Wooden skyscrapers, Chernobyl Stalkers, and “The Nine Billion Names of God” in Javascript

Inside the Chernobyl Exclusion Zone, by Aram Balakjian

It’s Monday, which means you now have to pretend to work.

So, pour a coffee and peruse this week’s “Linkfest”, my collection of the finest procrastination material I could hunt down; I am knocking myself out for you fine people!

Forthwith …

1) ☢️ “Chernobyl stalkers” are breaking into the contaminated zone to explore

Over at The Calvert Journal, Aram Balakjian writes a fascinating story where he accompanies “Chernobyl Stalkers”, a subculture of people who illegally hike deep into the Chernobyl Exclusion Zone. The photos are epic, and he lands on this observation:

The idea that Ukrainians are drawn to stalking as a form of catharsis is logical. By occupying the Zone, they redefine a wound in the national psyche. It becomes at once a museum, a nature reserve, and a haven from the turbulent country outside. As the nation struggles with chronic uncertainty, life in the Zone remains the very antithesis of instability. Even as an outsider, these motivations remain pertinent. Stalking delivers an insight into a historical event of chilling relevance in a way that an official tour cannot. Meanwhile, the sheer physical rewards of risk and survival combine, in a fashion, to deliver an unlikely meditative escape.

2) 🚎 Why our preferred commute time is 16 minutes

“The reading room”, by susanjanegolding

In my reporting on the pandemic, I’ve consistently found that about 1/3 of the people I talk to miss their commute. This piece in the The Atlantic sketches out some of the reasons why — such as the way it lets us switch from one role (a at home: parent, child, partner, etc) to another (sales manager, assistant, chef), in what’s known as “boundary theory”. So we need a commute — but we don’t want to waste too much time, which means there’s a golden mean …

In a 2001 paper, two researchers at UC Davis attempted to divine the ideal commute time. They settled on 16 minutes. To be sure, this was a substantial shortening of the study participants’ actual commutes (which were half an hour, on average). But it was not zero. In fact, a few wished for a longer commute. Asked why, they ticked off their reasons — the feeling of control in one’s own car; the time to plan, to decompress, to make calls, to listen to audiobooks. Clearly, the researchers wrote, the commute had some “positive utility.”

3) 🇨🇦 Explaining Canadian “eh” at the Yale Grammatical Diversity Project

At the Yale Grammatical Diversity Project, the scholars write wonderful explainers on non-standard grammar in North America — i.e. the linguistic inventions that aren’t considered “proper” English, often because they’re done by poor, Black, or rural folks.

They have a great database here, where you can click on any term in the left-hand column and read their write-up of it — like “bin”, “tryna”, and “a-prefixing” (like “I’ve gone a-fishin’”) . Being Canadian, I was impressed at how thorough and accurate was their explanation of the many, many ways we Canadians use “eh”.

As they conclude, one key thing about “eh”, and which makes it particularly Canadian, is that it is designed to indicate you’re not totally confident what you’re saying, and encouraging your conversational partner to chime in …

Johnson (1976) argues that eh can only be used when the assumptions associated with the sentence to which it is being added are weak. In other words, eh “leaves the door open for a different point of view to be expressed” (Johnson 1976: 155), which is also true of standard English tags.

Thus, eh is incompatible with sentences that are based on a strong set of assumptions. For example, although eh is not syntactically incompatible with imperatives, the following sentence would never be uttered by an army sergeant commanding his troops:

“#Forward, march, eh!”

4) 💥 “The Nine Billion Names of God”, in Javascript

Remember the famous 1953 Clarke story, “The Nine Billion Names of God”? Some Tibetan monks had spent 300 years trying to write out all the nine billion possible names of God —by generating all possible words of no more than nine letters, written using their alphabet. Since it’s now 1953 they realize they can do it with a newfangled computer, so they hire a firm to build them one, and after a few weeks of running the job is almost done. (I won’t spoil the famous ending; the story’s here.)

The other day I chuckled realized you could do this very easily today: Tons of processing power, lots of languages! A quick Google and le voila: Here’s a“coding golf” competition to write the code as tersely as possible. Behold Python 2 …

from itertools import chain,product as p
a='ABCDEFGHIJKLM'
q={c*4 for c in a}
c=0
for n in chain(*(p(*([a]*l)) for l in range(1,10))):
n=''.join(n)
if not any(u in n for u in q):print n
c+=1
if c==10**9:break

Perl is even more compressed …

#!perl -l
/(.)\1{3}|[N-Z]/||print for A..1x9

And since Everything Will Eventually Be Done In Javascript, here’s a Javascript version so you can click “Start” and … see what happens.

5) 🦕 Why no dinosaur fossils are ever found in the Appalachian mountains

It’s because the Appalachian mountains are “incomprehensibly old”: They were formed 480 million years ago, which is 100 million years before animals walked on land. There weren’t even fish yet. So, as Alex explains in this epic twitter thread, the only fossils you’re going to find are things like trilobites and other truly ancient marine organisms …

So the vast majority of the fossils found in the Appalachian mountains are from when all life lived in the oceans. And that produces some strange results that may not even look like fossils to the untrained eye … The majority of the fossils in this region are so old that they come from limestone rocks, formed on the bottom of the ocean, when life as we know it hadn’t yet evolved. Some of these fossils date back as far as the Ordovician period, which is before FISH evolved.

Also: As Alex notes, the Appalachians are so old they extend to Europe. They formed during Pangea. “The Appalachian Mountains are older than the Atlantic Ocean.”

6) 🚪 They’re building high-rises out of wood

For decades now, mid-rise and high-rise buildings have been made mostly from steel, glass and concrete. Recently an old-school material is making a comeback: Wood. In Toronto, developers recently unveiled “V6 Leslieville”, a five-story building in which the frame is made entirely from wood (above).

It sounds nuts to make higher-rise buildings with wood, yes? But hey, welcome a better environmental future! This is “mass timber”, highly compressed and engineered wood that can bear much heavier loads than your standard 2x4. It has a far lower carbon footprint than concrete (which requires monstrous amounts of electricity), is easier to keep cool, can be grown locally, and reduces buiding costs — you can prefab the wood off-site and basically snap it together. It’s also resilient stuff: Wood bends instead of breaking, and is cheaper and easier to fix and maintain. Vancouver is planning a 40-storey tower made from mass timber:

“This is the first new way of building a skyscraper in a century,” said Green, whose firm recently finished Minneapolis’ T3 building, a seven-storey wood structure.

Also: Wood looks amazing. Concrete is ugly as sin, so you have to cover it with drywall, but with a wood high-rise you can leave the wood exposed and it stokes our biophilia, the pleasure we get from beholding nature.

7) 💡 Doing deep-learning by using light

Graphic by David Schneider

Deep learning is everywhere, but training a neural net is wildly energy-intensive; when OpenAI made a robot hand solve a Rubik’s cube it used 2.8 gigawatt-hours of electricity, by one estimate. But there’s a fascinating new way to do neural-network math that could wildly more efficient — using pulses of light.

Ryan Hamerly is building “photonic” processors; in this piece he gives a wonderfully crisp layperson’s explainer of how they work. The gist of it is that a) if you split up beams of light with mirrors, you can do linear algebra with them, and b) you save a ton of juice because you can do a bunch of many different calculations and read them only once.

The energy upshot:

Based on the technology that’s currently available for the various components (optical modulators, detectors, amplifiers, analog-to-digital converters), it’s reasonable to think that the energy efficiency of neural-network calculations could be made 1,000 times better than today’s electronic processors. Making more aggressive assumptions about emerging optical technology, that factor might be as large as a million.

8) 🏆 Final sudden-death round, if you’re *still* not ready to start working …

▶️ An argument for turning your website into a series of linked PDFs. ▶️ Why we need more utopian literature. ▶️ Ford files a patent for controlling your car with you mind. ▶️ Kids are using soft drinks to fake positive COVID tests; here’s how the chemistry works. ▶️ Facial-recognition misidentifies a Black teenager and she’s banned from a roller rink. ▶️ The “Eternal September” dynamics of the massive Facebook group devoted to the New York Times’ Spelling Bee daily puzzle. ▶️ Parents seem to talk to their kids less often if they’re close to payday and financially strapped. ▶️ An oral history of Black Twitter. Microsoft puts an Altair 8800 on the cloud. ▶️ A nuclear-powered game of Tetris. ▶️ Behold this extremely well-camouflaged owl in a tree.

Clive Thompson is a contributing writer for the New York Times Magazine, a columnist for Wired and Smithsonian magazines, and a regular contributor to Mother Jones. He’s the author of Coders: The Making of a New Tribe and the Remaking of the World, and Smarter Than You Think: How Technology is Changing our Minds for the Better. He’s @pomeranian99 on Twitter and Instagram.

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Clive Thompson

Clive Thompson

I write 3X a week on tech, science, culture — and how those collide. Writer at NYT mag/Wired; author, “Coders”. @pomeranian on Twitter, clive@clivethompson.net