Interesting misconception that Dan flagged today - people think that we are (or could be) using LLMs for spam detection. 

With the way LLMs work today, that's like using a hammer to cut your fingernails. LLMs are slow, expensive and don't really have a deep understanding of what spam is in the context of Farcaster. 

We use a random-forest decision tree that @akshaan designed, and feed it a bunch of signals using embeddings, user actions and graph data.

Technowatermelon. Elder Millenial. Building Farcaster. 

nf.td/varun

LLMs not suited for spam detection; random-forest decision tree better. Use embeddings, user actions, and graph data for accuracy