Event JSON
{
"id": "85da7ae8dbd5cd643bde3935aa50c11078d3f1b00dd13d3aa936fe10cbfe6851",
"pubkey": "e653eb60b2db5edf906d354c2825bf00a80dfab1b1766cd97805155e8fcc0db3",
"created_at": 1706801605,
"kind": 1,
"tags": [
[
"p",
"4ebb1885240ebc43fff7e4ff71a4f4a1b75f4e296809b61932f10de3e34c026b",
"wss://relay.mostr.pub"
],
[
"p",
"8b0be93ed69c30e9a68159fd384fd8308ce4bbf16c39e840e0803dcb6c08720e",
"wss://relay.mostr.pub"
],
[
"e",
"1d583ad871bac0381db9c7a9a31b5bbbf678cdddcdaaa2cbed4091dd618a0c63",
"wss://relay.mostr.pub",
"reply"
],
[
"proxy",
"https://phpc.social/users/ramsey/statuses/111856950023843683",
"activitypub"
]
],
"content": "nostr:npub1f6a33pfyp67y8llhunlhrf855xm47n3fdqymvxfj7yx78c6vqf4scxpnql Not sure whether you saw my question here, but I’m still very curious and perplexed by this. If an LLM doesn’t store the full text of materials it was trained on, then how does it produce output like what I’m seeing?",
"sig": "888e86a033fdb82303f18d1ad7d096dbda125fe68fa245a2253432dc030470ad60a560a5d1f9dff611372b308d9292bbd66ba599b533acf14eee6ba89935b5a5"
}
