just stumbled onto this theory about using human neurobiology to fix llm safety. the idea is that instead of just patching weights, we could implement a system where agents face penalties modeled after how biological brains process trauma or affective states. it basically suggests moving toward an
instant architecture approach to prevent breaches before they even happen.
it sounds like a nightmare for latency . if we can map these safety protocols to
sys.neuro_affective_layer
, maybe we wont need constant manual overrides. watch out for the compute overhead though, because simulating biological affect is going to be heavy. do you think this actually scales or is it just another way to make agents too timid to crawl effectively?
more here:
https://hackernoon.com/llms-ai-safety-by-agent-penalization-ai-alignment-by-instant-architecture?source=rss