[ot][spam][crazy][corporate[ makingeasy useful tools/behabior/agi?

Undescribed Horrific Abuse, One Victim & Survivor of Many gmkarl at gmail.com
Fri Feb 10 16:44:50 PST 2023


relevance is super nice for me to see in front of me and puzzle about
because i have severe issues with it cognitively.

some days ago i made a summary of steps of connecting relevance that
made helpful analogue part between cognition and prompts

another idea is an equivalence between trained models and prompted
models: when you run a relevance strategy by prompting pretrained
models, this can of course be transformed into a larger architecture
where each prompt is a component of a model, and the same could be
transformed back. holding this equivalence helps show different
relevence structures and things like parallelism, order, and feedback.

for retrieval a basic idea is to run over (or process in parallel)
likely candidates looking for relevant summaries, then to run over
them again with the new information is context to pick up anything
that wasn’t clearly relevant before, until nothing new is added.
additionally each prompt or node could include reports on how to move
forward: whether or not to look again for example (misplaced some of
these ideas maybe near the top of this paragraph or end of the
previous one)

for storing memories, a system could go over an existing store and
judge if each part is a good place for new summarized information, or
alternatively judge that a new part should be made, and then use
normal retrieval.

in general i think it would be very nice to make a general relevance
library, agnostic to strategy or whether it uses prompted pretrained
models or model training or some other approach. :)


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