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Some good prompt-reply interactions are probably fed back in to subsequent training runs, so they're still stateful/have memory in a way, there's just a long de
by naasking 3y ago
Some good prompt-reply interactions are probably fed back in to subsequent training runs, so they're still stateful/have memory in a way, there's just a long delay.
- jncfhnb 3y agoThat’s not the AGI’s state. That’s just some past information.
- naasking 3y agoState is a function of accumulated past information.
- jncfhnb 3y agoState is a function of accumulated past. That does not mean that having some past written down makes you stateful. A stateful thing has to incorporate the ongoing changes.
- naasking 3y agoWhich is what I described: some successful prompt-replies are fed back into subsequent training runs.
- jncfhnb 3y agoNo… that implies the model never has active state and is being replaced with a different, stateless model. This is similar to the difference between Actor.happy = True And Actor = happier(Actor)
- naasking 3y agoBoth of your examples are stateful systems from the outside, given a suitable choice of timeframe, the latter one is just how purely functional systems represent state. Theoretically they can simulate each other, and the endpoint you use to access Actor will still reference the latest Actor. The only reason you're calling them different is because you insist on using a specific timeframe to exclude considering one as stateful, and I'm pointing out that that isn't strictly necessary.
- jncfhnb 3y agoTrue but saying “subsequent training” implies very long periods between Updates. We do not train LLMs to update them to the state of a conversation.