This Week in Neo4j: Announcing NODES 2023, Graph Training, Private ChatGPT, Kafka, NASA, LLMs, H2O and More

NODES 2023 is back for an online, non-stop, 24-hour conference on October 26th! We just opened the call for papers this week, so take a look at your current or recent projects and find a topic you would like to present. Conference content is expected to be as varied as the many use cases for graphs in machine learning, applications, visualization, etc. If you need some assistance developing a topic for your talk, head to the community for tips and get feedback on talk ideas. Make sure to save the date in your calendar.

It’s always a good time to learn something new, especially when it fits into your already busy schedule. Try an email course, broken up into smaller pieces for convenience. In “30 Days to Master Neo4j, a Comprehensive Guide for Developers and Data Scientists with Neo4j Aura”, you’ll learn everything you need to build a data model, import data, write Cypher queries, and put Neo4j into production. A new lesson is delivered to your inbox every weekday, small enough to complete during your morning coffee or tea.

Yolande Poirier


Mike Morley is the Director of AI/ML Strategy at Arcurve. Mike has helped design solutions for engineers, data scientists, and analysts across the environmental, mining, oil, and gas industries with innovative software solutions and technology inventions. He is a graph enthusiast, running a graph user group in Canada, and is a NODES speaker. Follow him on LinkedIn.

In his NODES 2022 presentation with Pete Tunkis, he demonstrates how to utilize data about roles, experience, skills, and capacity to dynamically recommend the best teams using graph technology. Watch his talk!

CHATGPT: How to Create a Private ChatGPT With Your Own Data
Mick Vleeshouwer discusses the architecture and design patterns needed to create your own Q&A engine with ChatGPT/LLMs. He recommends separating the knowledge base from the large language model and only generating answers based on the provided context.
STREAMING DATA: Enabling Neo4j With AWS Managed Streaming for Kafka (MSK)
In this blog, Owen Robertson describes a real-time heterogeneous application and data integration model with a Neo4j graph and AWS/MSK streaming. AWS/MSK integrates the data sources and a single Neo4j query traverses the events.

Michael Hunger dives into the NASA Firms (Fire Information for Resource Management System) dataset, which provides information about active fires around the world. The data is gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on NASA’s Terra and Aqua satellites.

LLMs for ENTERPRISES: A Comprehensive Guide to Navigating the New AI Frontier

In this blog, David Hughes outlines an upcoming series of articles describing large language models: the key concepts, history, legal implications, transformative potential, and risks. Stay tuned for valuable insights, practical guidance, and thought-provoking discussions.

LLM: Fine-Tuning an LLM Model With H2O LLM Studio to Generate Cypher Statements

Generating Cypher with LLMs doesn’t mean you have to leak your proprietary information to OpenAI. Tomaz Bratanic fine-tunes open-sourced LLM models with H2O’s LLM Studio tool to reliably generate Cypher statements.

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