Raphael De Lio is a passionate software engineer who loves to think about solutions and ways to improve anything he touches. With over seven years of experience across multiple roles, industries, and countries, he brings a rich perspective to solving technical challenges and connecting with developer communities.
Born in Brazil, Raphael lived in Portugal for six years before moving to the Netherlands in 2022. His main role was a Software Engineer, with expertise in Java, Kotlin, and scalable systems. He also served as the organizer and host of the Dutch Kotlin User Group, building a community for Kotlin enthusiasts in Amsterdam.
Currently, he serves as a Developer Advocate at Redis, where he combines his love for coding with his enthusiasm for empowering others through education, advocacy, and community engagement.
What happens when you combine the Apollo program’s historical data with modern AI tools? You get a way to interact with one of humanity’s greatest adventures like never before!
In this session, I’ll show you how I used Redis OM Spring and Spring AI to explore Apollo mission data—aligning transcripts, telemetry, and images to uncover hidden connections and insights. We’ll dive into how Semantic Search powered by vector embeddings makes sense of unstructured text, how Redis as a vector database enables lightning-fast retrieval, and why these tools unlock new ways to explore complex datasets.
Don’t know what embeddings or vector databases are? No worries—I’ll break it all down and show you how it works.
Come for the Moon missions, stay for the AI magic, and leave ready to build your own intelligent search experiences!
A Count-Min Sketch, a Bloom Filter, and a TopK might sound fancy, but they’re just smart ways to work with huge amounts of data using very little memory.
In this talk, we’ll explore three powerful probabilistic data structures that trade a bit of accuracy for a lot of speed and scalability. You’ll learn:
- What Count-Min Sketch, Bloom Filter, and TopK actually are
- How each of them works under the hood
- How I used them together to build an efficient version of Trending Topics for Bluesky
By the end, you’ll see how these tools help you process large data streams without blowing up your memory, and how to apply them in real-world systems where being fast matters more than being perfect.
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