time. Hopi Nation does not observe daylight saving time. You can drive three hours in that area and cross timezones eight times.

All of the individual decisions make totally sense:

Arizona does not adhere to daylight saving time because any measure that makes sure Arizona residents get more sunshine is worse than bringing coals to Newcastle, as the saying goes. They are smart to not use daylight saving time.

Navajo Nation uses daylight saving time because they want to have the same timezone for their whole area, and they are also in two other states, Utah and New Mexico, which both have daylight saving time, so they decided to do so too, which makes totally sense.

And Hopi Nation, even though it is enclosed by the Navajo Nation, lies entirely within the state of Arizona, so it makes sense for them to follow *that* state.

All the individual decisions make sense, but the outcome must be rather inconvenient and potentially confusing for the people living there.

(Bonus:the solution for these seem obvious to me. Utah and New Mexico and many other southern US states should just get rid of daylight saving time, just as Arizona did, and Navajo Nation should follow suit. But that's just my opinion.)

New home in Emeryville

Our new (temporary home) is the City of Emeryville. Emeryville has a population of almost 13,000 people. The apartment complex we live in has about 400 units, and I estimate that they have about 2 people on average in each. Assuming that about 90% of the apartments are occupied, this single apartment complex would constitute between 5 and 10% of the population of the whole city.

A conspiracy to kill a browser

Great story about how YouTube helped with moving away from IE6.

"Our most renegade web developer, an otherwise soft-spoken Croatian guy, insisted on checking in the code under his name, as a badge of personal honor, and the rest of us leveraged our OldTuber status to approve the code review."

I swear that wasn't me. Although I would have loved to do it.

• Chris Zacharias, A conspiracy to kill IE6

(first published on Facebook March 12, 2024)

35th birthday of the Web

Celebrating the 35th birthday of the World Wide Web, a letter by its founder, Tim Berners-Lee.

Discussing some of the issues of the Web of today: too much centralization, too much exploitation, too much disinformation, all made even more dire by the development of AI.

What to do? Some of the solution the letter mentions are Mastodon, a decentralized social network, and Solid, a Web-standards-based data governance solution, but it recognizes that more is needed, "to back the morally courageous leadership that is rising, collectivise their solutions, and to overturn the online world being dictated by profit to one that is dictated by the needs of humanity." I agree with that, but find it a bit vague.

• Tim Berners-Lee on the 35th birthday of the Web, Web Foundation

I first was terribly annoyed that the letter was published on Medium, as this is a symptom of the centralization of the Web. I say, completely conscious that I am discussing it on Facebook. Obviously, both of this should be happening on our own domains, and it also does: I link not to Medium, but to the Web Foundation site, and I also have this posted on my own site and on my Mastodon account. So, it is there, on the real Web, not just on the closed walled gardens of Facebook and on one of the megasites such as Medium. But there is no indication of engagement on the Web Foundation's post, whereas the Medium article records more than 10,000 reactions, and my Facebook post will also show more reactions than my Website (but the Mastodon page could be competitive with Facebook for me).

I want to believe that Solid is the next important step, but Leigh Dodds's recent post on Solid, and particularly the discussion in the post, didn't inspire hope.

Gödel on language

"The more I think about language, the more it amazes me that people ever understand each other at all." - Kurt Gödel

Rainbows end

Rainbows end.

The book, written in 2006, was set in 2025 in San Diego. Its author, Vernor Vinge, died yesterday, March 20, 2024, in nearby La Jolla, at the age of 79. He is probably best known for popularizing the concept of the Technological Singularity, but I found many other of his ideas far more fascinating.

Rainbows end explores themes such as shared realities, digital surveillance, and the digitisation of the world, years before Marc Andreessen proclaimed that "software is eating the word", describing it much more colorfully and rich than Andreessen ever did.

His other work that I enjoyed is True Names, discussing anonymity and pseudonymity on the Web. A version of the book was published with essays by Marvin Minsky, Danny Hillis, and others. who were inspired by True Names.

His Science Fiction was in a rare genre, which I love to read more about: mostly non-dystopian, in the nearby future, hard sci-fi, and yet, imaginative, exploring novel technologies and their implications on individuals and society.

Rainbows end.

• Photo of a sign I took in 2008 in New Zealand, pointing to Rainbows End - a local theme park.

From vexing uncertainty to intellectual humility

A philosopher with schizophrenia wrote a harrowing account of how he experiences schizophrenia. And I wonder if some of the lessons are true for everyone, and what that means for society.

"It’s definite belief, not certainty, that allows me to get along. It’s not that certainty, or something like it, never matters. If you are fixing dinner for me I’ll try to be clear about the eggplant allergy [...] But most of the time, just having a definite, if unconfirmed and possibly false, belief about the situation is fine. It allows one to get along.

"I think of this attitude as a kind of “intellectual humility” because although I do care about truth—and as a consequence of caring about truth, I do form beliefs about what is true—I no longer agonize about whether my judgments are wrong. For me, living relatively free from debilitating anxiety is incompatible with relentless pursuit of truth. Instead, I need clear beliefs and a willingness to change them when circumstances and evidence demand, without worrying about, or getting upset about, being wrong. This attitude has made life better and has made the “near-collapses” much rarer."

• From Vexing Uncertainty to Intellectual Humility by Michael Dickson

(first published on Facebook March 13, 2024)

Feeding the cat

Every morning, I lovingly and carefully scoop out every single morsel of meat from the tin of wet food for our cat. And then he eats a tenth of it.

Dolly Parton's What's up?

Dolly Parton is an amazing person. On "Rockstar", her latest album, she covered a great number of songs, with amazing collaborators, often the original interpreters or writers. In her cover of "What's up?", a song I really love, with Linda Perry, she changed a few lines of the lyrics, as one often does when covering, to make a song their own.

Instead of "Twenty-five years and my life is still...", she's singing "All of these years and my life is still..." - and makes total sense, because unlike Linda Perry she wasn't 25 when she wrote it, she was 77 when she recorded it.

Instead of "I take a deep breath and I get real high", Dolly takes "a deep breath and wonders why", and it makes sense, because, hey, it's Dolly Parton.

But here's the line that hurts, right there when the song reaches its high point:

"And I pray,

Oh my God do I pray!

I pray every. single. day.

for a revolution!"

She changed one letter in the last word:

"for a resolution"

And it just breaks my heart. Because it feels so weak. Because it seems to betray the song. Because it seems to betray everything. And also because I might agree with her, and that feels like betrayal too.

• Dolly Parton and Linda Perry: What's up?

Views on the US economy 2024

By most metrics, the American economy is doing well. But the perception of the American economy is much weaker than its actual strength. This seems to finally slowly break up a bit, and people are realizing that things are actually not that bad.

Here's an article that tries to explain it: because of high interest rates, credit is expensive, including credit card debt, and if someone is buying a home now.

• ‘I’m making the most money I’ve ever made, and I’m still living paycheck to paycheck’, Fortune, March 15, 2024, by Claire Ballentine, Eliza Ronalds-Hannon and Bloomberg

But if you go beyond the anecdotes as this essay does, and look at the actual data, you will find something else: it is a very partisan thing.

For Democrats we find that it depends. Basically, the more you fit to the dominant group - the richer you are, the older, the better educated, the "whiter", the "maler" - the better your view of the economy.

For Republicans we don't find any such differentiation. Everyone is negative about it, across the board. Their perception of the economic situation are crassly different from the perception of their Democratic peers.

• Views of the nation's economy, Pew Research

Libertarian cities

I usually try to contain my "Schadenfreude", but reading this article made it really difficult to do so. It starts with the story of Rio Verde Foothills and its lack of water supply after it was intentionally built to circumvent zoning regulations regarding water supply, and lists a few other examples, such as

"Grafton, New Hampshire. It’s a tiny town that was taken over by libertarians who moved there en masse to create their vision of heaven on earth. They voted themselves into power, slashed taxes and cut the town’s already minuscule budget to the bone. Journalist Matthew Hongoltz-Hetling recounts what happened next:

'Grafton was a poor town to begin with, but with tax revenue dropping even as its population expanded, things got steadily worse. Potholes multiplied, domestic disputes proliferated, violent crime spiked, and town workers started going without heat. ...'

Then the town was taken over by bears."

The article is worth reading:

• Why libertarian cities fail by Adam Lee, April 6, 2023, OnlySky Media

The Wikipedia article is even more damning:

"Grafton is an active hub for Libertarians as part of the Free Town Project, an offshoot of the Free State Project. Grafton's appeal as a favorable destination was due to its absence of zoning laws and a very low property tax rate. Grafton was the focus of a movement begun by members of the Free State Project that sought to encourage libertarians to move to the town. After a rash of lawsuits from Free Towners, an influx of sex offenders, an increase of crime, problems with bold local bears, and the first murders in the town's history, the Libertarian project ended in 2016."

• Grafton, New Hampshire - English Wikipedia

Get Morse code from text

On Wikifunctions we have a function that translates text to Morse code. Go ahead, try it out.

I am stating that mostly in order to see if we can get Google to index the function pages on Wikifunctions, because we initially accidentally had them all set to not be indexed.

Playing around with Aliquot

Warning! Very technical, not particularly insightful, and overly long post about hacking, discrete mathematics, and rabbit holes. I don't think that anything here is novel, others have done more comprehensive work, and found out more interesting stuff. This is not research, I am just playing around.

Ernest Davis is a NYU professor, author of many publications (including “Rebooting AI” with Gary Marcus) and a friend on Facebook. Two days ago he posted about Aliquot sequences, and that it is yet unknown how they behave.

What is an Aliquot sequence? Given a number, take all its proper divisors, and add them up. That’s the next number in the sequence.

It seems that most of these either lead to 0 or end in a repeating pattern. But it may also be that they just keep on going indefinitely. We don’t know if there is any starting number for which that is the case. But the smallest candidate for that is 276.

So far, we know the first 2,145 steps for the Aliquot sequence starting at 276. That results in a number with 214 digits. We don’t know the successor of that number.

I was curious. I know that I wouldn’t be able to figure this out quickly, or, probably ever, because I simply don’t have enough skills in discrete mathematics (it’s not my field), but I wanted to figure out how much progress I can make with little effort. So I coded something up.

Anyone who really wanted to make a crack on this problem would probably choose C. Or, on the other side of the spectrum, Mathematica, but I don’t have a license and I am lazy. So I chose JavaScript. There were two hunches for going with JavaScript instead of my usual first language, Python, which would pay off later, but I will reveal them later in this post.

So, my first implementation was very naïve (source code). The function that calculates the next step in the Aliquot sequence is usually called s in the literature, so I kept that name:

 const divisors = (integer) => {
   const result = []
   for(let i = BigInt(1); i < integer; i++) {
     if(integer % i == 0) result.push(i)
   }
   return result
 }

 const sum = x => x.reduce(
   (partialSum, i) => partialSum + i, BigInt(0)
 )

 const s = (integer) => sum(divisors(integer))

I went for BigInt, not integer, because Ernest said that the 2,145th step had 214 digits, and the standard integer numbers in JavaScript stop being exact before we reach 16 digits (at 9,007,199,254,740,991, to be exact), so I chose BigInt, which supports arbitrary long integer numbers.

The first 30 steps ran each under a second on my one decade old 4 core Mac occupying one of the cores, reaching 8 digits, but then already the 36th step took longer than a minute - and we only had 10 digits so far. Worrying about the limits of integers turned out to be a bit preliminary: With this approach I would probably not reach that limit in a lifetime.

I dropped BigInt and just used the normal integers (source code). That gave me 10x-40x speedup! Now the first 33 steps were faster than a second, reaching 9 digits, and it took until the 45th step with 10 digits to be the first one to take longer than a minute. Unsurprisingly, a constant factor speedup wouldn’t do the trick here, we’re fighting against an exponential problem after all.

It was time to make the code less naïve (source code), and the first idea was to not check every number smaller than the target integer whether it divides (line 3 above), but only up to half of the target integer.

 const divisors = (integer) => {
   const result = []
   const half = integer / 2
   for(let i = 1; i <= half; i++) {
     if(integer % i == 0) result.push(i)
   }
   return result
 }

Tiny change. And exactly the expected impact: it ran double as fast. Now the first 34 steps ran under one second each (9 digits), and the first one to take longer than a minute was the 48th step (11 digits).

Checking until half of the target seemed still excessive. After all, for factorization we only need to check until the square root. That should be a more than constant speedup. And once we have all the factors, we should be able to quickly reconstruct all the divisors. Now this is the point where I have to admit that I have a cold or something, and the code for creating the divisors from the factors is probably overly convoluted and slow, but you know what? It doesn’t matter. The only thing that matters will be the speed of the factorization.

So my next step (source code) was a combination of a still quite naïve approach to factorization, with another function that recreates all the divisors.

 const factorize = (integer) => {
   const result = [ 1 ]
   let i = 2
   let product = 1
   let rest = integer
   let limit = Math.ceil(Math.sqrt(integer))
   while (i <= limit) {
     if (rest % i == 0) {
       result.push(i)
       product *= i
       rest = integer / product
       limit = Math.ceil(Math.sqrt(rest))
     } else {
       i++
     }
   }
   result.push(rest)
   return result
 }

 const divisors = (integer) => {
   const result = [ 1 ]
   const inner = (integer, list) => {
     result.push(integer)
     if (list.length === 0) {
       return [ integer ]
     }
     const in_results = [ integer ]
     const in_factors = inner(list[0], list.slice(1))
     for (const f of in_factors) {
       result.push(integer*f)
       result.push(f)
       in_results.push(integer*f)
       in_results.push(f)
     }
     return in_results
   }
   const list = factorize(integer)
   inner(list[0], list.slice(1))
   const im = [...new Set(result)].sort((a, b) => a - b)
   return im.slice(0, im.length-1)
 }

That made a big difference! The first 102 steps all were faster than a second, reaching 20 digits! That’s more than 100x speedup! And then, after step 116, the thing crashed.

Remember, integer only does well until 16 digits. The numbers were just too big for the standard integer type. So, back to BigInt. The availability of BigInt in JavaScript was my first hunch for choosing JavaScript (although that would have worked just fine in Python 3 as well). And that led to two surprises.

First, sorting arrays with BigInts is different from sorting arrays with integers. Well, I find already sorting arrays of integers a bit weird in JavaScript. If you don’t specify otherwise it sorts numbers lexicographically, instead of by value:

 [ 10, 2, 1 ].sort() == [ 1, 10, 2 ]

You need to provide a custom sorting function in order to sort the numbers by value, e.g.

 [ 10, 2, 1 ].sort((a, b) => a-b) == [ 1, 2, 10 ]

The same custom sorting functions won’t work for BigInt, though. The custom function for sorting requires an integer result, not a BigInt. We can write something like this:

 .sort((a, b) => (a < b)?-1:((a > b)?1:0))

The second surprise was that BigInt doesn’t have a square root function in the standard library. So I need to write one. Well, Newton is quickly implemented, or copy and pasted (source code).

Now, with switching to BigInt, we get the expected slowdown. The first 92 steps run faster than a second, reaching 19 digits, and then the first step to take longer than a minute is step 119, with 22 digits.

Also, the actual sequences started indeed diverging, due to the inaccuracy of large JavaScript integer: step 83 resulted in 23,762,659,088,671,304 using integers, but 23,762,659,088,671,300 using BigInt. And whereas that looks like a tiny difference on only the last digit, the number for the 84th step showed already what a big difference that makes: 20,792,326,702,587,410 with integers, and 35,168,735,451,235,260 with BigInt. The two sequences went entirely off.

What was also very evident is that at this point some numbers took a long time, and others were very quick. This is what you would expect from a more sophisticated approach to factorization, that it depends on the number and size of the factors. For example, calculating step 126 required to factorize the number 169,306,878,754,562,576,009,556, leading to 282,178,131,257,604,293,349,484, and that took more than 2 hours with that script on my machine. But then in Step 128 the result 552,686,316,482,422,494,409,324 was calculated from 346,582,424,991,772,739,637,140 in less than a second.

At that point I also started taking some of the numbers, and googled them, surfacing a Japanese blog post from ten years ago that posted the first 492 numbers, and also confirming that the 450th of these numbers corresponds to a published source. I compared the list with my numbers and was happy to see they corresponded so far. But I guesstimated I would not in a lifetime reach 492 steps, never mind the actual 2,145.

But that’s OK. Some things just need to be let rest.

That’s also when I realized that I was overly optimistic because I simply misread the number of steps that have been already calculated when reading the original post: I thought it was about 200-something steps, not 2,000-something steps. Or else I would have never started this. But now, thanks to the sunk cost fallacy, I wanted to push it just a bit further.

I took the biggest number that was posted on that blog post, 111,953,269,160,850,453,359,599,437,882,515,033,017,844,320,410,912, and let the algorithm work on that. No point in calculating steps 129, which is how far I have come, through step 492, if someone else already did that work.

While the computer was computing, I leisurely looked for libraries for fast factorization, but I told myself that no way am I going to install some scientific C library for this. And indeed, I found a few, such as the msieve project. Unsurprising, it was in C. But I also found a Website, CrypTool-Online with msieve on the Web (that’s pretty much one of the use cases I hope Wikifunctions will also support rather soonish). And there, I could not only run the numbers I already calculated locally, getting results in subsecond speed which took minutes and hours on my machine, but also the largest number from the Japanese website was factorized in seconds.

That just shows how much better a good library is than my naïve approach. I was slightly annoyed and challenged by the fact how much faster it is. Probably also runs on some fast machine in the cloud. Pretty brave to put a site like that up, and potentially have other people profit from the factorization of large numbers for, e.g. Bitcoin mining on your hardware.

The site is fortunately Open Source, and when I checked the source code I was surprised, delighted, and I understood why they would make it available through a Website: they don’t factorize the number in the cloud, but on the edge, in your browser! If someone uses a lot of resources, they don’t mind: it’s their own resources!

They took the msieve C library and compiled it to WebAssembly. And now I was intrigued. That’s something that’s useful for my work too, to better understand WebAssembly, as we use that in Wikifunctions too, although for now server side. So I rationalized, why not see if I can get that run on Node.

It was a bit of guessing and hacking. The JavaScript binding was written to be used in the browser, and the binary was supposed to be loaded through fetch. I guessed a few modifications, replacing fetch with Node’s FS, and managed to run it in Node. The hacks are terrible, but again, it doesn’t really matter as long as the factorization would speed up.

And after a bit of trying and experimenting, I got it running (source code). And that was my second hunch for choosing JavaScript: it had a great integration for using WebAssembly, and I figured it might come in handy to replace the JavaScript based solution. And now indeed, the factorization was happening in WebAssembly. I didn’t need to install any C libraries, no special environments, no nothing. I just could run Node, and it worked. I am absolutely positive there are is cleaner code out there, and I am sure I mismanaged that code terribly, but I got it to run. At the first run I found that it added an overhead of 4-5 milliseconds on each step, making the first few steps much slower than with pure JavaScript. That was a moment of disappointment.

But then: the first 129 steps, which I was waiting hours and hours to run, zoomed by before I could even look. Less than a minute, and all the 492 steps published on the Japanese blog post were done, allowing me to use them for reference and compare for correctness so far. The overhead was irrelevant, even across the 2,000 steps the overhead wouldn’t amount to more than 10 seconds.

The first step that took longer than a second was step 596, working on a 58 digit number. All the first 595 steps took less than a second each. The first step that took more than a minute, was step 751, a 76 digit number, taking 62 seconds, factorizing 3,846,326,269,123,604,249,534,537,245,589,642,779,527,836,356,985,238,147,044,691,944,551,978,095,188. The next step was done in 33 milliseconds.

The first 822 steps took an hour. Step 856 was reached after two hours, so that’s another 34 steps in the second hour. Unexpectedly, things slowed down again. Using faster machines, modern architectures, GPUs, TPUs, potentially better algorithms, such as CADO-NFS or GGNFS, all of that could speed that up by a lot, but I am happy how far I’ve gotten with, uhm, little effort. After 10 hours, we had 943 steps and a 92 digit number, 20 hours to get to step 978 and 95 digits. My goal was to reach step 1,000, and then publish this post and call it a day. By then, a number of steps already took more than an hour to compute. I hit step 1000 after about 28 and a half hours, a 96 digit number: 162,153,732,827,197,136,033,622,501,266,547,937,307,383,348,339,794,415,105,550,785,151,682,352,044,744,095,241,669,373,141,578.

I rationalize this all through “I had fun” and “I learned something about JavaScript, Node, and WebAssembly that will be useful for my job too”. But really, it was just one of these rabbit holes that I love to dive in. And if you read this post so far, you seem to be similarly inclined. Thanks for reading, and I hope I didn’t steal too much of your time.

I also posted a list of all the numbers I calculated so far, because I couldn’t find that list on the Web, and I found the list I found helpful. Maybe it will be useful for something. I doubt it. (P.S.: the list was already on the Web, I just wasn't looking careful enough. Both, OEIS and FactorDB have the full list.)

I don’t think any of the lessons here are surprising:

• for many problems a naïve algorithm will take you to a good start, and might be sufficient
• but never fight against an exponential algorithm that gets big enough, with constant speedups such as faster hardware. It’s a losing proposition
• But hey, first wait if it gets big enough! Many problems with exponential complexity are perfectly solvable with naïve approaches if the problem stays small enough
• better algorithms really make a difference
• use existing libraries!
• advancing research is hard
• WebAssembly is really cool and you should learn more about it
• the state of WebAssembly out there can still be wacky, and sometimes you need to hack around to get things to work

In the meantime I played a bit with other numbers (thanks to having a 4 core computer!), and I will wager one ambitious hypothesis: if 276 diverges, so does 276,276, 276,276,276, 276,276,276,276, etc., all the way to 276,276,276,276,276,276,276,276,276, i.e. 9 times "276".

I know that 10 times "276" converges after 300 steps, but I have tested all the other "lexical multiples" of 276, and reached 70 digit numbers after hundreds of steps. For 276,276 I pushed it further, reaching 96 digits at step 640. (And for at least 276,276 we should already know the current best answer, because the Wikipedia article states that all the numbers under one million have been calculated, and only about 9,000 have an unclear fate. We should be able to check if 276,276 is one of those, which I didn't come around to yet).

Again, this is not research, but just fooling around. If you want actual systematic research, the Wikipedia article has a number of great links.

Thank you for reading so far!

P.S.: Now that I played around, I started following some of the links, and wow, there's a whole community with great tools and infrastructure having fun about Aliquot sequences and prime numbers doing this for decades. This is extremely fascinating.

The Surrounding Sea

Explore the ocean of words in which we all are swimming, day in day out. A site that allows you to browse through the lexicographic data in Wikidata along four dimensions:

• alphabetical, like in a good old fashioned dictionary
• through translations and synonyms
• where does this word come from, and where did it go
• narrower and wider words, describing a hierarchy of meanings

Wikidata contains over 1.2 million lexicographic entries, but you will see the many gaps when exploring the sea of words. Please join us in charting out more of the world of words.

Happy 23rd birthday to Wikipedia and the movement it started!

• The Surrounding Ocean

Das Mädchen Doch

Sie sagten ihrer Mutter
Kinder werde sie nie haben
Und als sie geboren wurde
Nannte ihre Mutter sie
Doch

Sie sagten sie sei schwach
Und klein und krank
Und dass sie nicht
Lange zu leben habe
Doch

Ihre Mutter hoffte
Das sie in einer Welt aufwuchs
In der alle gleich behandelt wurden
Aber leider
Doch

Sie sagten Mathe und Autos
Seien nichts für Mädchen
Dass sie sich interessiert
Für Puppen und für Kleidung
Doch

Sie sagten die Welt
Ist wie sie ist
Und sie zu ändern
Sei nichts für kleine kranke Mädchen
Doch

Sie sagten gut dass Du darüber sprachst
Wir sollten darüber nachdenken
Lass uns jetzt darüber debattieren
Und wir (nicht Du) entscheiden dann
Doch

Sie sagten man kann nicht alles haben
Man muss sich entscheiden
Aber so selbstsüchtig
Ich meine, keine Kinder zu wollen
Doch

Sie sagten sie sei unanständig
So ein Leben sei nicht richtig
Benannten sie mit unanständigen Worten
Was sie sich denn erlaube
Doch

Sie sagten das geht doch nicht
So ein Leben sei kein Leben
Das ist jetzt schon sehr anders
Das ist nicht einfach nur Neid
Doch

Sie sagten wir sind halt nicht so
Und wollen auch nicht so sein
Wir sind glücklich wie wir sind
Und deswegen darfst du glücklich nicht sein
Doch

Languages with the best lexicographic data coverage in Wikidata 2023

Languages with the best coverage as of the end of 2023

1. English 92.9%
2. Spanish 91.3%
3. Bokmal 89.1%
4. Swedish 88.9%
5. French 86.9%
6. Danish 86.9%
7. Latin 85.8%
8. Italian 82.9%
9. Estonian 81.2%
10. Nynorsk 80.2%
11. German 79.5%
12. Basque 75.9%
13. Portuguese 74.8%
14. Malay 73.1%
15. Panjabi 71.0%
16. Slovak 67.8%
17. Breton 67.3%

What does the coverage mean? Given a text (usually Wikipedia in that language, but in some cases a corpus from the Leipzig Corpora Collection), how many of the occurrences in that text are already represented as forms in Wikidata's lexicographic data.

The list contains all languages where the data covers more than two thirds of the selected corpus.

Progress in lexicographic data in Wikidata 2023

Here are some highlights of the progress in lexicographic data in Wikidata in 2023

• Greek jumped from 0% to 45% right away
• Panjabi jumped right away from 0% to 71% (but on an admittedly small corpus)
• Italian made a huge jump from 52% to 82% by increasing the number of forms from 9,000 to 286,000
• Turkish jumped from 0.9% to 22%
• Sindhi climbed from 15% to 25%
• Farsi climbed from 15% to 24% increasing the number of forms from 4,000 to 33,000
• Western Panjabi climbed from 36.9% to 47.9%
• Hindi climbed from 49.9% to 65.9%
• Breton increased from 56% to 67%
• Croatian increased from 40% to 45%
• Dutch went from 20% to 29%
• French from 82.9% to 86.9%, mostly by dealing better with apostrophes in the analysis
• Nynorsk pushed from 75% to 80% by increasing the number of forms from 18,000 to 68,000
• Danish from 83.9% to 86.9% by increasing the number of forms in Wikidata from 65,000 to 170,000
• German from 76% to 79% by increasing the number of forms in Wikidata from 90,000 to 200,000
• Spanish pushed from 88% to 91% by increasing the number of forms from 280,000 to 430,000

What does the coverage mean? Given a text (usually Wikipedia in that language, but in some cases a corpus from the Leipzig Corpora Collection), how many of the occurrences in that text are already represented as forms in Wikidata's lexicographic data. Note that every percent more gets much more difficult than the previous one: an increase from 1% to 2% usually needs much much less work than from 91% to 92%.

RIP Niklaus Wirth

RIP Niklaus Wirth;

BEGIN

I don't think there's a person who created more programming languages that I used than Wirth: Pascal, Modula, and Oberon; maybe Guy Steele, depending on what you count;

Wirth is also famous for Wirth's law: software becomes slower more rapidly than hardware becomes faster;

He received the 1984 Turing Award, and had an asteroid named after him in 1999; Wirth died at the age of 89;

END.

Wikidata lexicographic data coverage for Croatian in 2023

Last year, I published ambitious goals for the coverage of lexicographic data for Croatian in Wikidata. My self-proclaimed goal was widely missed: I wanted to go from 40% coverage to 60% -- instead, thanks to the help of contributors, we reached 45%.

We grew from 3,124 forms to 4,115, i.e. almost a thousand new forms, or about 31%. The coverage grew from around 11 million tokens to about 13 million tokens in the Croatian Wikipedia, or, as said, from 40% to 45%. The covered forms grew from 1.4% to 1.9%, which illustrates neatly the increased difficulty to reach more coverage (thanks to Zipf's law): last year, we increased covered forms by 1%, which translated to an overall coverage increase of occurrences by 35%. This year, although we increased the covered forms by another 0.5%, we only got an overall coverage increase of occurrences by 5%.

But some of my energy was diverted from adding more lexicographic data to adding functions that help with adding and checking lexicographic data. We launched a new project, Wikifunctions, that can hold functions. There, we collected functions to create the regular forms for Croatian nouns. All nouns are now covered.

I think that's still a great achievement and progress. Sure, we didn't meet the 60%, but the functions helped a lot to get to the 45%, and they will continue to benefit us 2024 too. Again, I want to declare some goals, at least for myself, but not as ambitious with regards to coverage: the goal for 2024 is to reach 50% coverage of Croatian, and in addition, I would love us to have Lexeme forms available for verbs and adjectives, not only for nouns, (for verbs, Ivi404 did most of the work already), and maybe even have functions ready for adjectives.

• Changes in Croatian coverage in 2023
• List of missing forms for Croatian

Star Trek's 32nd century

I like Star Trek for the cool technology, which has inspired plenty of people to work eg on "the Star Trek computer". I love Star Trek for the utopian society of plenty they sketch in the 23rd and 24th century.

I claim it is because of the laziness of the writing: they don't keep that utopia up.

When I heard about Discovery going to the 32nd century, I was excited about the wonders they would dream up. The new technology. The society. The culture. The breakthroughs.

With regards to that, it was a massive let down. Extremely disappointing.

Finding God through Information Theory

I found that surprising: Luciano Floridi, one of the most-cited living philosophers, started studying information theory because young Floridi, still Catholic, concluded that God's manifestation to humanity must be an information process. He wanted to understand God's manifestation through the lens of information.

He didn't get far in answering that question, but he did become the leading expert in the Philosophy of Information, and an expert in Digital Ethics (and also, since then, an agnostic).

Post scriptum: The more I think about it, the more I like the idea. Information theory is not even one of these vague, empirical disciplines such as Physics, but more like Mathematics and Logics, and thus unavoidable. Any information exchange, i.e. communication, must follow its rules. Therefore the manifestation of God, i.e. the way God chooses to communicate themselves to us, must also follow information theory. So this should lead to some necessary conditions on the shape of such a manifestation.

It's a bright idea. I am not surprised it didn't go anywhere, but I still like the idea.

Could have at least engendered a novel Proof for the Existence of God. They have certainly come from more surprising corners.

Source: https://philosophy.fireside.fm/1

More about Luciano Flordi on Wikipedia.

Little One's first GIF

Little One made her first GIF!

Moving to Germany

We are moving to Germany. It was a long and difficult decision process.

Is it the right decision? Who knows. These kinds of decisions are rarely right or wrong, but just are.

What about your job? I am thankful to the Wikimedia Foundation for allowing me to move and keep my position. The work on Abstract Wikipedia and Wikifunctions is not done yet, and I will continue to lead the realization of this project.

Don’t we like it in California? We love so many things about California and the US, and the US has been really good to us. Both my wife and I grew here in our careers, we both learned valuable skills, and met interesting people, some of whom became friends, and who I hope to continue to keep in touch. Particularly my time at Google was also financially a boon. And it also gave me the freedom to prepare for the Abstract Wikipedia project, and to get to know so many experts in their field and work together with them, to have the project criticized and go through several iterations until nothing seems obviously wrong with it. There is no place like the Bay Area in the world of Tech. It was comparably easy to have meetings with folks at Google, Facebook, Wikimedia, LinkedIn, Amazon, Stanford, Berkeley, or to have one of the many startups reach out for a quick chat. It is, in many ways, a magical place, and no other place we may move to will come even close to it with regards to its proximity to tech.

And then there’s the wonderful weather in the Bay Area and the breathtaking nature of California. It never gets really hot, it never gets really cold. The sun is shining almost every day, rain is scarce (too scarce), and we never have to drive on icy streets or shovel snow. If we want snow, we can just drive up to the Sierras. If we want heat, drive inland. We can see the largest trees in the world, walk through the literal forests of Endor, we can hike hills and mountains, and we can walk miles and miles along the sand beaches of the Pacific Ocean. California is beautiful.

Oh, and the food and the produce! Don’t get me started on Berkeley Bowl and its selection of fruits and vegetables. Of the figs in their far too short season, of the dry-farmed Early Girl tomatoes and their explosion of taste, of the juicy and rich cherries we picked every year to carry pounds and pounds home, and to eat as many while picking, the huge diversity of restaurants in various states from authentic to fusion, but most of them with delicious options and more dishes to try than time to do it.

And not just the fruits and vegetables are locally sourced: be it computers from Apple, phones from Google, the social media from Facebook or Twitter, the wonderful platform enabling the Wikimedia communities, be it cars from Tesla, be it movies from Pixar, the startups, the clouds, the AIs: so. many. things. are local. And every concert tour will pass by in the Bay Area. In the last year we saw so many concerts here, it was amazing. That’s a place the tours don’t skip.

Finally: in California, because so many people are not from here, we felt more like we belong just as well as everyone else, than anywhere else. Our family is quite a little mix, with passports from three continents. Our daughter has no simple roots. Being us is likely easier in the United States than in any of the European nation states with their millenia of identity. After a few years I felt like an American. In Germany, although it treated me well, after thirty years I still was an Ausländer.

As said, it is a unique place. I love it. It is a privilege and an amazing experience to have spent one decade of my life here.

Why are we moving? In short, guns and the inadequate social system.

In the last two years alone, we had four close-ish encounters with people wielding guns (not always around home). And we are not in a bad neighborhood, on the contrary. This is by all statistics one of the safest neighborhoods you will find in the East Bay or the City.

We are too worried to let the kid walk around by herself or even with friends. This is such a huge difference to how I grew up, and such a huge difference to when we spent the summer in Croatia, and she and other kids were off by themselves to explore and play. Here, there was not a single time she went to the playground or visited a friend by herself, or that one of her friends visited our house by themselves.

But even if she is not alone: going to the City with the kid? There are so many places there I want to avoid. Be it around the city hall, be it in the beautiful central library, be it on Market Street or even just on the subway or the subway stations: too often we have to be careful to avoid human excrement, too often we are confronted with people who are obviously in need of help, and too often I feel my fight or flight reflexes kicking in.

All of this is just the visible effect of a much larger problem, one that we in the Bay Area in particular, but as Americans in general should be ashamed of not improving: the huge disparity between rich and poor, the difficult conditions that many people live in. It is a shame that so many people who are in dire need of professional help live on the streets instead of receiving mental health care, that there are literal tent cities in the Bay Area, while the area is also the home of hundreds of thousands of millionaires and more than sixty billionaires - more than the UK, France, or Switzerland. It is a shame that so many people have to work two or more jobs in order to pay their rent and feed themselves and their children, while the median income exceeds $10,000 a month. It is a shame that this country, which calls itself the richest and most powerful and most advanced country in the world, will let its school children go hungry. Is “school lunch debt” a thing anywhere else in the world? Is “medical bankruptcy” a thing anywhere else in the world? Where else are college debts such a persistent social issue?

The combination of the easy availability of guns and the inadequate social system leads to a large amount of avoidable violence and to tens of thousands of seemingly avoidable deaths. And they lead to millions of people unnecessarily struggling and being denied a fair chance to fulfill their potential.

And the main problem, after a decade living here, is not where we are, but the trajectory of change we are seeing. I don’t have hope that there will be a major reduction in gun violence in the coming decade, on the contrary. I don’t have hope for any changes that will lead to the Bay Area and the US spreading the riches and gains it is amassing substantially more fairly amongst its population, on the contrary. Even the glacial development in self-driving cars seems breezy compared to the progress towards killing fewer of our children or sharing our profits a little bit more fairly.

After the 1996 Port Arthur shooting, Australia established restrictions on the use of automatic and semi-automatic weapons, created a gun buyback program that removed 650,000 guns from circulation, a national gun registry, and a waiting period for firearms sales. They chose so.

After the 2019 Christchurch shooting, New Zealand passed restrictions on semi-automatic weapons and a buyback program removed 50,000 guns. They chose so.

After the shootings earlier this year in Belgrade, Serbia introduced stricter laws and an amnesty for illegal weapons and ammunition if surrendered, leading to more than 75,000 guns being removed. They chose so.

I don’t want to list the events in the US. There are too many of them. And did any of them lead to changes? We choose not to.

We can easily afford to let basically everyone in the US live a decent life and help those that need it the most. We can easily afford to let no kid be hungry. We can easily afford to let every kid have a great education. We choose not to.

I don’t want my kid to grow up in a society where we make such choices.

I could go on and rant about the Republican party, about Trump possibly winning 2024, about our taxes supporting and financing wars in places where they shouldn’t, about xenophobia and racism, about reproductive rights, trans rights, and so much more. But unfortunately many of these topics are often not significantly better elsewhere either.

When are we moving? We plan to stay here until the school year is over, and aim to have moved before the next school year starts. So in the summer of ‘24.

Where are we moving? I am going back to my place of birth, Stuttgart. We considered a few options, and Stuttgart led overall due to the combination of proximity to family, school system compatibility for the kid, a time zone that works well for the Abstract Wikipedia team, language requirements, low legal hurdles of moving there, and the cost of living we expect. Like every place it also comes with challenges. Don’t get me started on the taste of tomatoes or peaches.

What other places did we consider? We considered many other places, and we traveled to quite a few of them to check them out. We loved each and every one of them. We particularly loved Auckland due to our family there and the weather, we loved the beautiful city of Barcelona for its food and culture, we loved Dublin, London, Zürich, Berlin, Vienna, Split. We started making a large spreadsheet with pros and contras in many categories, but in the end the decision was a gut decision. Thanks to everyone who talked with us and from whom we learned a lot about those places!

Being able to even consider moving to these places is a privilege. And we understand that and are thankful for having this privilege. Some of these places would have been harder to move for us due to immigration regulation, others are easy thanks to our background. But if you are thinking of moving, and are worried about certain aspects, feel free to reach out and discuss. I am happy to offer my experience and perspective.

Is there something you can help with? If you want to meet up with us while we are still in the US, it would be good to do so timely. We are expecting to sell the house quite a bit sooner, and then we won’t be able to host guests easily. I am also looking forward to reconnecting with people in Europe after the move. Finally, if you know someone who is interested in a well updated 3 bedroom house with a surprisingly large attic that can be used as a proper hobby space, and with a top walkability index in south Berkeley, point them our way.

Also, experiences and advice regarding moving from the US to Germany are welcome. Last time we moved the other way, and we didn’t have that much to move, and Google was generously organizing most of what needed to be done. This time it’s all on us. How to get a container and get it loaded? How to ship it to Germany? Where to store it while we are looking for a new home? How to move the cat? How to make sure all goes well with the new school? When to sell the house and where to live afterwards? How to find the right place in Germany? What are the legal hurdles to expect? How will taxes work? So many questions we will need to answer in the coming months. Wish us luck for 2024.

We also accept good wishes and encouraging words. And I am very much looking forward to seeing some of you again next year!

Sam Altman and the veil of ignorance

(This is not about Altman having been removed as CEO of OpenAI)

During the APEC forum on Thursday, Sam Altman has been cited to having said the following thing: "Four times now in the history of OpenAI—the most recent time was just in the last couple of weeks—I’ve gotten to be in the room when we push the veil of ignorance back and the frontier of discovery forward. And getting to do that is like the professional honor of a lifetime."

He meant that as an uplifting quote to describe how awesome his company and their achievements are.

I find it deeply worrying. Why?

The "veil of ignorance" (also known as the original position) is a thought experiment introduced by John Rawls, one of the leading American moral and political philosophers of the 20th century. The goal is to think about the fairness of a society or a social system without you knowing where in the system you end up: are you on top or at the bottom? What are your skills, your talents? Who are your friends? Do you have disabilities? What is your gender, your family history?

The whole point is to *not* push the veil of ignorance back, otherwise you'll create an unfair system. It is a good tool to think about the coming disruptions by AI technology.

The fact that he's using that specific term but is obviously entirely oblivious to its meaning tells us that there was a path that term took, probably from someone working on ethics to then-CEO Altman, and that someone didn't listen. The meaning was lost, and the beautiful phrase was entirely repurposed.

Given that's coming from the then-CEO of the company that claims and insists on, again and again (without substantial proof) that they are doing all this for the greater benefit of all humanity, that are, despite their name, increasingly closing their results, making public scrutiny increasingly difficult if not impossible - well, I find that worrying. The quote indicates that they have no idea about a basic tool towards evaluating fairness, even worse, have heard about it - but they have not listened or comprehended.

• Wikipedia on the veil of ignorance
• Source of the Altman quote

Babel

Strong recommendation for "Babel" by R.F. Kuang. It's a speculative fiction story set in 1830s Oxford with an, as far as I can tell, novel premise: one can cast spells (although they don't call it spells but it's just science in this world) by using two words that translate into each other, and the semantic difference between the two words - because no translation is perfect - is the effect of the spell. But the effect can only be achieved if you have a speaker who's fluent enough in both languages to have a native understanding of the difference.

One example would be the French parcelle and the English parcel, both meaning package, but the French still carries some of the former "to split into parts", with the effect that packages are lighter and easier to transport for the Royal Mail.

The story remains comfortable for the first half of the volume, with beautiful world building, character drawing, and the tranquil academic life of Oxford students, but then it suddenly picks up speed, and we can experience the events unfold with a merciless speed. The end is just in the right place, and it leaves me to yearn to revisit this world and the desire to learn what happened next.

The volume discusses some heavy topics - colonialism, dependency on technology, fairness, what is allowed in a revolution, the "neutrality" of science - and while we are still in the first half of the volume, it feels very on the nose, very theoretical - but that changes dramatically as we swing into the second half of the volume, and suddenly all these theoretical discussions become very immediate. Which does remind me of student life, where discussions about different political systems and abstract notions of justice are just as prevalent and as consequence-free as they seem to be here, at first.

The book was recommended by the Lingthusiasm podcast, which is how I found it.

I came for the linguistic premise, but I stayed for the characters and their fates in a colonial world.

• Wikipedia article

Existential crises

I think the likelihood of AI killing all humans is bigger than the likelihood of climate change killing all humans.

Nevertheless I think that we should worry and act much more about climate change than about AI.

Allow me to explain.

Both AI and climate change will, in this century, force changes to basically every aspect of the lives of basically every single person on the planet. Some people may benefit, some may not. The impact of both will be drastic and irreversible. I expect the year 2100 to look very different from 2000.

Climate change will lead to billions of people to suffer, and to many deaths. It will destroy the current livelihoods of many millions of people. Many people will be forced to leave their homes, not because they want to, but because they have to in order to survive. Richer countries with sufficient infrastructure to deal with the direct impact of a changed climate will have to decide how to deal with the millions of people who want to live and who want their children not to die. We will see suffering on a scale never seen before, simply because there have never been this many humans on the planet.

But it won't be an existential threat to humanity (the word humanity has at least two meanings: 1) the species as a whole, and 2) certain values we associate with humans. Unfortunately, I only refer to the first meaning. The second meaning will most certainly face a threat). Humanity will survive, without a doubt. There are enough resources, there are enough rich and powerful people, to allow millions of us to shelter away from the most life threatening consequences of climate change. Millions will survive for sure. Potentially at the costs of many millions lives and the suffering of billions. Whole food chains, whole ecosystems may collapse. Whole countries may be abandoned. But humanity will survive.

What about AI? I believe that AI can be a huge boon. It may allow for much more prosperity, if we spread out the gains widely. It can remove a lot of toil from the life of many people. It can make many people more effective and productive. But history has shown that we're not exactly great at sharing gains widely. AI will lead to disruptions in many economic sectors. If we're not careful (and we likely aren't) it might lead to many people suffering from poverty. None of these pose an existential threat to humanity.

But there are outlandish scenarios which I think might have a tiny chance of becoming true and which can kill every human. Even a full blown Terminator scenario where drones hunt every human because the AI has decided that extermination is the right step. Or, much simpler, that in our idiocy we let AI supervise some of our gigantic nuclear arsenal, and that goes wrong. But again, I merely think these possible, but not in the slightest likely. An asteroid hitting Earth and killing most of us is likelier if you ask my gut.

Killing all humans is a high bar. It is an important bar for so called long-termists, who may posit that the death of four or five billion people isn't significant enough to worry about, just a bump in the long term. They'd say that they want to focus on what's truly important. I find that reasoning understandable, but morally indefensible.

In summary: there are currently too many resources devoted to thinking about the threat of AI as an existential crisis. We should focus on the short term effect of AI and aim to avoid as many of the negative effects as possible and to share the spoils of the positive effects. We're likely to end up with socializing the negative effects, particularly amongst the weakest members of society, and privatizing the benefits. That's bad.

We really need to devote more resources towards avoiding climate change as far as still possible, and towards shielding people and the environment from the negative effects of climate change. I am afraid we're failing at that. And that will cause far more negative impact in the course of this century than any AI will.

Wikidata crossed 2 billion edits

The Wikidata community edited Wikidata 2 billion times!

Wikidata is, to the best of my knowledge, the first and only wiki to cross 2 billion edits (the second most edited one being English Wikipedia with 1.18 billion edits).

Edit Nr 2,000,000,000 was adding the first person plural future of the Italian verb 'grugnire' (to grunt) by user Luca.favorido.

Wikidata also celebrated 11 years since launch with the hybrid WikidataCon 2023 in Taipei last weekend.

It took from 2012 to 2019 to get the first billion, and from 2019 to now for the second. As they say, the first billion is the hardest.

That the two billionth edit happens right on the Birthday is a nice surprise.

The letter Đ

The letter Đ was introduced to Serbo-Croatian by Đuro Daničić, according to Wikipedia. I found that highly amusing, that he introduced the letter that is the first letter in his name.

Wikipedia also claims that he was born Đorđe Popović, and all I can think of is "nah, that can't be right".

That would be like Jebediah Springfield who was born in a cabin that he helped build.

Pastir Loda

Vladimir Nazor is likely the most famous author from the island of Brač, the island my parents are from. His most acclaimed book seems to be Pastir Loda, Loda the Shepherd. It tells the story of a satyr that, through accidents and storms, was stranded on the island of Brač, and how he lived on Brač for the next almost two thousand years.

It is difficult to find many of his works, they are often out of print. And there isn't much available online, either. Since Nazor died in 1949, his works are in the public domain. I acquired a copy of Pastir Loda from an antique book shop in Zagreb, which I then forwarded to a friend in Denmark who has a book scanner, and who scanned the book so I can make the PDF available now.

The book is written in Croatian. There is a German translation, but that won't get into the public domain until 2043 (the translator lived until 1972), and according to WorldCat there is a Czech translation, and according to Wikipedia a Hungarian translation. For both I don't know who the translator is, and so I don't know the copyright status of these translations. I also don't know if the book has ever been translated to other languages.

I wish to find the time to upload and transcribe the content on Wikisource, and then maybe even do a translation of it into English. For now I upload the book to archive.org, and I also make it available on my own Website. I want to upload it to Wikimedia Commons, but I immediately stumbled upon the first issue, that it seems that to upload it to Commons the book needs to be published before 1928 and the author has to be dead for more than 70 years (I think that should be an or). I am checking on Commons if I can upload it or not.

Until then, here's the Download:

• Vladimir Nazor: Pastir Loda

F in Croatian

I was writing some checks to find errors in the lexical data in Wikidata for Croatian, and one of the things I tried was to check whether the letters in the words are all part of the Croatian alphabet. But instead of just taking a list, or writing down from memory, I looked at the data, and added letter after letter. And then I was surprised to find that the letter "f" only appears in loanwords. And I look it up in the Croatian Encyclopedia and it simply states that "f" is not a letter of the old slavic language.

I was mindblown. I speak this language since I can remember, and i didn't notice that there is no "f" but in loanwords. And "f" seems like such a fundamental sound! But no, wrong!

If you speak a slavic language, do you have the letter "f"?

Do you hear the people sing?

"Do you hear the people sing, singing the song of angry men..."

Yesterday, a London performance of Les Miserables was interrupted by protesters raising awareness about climate change.

The audience booed.

It seems the audience was unhappy about having to experience protests and unrest during the performance of protests and unrest they wanted to enjoy.

The hypocrisy is rich in this one, but a very well engineered and expected one. But I guess only with the luxury of being detached from the actual event one can afford to enjoy the hypocrisy. I assume that for many people attending a West End London production of Les Miserables aims to be a proper highlight of the year, if not more. It's something that children gift their parents for the 30th wedding anniversary. It may be the reason for a trip to London. In addition, attending a performance like this is an escapist act, that you don't want interrupted with the problems of the real world. And given that it is a life performance, it seems disrespectful to the cast, to the artists, who pour their lives into their roles.

On the other side, the existential dread about climate change, and the insufficient actions by world leaders seem to demand increasingly bolder action and more attention. We are teaching our kids that they should act if something is not right. And we are telling them about the predictions for climate change. And then we are surprised if they try to do something? The message that climate change will be extremely disruptive to our lives and that we need to act much more decisively has obviously not yet been understood by enough people. And we, humanity, our leaders, elected or not, are most certainly not yet doing enough to try to prevent or at least mitigate the effects of climate change that are starting to roll over us.

It would be good, but admittedly unlikely, if both sides could appreciate the other more. Maybe the audience might be a bit appreciative of seeing the people sing the song of angry men in real. And maybe the protesters could choose their targets a bit more wisely. Why choose art? There are more disruptive targets if you were to protest the oil industry than a performance of Les Miserables. To be honest, if i were working for the oil industry, this is exactly the kind of actions I would be setting up. And with people who are actually into the cause. That way I can ensure that people will talk about interrupted theater productions and defaced paintings, instead of again having the hottest year in history, of floods, heatwaves, hurricanes, and the thousands of people who already died due to climate change induced catastrophes - and the billions more whose life will be turned upside down.

• The Guardian on the event

Immortal relationships

I saw a beautiful meme yesterday that said that from the perspective of a cat or dog, humans are like elves who live for five hundred years and yet aren't afraid to bond with them for their whole life. And it is depicted as beautiful and wholesome.

It's so different from all those stories of immortals, think of Vampires or Highlander or the Sandman, where the immortals get bitter, or live in misery and loss, or become aloof and uncaring about human lives and their short life spans, and where it hurts them more than it does them good.

There seem to be more stories exploring the friendship of immortals with short-lived creatures, be it in Rings of Power with the relationship of Elrond and Durin, be it the relation of Star Trek's Zora with the crew of the Discovery or especially with Craft in the short movie Calypso, or between the Eternal Sersi and Dane Whitman. All these relations seem to be depicted more positively and less tragic.

In my opinion that's a good thing. It highlights the good parts in us that we should aspire to. It shows us what we can be, based in a very common perception, the relationship to our cats and dogs. Stories are magic, in it's truest sense. Stories have an influence on the world, they help us understand the world, imagine the impact we can have, explore us who we can be. That's why I'm happy to see these more positive takes on that trope compared to the tragic takes of the past.

(I don't know if any of this is true. I think it would require at least some work to actually capture instances of such stories, classify and tally them, to see if that really is the case. I'm not claiming I've done that groundwork, but just capture an observation that I'd like to be true, but can't really vouch for it.)

Molly Holzschlag (1963-2023)

May her memory be a blessing.

She taught the Web to many, and she fought for the Web of many.

• Wikipedia: Molly Holzschlag

Doug Lenat (1950-2023)

When I started studying computer science, one of the initiation rites was to read the Jargon File. I stumbled when I read the entry on the microlenat:

microlenat: The unit of bogosity. Abbreviated μL, named after Douglas Lenat. Like the farad it is considered far too large a unit for practical use, so bogosity is usually expressed in microlenats.

I had not heard of Douglas Lenat then. English being my third language, I wasn’t sure what bogosity is. So I tried to learn a bit more to understand it, and I read a bit about Cyc and Eurisko, but since I just started computer science, my mind wasn’t really ready for things such as knowledge representation and common sense reasoning. I had enough on my plate struggling with resistors, electronegativity, and fourier transformations. Looking back, it is ironic that none of these played a particular role in my future, but knowledge representation sure did.

It took me almost ten years to come back to Cyc and Lenat’s work. I was then studying ontological engineering, a term that according to Wikipedia was coined by Lenat, a fact I wasn’t aware of at that time. I was working with RDF, which was co-developed by Guha, who has worked with Lenat at Cycorp, a fact I wasn’t aware of at that time. I was trying to solve problems that Lenat had tackled decades previously, a fact I wasn’t aware of at that time.

I got to know Cyc through OpenCyc and Cyc Europe, led by Michael Witbrock. I only met Doug Lenat a decade later when I was at Google.

Doug’s aspirations and ambitions had numerous people react with rolling eyes and sneering comments, as can be seen in the entry in the Jargon File. And whereas I might have absorbed similar thoughts as well, they also inspired me. I worked with a few people who told me “consider yourself lucky if you have a dozen people reading your paper, that’s the impact you will likely have”, but I never found that a remotely satisfactory idea. Then there were people like Doug, who shouted out “let’s solve common sense!”, and stormed ahead trying to do so.

His optimism and his bias to action, his can-do attitude, surely influenced me profoundly in choosing my own way forward. Not only once did I feel like I was channeling Lenat when I was talking about knowledge bases that anyone can edit, about libraries of functions anyone can use, or about abstract representations of natural language texts. And as ambitious as these projects have been called, they all carefully avoid the incomparably more ambitious goals Doug had his eyes set on.

And Doug didn’t do it from the comfort of a tenured academic position, but he bet his career and house on it, he founded a company, and kept it running for four decades. I was always saddened that Cyc was kept behind closed doors, and I hope that this will not hinder the impact and legacy it might have, but I understand that this was the magic juice that kept the company running.

One of Doug’s systems, Eurisko, became an inspiration and namesake for an AI system that played the role of the monster of the week in a first season episode of the X-Files, a fact I wasn’t aware of until now. Doug was a founder and advisory member of the TTI/Vanguard series of meetings, to which I was invited to present an early version of Abstract Wikipedia, a fact I wasn’t aware of until now. And I am sure there are more facts about Doug and his work and how it reverberated with mine that I am unaware of still.

Doug was a person ahead of their time, a person who lived, worked on and saw a future about knowledge that is creative, optimistic and inspiring. I do not know if we will ever reach that future, but I do know that Doug Lenat and his work will always be a beacon on our journey forward. Doug Lenat died yesterday in Austin, Texas, two weeks shy of his 73rd birthday, after a battle with cancer.

To state it in CycL, the language Cyc is written in:

 (#$dateOfDeath #$DougLenat "2023-08-31")

 (#$restInPeace #$DougLenat)

Butter

So, I went to the store with Little One today, and couldn't find the butter.

I ask the person at the cheese stand, who points me to the burrata. Tasty, but not what I'm looking for. I ask again and he sends me to the bread section.

I can't find it at the bread section, so I ask the person at the pastries stand where the butter is. She points me to the bagels. I say no, butter. She says, ah, there, pointing to the bathrooms. I'm getting exasperated, and I ask again. She points back to the cheeses with the burrata. I try again. She gets a colleague, and soon they both look confused.

Finally my daughter chimes in, asking for the butter. They immediately point her to the right place and we finally get the butter.

I haven't been so frustrated about my English pronunciation since I tried to buy a thermometer.

The Jones Brothers

The two Jones brothers never got along, but both were too stubborn to leave the family estate. They built out two entrances to the estate, one from the south, near Jefferson Avenue, and the newer, bigger one, closer to the historic downtown, and each brother chose to use one of the entrances exclusively, in order to avoid the other and their family. To the confusion of the local folk (but to the open enjoyment of the high school's grammar teacher, who was, surprisingly for his role, a descriptivist), they named the western gate the Jones' gate, and the southern one the Jones's gate, and the brothers earnestly thought that that settled it.

It didn't.

The Future of Knowledge Graphs in a World of Large Language Models

The Knowledge Graph Conference 2023 in New York City invited me for a keynote on May 11, 2023. Given that basically all conversations these days are about large language models, I have given a talk about my understanding on how knowledge graphs and large language models go together.

After the conference, I did a recording of the talk, giving it one more time, in order to improve the quality of the recording. The talk had gotten more than 10,000 views on YouTube so far, which, for me, is totally astonishing.

I forgot to link it here, so here we go finally:

• The Future of Knowledge Graphs in a World of Large Language Models

Hot Skull

I watched Hot Skull on Netflix, a Turkish Science Fiction dystopic series. I knew there was only one season, and no further seasons were planned, so I was expecting that the story would be resolved - but alas, I was wrong. And the book the show is based on is only available in Turkish, so I wouldn't know of a way to figure out how the story end.

The premise is that there is a "semantic virus", a disease that makes people 'jabber', to talk without meaning (but syntactically correct), and to be unable to convey or process any meaning anymore (not through words, and very limited through acts). They seem also to loose the ability to participate in most parts of society, but they still take care of eating, notice wounds or if their loved ones are in distress, etc. Jabbering is contagious, if you hear someone jabber, you start jabbering as well, jabberers cannot stop talking, and it quickly became a global pandemic. So they are somehow zombieish, but not entirely, raising questions about them still being human, their rights, etc. The hero of the story is a linguist.

Unfortunately, the story revolves around the (global? national?) institution that tries to bring the pandemic under control, and which has taken over a lot of power (which echoes some of the conspiracy theories of the COVID pandemic), and the fact that this institution is not interested in finding a cure (because going back to the former world would require them to give back the power they gained). The world has slid into economic chaos, e.g. getting chocolate becomes really hard, there seems to be only little international cooperation and transportation going on, but there seems to be enough food (at least in Istanbul, where the story is located). Information about what happened in the rest of the world is rare, but everyone seems affected.

I really enjoyed the very few and rare moments where they explored the semantic virus and what it does to people. Some of them are heart-wrenching, some of them are interesting, and in the end we get indications that there is a yet unknown mystery surrounding the disease. I hope the book at least resolves that, as we will probably never learn how the Netflix show was meant to end. The dystopic parts about a failing society, the whole plot about an "organization taking over the world and secretly fighting a cure", and the resistance to that organization, is tired, not particularly well told, standard dystopic fare.

The story is told very slowly and meanders leisurely. I really like the 'turkishness' shining through in the production: Turkish names, characters eating simit, drinking raki, Istanbul as a (underutilized) background, the respect for elders, this is all very well meshed into the sci-fi story.

No clear recommendation to watch, mostly because the story is unfinished, and there is simply not enough payoff for the lengthy and slow eight episodes. I was curious about the premise, and still would like to know how the story ends, what the authors intended, but it is frustrating that I might never learn.

• Hot Skull on Netflix

The right to work

I've been a friend of Universal Basic Income for thirty years, but in the last twenty years, I have growing reservations about it, and many questions. This article about an experiment with a right to work was the first text in a while I read on it that substantially impacted my thinking on this (text is in German). I recommend reading it.

Work is not just a source of money, but for many also a source of meaning, pride, structure, motivation, social connections. Having voluntary access to work seems to be one major component that is necessary on a societal level, in addition to a universal basic income that allows that everyone can live in dignity. Note: I think work should be widely construed. If someone has something that fills that need, that's work. Raising children, taking care of a garden, writing a book, refining piano skills, creating art, taking care of others, taking care of yourself, all these easily count as work in my book.

I wish we were willing and able to experiment with different ways of structuring society as we are willing and able to experiment with technology. We deployed the Internet to the world without worrying about the long term consequences, but we're cautious about giving everyone enough money to not be hungry. That's just broken. I was always disappointed about the fact that sociology and politics as studied and taught by academia were mostly descriptive and not constructive endeavors.

• https://perspective-daily.de/article/2567-was-passiert-wenn-dir-der-staat-einen-job-garantiert/BDn2v8pM

Wikidata - The Making of

Markus Krötzsch, Lydia Pintscher and I wrote a paper on the history of Wikidata. We published it in the History of the Web track at The Web Conference 2023 in Austin, Texas (what used to be called the WWW conference). This spun out of the Ten years of Wikidata post I published here.

The open access paper is available here as HTML: dl.acm.org/doi/fullHtml/10.1145/3543873.3585579

Here as a PDF: dl.acm.org/doi/pdf/10.1145/3543873.3585579

Here on Wikisource, thanks to Mike Peel for reformatting: Wikisource: Wikidata - The Making Of

Here is a YouTube trailer for the talk: youtu.be/YxWs_BS31QE

And here is the full talk (recreated) on YouTube: youtu.be/P3-nklyrDx4

20 years of editing Wikipedia

Today it's been exactly twenty years since I made my first edit to Wikipedia. It was about the island of Brač, in the German Wikipedia.

Here is the version of the article I have created: Brač (as of May 11, 2003)

How much April 1st?

In my previous post, I was stating that I might miss April 1st entirely this year, and not as a joke, but quite literally. Here I am chronicling how that worked out. We were flying flight NZ7 from San Francisco to Auckland, starting on March 31st and landing on April 2nd, and here we look into far too much detail to see how much time the plane spent in April 1st during that 12 hours 46 minutes flight. There’s a map below to roughly follow the trip.

5:45 UTC / 22:45 31/3 local time / 37.62° N, 122.38° W / PDT / UTC-7

The flight started with taxiing for more than half an hour. We left the gate at 22:14 PDT time (doesn’t bode well), and liftoff was at 22:45 PDT.. So we had only about an hour of March left at local time. We were soon over the Pacific Ocean, as we would stay for basically the whole flight. Our starting point still had 1 hour 15 minutes left of March 31st, whereas our destination at this time was at 18:45 NZDT on April 1st, so still had 5 hours 15 minutes to go until April 2nd. Amusingly this would also be the night New Zealand switches from daylight saving time (NZDT) to standard time (NZST). Not the other way around, because the seasons are opposite in the southern hemisphere.

6:00 UTC / 23:00 31/3 local time / 37° N, 124° W / PDT / UTC-7

We are still well in the PDT / UTC-7 time zone, which, in general, goes to 127.5° W, so the local time is 23:00 PDT. We keep flying southwest.

6:27 UTC / 22:27 31/3 local time? / 34.7° N, 127.5° W / AKDT? / UTC-8?

About half an hour later, we reach the time zone border, moving out of PDT to AKDT, Alaska Daylight Time, but since Alaska is far away it is unclear whether daylight saving applies here. Also, at this point we are 200 miles (320 km) out on the water, and thus well out of the territorial waters of the US, which go for 12 nautical miles (that is, 14 miles or 22 km), so maybe the daylight saving time in Alaska does not apply and we are in international waters? One way or the other, we moved back in local time: it is suddenly either 22:27pm AKDT or even 21:27 UTC-9, depending on whether daylight saving time applies or not. For now, April 1 was pushed further back.

7:00 UTC / 23:00 31/3 local time? / 31.8° N, 131.3 W / AKDT? / UTC-8?

Half an hour later and midnight has reached San Francisco, and April 1st has started there. We were more than 600 miles or 1000 kilometers away from San Francisco, and in local time either at 23:00 AKDT or 22:00 UTC-9. We are still in March, and from here all the way to the Equator and then some, UTC-9 stretched to 142.5° W. We are continuing southwest.

8:00 UTC / 23:00 31/3 local time / 25.2° N, 136.8° W / GAMT / UTC-9

We are halfway between Hawaii and California. If we are indeed in AKDT, it would be midnight - but given that we are so far south, far closer to Hawaii, which does not have daylight saving time, and deep in international waters anyway, it is quite safe to assume that we really are in UTC-9. So local time is 23:00 UTC-9.

9:00 UTC / 0:00 4/1 local time / 17.7° N, 140.9° W / GAMT / UTC-9

There is no denying it, we are still more than a degree away from the safety of UTC-10, the Hawaiian time zone. It is midnight in our local time zone. We are in April 1st. Our plan has failed. But how long would we stay here?

9:32 UTC / 23:32 31/3 local time / 13.8° N, 142.5° W / HST / UTC-10

We have been in April 1st for 32 minutes. Now we cross from UTC-9 to UTC-10. We jump back from April to March, and it is now 23:32 local time. The 45 minutes of delayed take-off would have easily covered for this half hour of April 1st so far. The next goal is to move from UTC-10, but the border of UTC-10 is a bit irregular between Hawaii, Kiribati, and French Polynesia, looking like a hammerhead. In 1994, Kiribati pushed the Line Islands a day forward, in order to be able to claim to be the first ones into the new millennium.

10:00 UTC / 0:00 4/1 local time / 10° N, 144° W / HST / UTC-10

We are pretty deep in HST / UTC-10. It is again midnight local time, and again April 1st starts. How long will we stay there now? For the next two hours, the world will be in three different dates: in UTC-11, for example American Samoa, it is still March 31st. Here in UTC-10 it is April 1st, as it is in most of the world, from New Zealand to California, from Japan to Chile. But in UTC+14, on the Line Islands, 900 miles southwest, it is already April 2nd.

11:00 UTC / 1:00 4/1 local time / 3° N, 148° W / HST / UTC-10

We are somewhere east of the Line Islands. It is now midnight in New Zealand and April 1st has ended there. Even without the delayed start, we would now be solidly in April 1st local time.

11:24 UTC / 1:24 4/1 local time / 0° N, 150° W / HST / UTC-10

We just crossed the equator.

12:00 UTC / 2:00 4/2 local time / 3.7° S, 152.3° W / LINT / UTC+14

The international date line in this region does not go directly north-south, but goes one an angle, so without further calculation it is difficult to exactly say when we crossed the international date line, but it would be very close to this time. So we just went from 2am local time in HST / UTC-10 on April 1st to 2am local time in LINT / UTC+14 on April 2nd! This time, we have been in April 1st for a full two hours.

(Not for the first time, I wish Wikifunctions would already exist. I am pretty sure that taking a geocoordinate and returning the respective timezone will be a function that will be available there. There are a number of APIs out there, but none of which seem to provide a Web interface, and they all seem to require a key.)

12:44 UTC / 2:44 4/1 local time / 8° S, 156° W / HST / UTC-10

We just crossed the international date line again! Back from Line Island Time we move to French Polynesia, back from UTC+14 to UTC-10 again - which means it switches from 2:44 on April 2nd back to 2:44 on April 1st! For the third time, we go to April 1st - but for the first time we don’t enter it from March 31st, but from April 2nd! We just traveled back in time by a full day.

13:00 UTC / 3:00 4/1 local time / 9.6° S, 157.5° W / HST / UTC-10

We are passing between the Cook Islands and French Polynesia. In New Zealand, daylight saving time ends, and it switches from 3:00 local time in NZDT / UTC+13 to 2:00 local time in NZST / UTC+12. While we keep flying through the time zones, New Zealand declares itself to a different time zone.

14:00 UTC / 4:00 4/1 local time / 15.6° S, 164.5° W / HST / UTC-10

We are now “close” to the Cook Islands, which are associated with New Zealand. Unlike New Zealand, the Cook Islands do not observe daylight saving time, so at least one thing we don’t have to worry about. I find it surprising that the Cook Islands are not in UTC+14 but in UTC-10, considering they are in association with New Zealand. On the other side, making that flip would mean they would literally lose a day. Hmm. That could be one way to avoid an April 1st!

14:27 UTC / 3:27 4/1 local time / 18° S, 167° W / SST / UTC-11

We move from UTC-10 to UTC-11, from 4:27 back to 3:27am, from Cook Island Time to Samoa Standard Time. Which, by the way, is not the time zone in the independent state of Samoa, as they switched to UTC+13 in 2011. Also, all the maps on the UTC articles in Wikipedia (e.g. UTC-12) are out of date, because their maps are from 2008, not reflecting the change of Samoa.

15:00 UTC / 4:00 4/1 local time / 21.3° S, 170.3° W / SST / UTC-11

We are south of Niue and east of Tonga, still east of the international date line, in UTC-11. It is 4am local time (again, just as it was an hour ago). We will not make it to UTC-12, because there is no UTC-12 on these latitudes. The interesting thing about UTC-12 is that, even though no one lives in it, it is relevant for academics all around the world as it is the latest time zone, also called Anywhere-on-Earth, and thus relevant for paper submission deadlines.

15:23 UTC / 3:23 4/2 local time / 23.5° S, 172.5° W / NZST / UTC+12

We crossed the international date line again, for the third and final time for this trip! Which means we move from 4:23 am on April 1st local time in Samoa Standard Time to 3:23 am on April 2nd local time in NZST (New Zealand Standard Time). We have now reached our destination time zone.

16:34 UTC / 4:34 4/2 local time / 30° S, 180° W / NSZT / UTC+12

We just crossed from the Western into the Eastern Hemisphere. We are about halfway between New Zealand and Fiji.

17:54 UTC / 5:52 4/2 local time / 37° S, 174.8°W / NZST / UTC+12

We arrived in Auckland. It is 5:54 in the morning, on April 2nd. Back in San Francisco, it is 10:54 in the morning, on April 1st.

Green is March 31st, Red April 1st, Blue April 2nd, local times during the flight.

Basemap https://commons.wikimedia.org/wiki/File:Standard_time_zones_of_the_world_%282012%29_-_Pacific_Centered.svg CC-BY-SA by TimeZonesBoy, based on PD by CIA World Fact Book

Postscript

Altogether, there was not one April 1st, but three stretches of April 1st: first, for 32 minutes before returning to March 31st, then for 2 hours again, then we switched to April 2nd for 44 minutes and returned to April 1st for a final 2 hours and 39 minutes. If I understand it correctly, and I might well not, as thinking about this causes a knot in my brain, the first stretch would have been avoidable with a timely start, the second could have been much shorter, but the third one would only be avoidable with a different and longer flight route, in order to stay West of the international time line, going south around Samoa.

In total, we spent 5 hours and 11 minutes in April 1st, in three separate stretches. Unless Alaskan daylight saving counts in the Northern Pacific, in which case it would be an hour more.

So, I might not have skipped April 1st entirely this year, but me and the other folks on the plane might well have had the shortest April 1st of anyone on the planet this year.

I totally geeked out on this essay. If you find errors, I would really appreciate corrections. Either in Mastodon, mas.to/@vrandecic, or on Twitter, @vrandecic. Email is the last resort, vrandecic@gmail.com (The map though is just a quick sketch)

One thing I was reminded of is, as Douglas Adams correctly stated, that writing about time travel really messes up your grammar.

The source for the flight data is here:

• https://flightaware.com/live/flight/ANZ7/history/20230401/0510Z/KSFO/NZAA
• https://flightaware.com/live/flight/ANZ7/history/20230401/0510Z/KSFO/NZAA/tracklog

No April Fool's day

This year, I am going to skip April Fool's day.

I am not being glib, but quite literal.

We are taking flight NZ7 starting on the evening of March 31 in San Francisco, flying over the Pacific Ocean, and will arrive on April 2 in the early morning in Auckland, New Zealand.

Even if one actually follows the flight route and overlays it over the timezone map, it looks very much like we are not going to spend more than a few dozen minutes, or at most a few hours, in April 1, if all goes according to plan.

Looking forward to it!

Here's the flight data of a previous NZ7 flight, from Sunday: https://flightaware.com/live/flight/ANZ7/history/20230327/0410Z/KSFO/NZAA/tracklog

Here are the timezones (but it's Northern winter time). Would be nice to overlay the two maps:

Where's Wikifunctions when it's needed?

The question seems to be twofold: how often do we cross the dateline, and how close are we to local time midnight while crossing the dateline. For a perfect date miss one would need to cross the dateline exactly once, at a 24 hour difference, as close as possible to local midnight.

Gordon Moore (1929-2023)

Gordon Moore was not only the co-founder of Intel and the namesake for Moore's law, the claim that every two years the number of components on a chip would double, he was also, together with his wife Betty Moore, one of the generous donors who made Wikidata possible. Gordon and Betty Moore were known for their philanthropy, and it is easy to find their names engraved at the universities, zoos, museums, and galleries in the Bay Area. Gordon Moore died today at the age of 94.

Thank you for enabling us to make Wikidata happen.

Last Unicorn dreamcast

One thing my sister and I were doing from time to time was to think, if the Last Unicorn was remade as a live action movie, who would we cast in the different roles? It is sad to see how many of our dreamcast have since died: our favorite Prince Lir was Heath Ledger, and King Haggard, unsurprisingly, Christopher Lee.

Since I was reading the book with Little One, and now watched the movie again (for the 120th time or so), I was again going through my current dreamcast. Here we go.

• Lady Amalthea - Anna Taylor-Joy
• Schmendrick - Zach Braff, Donald Glover
• Molly Grue - Mia Farrow
• Prince Lir - Owen Wilson, no, getting too old; Liam Hemsworth? Chloe Moretz would be an interesting choice
• King Haggard - Anthony Hopkins, Jack Nicholson

Since it is en vogue, I also asked Bard and ChatGPT. Here's Bard:

• Jeff Bridges as Schmendrick the Magician
• Mia Farrow as Molly Grue
• Angela Lansbury as the Unicorn
• Daryl Hannah as Filidor
• Jeff Goldblum as Schmendrick's sidekick, Bungle
• Peter Dinklage as the Red Bull
• Uma Thurman as Mommy Fortuna
• Alan Rickman as King Haggard

OK, Alan Rickman is a great choice, but unfortunately dead. Uma Thurman as Mommy Fortuna is weird. Peter Dinklage as the Red Bull... why does the Red Bull need to be cast at all? Who are Bungle and Filidor? Angela Lansbury as the Unicorn / Lady Amalthea is... not the right choice. Also dead. Mia Farrow and Jeff Bridges are too obvious choices given their roles in the cast of the animation movie, also Angela Lansbury is from the original cast. I would give Bard a D for that answer.

ChatGPT says:

• Unicorn - Saoirse Ronan or Emma Watson
• Schmendrick - Timothee Chalamet or Eddie Redmayne
• Molly Grue - Meryl Streep or Helen Mirren
• King Haggard - Ian McKellen or Christopher Lee (if he were still alive)
• Prince Lir - Tom Holland or Ansel Elgort
• Mommy Fortuna - Tilda Swinton or Cate Blanchett

Not even close to my choice, but heck, those are good choices. Molly Grue and Mommy Fortuna seem both a bit over-cast. Prince Lir and Schmendrick are pretty brilliant choices. I am not particularly impressed by Emma Watson for Lady Amalthea, I could see Saoirse Ronan work.

I'd give a B+ to ChatGPT.

I feel like ChatGPT seems to go for actors and actresses that are popular with the crowd who likes The Last Unicorn? Not the worst choice.

I followed up with Bard to see who Bungle and Filidor are, because they don't appear neither in the book nor in the movie, if I remember correctly. So, "Bungle is a red unicorn who is Schmendrick's sidekick in the novel The Last Unicorn. He is a clumsy and incompetent unicorn, but he is also a loyal and brave friend. Bungle is played by Jeff Goldblum in the 1982 animated film adaptation of the novel." And "Filidor is a bard in the novel The Last Unicorn. He is a wandering minstrel who travels the land singing songs and telling stories. Filidor is a wise and kind-hearted man, and he is always willing to help those in need. He is played by Daryl Hannah in the 1982 animated film adaptation of the novel." That's entirely a fabrication.

Running out of text

Many of the available text corpora have by now been used for training language models. One untapped corpus so far have been our private messages and emails.

How fortunate that none of the companies that train large language models have access to humongous logs of private chats and emails, often larger than any other corpus for many languages.

How fortunate that those who do have well working ethic boards established, who would make sure that such requests are evaluated.

How fortunate that we have laws in place to protect our privacy.

How fortunate that when new models are published also the corpora are being published on which the models are being trained.

What? Your telling me, "Open"AI is keeping the training corpus for GPT-4 secret? The company closely associated with Microsoft, who own Skype, Office, Hotmail? The same Microsoft who just fired an ethics team? Why would all that be worrisome?

P.S.: To make it clear: I don't think that OpenAI has used private chat logs and emails as training data for GPT-4. But by not disclosing their corpora, they might be checking if they can get away with not being transparent, so that maybe next time they might do it. No one would know, right? And no one would stop them. And hey, if it improves the metrics...

Oscar winning families

Yesterday, when Jamie Lee Curtis won her Academy Award, I learned that both her parents were also nominated for Academy Awards. Which lead to the question: who else?

I asked Wikidata, which lists four others:

• Laura Dern
• Liza Minnelli
• Nora Ephron
• Sean Astin

Only one of them belongs to the even more exclusive club of people who won an Academy Award, and where both parents also did: Liza Minnelli, daughter of Vincente Minelli and Judy Garland.

Wikidata query

Also interesting: List of Academy Award-winning families