Thanks, this is a great analysis on the power of agentized LLMs, which I probably need to spend some more time thinking about. I will work my way through the post over the next few days. I briefly skimmed the episodic memory section for now, and I see it is like an embedding based retrieval system for past outputs/interactions of the model, reminiscent of the way some Helper chatbots look up stuff from FAQs. My overall intuitions on this:
It’s definitely something, but the method of embedding and retrieval, if static, would be very limiting
Someone will probably add RL on top of it to adjust the EBR system, which will improve on that part significantly… if they can get the hparams correct.
It still doesn’t seem to me as much “long term memory” so much as it’s access to Google or CTRL-F on one’s e-mail
I imagine actually updating the internals of the system is a fundamentally different kind of update.
It might be possible that a hybrid approach would end up working better, perhaps not even “continuous learning”, but batched episodic learning. (“Sleep” but not sure how far that analogy goes.)
Thanks, this is a great analysis on the power of agentized LLMs, which I probably need to spend some more time thinking about. I will work my way through the post over the next few days. I briefly skimmed the episodic memory section for now, and I see it is like an embedding based retrieval system for past outputs/interactions of the model, reminiscent of the way some Helper chatbots look up stuff from FAQs. My overall intuitions on this:
It’s definitely something, but the method of embedding and retrieval, if static, would be very limiting
Someone will probably add RL on top of it to adjust the EBR system, which will improve on that part significantly… if they can get the hparams correct.
It still doesn’t seem to me as much “long term memory” so much as it’s access to Google or CTRL-F on one’s e-mail
I imagine actually updating the internals of the system is a fundamentally different kind of update.
It might be possible that a hybrid approach would end up working better, perhaps not even “continuous learning”, but batched episodic learning. (“Sleep” but not sure how far that analogy goes.)