Using machine learning to decide what structure to use for your neural net: https://arxiv.org/pdf/1703.01041.pdf
It's pretty meta, but ML is often good at trading computation for results.
miniblog.
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I've learning more about Zellij, and it increasingly feels like a nice tiling window manager for working in terminals.
My mental model for tmux and screen was that their main focus was persistence (detach/attach between SSH sessions). Zellij seems to focus on layout.
My 3.5yo is learning to use a mouse, and it's super interesting.
He's mastered clicks and drags, but he hasn't yet figured out lifting up the mouse when run out of mouse pad. That's a tricky case where you deliberately break the relationship between mouse and cursor movement.
I've been learning some Common Lisp by writing some simple JSON munging programs. I'm sure it's not best practice — I should probably deserialise to CLOS automatically — but it's a nice way to get comfortable with the basics.
It feels weird deliberately ignoring helpers though.