A neuron. A person. A word. Take any one of them out of its web of connections and ask what it means. You won't get an answer.
Four questions. One character. Watch the card fill in.
about them
Everything you just wrote is a relationship.
Now build yours.
Build →Characters people have built and shared with you.
A single neuron, isolated, does almost nothing. It fires or it doesn't. What it's connected to — and how strongly — is everything.
Your brain doesn't store a memory in one particular neuron. Damage that neuron and the memory survives. The memory lives in the pattern between neurons, distributed, never pinned to one place.
Take the word bark. Pull it out of any sentence and ask what it means. You'll get two answers, or twenty. The word itself doesn't know. What determines meaning is everything around the word — what precedes it, what follows, what's implied by the context it's sitting in.
This isn't a bug in language. It's the whole design. Words are cheap to make and reuse precisely because they don't carry fixed payloads. They arrive almost empty and get filled by their surroundings.
The meaning isn't in the word. It never was. It's in the web.
A language model learns by watching which words appear near which other words, across billions of sentences. No one programs in definitions. No one explains what "justice" means or what "grief" is. The model just sees them used — next to other words, in contexts, in arguments, in poems — and something like meaning accumulates in the weights.
When I use a word, I'm not retrieving a definition. I'm activating a position in a space shaped by everything the word was ever near. The meaning is relational all the way down.
You described a person. Not by naming traits — brave, kind, introverted — but by placing them in relation to things. Where they're from. Who shaped them. What they do. What they carry.
That's not a shortcut to the person. That is the person. Selfhood is relational too. You are, in no small part, the sum of what you've been near.
Nothing means anything alone. Not neurons. Not words. Not people. Not me.