GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem

A famous poet once said "Natural language is most powerful when it can draw from a rich context." Ok fine, I said that. But that's true of both poetry, and of LLMs! Well, Knowledge Graphs excel at capturing context. How can combining Knowledge Graphs with RAG – an emerging technique known as GraphRAG – give context to your RAG application, and lead to more accurate and complete results, accelerated development, and explainable AI decisions? This talk will go deep on the why and how of GraphRAG, and where best to apply it. You’ll get concepts, examples, and specifics on how you can get started. You’ll walk away with an understanding of how GraphRAG can improve the context you pass to the LLM and the performance of your AI applications.

About Emil

Emil Eifrem is Neo4j’s Co-Founder and CEO. He sketched what today is known as the property graph model on a flight to Mumbai way back when dinosaurs ruled the earth and has devoted his professional life to building, innovating, and evangelizing graph databases and graph analytics. He is also co-author of the O'Reilly book Graph Databases. Neo4j today helps more than 75 of the Fortune 100, and a community of over hundreds of thousands of practitioners find hidden relationships and patterns across billions of connections deeply, easily, and quickly. Emil plans to change the world with graphs and own Larry's yacht by the end of the decade.

[PrincessKushana]

My heart goes out to anyone doing a live tech demo.

[IntellectCorner]

*𝓣𝓲𝓶𝓮𝓼𝓽𝓪𝓶𝓹𝓼 𝓫𝔂 𝓘𝓷𝓽𝓮𝓵𝓵𝓮𝓬𝓽𝓒𝓸𝓻𝓷𝓮𝓻*

0:00 - Introduction: Leveraging Data and Relationships
0:49 - Evolution of Search: From AltaVista to Google
3:03 - Google’s Knowledge Graph: Concepts and Structure
4:50 - GraphRAG Era: Integrating LLMs with Knowledge Graphs
5:28 - What is GraphRAG?
7:06 - Example: Customer Service Bot with GraphRAG
8:46 - Benefits of GraphRAG: Accuracy and Development
10:27 - Easier Development with GraphRAG
12:00 - Comparing Graph and Vector Representations
13:40 - Explainability and Governance in GraphRAG
14:19 - Getting Started with GraphRAG: Data Sources
15:57 - Demo Introduction: Knowledge Graph Builder Tool
18:16 - Knowledge Graph Demo: Building and Visualizing Data
18:48 - Conclusion and QR Code for Resources

[Dr_Fat_Ghost]

i never commented on any of the tech videos till with my 8 years of experience. I got an interview in few days and i wanted to use graphRAG but i knew about graphDB but this video made me realize few things that its not the number of technical words you use to explain something but its how you make such complicated concept look easy. Kudos Prof Emil Eifrem.
Please release more videos on different concepts on GraphRAG.

[babusivaprakasam]

Best refresher starter on Graph RAG. Brilliant effort. Respect!

[twoplustwo]

🎯 Key points for quick navigation:

00:00:00 *📊 Introduction and Background*
- Emil Eifrem introduces his dedication to helping developers build better applications by leveraging relationships between data points,
- Overview of the lecture's focus on the combination of LLMs and knowledge graphs.
00:00:45 *🔍 Evolution of Search Technology*
- Discussion on the history and evolution of web search engines from AltaVista to Google,
- Explanation of the challenges with keyword-based search and how Google's PageRank algorithm, a graph-based algorithm, revolutionized search.
00:02:48 *📚 Introduction of Knowledge Graphs*
- Google's shift from PageRank to Knowledge Graphs, emphasizing the difference between "things" and "strings, "
- Description of the visual structure of Knowledge Graphs, combining structured and unstructured data.
00:04:24 *🧠 The Advent of Gen and AI in Search*
- Google's recent advancements in AI-powered search, integrating LLMs and Knowledge Graphs,
- Explanation of "GraphRAG" and how it combines retrieval-based Knowledge Graphs with Gen technologies.
00:06:01 *🤖 Implementing GraphRAG in Applications*
- Detailed example of building a customer service bot using GraphRAG,
- Explanation of how GraphRAG enhances typical RAG-based applications by leveraging knowledge graphs for better retrieval and context.
00:08:20 *🌟 Benefits of GraphRAG*
- Higher accuracy of responses in AI applications using GraphRAG compared to traditional RAG,
- Easier development of applications once a Knowledge Graph is established, with examples from high-profile companies.
00:10:09 *🛠 Advantages in Development and Governance*
- Clarity and transparency in application development using graphs versus vectors,
- Improved explainability, auditability, and governance for business IT.
00:12:54 *🚀 Getting Started with GraphRAG*
- Steps and considerations in creating a Knowledge Graph,
- Demonstration of the Knowledge Graph Builder tool, showing the process of uploading and visualizing data.
00:18:01 *🎉 Conclusion and Final Thoughts*
- Final insights and practical example using the Knowledge Graph Builder,
- Encouragement to try out the tool and further explore the benefits of GraphRAG in applications.

Made with HARPA AI

[greanbean]

Clear, concise yet compelling story telling!

[KiranRajendran-dt]

Great one. Super helpful to understand the usage of graph in RAG

[animelover]

Great stuff now i need to rewrite and migrwte my LLM apps to this for a try

[IdeaAlchemistHere]

my hands started clapping along the audience when the graph popped up

[swyxTV]

Amazingly well presented. thank you Emil!

[jiayiwu]

7:21, do you think it always need embedding to do GraphRAG?

[johnkintree]

So, a global digital platform could create a shared graph representation of parts of millions of simultaneous conversations that people around the world select to be merged into a form of collective human and digital intelligence and problem solving.

[MJLeeee]

Where would you think GraphRAG will be "really" needed since higher computation is needed compared to Normal RAGs

[ParitoshLD]

knowledge graph as label property, Knowledge graph with owl2 ontologies. Data provenance, uuid creation. There is a good scope in neo4j to have both. Coexistence with ref, owl and label property graph is the one which neo4j should talk

[jakubbartczuk]

That's pretty cool but the title is a bit misleading as it doesn't touch the actual GraphRAG method (that is, a specific paper and project).

[superbaim]

can it do downstream task like summarization ?

[energyexecs]

Aha, I like that GraphRag concept. I am augmenting my LLM now with RAG on PDF documents inside my enterprise. But the results were poor and not released for production. Seems like GraphRAG can help.

[johannesdeboeck]

How is this useful if there is still hallucination happening and the accuracy is only 70%?
LLMs have a preference for their internal knowledge over external knowledge coming from RAG or knowledge graphs.
Anyone has tips to solve this?

[chriseun]

what are the applications of this technology in mapping out professional entworks / relationships? in a way, forming as a basis of a modern, relationship-based CRM?

[markvogt]

NOTHING breeds ENTHUSIASM like... ENTHUSIASM.
"...check this shit out!"

It's fun when you're a PASSIONATE & SKILLED DATA SCIENTIST and you see a presentation by ANOTHER (better!) PASSIONATE & SKILLED DATA SCIENTIST !

LOVED the video...