Sudhir Hasbe
@shasbe
Chief Product Officer @ Neo4j. ex-Google Sr. Director of Data Analytics Services.
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Good read…
Yes, we did shut down Salesforce a year ago, as we have many SaaS providers—an internal estimate is about 1,200 SaaS shut down. No, I don't think it is the end of Salesforce; might be the opposite. Here is what actually happened and how/why we originally intended to NOT share…
It was fun talking to Sinan Ozdemir and Akshay Bhushan on why knowledge graphs are revolutionizing RAG and AI applications. youtube.com/watch?v=2JBavj…
youtube.com
YouTube
E17: Graph Databases Are the Future of RAG and AI with Sudhir Hasbe
Our product vision: premium, trusted cloud native graph database platform. @shasbe at #GraphSummit Europe
What a fantastic way to end our #GraphSummit in NYC! #Neo4j on Times Square! 🤩👏 @shasbe @emileifrem @steveonjava @chandrarangan
Super sad news. Huge loss to tech community. Life is too short. RIP Susan.
Unbelievably saddened by the loss of my dear friend @SusanWojcicki after two years of living with cancer. She is as core to the history of Google as anyone, and it’s hard to imagine the world without her. She was an incredible person, leader and friend who had a tremendous…
Jerry said it really well. I think of it in two ways: 1. GraphRAG is a superset of vector-only RAG. It's not graphs INSTEAD OF vectors. It's graph AND vectors. 2. As an industry, we already converged on the best way to do Retrieval for the web. The key to a good R was graph…
Graph RAG makes sense if you think about it as a superset of "standard" vector RAG: 1. Find an initial set of nodes via vector/keyword search 2. Augment context by traversing relationships 3. Augment context by also running other graph retrieval algorithms like text-to-cypher…
Super excited to share our vision demo of 𝐆𝐫𝐚𝐩𝐡 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐚𝐬 𝐚 𝐒𝐚𝐚𝐒 offering powered by Microsoft Fabric and Neo4j. This should be ready for customers in coming months. youtube.com/watch?v=dmvpzq…
youtube.com
YouTube
Preview: Microsoft Fabric Neo4j Graph Analytics Workload Demo with...
I am speaking at Microsoft Fabric Community Conference. Please check out my talk if you're attending the event! - via #Whova event app
Awesome read… What I Wish Someone Had Told Me blog.samaltman.com/what-i-wish-so…
Wow. That's the power of graph + vector search compared to just vector search. Check out the screenshot below. Using relationships in your data is a RAG superpower.
Graph RAG makes sense if you think about it as a superset of "standard" vector RAG: 1. Find an initial set of nodes via vector/keyword search 2. Augment context by traversing relationships 3. Augment context by also running other graph retrieval algorithms like text-to-cypher…
Americas, are you ready?? Take a look at the agenda. #NODES2023 continuing livestream: @mesirii introducing Professor @FryRsquared, our keynote speaker and then, #Neo4j - Product Vision and Roadmap with @shasbe 🔵 LIVE: bit.ly/494ZfgQ
Panel discussion on Large language model training: tackling data challenges session at Google Cloud Next with Dr. Ali, Paroma Varma and Benjamin Flast. youtube.com/watch?v=s45kxe…
youtube.com
YouTube
Large language model training: tackling data challenges
Last week we announced support for Vector Search in Neo4j (including AuraDB). Here is a great article by Tomaz Bratanic on how you can use this from #langchain. medium.com/neo4j/langchai…
Super Excited to announce support for Vector Search in Neo4j database and available for our AuraDB customers to try for free. Now you can use Neo4j as long term memory for LLMs and leverage it for RAG based GenAI applications. neo4j.com/blog/vector-se…
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