Getting Started With GenAI: Pragmatic Advice for Real-World App Building
On-Demand
If you want to add GenAI to your skill set, this on-demand webinar is the right place to start.
Unlike tutorials for hypothetical “Hello World” demo chatbots, this session will show you how to build GenAI applications for real-world use cases. That includes how to get accurate, explainable answers from LLMs.
We’ll cover:
- The promise of GenAI – and common pitfalls like LLM hallucinations
- GenAI tech stack fundamentals, from database to developer application technologies
- The benefits of grounding GenAI apps in knowledge graphs with native vector search
- How to implement retrieval-augmented (RAG) workflows
- Real-world coded examples
Afterward, we’ll give you the reference applications and materials you need to continue your learning journey.
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Speakers
Andreas Kollegger
Sr. Developer Advocate, Neo4j
Andreas is a technological humanist. Starting at NASA, Andreas designed systems from scratch to support science missions. Then, in Zambia, he built medical informatics systems to apply technology for social good. Now with Neo4j, he is spreading the good news about how to think in graphs and to validate and extend our intuitions about how the world works. Everything is connected.
Zachary Blumenfeld
Product Specialist, Neo4j
Zach helps empower the field with Neo4j’s industry-leading graph data science capabilities. Zach is a graph enthusiast who helps data scientists, engineers, and business leaders understand and implement graph analytics to solve challenging business problems. He has first-hand experience with a wide range of modern-day analytical challenges, including criminal fraud detection, identity resolution, and recommendation systems. Serving in both data science and software developer capacities, Zach has applied graph computing to law enforcement and government entities in support of missions that counter drug trafficking, human smuggling, money laundering, and child exploitation. He has led the development and deployment of full-stack graph systems designed to facilitate broad search and analytical query requirements.