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with only a couple of prompts, Gemini CLI can convert a messy folder containing hundreds of notes into a neatly named, well-structured, cross-linked Obsidian knowledge graph all in about half an hour and at minimal cost. from r/singularity/Ryoiki-Tokuiten

Rohan Paul

151,819 subscribers

415,737 просмотров • 1 год назад •via X (Twitter)

Наука и технологии Новости и политика Образование

Anya Rossi• Live Now

Private livecam show

Комментарии: 10

Фото профиля Rohan Paul

Rohan Paul1 год назад

OP first saved all his notes—about 400 markdown files—from another app onto his computer. He put these files into an Obsidian folder. Next, he opened Gemini’s CLI tool and typed two short instructions: one told Gemini to rename and neatly sort every note into folders, and the other told it to link related notes so Obsidian’s graph view would show the connections. Gemini ran for ~30mins, used only a small part of its memory window, and finished with most notes correctly organized and cross-linked

Фото профиля Pale Blue Mediocrity

Pale Blue Mediocrity1 год назад

I've seen so many of these demoes over the past DECADES, yet not a single time I've seen a person actually doing something with this "generated PKM knowledge graph". I've seen plenty of manually structured notes which are always used like second nature. Just an observation.

Фото профиля ⓧaugmntd 🛞 Xakubio

ⓧaugmntd 🛞 Xakubio1 год назад

sheesh

Фото профиля Kayli Lewis

Kayli Lewis1 год назад

🧐

Фото профиля Yinan (Steven) Na

Yinan (Steven) Na1 год назад

Thank you for this Rohan

Фото профиля Rohan Paul

Rohan Paul1 год назад

👊👊🙏

Фото профиля Danny Sun

Danny Sun1 год назад

why a cli text interface? c64 vibes.

Фото профиля alby13

alby131 год назад

Great visual!

Фото профиля Richand Handsome

Richand Handsome1 год назад

Thought it was free

Фото профиля Rohan Paul

Rohan Paul1 год назад

Gemini CLI itself is a free, open-source tool, and and you get up to 1000 model requests a day (60 per minute i think.) But beyond this limit, when the CLI tool talks to the paid Gemini API or to Vertex AI keys, that will be billed by the million tokens normally.

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turned this into a web app you can use with your own obsidian vault! no install, just one html file: point it at your notes folder, it embeds everything with gemini, clusters by meaning, and renders the 3d network in your browser. available now for x/twitter subscribers <3

turned this into a web app you can use with your own obsidian vault! no install, just one html file: point it at your notes folder, it embeds everything with gemini, clusters by meaning, and renders the 3d network in your browser. available now for x/twitter subscribers <3

Kat ⊷ the Poet Engineer

105,960 просмотров • 5 месяцев назад

Most notes die the moment you save them. Karpathy’s workflow, paired with Obsidian and Claude Code, turns them into a living knowledge base you can actually use. Instead of digging through thousands of forgotten notes, you get an AI-powered second brain that remembers, connects, and surfaces exactly what you need.

Most notes die the moment you save them. Karpathy’s workflow, paired with Obsidian and Claude Code, turns them into a living knowledge base you can actually use. Instead of digging through thousands of forgotten notes, you get an AI-powered second brain that remembers, connects, and surfaces exactly what you need.

Evan Luthra

64,681 просмотров • 29 дней назад

A 26-YEAR-OLD AI ENGINEER WHOSE BIRMINGHAM THESIS OUTPERFORMED GOOGLE SCHOLAR BY 50% JUST SHIPPED GRAPHIFY: ONE COMMAND TURNS ANY FOLDER INTO A CLAUDE CODE SECOND BRAIN Safi Shamsi built Graphify 48 hours after Karpathy posted his LLM wiki idea. It turns any folder, codebase, docs, PDFs, into a knowledge graph Claude reads instead of grepping. Up to 43x fewer tokens per query. The trick almost nobody is using yet: one flag exports the entire graph as a fully-linked Obsidian vault. Repo: /safishamsi/graphify Setup, end to end: 1. Install: uv tool install graphifyy (or pipx install graphifyy). Verify with graphify --version. 2. Install the skill in Claude Code: graphify claude install. This wires Graphify into Claude Code so you can call it as a skill. 3. Open the folder you want mapped in Claude Code. In the terminal: graphify . It extracts every concept and builds the graph in graphify-out/. 4. Export to Obsidian: graphify . --obsidian. Writes one note per concept, every relationship as a wikilink, every node linked back to its source. 5. Open the new vault in Obsidian (Manage vaults → Open folder as a vault), or drag it as a subfolder into your existing one. That's it. Your Claude Code instance now has a navigable map of the codebase that loads instantly instead of re-reading files every session. Full step-by-step build of the Claude + Obsidian second brain in the article below. Bookmark this

A 26-YEAR-OLD AI ENGINEER WHOSE BIRMINGHAM THESIS OUTPERFORMED GOOGLE SCHOLAR BY 50% JUST SHIPPED GRAPHIFY: ONE COMMAND TURNS ANY FOLDER INTO A CLAUDE CODE SECOND BRAIN Safi Shamsi built Graphify 48 hours after Karpathy posted his LLM wiki idea. It turns any folder, codebase, docs, PDFs, into a knowledge graph Claude reads instead of grepping. Up to 43x fewer tokens per query. The trick almost nobody is using yet: one flag exports the entire graph as a fully-linked Obsidian vault. Repo: /safishamsi/graphify Setup, end to end: 1. Install: uv tool install graphifyy (or pipx install graphifyy). Verify with graphify --version. 2. Install the skill in Claude Code: graphify claude install. This wires Graphify into Claude Code so you can call it as a skill. 3. Open the folder you want mapped in Claude Code. In the terminal: graphify . It extracts every concept and builds the graph in graphify-out/. 4. Export to Obsidian: graphify . --obsidian. Writes one note per concept, every relationship as a wikilink, every node linked back to its source. 5. Open the new vault in Obsidian (Manage vaults → Open folder as a vault), or drag it as a subfolder into your existing one. That's it. Your Claude Code instance now has a navigable map of the codebase that loads instantly instead of re-reading files every session. Full step-by-step build of the Claude + Obsidian second brain in the article below. Bookmark this

Yarchi

141,580 просмотров • 1 месяц назад

An China guy discovered a method to learn any knowledge instantly using AI. The key is Obsidian + any AI — Kimi, Claude, or Gemini. Most people learn slowly: read, forget, read again, forget again. His method: use AI to transform any content into small, interconnected notes. Use Obsidian to link them, so every piece of knowledge is never isolated. Slow method: highlight books, keep going, forget after a week. Fast method: AI breaks it into atomic notes, Obsidian links them into a network. Six months later, a new idea instantly connects to twenty things you already know. I compiled the full A–Z guide to building a second brain with Obsidian — works with Kimi, Claude, or Gemini — that most people have never discovered. Article below

An China guy discovered a method to learn any knowledge instantly using AI. The key is Obsidian + any AI — Kimi, Claude, or Gemini. Most people learn slowly: read, forget, read again, forget again. His method: use AI to transform any content into small, interconnected notes. Use Obsidian to link them, so every piece of knowledge is never isolated. Slow method: highlight books, keep going, forget after a week. Fast method: AI breaks it into atomic notes, Obsidian links them into a network. Six months later, a new idea instantly connects to twenty things you already know. I compiled the full A–Z guide to building a second brain with Obsidian — works with Kimi, Claude, or Gemini — that most people have never discovered. Article below

Kirill

73,340 просмотров • 1 месяц назад

One month later and The Hat’s new Las Vegas location is still packed with no sign of slowing down. At 3pm, the line outside is about a half hour wait while drive through is an hour to an hour and a half.

One month later and The Hat’s new Las Vegas location is still packed with no sign of slowing down. At 3pm, the line outside is about a half hour wait while drive through is an hour to an hour and a half.

Chris Holmes

52,095 просмотров • 2 месяцев назад

Obsidian just became the most dangerous folder on your computer, and Andrej Karpathy predicted it with 1 markdown file. His method is called append-and-review. He described it years ago and almost nobody listened: 1 single note, every thought appended to the top, reviewed on random scrolls. No tags, no folders, no Notion dashboards with 40 linked databases. The problem was always the same the note remembers, but it can't act. That changed the moment people pointed Claude Code at an Obsidian vault. Here's the setup that's quietly spreading: Part 1 — The vault becomes a database. Obsidian stores everything as plain markdown on your disk, which means Claude Code can read it like a codebase. You open a terminal inside the vault folder and your 2,000 notes turn into queryable memory. Part 2 — The CLAUDEmd file becomes the brain stem. One file at the root tells the agent who you are, what you're building, and how your notes are structured. From that point every session starts with full context instead of a blank chat window. Part 3 — Karpathy append log becomes fuel. You dump raw thoughts all day ideas, links, half-sentences. Then 1 command at night: review today's appends, extract action items, draft the 3 posts hiding in there, link them to existing notes. The messy log goes in, structured output comes out, and the vault rewrites itself while you sleep. Part 4 — Agents start living in your notes. People are running weekly reviews, content calendars, even market research as scheduled Claude Code runs over their vault. Your second brain stops being a graveyard of highlights and starts shipping. The honest math: setup takes about 90 minutes, the first week feels like overkill, and by day 30 you're sitting on a system where every note you've written in 5 years is working for you instead of rotting in a folder. Notion needed a server, a subscription and your data on someone else's machine. Obsidian needed a text file and now the text file has an employee.

Obsidian just became the most dangerous folder on your computer, and Andrej Karpathy predicted it with 1 markdown file. His method is called append-and-review. He described it years ago and almost nobody listened: 1 single note, every thought appended to the top, reviewed on random scrolls. No tags, no folders, no Notion dashboards with 40 linked databases. The problem was always the same the note remembers, but it can't act. That changed the moment people pointed Claude Code at an Obsidian vault. Here's the setup that's quietly spreading: Part 1 — The vault becomes a database. Obsidian stores everything as plain markdown on your disk, which means Claude Code can read it like a codebase. You open a terminal inside the vault folder and your 2,000 notes turn into queryable memory. Part 2 — The CLAUDEmd file becomes the brain stem. One file at the root tells the agent who you are, what you're building, and how your notes are structured. From that point every session starts with full context instead of a blank chat window. Part 3 — Karpathy append log becomes fuel. You dump raw thoughts all day ideas, links, half-sentences. Then 1 command at night: review today's appends, extract action items, draft the 3 posts hiding in there, link them to existing notes. The messy log goes in, structured output comes out, and the vault rewrites itself while you sleep. Part 4 — Agents start living in your notes. People are running weekly reviews, content calendars, even market research as scheduled Claude Code runs over their vault. Your second brain stops being a graveyard of highlights and starts shipping. The honest math: setup takes about 90 minutes, the first week feels like overkill, and by day 30 you're sitting on a system where every note you've written in 5 years is working for you instead of rotting in a folder. Notion needed a server, a subscription and your data on someone else's machine. Obsidian needed a text file and now the text file has an employee.

Spike 1%

58,428 просмотров • 28 дней назад

THIS GUY TURNED OBSIDIAN INTO A DIGITAL TWIN OF HIS OWN BRAIN, 400 PLUS NODES, 6 KNOWLEDGE CLUSTERS, 1 LOCAL VAULT, AND A MAP THAT GETS SMARTER WITH EVERY NOTE 00:05 the graph begins as one dense sphere, then individual paths light up across the screen, showing how a single note can connect to dozens of ideas instead of disappearing inside another folder. most people store information in straight lines, one file after another. his vault grows like a network, research connects to projects, projects connect to decisions, and old notes keep feeding new work months later. after 100 notes, it still feels like storage. around 300, clusters begin exposing repeated interests, unfinished threads, and topics that keep returning even after he stops thinking about them. with claude connected, the network becomes usable context. instead of pasting 20 files into one chat, an agent can follow 5 linked notes, pull original sources, compare old decisions, and write the result back into the same vault. a real second brain is not the pretty graph. it is a local system where every new thought strengthens old connections, buried ideas come back when needed, and knowledge keeps compounding without leaving your machine.

THIS GUY TURNED OBSIDIAN INTO A DIGITAL TWIN OF HIS OWN BRAIN, 400 PLUS NODES, 6 KNOWLEDGE CLUSTERS, 1 LOCAL VAULT, AND A MAP THAT GETS SMARTER WITH EVERY NOTE 00:05 the graph begins as one dense sphere, then individual paths light up across the screen, showing how a single note can connect to dozens of ideas instead of disappearing inside another folder. most people store information in straight lines, one file after another. his vault grows like a network, research connects to projects, projects connect to decisions, and old notes keep feeding new work months later. after 100 notes, it still feels like storage. around 300, clusters begin exposing repeated interests, unfinished threads, and topics that keep returning even after he stops thinking about them. with claude connected, the network becomes usable context. instead of pasting 20 files into one chat, an agent can follow 5 linked notes, pull original sources, compare old decisions, and write the result back into the same vault. a real second brain is not the pretty graph. it is a local system where every new thought strengthens old connections, buried ideas come back when needed, and knowledge keeps compounding without leaving your machine.

Gipp 🦅

20,183 просмотров • 1 месяц назад

Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by Neo4j Innovation Lead Andreas Kollegger, shows you how. Knowledge graphs are an important way to store information accurately but they are a lot of work to build manually. In this course you’ll learn how to build a team of agents that turn data– in this case product reviews and invoices from suppliers–into structured graphs of entities and relationships for RAG. Learn how agents can automatically handle the time-consuming work of building graphs — extracting entities and relationships (e.g., Product "contains" Assembly, Part "supplied_by" Supplier, Customer review "mentions" Product), deduplicating them, fact-checking them, and committing them to a graph database — so your retrieval system can find right information to generate accurate output. For example, you can use agents to help trace customer complaints directly to specific suppliers, manufacturing processes, and product hierarchies, thus turning fragmented information into queryable business intelligence. Skills you’ll gain: - Build, store, and access knowledge graphs using the Neo4j graph database - Build multi-agent systems using Google’s Agent Development Kit (ADK) - Set up a loop of agentic workflows to propose and refine a graph schema through fact-checking - Connect agent-generated graphs of unstructured and structured data into a unified knowledge graph This course gets into the practicum of why knowledge graphs give more accurate information retrieval than vector search alone, especially for high-stakes applications where precision matters more than fuzzy similarity matching. Sign up here:

Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by Neo4j Innovation Lead Andreas Kollegger, shows you how. Knowledge graphs are an important way to store information accurately but they are a lot of work to build manually. In this course you’ll learn how to build a team of agents that turn data– in this case product reviews and invoices from suppliers–into structured graphs of entities and relationships for RAG. Learn how agents can automatically handle the time-consuming work of building graphs — extracting entities and relationships (e.g., Product "contains" Assembly, Part "supplied_by" Supplier, Customer review "mentions" Product), deduplicating them, fact-checking them, and committing them to a graph database — so your retrieval system can find right information to generate accurate output. For example, you can use agents to help trace customer complaints directly to specific suppliers, manufacturing processes, and product hierarchies, thus turning fragmented information into queryable business intelligence. Skills you’ll gain: - Build, store, and access knowledge graphs using the Neo4j graph database - Build multi-agent systems using Google’s Agent Development Kit (ADK) - Set up a loop of agentic workflows to propose and refine a graph schema through fact-checking - Connect agent-generated graphs of unstructured and structured data into a unified knowledge graph This course gets into the practicum of why knowledge graphs give more accurate information retrieval than vector search alone, especially for high-stakes applications where precision matters more than fuzzy similarity matching. Sign up here:

Andrew Ng

168,153 просмотров • 11 месяцев назад

48 HOURS AFTER KARPATHY POSTED HIS LLM WIKI IDEA, A 26-YEAR-OLD BIRMINGHAM GRAD SHIPPED THE ONE COMMAND THAT MAKES IT WORK. IT NOW HAS 76,000 GITHUB STARS 1 command. 71.5x fewer tokens per query. 0 vector databases points graphify at any folder - codebase, docs, PDFs, screenshots, video. Tree-sitter parses the code, Claude reads the prose, the whole thing lands as a knowledge graph in graphify-out/ one flag - --obsidian - writes the entire graph as a fully-linked Obsidian vault: one markdown note per concept, every relationship a wikilink, every node linked back to its source. Drop the vault into Claude Code as a skill. Claude queries the graph instead of grepping through raw files, forever Safi Shamsi finished his MSc at Birmingham with Distinction in 2025. His thesis was a knowledge-graph RAG system for academic search. He shipped Graphify 48 hours after Karpathy's post, iterates every week, and has already been forked by Rootly AI Labs for incident data. Hacker News, Analytics Vidhya, Towards AI - all organic.76,000 stars. Three months old no neo4j server. no vector db. no embedding pipeline. no cloud. no monthly fee you're reading this on a device that could clone the repo, run one command, and have a Claude-native knowledge graph of your entire codebase in Obsidian before your next standup

48 HOURS AFTER KARPATHY POSTED HIS LLM WIKI IDEA, A 26-YEAR-OLD BIRMINGHAM GRAD SHIPPED THE ONE COMMAND THAT MAKES IT WORK. IT NOW HAS 76,000 GITHUB STARS 1 command. 71.5x fewer tokens per query. 0 vector databases points graphify at any folder - codebase, docs, PDFs, screenshots, video. Tree-sitter parses the code, Claude reads the prose, the whole thing lands as a knowledge graph in graphify-out/ one flag - --obsidian - writes the entire graph as a fully-linked Obsidian vault: one markdown note per concept, every relationship a wikilink, every node linked back to its source. Drop the vault into Claude Code as a skill. Claude queries the graph instead of grepping through raw files, forever Safi Shamsi finished his MSc at Birmingham with Distinction in 2025. His thesis was a knowledge-graph RAG system for academic search. He shipped Graphify 48 hours after Karpathy's post, iterates every week, and has already been forked by Rootly AI Labs for incident data. Hacker News, Analytics Vidhya, Towards AI - all organic.76,000 stars. Three months old no neo4j server. no vector db. no embedding pipeline. no cloud. no monthly fee you're reading this on a device that could clone the repo, run one command, and have a Claude-native knowledge graph of your entire codebase in Obsidian before your next standup

chewa.

299,208 просмотров • 1 месяц назад

There were tears of joy at the Old Bailey today when all but one of a group charged with breaking into an Israel-linked weapons firm were released on bail. Some of them had spent over a year-and-a-half on remand.

There were tears of joy at the Old Bailey today when all but one of a group charged with breaking into an Israel-linked weapons firm were released on bail. Some of them had spent over a year-and-a-half on remand.

Channel 4 News

17,956 просмотров • 5 месяцев назад

Andrej Karpathy quietly shipped the best second brain idea in years not an app. a pattern. let an llm maintain a wiki of your notes. you dump sources, it reads them, links them, files them. knowledge compounds like interest. someone built it into a free claude code plugin. setup is two commands: claude plugin marketplace add AgriciDaniel/claude-obsidian claude plugin install claude-obsidian@agricidaniel-claude-obsidian then open obsidian, open claude code in the same folder, type /wiki. that's it. your notes are now queryable by claude and they get richer every time you read something. bookmark this. best thing you'll build this weekend.

Andrej Karpathy quietly shipped the best second brain idea in years not an app. a pattern. let an llm maintain a wiki of your notes. you dump sources, it reads them, links them, files them. knowledge compounds like interest. someone built it into a free claude code plugin. setup is two commands: claude plugin marketplace add AgriciDaniel/claude-obsidian claude plugin install claude-obsidian@agricidaniel-claude-obsidian then open obsidian, open claude code in the same folder, type /wiki. that's it. your notes are now queryable by claude and they get richer every time you read something. bookmark this. best thing you'll build this weekend.

Avid

338,253 просмотров • 2 месяцев назад

🚀 The team at Google DeepMind just released Gemini Embedding 2, a frontier embeddings model with 3072 dimensions and state-of-the-art semantic quality. 👩‍💻 We built a demo showing how to integrate it across the LlamaIndex ecosystem, from LlamaParse to LlamaAgents: 𝗮𝘂𝗱𝗶𝗼-𝗸𝗯, a knowledge base for your audio notes. With audio-kb, you can: 🔹 Upload an MP3 or record directly from your terminal 🔹 LlamaParse extracts the transcript from the audio 🔹 Gemini Embedding 2 generates embeddings 🔹 Metadata + vectors are stored in SurrealDB and indexed with HNSW 🔍 Once ingested, you can search all your audio notes directly from the terminal. 🎙️ Perfect for turning voice memos, meetings, or lectures into a searchable knowledge base. 📖 Full blog: 💻 GitHub: ⚡ Try LlamaParse:

🚀 The team at Google DeepMind just released Gemini Embedding 2, a frontier embeddings model with 3072 dimensions and state-of-the-art semantic quality. 👩‍💻 We built a demo showing how to integrate it across the LlamaIndex ecosystem, from LlamaParse to LlamaAgents: 𝗮𝘂𝗱𝗶𝗼-𝗸𝗯, a knowledge base for your audio notes. With audio-kb, you can: 🔹 Upload an MP3 or record directly from your terminal 🔹 LlamaParse extracts the transcript from the audio 🔹 Gemini Embedding 2 generates embeddings 🔹 Metadata + vectors are stored in SurrealDB and indexed with HNSW 🔍 Once ingested, you can search all your audio notes directly from the terminal. 🎙️ Perfect for turning voice memos, meetings, or lectures into a searchable knowledge base. 📖 Full blog: 💻 GitHub: ⚡ Try LlamaParse:

LlamaIndex 🦙

34,945 просмотров • 5 месяцев назад

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

Dan McAteer

174,267 просмотров • 1 месяц назад

More updates to the Shader Graph Editor! Now, with markdown nodes. Write an article, book, blog, and notes, all with embedded shaders. Here's an article by patricio gonzalez vivo on Algorithmic drawing from The Book of Shaders in a fully interactive playground.

More updates to the Shader Graph Editor! Now, with markdown nodes. Write an article, book, blog, and notes, all with embedded shaders. Here's an article by patricio gonzalez vivo on Algorithmic drawing from The Book of Shaders in a fully interactive playground.

Palash Bansal

36,805 просмотров • 2 лет назад

KARPATHY JUST MADE EVERY SECOND BRAIN GURU LOOK STUPID an artist with zero tech background took her obsidian vault, plugged it into blender and claude and turned her notes into a 3d map of her entire city no zettelkasten course, no notion templates, no productivity system just obsidian graphs that became something you can actually see and navigate this is what happens when your second brain stops being a folder and starts being a living structure save this for when someone tells you obsidian is just for nerds ↓

KARPATHY JUST MADE EVERY SECOND BRAIN GURU LOOK STUPID an artist with zero tech background took her obsidian vault, plugged it into blender and claude and turned her notes into a 3d map of her entire city no zettelkasten course, no notion templates, no productivity system just obsidian graphs that became something you can actually see and navigate this is what happens when your second brain stops being a folder and starts being a living structure save this for when someone tells you obsidian is just for nerds ↓

leopardracer

81,692 просмотров • 1 месяц назад

With Codex and Box, you can automate a lot of knowledge worker tasks. A single file in Box turns into structured data, tracked work in Linear, and a live update in Slack. No handoffs. No follow-ups. Just flow. Watch it in action.👇

With Codex and Box, you can automate a lot of knowledge worker tasks. A single file in Box turns into structured data, tracked work in Linear, and a live update in Slack. No handoffs. No follow-ups. Just flow. Watch it in action.👇

Box

6,291,433 просмотров • 4 месяцев назад

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!

Andrew Ng

244,403 просмотров • 2 лет назад

So much of dev work happens in the context of a larger team, and now you can bring all of that work context into the GitHub Copilot CLI with Work IQ.

So much of dev work happens in the context of a larger team, and now you can bring all of that work context into the GitHub Copilot CLI with Work IQ.

Satya Nadella

76,099 просмотров • 6 месяцев назад