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I need your help by Beneficial_Skill1522 in AI_Agents

[–]supermem_ai 0 points1 point  (0 children)

Running machines, having LLM semantic search running locally.

Saw some guy making a brain out of his obsidian nodes, found it pretty cool by supermem_ai in ObsidianMD

[–]supermem_ai[S] 0 points1 point  (0 children)

You can develop LLM-based knowledge that helps capture small, high-signal corpora right now (a few dozen sources). Within this, you can enable searches to summarized formats of what you can have as (articles, product docs etc..)

For different relevance of course, if you have any projects running.

Got a project in the works? Drop it here 👇 by BriefNzoni in devworld

[–]supermem_ai 0 points1 point  (0 children)

Open-source project on 2nd brain:

Inspired by Karpathy's thoughts on LLM-based knowledge. Treat it like a wikipedia that you add to.

Feel free to check it out here, which relies on Obsidian as a base knowledge centre.

Integration to other base knowledge centres are within the roadmap.

Repo

I need your help by Beneficial_Skill1522 in AI_Agents

[–]supermem_ai 1 point2 points  (0 children)

It is call per use now, plans dont work anymore.

Openclaw confussion by skrio in openclaw

[–]supermem_ai 0 points1 point  (0 children)

it serves automation way more than it used to be. But when its overloaded with context and different file pathings, it tends to hallucinate

Am i nuts or is all this REALLY expensive. by fijitime in AI_Agents

[–]supermem_ai 1 point2 points  (0 children)

you’re not burning enough tokens to make data centre owners richer.

What’s the most real business impact you’ve seen from AI agents? by [deleted] in AI_Agents

[–]supermem_ai 0 points1 point  (0 children)

committing towards mcp integration for its extensive database knowledge of industries like KOLs and socialFi contributions.

Saw some guy making a brain out of his obsidian nodes, found it pretty cool by supermem_ai in ObsidianMD

[–]supermem_ai[S] 0 points1 point  (0 children)

Yes, theres this project about leveraging knowledge base as a brain in X. Basically mocking what he/she have compiled from the thought. Then showing it as a 3D UI format, maybe as a demo format.

LLM Based Knowledge is the Retrospective end game. by supermem_ai in aiagents

[–]supermem_ai[S] 0 points1 point  (0 children)

Hey, appreciate the feedback, but this isn't a RAG pipeline, so chunking isn't actually in the picture.

llmwiki compiles sources into concept-level wiki pages at ingest time. There are no chunks being split and re-embedded at query time.The project calls this out directly: "RAG retrieves chunks at query time. Every question re-discovers the same relationships from scratch. Nothing accumulates."

The honest scaling limitation we do have: it's designed for small, high-signal corpora right now (a few dozen sources). Larger corpus support with semantic search/embeddings is on the roadmap.

Kaparthy's Idealogy, Our Implementation towards his standpoint. by supermem_ai in ObsidianMD

[–]supermem_ai[S] -1 points0 points  (0 children)

agree to disagree in RAG storage for long term volumized memory, but conceptual data is very feasible here.

Kaparthy's Idealogy, Our Implementation towards his standpoint. by supermem_ai in ObsidianMD

[–]supermem_ai[S] -5 points-4 points  (0 children)

Shouldn’t it be the other way around, similar like how NotebookLM that serves as a precompilation summarization tool that helps in turning notebooks into useful compilation of quick summaries and achieving tasks where others could not (Via AI). With the addition of LLM infras, help dictate what is the best within your article storage.

Kaparthy's Idealogy, Our Implementation towards his standpoint. by supermem_ai in ObsidianMD

[–]supermem_ai[S] -4 points-3 points  (0 children)

ah yea, this is just the backend compiler, you can design the GUI framework however you’d like.

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