Diffbot

Exactly 1 week away, still some room left for more hackers, creators, or ideators. RSVP at https://lnkd.in/gJhhB2S8

This is a few months old, but too cool not to share. I've blogged about Diffbot a few times in the past, and apparently they've added a Free Tier, *not* a free trial. Very cool and I definitely recommend checking them out - their APIs are trivial to use. https://lnkd.in/ey4N7AKW

Are you in SF on September 10th? Make sure to come out for this Hack Night at GitHub for a fun evening with incredible builders in the community!

Graph RAG or vector-based RAG? There's some discussions (debate) around which is better. (but we're not continuing this conversation...) Thanks to Tomaz Bratanic, one of the thought leaders and trailblazers in the graph world with cool applications, we jointly explore a project that realizes and visualizes the idea of"bringing unstructured and structured data" together. You'll see side-by-side comparisons of AI-generated responses between vector-only searches and vector+knowledge graph in the video, showing how the latter can outperform the former. Neo4j can store both graph data and text embeddings for vector-based searches, and Diffbot provides verified data from the web — the exact opposite of hallucinated LLM-based sources, so AI applications don't suffer from unreliable outputs. To see the cool network visualization in the app, jump to 3:51 and check out Tomaz and Anej's work. You can always go back and see how we use Diffbot's Article, Natural Language Processing, and Enhance APIs to enrich knowledge graphs with accurate and reliable information. p.s. Who's also going to AI Engineer World's Fair the next 2 days in SF? DM if you're around! #neo4j #diffbot #graphrag

Hi everyone. Have you ever had a pile of personal or work documents that you wanted to make sense of or find all relevant information from? In three well-documented projects, I have addressed this challenge. I implemented a Retrieval-Augmented Generation (RAG) system using a recent architecture, RAPTOR. However, this system could not answer all questions. To cover these limitations, I used a Knowledge Graph. Finally, I implemented everything locally to ensure the privacy of proprietary documents, which is of paramount importance. Visit my webpage to read more and watch the videos of the three projects: https://lnkd.in/gNnnH3Ne In the implementation of RAG, I did not sweep anything under the rug. All limitations are exposed, and I provide suggestions for improvements to set realistic expectations for the deployment of this AI system. Some technologies I used for implementation include: Neo4j Graph DBMS, Diffbot API, Cypher query language, LangChain, Mistral Language model, Nomic AI embeddings, Beautiful Soup for web scraping, Streamlit for UI, Vector Database, Credits: + Inventures 2024 website is the source of my training data. + YouTube thumbnails are made by Sombilon Studios + I am thankful for Javier A. Jaime Serrano, who answered my questions on Graph DBMS. + Soundtrack: Persian Version of Game Of Thrones Song Other references on my page ?? Disclaimers: + This is an educational purpose porjece, in-line with Alberta Innovates privacy policies. Any further use of the sessions data should be checked with their latest privacy policy. + Language models may modify the text during summarization process. The only source of data for reference is their webpage at https://lnkd.in/gHk7k4r6

What's the best IDE to view huge Diffbot data dumps? Hint —

?? Hi friends, we're going to be hanging out at the upcoming AI Engineer World's Fair in San Francisco the week of June 24-28. If you're in San Francisco, we'd love to meet you! Leave a comment to let us know. We may even have a t-shirt in your size! Here, I even modeled for you.

Am I procrastinating on a more important project? Yes. By shopping for overpriced shirts? Also yes.

Neo4j + Diffbot is an incredible combination. Here's how you can learn more about it! This month on the new episode of GraphStuff.fm, the official Neo4j Podcast, my colleagues Jennifer Reif and Jason Koo welcome Leann Chen to talk about knowledge graphs and Diffbot. Leann is a developer advocate at Diffbot and focused on using knowledge graphs to improve LLM based applications. This is a must-listen if you are interested in the intersection of knowledge graphs and LLMs. You can find the full episode here: https://buff.ly/4e7RwB6 Follow me Daniel Bukowski for daily content about the intersection of graphs, data science, and GenAI. #neo4j #diffbot #genai #llm #knowledgegraphs

Looking good!