This Week in Neo4j: Embeddings, Algorithms, Docker, LangChain and more
Blog post from Neo4j
Neo4j is featuring a method to improve embeddings using Neo4j APOC ML procedures, which enhances similarity search in GenAI solutions without relying on conventional techniques. The company has also introduced new algorithms for Directed Acyclic Graphs (DAGs), including Longest Path and Topological Sort. Additionally, there are tutorials available on how to get started with Neo4j on Docker and LangChain templates. Various meetups and events are being organized, including NODES 2023: Watch Recordings, Live Stream: Going Meta: Episode 25, JFokus 2024 in Stockholm, Sweden, Meetup: Meet us in Berlin, DE on February 8 & in Kansas City, MO on February 9. There is also a GraphSummit Series and a GraphAcademy Live session on importing CSV Data. The company's featured Node speaker is Karina Isla-Rios, who discusses the use of graphs in representing clinically meaningful glycomics data to help fight cancer. A tweet from Tomaz Bratanic highlights the need for publicly available text2cypher datasets for finetuning LLMs.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 5 | 2,087 | 216 | 81 | +23% |
| LLM | 3 | 2,401 | 292 | 122 | -7% |
| AI Model Fine-tuning | 1 | 474 | 91 | 59 | +12% |
| Observability | 1 | 1,155 | 262 | 90 | -8% |
| RAG | 1 | 1,125 | 154 | 56 | -17% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.