PyData London - 109th Meetup

Venue: Riverbank House, 2 Swan Ln, London EC4R 3AD
Please note:
1. 🚨🚨🚨 A valid photo ID is required by building security. 🚨🚨🚨
2. This event follows the NumFOCUS Code of Conduct. Please familiarise yourself with it before attending.

If your RSVP status says "You're going" you will be able to get in. No need to show your RSVP confirmation when signing in.
If you can no longer make it, please unRSVP as soon as possible.

Code of Conduct:
This event follows the NumFOCUS Code of Conduct. Please get in touch with the organisers with any questions or concerns.

As always, there will be free food and drinks, generously provided by our host, Man Group.

Main Talks

1. Sefik Serengil - RAG Is Dead, Long Live GraphRAG!
   Traditional RAG pipelines typically break documents into independent chunks—such as paragraphs or pages—and convert each chunk into an embedding. While effective for basic retrieval, this approach loses the semantic continuity that naturally exists across chunk boundaries. A sentence at the end of one page may be tightly connected to the first sentence of the next, yet classic RAG treats them as unrelated vector islands. Neo4j’s open-source GraphRAG project addresses this fundamental limitation by converting chunks into a graph representation where entities, relationships, and contextual links are explicitly modeled. Instead of isolated embeddings, GraphRAG creates a connected structure in which both the chunks themselves and the entities inside them can be embedded using graph algorithms and LLM-based backends. This allows semantic meaning to flow across the graph, preserving context at multiple levels while enabling richer retrieval and more accurate reasoning.
   In this talk, we will explore how GraphRAG builds these graph-native representations, how it leverages Neo4j to store and traverse them, and how its embedding strategies differ from conventional RAG systems. We will also discuss practical workflows, example architectures, and the benefits of using a graph-oriented approach for tasks that require higher-fidelity context understanding. Attendees will gain a clear picture of why GraphRAG matters, what problems it solves, and how to start using the open-source package in real-world applications.

Lightning Talks

1. Rafael Garcia-Dias - AI on the NHS: Can federated learning preserve patient privacy?
2. Chaerin Kwon - The Hardest Word to Translate: Teaching Machine Translation to Say "You" in Korean

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Logistics

• Doors open at 6.30 pm (get there early as you'll need to sign in with building security).
• Talks start at 7:00 pm, with drinks afterwards from 9:00 pm at The Banker (EC4).

We have reduced capacity for this event, but there will be plenty of people to discuss data science questions with.
Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members.