It wouldn't be just friends, but that's how I phrased it there. I called it "supporters" in these 280 characters:
"Some people just get along. They are compatible. They mesh.
I think it's possible to predict whether any two people will hit it off, and to create groups composed entirely of highly compatible, highly synergistic people.
What will happen when EVERYONE has a THOUSAND SUPPORTERS?"
And it wouldn't just be friends or supporters, either:
"Just as the system can find those who are your mirror reflection by minimizing adjacency distances, so it can find your very antithesis by maximizing them, as well as anything in-between."
I think after implementation, adoption is inevitable since the value is truly insane, better than anything else online (unless you're antisocial, etc.)
Okay. The problem is something like "social knowing doesn't naturally scale" but the entirety of the problem is how to make it do so effectively without ill side effect. I'm curious if you've gone the further step on how the system may simply iterate the current state. What ends do you seek? Most important... What have you done to start solving this problem?
"Some people just get along. They are compatible. They mesh.
I think it's possible to predict whether any two people will hit it off, and to create groups composed entirely of highly compatible, highly synergistic people.
What will happen when EVERYONE has a THOUSAND SUPPORTERS?"
And it wouldn't just be friends or supporters, either:
"Just as the system can find those who are your mirror reflection by minimizing adjacency distances, so it can find your very antithesis by maximizing them, as well as anything in-between."
That's from this post which explores implementation: https://zeroprecedent.substack.com/p/a-technique-for-generat...
I think after implementation, adoption is inevitable since the value is truly insane, better than anything else online (unless you're antisocial, etc.)