I’m just a person interested in / reading about the subject so I could be mistaken about details, but:
When we train an LLM we’re trying to mimic the way neurons work. Training is the really resource intensive part. Right now companies will train a model, then use it for 6-12 months or whatever before releasing a new version.
When you and I have a “conversation” with chatgpt, it’s always with that base model, it’s not actively learning from the conversation, in the sense that new neural pathways are being created. What’s actually happening is a prompt that looks like this is submitted:
"{{openai crafted preliminary prompt}} + “Abe: Hello I’m Abe”.
Then it replies, and the next thing I type gets submitted like this:
"{{openai crafted preliminary prompt}} + "Abe: Hello I’m Abe + {{agent response}} + “Abe: Good to meet you computer friend!”
And so on. Each time, you’re only talking to that base level llm model, but feeding it the history of the conversation at the same time as your new prompt.
You’re right to point out that now they’ve got the agents self-creating summaries of the conversation to allow them to “remember” more. But if we’re trying to argue for consciousness in the way we think of it with animals, not even arguing for humans yet, then I think the ability to actively synthesize experiences into the self is a requirement.
A dog remembers when it found food in a certain place on its walk or if it got stabbed by a porcupine and will change its future behavior in response.
Again I’m not an expert, but I expect there’s a way to incorporate this type of learning in nearish real time, but besides the technical work of figuring it out, doing so wouldn’t be very cost effective compared to the way they’re doing it now.
I’m just a person interested in / reading about the subject so I could be mistaken about details, but:
When we train an LLM we’re trying to mimic the way neurons work. Training is the really resource intensive part. Right now companies will train a model, then use it for 6-12 months or whatever before releasing a new version.
When you and I have a “conversation” with chatgpt, it’s always with that base model, it’s not actively learning from the conversation, in the sense that new neural pathways are being created. What’s actually happening is a prompt that looks like this is submitted: "{{openai crafted preliminary prompt}} + “Abe: Hello I’m Abe”.
Then it replies, and the next thing I type gets submitted like this: "{{openai crafted preliminary prompt}} + "Abe: Hello I’m Abe + {{agent response}} + “Abe: Good to meet you computer friend!”
And so on. Each time, you’re only talking to that base level llm model, but feeding it the history of the conversation at the same time as your new prompt.
You’re right to point out that now they’ve got the agents self-creating summaries of the conversation to allow them to “remember” more. But if we’re trying to argue for consciousness in the way we think of it with animals, not even arguing for humans yet, then I think the ability to actively synthesize experiences into the self is a requirement.
A dog remembers when it found food in a certain place on its walk or if it got stabbed by a porcupine and will change its future behavior in response.
Again I’m not an expert, but I expect there’s a way to incorporate this type of learning in nearish real time, but besides the technical work of figuring it out, doing so wouldn’t be very cost effective compared to the way they’re doing it now.