[djangelic]

Forgive my conjecture, as I'm no expert in this field, but have enjoyed playing with the different models.

I see it as a matter of attention. GPT-4 is limited in the number of tokens you can feed it and receive back from it. I see this as how much attention the LLM can give you. I see meta-gpt and other models like this as increasing the attention of the LLM by allowing it combine it's short attention span with multiple assessments of the request, and give you a more complete picture of what you want because it can keep giving it consistent attention to the problem at hand, instead of simply trying to solve it on the first try.

Someone please correct me if I'm way off, but this simple mental model helps me abstract this.

[hooande]

The problem with this is that it has no memory across the different contexts. An analogy would be giving one page of a five page document to five different people, then taking it away and asking them to collaborate. While they can each give more attention to their individual page, none of them can see the whole picture and a lot of information will be lost when trying to communicate.

You can use multiple agents, or split a lot of information across multiple requests to one agent. The result is the same. Some problems require a full understanding of the whole picture.

[djangelic]

That’s a great analogy thank you!