@shannholmberg: how gbrain's dream cycle works most knowledge bases degrade as you dump more things in, they go stale, duplicates pile …

how gbrain’s dream cycle works

most knowledge bases degrade as you dump more things in, they go stale, duplicates pile up, citations break, and after a week or two you stop using it

gbrain’s fix for that is the dream cycle, a 24/7 loop that works on the brain on its own, mostly overnight

every dream cycle it:

ingests the day, the meetings, emails, notes and calls, and files them into the brain enriches every person and company it saw, adding new details so their pages stay current consolidates the day’s conversations, turning raw chat into clean, synthesized pages merges duplicate pages, spotting two pages about the same thing and combining them into one fixes broken citations, repairing links and sources that no longer point anywhere ranks each page by importance, so the ones you reference most surface first in a search flags pages that contradict each other, so you catch the conflict instead of trusting the wrong one preps tomorrow, lining up the next day’s tasks and context

Shann³ (@shannholmberg): how embeddings make Gbrain smarter than a plain LLM wiki

a plain LLM wiki finds pages by matching the words you typed. if the wording doesn’t match, it misses the right page. gbrain adds embedding models, and that’s the real upgrade

think of it as a map of meaning

an embedding