#Knowledge Graph

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Трендовые Reels

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#Knowledge Graph Reel by @tectalks.io (verified account) - Your notes aren't just notes anymore, they're alive. This turns an Obsidian vault into a living 3D mind map, where ideas stop sitting in folders and
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@tectalks.io
Your notes aren’t just notes anymore, they’re alive. This turns an Obsidian vault into a living 3D mind map, where ideas stop sitting in folders and start behaving like a real thinking system. In one view, everything orbits a single core idea. In another, thoughts self-organize into themed hubs. And in the wildest version, there’s no center at all, just a fully distributed network where ideas explain their own relationships to each other. It feels less like knowledge management and more like watching cognition happen in real time. Your brain, but spatial. Your thoughts, but navigable. This is what thinking looks like when AI stops organizing information and starts revealing how ideas actually connect. Built by @poetengineer_ #AI #KnowledgeGraph #Obsidian #SecondBrain #3DVisualization
#Knowledge Graph Reel by @arjay_the_dev (verified account) - Knowledge Graph vs Vector Database Both of these tools can be used by LLM to pull in information to answer a users question (RAG). Using a knowledge
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@arjay_the_dev
Knowledge Graph vs Vector Database Both of these tools can be used by LLM to pull in information to answer a users question (RAG). Using a knowledge graph is best for discovering relations between things, and using a vector database is best for finding similar things. #coding #programming #rag
#Knowledge Graph Reel by @the_ai_dude (verified account) - Comment 'Graph' to get the full document! . . . . In RAG (Retrieval-Augmented Generation), a knowledge graph organizes data as interconnected entitie
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@the_ai_dude
Comment 'Graph' to get the full document! . . . . In RAG (Retrieval-Augmented Generation), a knowledge graph organizes data as interconnected entities and relationships, enabling better context understanding and retrieval. It helps LLMs fetch precise, structured insights from linked information, improving reasoning, accuracy, and relevance of generated responses beyond traditional text-based document retrieval. . . . #rag #knowledgegraph #ai
#Knowledge Graph Reel by @alassafi.ai (verified account) - Comment "BRAIN" and I'll DM you the full guide 🧠 Your AI is resetting every single session. Every breakthrough. Every decision. Every pattern you s
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@alassafi.ai
Comment “BRAIN” and I’ll DM you the full guide 🧠 Your AI is resetting every single session. Every breakthrough. Every decision. Every pattern you spent hours debugging. Gone. Not because Claude isn’t smart enough — because you never gave it a memory system. Here’s what changes when you do: 👾 CLAUDE.md — The first thing Claude reads every session. Not a config file. A teaching document. Your architecture, your conventions, your hard nos. It shows up to every session already knowing who you are. 💾 Auto-memory directory — Claude starts writing down what it learns. Patterns it noticed. Things you corrected. Solutions that worked. Organised into topic files. Persistent across every session from now on. 🧠 Obsidian + MCP — Your vault becomes a live knowledge graph it can search at runtime. Two MCP servers: smart-connections for semantic search, qmd for structured queries. The key? Name notes as claims, not categories. Not `memory-systems.md` — `memory graphs beat giant memory files.md`. The titles alone tell Claude if something’s relevant before it reads a word. ”brain-ingest pipeline” — One command. Paste a YouTube link, a voice memo, a meeting recording. It downloads, transcribes locally, extracts the key claims and frameworks, and drops a structured note straight into your Obsidian inbox. That’s the insight from a talk you watched 6 weeks ago — available to Claude today. Each layer compounds on the last. Skip one and the others degrade. Comment “BRAIN” — full guide with MCP config, vault structure, and setup checklist 👇
#Knowledge Graph Reel by @techwith.ram - Comment "Graph" to get the details This open-source tool runs 100% in your browser: GitNexus indexes your entire project into a structured knowledge
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@techwith.ram
Comment “Graph” to get the details This open-source tool runs 100% in your browser: GitNexus indexes your entire project into a structured knowledge graph—mapping dependencies, call chains, clusters, and execution flows—so nothing important gets missed (even by AI agents). Here’s how it works: → Paste a public GitHub repository URL (or upload a ZIP) → It parses the code using Tree-sitter (AST-based parsing, not regex hacks) → Extracts functions, classes, imports, and relationships → Builds an interactive graph visualization in the browser (D3. js) → Generates a call graph and dependency map across the project - Follow @techwith.ram for more such content
#Knowledge Graph Reel by @hasantoxr (verified account) - 🚨 Someone just built a tool that turns any GitHub repo into an interactive knowledge graph and open sourced it for free. It's called GitNexus. Think
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@hasantoxr
🚨 Someone just built a tool that turns any GitHub repo into an interactive knowledge graph and open sourced it for free. It’s called GitNexus. Think of it as a visual X-ray of your codebase but with an AI agent you can actually talk to. Here’s what it does inside your browser: → Parses your entire GitHub repo or ZIP file in seconds → Builds a live interactive knowledge graph with D3.js → Maps every function, class, import, and call relationship → Runs a 4-pass AST pipeline: structure → parsing → imports → call graph → Stores everything in an embedded KuzuDB graph database → Lets you query your codebase in plain English with an AI agent Here’s the wildest part: It uses Web Workers to parallelize parsing across threads so a massive monorepo doesn’t freeze your tab. The Graph RAG agent traverses real graph relationships using Cypher queries not embeddings, not vector search. Actual graph logic. Ask it things like “What functions call this module?” or “Find all classes that inherit from X” and it traces the answer through the graph. This is the kind of code intelligence tool enterprise teams pay thousands per month for. It runs entirely in your browser. Zero server. Zero cost. Works with TypeScript, JavaScript, and Python. 100% Open Source. MIT License. #ai #chatgpt #clawdbot #tech #artificialintelligence
#Knowledge Graph Reel by @wyrdshow (verified account) - Comment "Claude" and I'll DM you the full guide Your AI is resetting every single session. Every breakthrough. Every decision. Every pattern you sp
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@wyrdshow
Comment “Claude” and I’ll DM you the full guide Your AI is resetting every single session. Every breakthrough. Every decision. Every pattern you spent hours debugging. Gone. Not because Claude isn’t smart enough — because you never gave it a memory system. Here’s what changes when you do: 👾 CLAUDE.md — The first thing Claude reads every session. Not a config file. A teaching document. Your architecture, your conventions, your hard nos. It shows up to every session already knowing who you are. 💾 Auto-memory directory — Claude starts writing down what it learns. Patterns it noticed. Things you corrected. Solutions that worked. Organised into topic files. Persistent across every session from now on. 🧠 Obsidian + MCP — Your vault becomes a live knowledge graph it can search at runtime. Two MCP servers: smart-connections for semantic search, qmd for structured queries. The key? Name notes as claims, not categories. Not `memory-systems.md` — `memory graphs beat giant memory files.md`. The titles alone tell Claude if something’s relevant before it reads a word. ”brain-ingest pipeline” — One command. Paste a YouTube link, a voice memo, a meeting recording. It downloads, transcribes locally, extracts the key claims and frameworks, and drops a structured note straight into your Obsidian inbox. That’s the insight from a talk you watched 6 weeks ago — available to Claude today. Each layer compounds on the last. Skip one and the others degrade. Comment “Claude” — full guide with MCP config, vault structure, and setup checklist 👇
#Knowledge Graph Reel by @itsaiandy - GitNexus builds a 3D knowledge graph of your codebase enabling AI tools to provide smarter, faster coding help.
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@itsaiandy
GitNexus builds a 3D knowledge graph of your codebase enabling AI tools to provide smarter, faster coding help.
#Knowledge Graph Reel by @digitalsamaritan (verified account) - Prediction: the next mega trend in AI will downloading the free note taking app Obsidian Here's why: • The AI Memory Problem: LLMs like Claude are
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@digitalsamaritan
Prediction: the next mega trend in AI will downloading the free note taking app Obsidian Here’s why: • The AI Memory Problem: LLMs like Claude are brilliant, but their memory is notoriously surface-level. They might remember your name and current project, but they lose the deep context of past brainstorming sessions—especially when your ideas are scattered across Google Docs, Apple Notes, and random files. • The Obsidian Advantage: Obsidian isn’t just a digital notepad; it links your notes together to build a visual “knowledge graph.” It helps you track patterns and connections in your ideas across years of note-taking. • The Ultimate Combo: Power users are connecting their Obsidian vaults directly to Claude. By doing this, you are effectively giving the AI a true “second brain” that solves its memory issue. • The Result: Whenever you chat with Claude, it automatically pulls the exact right context from your massive web of notes. You never have to manually copy-paste background info into a prompt ever again I’ve been meaning to talk about it for weeks but there’s been so many Ai launches lately so finally got around it And if you wanna catch the trends early, get on daily newsletter #ai #aitools #learnai #digitalsamaritan
#Knowledge Graph Reel by @piyush.glitch (verified account) - Comment "GIT" to get access to this open-source GitHub link directly into your DM. Someone just built a tool that turns any GitHub repo into a live i
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@piyush.glitch
Comment “GIT” to get access to this open-source GitHub link directly into your DM. Someone just built a tool that turns any GitHub repo into a live interactive knowledge graph — and it runs entirely in your browser. Upload a repo. Watch every function, class, import, and call relationship map itself visually. Then talk to it. Ask: • What calls this module? • Which classes inherit from this? • Where is this function used? It doesn’t guess. It runs real graph queries on actual relationships. No server. No subscription. No enterprise paywall. This is the kind of code intelligence teams charge thousands for — and it’s 100% open source. If you work with large repos, monorepos, or inherited codebases… this will save you hours. Comment “GIT” and I’ll send the link.
#Knowledge Graph Reel by @inesthetechie (verified account) - Ever felt like your data is too complex for AI to understand? RAG retrieves similar text chunks - but it doesn't actually know how things connect. E
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@inesthetechie
Ever felt like your data is too complex for AI to understand? RAG retrieves similar text chunks — but it doesn’t actually know how things connect. Enter GraphRAG 🧠 It builds a knowledge graph, letting the AI follow relationships and reason better. Perfect when your data is messy, interconnected, or spread across multiple sources. Think of it like giving your AI a map instead of a pile of papers. 🗺️ #AIexplained #GraphRAG #KnowledgeGraph #AItools #GenAI #RAGvsGraphRAG #aiapps #llm
#Knowledge Graph Reel by @alextheaiguy - An Ai brain that knows you better than you know you.. It's called a knowledge graph and it's super powerful. Where we've come from are regular datab
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@alextheaiguy
An Ai brain that knows you better than you know you.. It’s called a knowledge graph and it’s super powerful. Where we’ve come from are regular databases to RAG to knowledge graphs. A database just gives you exact details of things (if they match). Think of a Google spreadsheet and trying to do a control + f search. You only get results if you type them in exactly the same way. A RAG allows you to use Ai to search using regular conversations. Think asking “what’s our policy for xyz “, “how many products have been order for my business so far”,etc. and the ai will search your database for you. But this often times just finds chunks of words that sound the most correct and hopes it gets close. With knowledge graphs it actually will help map this out visually and show real relationships. Think “If we make this upgrade, what clients does this affect”, “Why do we have a drop in business around this time”, Where are we falling short “ ? The graph bills a HUGE web of you, your business and how EVERYTHING is tied together. Way more in depth and way more attention to detail #ai #tech #fyp

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