3-Item Status

• Current Location: Milwaukee, WI

• Reading: Babel by RF Kuang

• Listening: Limelight by Tune-Yards

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Note

• I’ll be visiting family in Seattle next week, so I’m skipping next week’s newsletter, and will talk to you again the following week :)

New Work

• This week’s Let’s Know Things is about Ukraine and Iran

• This week’s Brain Lenses essay is about Gender Conformity & the pod is about Mental Subtraction

Directional Play

Hobbies are great because you don’t have to invest too much of yourself in them, but you absolutely can if you like, and if you do, you tend to get more out of them.

You can pick up a hobby—say coloring in coloring books or creating monsters with Legos or playing disc golf or performing interpretive dance—and you don’t have to convince a single person to give you money in exchange for your brick-hydra or your pubescence-inspired tap-dance. You can just do it, and keep doing it, and no one has to like what you do or how you do it but you.

I like to think of hobbies as directional play, as while hobbies tend to be fun (or otherwise enjoyable), there’s also room for growth and development. You can build really simplistic Lego monsters with a few dozen pieces, or you can engineer staggeringly large and complex grotesques. You can have a blast at either end of that spectrum, but you can also choose to progress from one side to the other, and you can stop anywhere you like along the way (and if you find a spot you especially like, you can stay there forever without negative consequence).

That directionality is nice because growth and accomplishment can feel good and be fulfilling.

But ‘play’ is also important, here, because most of us don’t play enough: we don’t just mess around, try and do things just for their own sake. Not as adults, anyway. And it’s liberating to have something in our lives that we don’t have to be good at, and in which we can just fumble around in whichever manner feels right at any given moment.

Hobbies can also, sometimes, evolve into other things, including professions.

There’s nothing at all wrong with this when it happens, but most of us will be best served by periodically reminding ourselves that not everything needs to be monetized, and not everything needs to be purposeful (in the sense of goosing some kind of growth metric, or helping us develop in a quantifiable way).

It’s okay just to do and try things, and to have hobbies that help us pass the time, give us an excuse to be around others, and that stoke and sate our curiosity.

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Interesting Links

• An Unstoppable Mushroom Is Tearing Through North American Forests

• Everything I Know About Self-Publishing

• How to Network When You’re Socially Anxious

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What Else

I am exhausted.

It’s a lot of work, getting ready for these Seattle trips. But these past few days I’ve also been knocked flat by whatever this cold/flu/covid thing is that’s going around right now. I thought I dodged it, but it finally got me.

So I’ve been aggressively resting in order to get over it (or bare minimum no longer contagious) by the time I leave for Seattle. But man, not fun.

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Western AI models “fail spectacularly” in farms and forests abroad.

All modern computer code has basically the same purpose: it allows us to write instructions that are intelligible to us humans, but in such a way that our intentions are legible to the machines, which means those intentions can be cleanly translated into binary—the long sequences of 1s and 0s that are these contraptions’ native tongue.

Assembly languages are very low-level and close to that binary in the sense that what the human writes doesn’t require too much translation to be converted.

Other languages, like Python, C++, or Java are higher-level and thus further from binary, but they’re also easier for humans to read and work with.

In this context, ‘higher-level’ basically means ‘more layers of abstraction.’ You start at the foundation (with binary) then go up a level, to something like assembly. Then you go up and up and up, adding more abstraction, hiding more of the computer-optimized complexity and replacing it with human-optimized intelligibility.

More abstraction generally means more people can create and wield digital tools, because you no longer need a doctorate in order to write “Hello, World!” on a computer.

As you move further up to more abstracted languages, then, you make these tools more accessible to more people, and allow more humans to use digital leverage in more intuitive ways.

As a trade-off, though, you lose some of the technical details and peculiarities that folks working in assembly or binary might notice and be capable of fiddling with at an extremely granular level. Your options become in some ways more limited and finite, even as your other capabilities grow.

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