11–20 of 59 posts
A question for people researching LLMs and their capabilities: Is there any reason to believe that the interaction of multiple agents (using the same model) will yield some emergent property that is beyond the capabilities of the agent model? I'm not working with LLMs, but my intuition is that whatever these multi agent setups come up with could also be achieved by a single agent just talking to itself, as they all a…
Are these 'safer' than using langchain-based agents that directly execute (arbitrary!) Python code? That was always my main issue with langchain
FWIW the “group research” and “chess” examples from the notebooks folder in their repo have been the best for explaining the utility of this tech to others - the meme generator does a good job showing functions stripped down but misses a lot of the important bits
A question for people researching LLMs and their capabilities: Is there any reason to believe that the interaction of multiple agents (using the same model) will yield some emergent property that is beyond the capabilities of the agent model? I'm not working with LLMs, but my intuition is that whatever these multi agent setups come up with could also be achieved by a single agent just talking to itself, as they all a…
Having conversations amongst agents is it like treating each agent as your traditional nodes? Maybe in the future there would be millions of nodes(agents) conversing and maybe this is how next gen AGI will form
Unless I'm missing something, how is this library different from prompting a single chatbot: "Write a dialog in which A, B, and C, each playing a different role, have a conversation and do something D"?
A question for people researching LLMs and their capabilities: Is there any reason to believe that the interaction of multiple agents (using the same model) will yield some emergent property that is beyond the capabilities of the agent model? I'm not working with LLMs, but my intuition is that whatever these multi agent setups come up with could also be achieved by a single agent just talking to itself, as they all a…
Since a single inference is limited by context length, a multiple agents model is able to process more context at each steps of the reasoning chain, which might improve the overall quality. However, given how easy it is getting to fine tune models, it's likely that multi-agent models will make a lot of sense to split the workload and assign each part to a specialized agent.