The hand-crank renaissance

Hey ๐Ÿ‘‹ โ€” today's got a real "how much should things cost us" thread running through it: an art installation that makes you sweat for your AI image, a language nine years in the making, and a professor who just learned the hard way what happens when a take-home exam meets a language model. Let's get into it.

THE EFFORT โ€“ Restoring friction in image creation

THE EFFORT โ€“ Restoring friction in image creation

Jakub Koลบniewski's installation wires a hand-crank generator to a Raspberry Pi running local Stable Diffusion, so producing a single image can cost you up to ten minutes of honest physical labor. It's a blunt, clever way to reintroduce the friction that AI tools are so busy removing, and it turns "prompt and wait" into "prompt and sweat." The piece isn't anti-AI so much as curious about what gets lost when creation stops costing us anything at all.

"Would machines taking away most of the effort also take away the joy of creative struggle?" โ€” Jakub Koลบniewski

NoiseLang: Where N = 5 is a Dirac delta

NoiseLang: Where N = 5 is a Dirac delta

Speaking of effort โ€” this one's been simmering for nine years. NoiseLang is a side-project language built on the idea that every value is secretly a probability distribution, with ordinary constants just Dirac deltas in disguise. Write out something like a dice sum or the birthday paradox and it hands you back simulation-based estimates, which makes uncertainty feel less like an edge case and more like the default state of numbers (via Lobsters discussion).

Why you should still learn to code

Val Town founder Steve Krouse makes the case that coding's value was never really about job prospects โ€” it's about the thinking it teaches, echoing Seymour Papert's old Mathland/LOGO philosophy of code as a medium for building intuition. In an era where AI can write the code for you, he argues that's exactly why learning to write it yourself, as a form of expression alongside writing or music, matters more.

A Brown University professor suspected his class used AI to cheat after a take-home midterm averaged 96%, prompting an in-person final, which averaged 48.6%

That argument gets a blunt real-world stress test here: a Brown professor grew suspicious when a take-home midterm averaged a suspiciously tidy 96%, so he switched to an in-person final โ€” average score, 48.6% (unverified, source page unreachable). Whatever the exact numbers, the gap tells its own story about what happens when the "effort" of learning gets outsourced entirely.

Is life just different?

Is life just different?

A change of pace to close out: Quanta digs into "biological agency," the contested idea that living things actually set and pursue their own goals, and asks whether that framing tells us anything real about the line between life and inert matter. It's the kind of question that sounds simple until you try to define "goal" without smuggling in a mind.

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