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We built a persistent agent memory layer on Elasticsearch with 0.89 recall
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Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#42Earlier quoted context omitted.
> but it's much smarter than "shove markdown files into directories". Is it, though? I mean, is there evidence "bunch of markdown files" is bad while "database the model has to be instructed how to use" is good? `rg` is fast as hell. Markdown is the LLMs native tongue. It does require maintenance of the Markdown files to keep them current, but maybe explicit management is fine. The models can do the grunt work. BMDF…
Because a bunch of markdown files is just RAG, and RAG is unintelligent, so the results are not great. If you want a smarter AI, it needs to have not-dumb memory. That's why this article (and the summary I posted) covers multiple kinds of memory, multiple ways of managing different memories, multiple ways of finding memories, a way to pick the best memory, and a way to manage memories long-term (and among multiple us…
[flagged]
Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#43[flagged]
Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#44This is such a basic thing nowadays, and ElasticSearch is massive overkill for it. Something like SQLite or LanceDB or basically any vector database is much more appropriate. This seems to be coming from the “we must make ElasticSearch AI-compatible” department more than anything.
Yeah, it's like this Dropbox service they made a big deal about, when one could just make one of its own with rsync and some bash scripting.
Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#45Earlier quoted context omitted.
> but it's much smarter than "shove markdown files into directories". Is it, though? I mean, is there evidence "bunch of markdown files" is bad while "database the model has to be instructed how to use" is good? `rg` is fast as hell. Markdown is the LLMs native tongue. It does require maintenance of the Markdown files to keep them current, but maybe explicit management is fine. The models can do the grunt work. BMDF…
Because a bunch of markdown files is just RAG, and RAG is unintelligent, so the results are not great. If you want a smarter AI, it needs to have not-dumb memory. That's why this article (and the summary I posted) covers multiple kinds of memory, multiple ways of managing different memories, multiple ways of finding memories, a way to pick the best memory, and a way to manage memories long-term (and among multiple us…
> If you want a smarter AI, it needs to have not-dumb memory.
Who says? According to what metric? How would you prove that assertion?
> Now the memory isn't dumb, so the results are better. (And the article shows you why it's better)
But, it doesn't. It explains what they built, and how it behaves. It does not show why it's better than any other alternative for making models "smarter", somehow.
Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#46Earlier quoted context omitted.
Because a bunch of markdown files is just RAG, and RAG is unintelligent, so the results are not great. If you want a smarter AI, it needs to have not-dumb memory. That's why this article (and the summary I posted) covers multiple kinds of memory, multiple ways of managing different memories, multiple ways of finding memories, a way to pick the best memory, and a way to manage memories long-term (and among multiple us…
> If you want a smarter AI, it needs to have not-dumb memory. Who says? According to what metric? How would you prove that assertion? > Now the memory isn't dumb, so the results are better. (And the article shows you why it's better) But, it doesn't. It explains what they built, and how it behaves. It does not show why it's better than any other alternative for making models "smarter", somehow.
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Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#47[flagged]
Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#48[flagged]
Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#49I built one into my agent using sqlite…
At this point building a memory tool for your ai agents is like a right of passage.
Re: We built a persistent agent memory layer on Elasticsearch with 0.89 recall
#50try Manticore Search, it's much more lightweight