AI Journeys: Avoiding the Pitfalls, Embracing the Potential with Graphs

This is a joint event with our event partners from Neo4j. For more information check out their homepage here.
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ABOUT THE TALKS

Winter is Coming... or is it? How to avoid the next AI winter
by Emily Gorcenski

The history of AI is full of boom and bust cycles, the most famous of them being the long AI winter that started in the 1970s following several high-profile failures to deliver. This talk will be a look at historical events in AI development, ranging from the DARPA Speech Understanding Research project to the Lighthill Report and the failure of Japan's 5th Generation Computer System. We'll explore what drives AI hype and how mismanaged expectations lead to systemic failures in project management, product management, and technical delivery. But we'll also look at what does work, and how we can avoid stepping on the same traps that have caught previous generations of AI research: by identifying clear product value, by developing continuous delivery for AI, and by tuning out the noise

Superpower your LLM-RAG Applications with a Knowledge Graph Platform like Neo4j
by Michael Hunger

As you might experienced yourself, LLMs like ChatGPT are powerful but not always trustworthy assistants. Being stochastic models that don't have access to the relevant data they can fabricate answers that are not grounded in truth. With a combination of a knowledge graph that can store real world information at high fidelity and vector search, you can provide the LLM with the correct, relevant context information it needs to answer your users questions. This is a combination of implementations of a pattern known as retrieval augmented generation (RAG) but with a twist.

In this talk we'll explain and demonstrate the building blocks of such an approach and show an example in code and in live action. Of course nothing is perfect, that's why it's important to walk through challenges with building such GenAI apps and how to address them. And if there is interest, we can dive into some more advanced patterns.
Learn more at https://neo4j.com/generativea

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ABOUT THE SPEAKERS

Emily Gorcenski
I am a Principal Data Scientist and Head of Data for Thoughtworks Germany. I have a background in research engineering and computational and applied mathematics. I work as a data and software engineer, developing and architecting data driven applications. I am a strong advocate for data journalism and have contributed research, materials, and expertise to multiple award-winning projects.

Michael Hunger
has been passionate about software development for more than 35 years. For the last 14 years, he has been working on the open source Neo4j graph database filling many roles, most recently leading Product Innovation and Developer Strategy. He especially loves to work with graph-related projects, users, and contributors, his current focus is generative AI, cloud integrations and developer experience.
As a developer Michael enjoys many aspects of programming languages, learning new things every day, participating in exciting and ambitious open source projects and contributing and writing software related books and articles. Michael spoke at numerous conferences and helped organize several of them. His efforts got him accepted to the JavaChampions program.
Michael helps kids to learn to program by running weekly girls-only coding classes at local schools.
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ON THE AGENDA

18:30 Welcome & Snacks
19:00 Stage Time & Q&A
20:15 Networking
21:30 See you next time!

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Code of Conduct
We adhere to the Berlin Code of Conduct to ensure a welcoming and respectful environment for all participants. The event space operates under largely compatible Thoughtworks Meetups & Events CoC.

Accessibility
The Location is accessible for wheelchair users. This includes the entrance (no steps to get into the location), toilets and the stage.