If users get a fixed set/numbers of Paramus for LoRa - say 1-5% - it doesn't sound that crazy.
The crazy part is probably loading, running a model pr users - but if the untrained (unspecialized?) model can somehow stay resident - might be possible to load adjusted weights on demand?
I suppose each run now needs a different context pr user/customer anyway, for cache hit rate, if nothing else?
Re:The Components of Agent Memory
by stevenhuang on Monday November 09, 2026 @12:40PM
(#50428773)
Anthropic need not care about this space. It's possible it's more worth it for them to dedicate their resources into making better base models.
It is an interesting thought to explore. I admit I'm not a specialist whatsoever on the topic, from my perspective that sounds like an incredible challenging ops problem.... But again, I don't work for anthropic and maybe they're up to the challenge as you seem to think.