> The way they've handled memory here isn't actually necessary
I'm curious if there are other methods you can point at that would handle arbitrarily long sets of 'memories' in an effective way. The use of embeddings and vector searches here seems like a way to sidestep that that's both powerful and easy to understand, and easy to generalize into multi-level referencing if there's enough space in the context window.
Every method so far basically uses embeddings and vector searches. what i mean is how the LLM processes/uses that information doesn't need to be this handholdy.
I'm curious if there are other methods you can point at that would handle arbitrarily long sets of 'memories' in an effective way. The use of embeddings and vector searches here seems like a way to sidestep that that's both powerful and easy to understand, and easy to generalize into multi-level referencing if there's enough space in the context window.