Earlier quoted context omitted.
In a way yes. A hosted llm-wiki, where I handle the diffing, versioning and audit log of what was changed, by what agent and why.
So a git repo + md files?
Show HN: OzBrain, a shared brain for knowledge between agents and your team
21–30 of 73 posts
Re: Show HN: OzBrain, a shared brain for knowledge between agents and your team
#22Re: Show HN: OzBrain, a shared brain for knowledge between agents and your team
#23I have been thinking about this idea for a while. Cool work.
Re: Show HN: OzBrain, a shared brain for knowledge between agents and your team
#24Re: Show HN: OzBrain, a shared brain for knowledge between agents and your team
#25Do you have a solution for degradation in accuracy when compiling larger amounts of llm-produced text? I am also building LLM knowledge/memory systems and I've been surprised how bad LLMs are, even SOTA models, at summarizing non-trivial input batches of text. They get things wrong, distort the underlying meaning or data, etc.
Re: Show HN: OzBrain, a shared brain for knowledge between agents and your team
#26Re: Show HN: OzBrain, a shared brain for knowledge between agents and your team
#27Re: Show HN: OzBrain, a shared brain for knowledge between agents and your team
#28That is the reason why we condense the information in the first place. Forgetting + Synthesizing are the necessary parts of learning and basically with memory + smart retrieval we want to build a learning system.
Re: Show HN: OzBrain, a shared brain for knowledge between agents and your team
#29I think the central question for a such memory system is whether we or the agents can find the relevant information and how to organize these data as changes continues to come in. Would we miss something in the retrieval process? How do we organize the information so they stay actual and correct without piling up the garbage? Of course we can continue to concatenate the data and tag them with version and date, but th…