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 AI to explore Apollo mission data—aligning transcripts, telemetry, and images to uncover hidden connections and insights.
We’ll dive into how Semantic Search helps make sense of unstructured text, why embeddings are the key to searching for intent instead of keywords, and how AI tools can enrich even the most complex datasets. Don’t know what embeddings or vector databases are? Don’t worry—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 create your own data-driven adventures!
A Count-Min Sketch is a data structure that estimates how often something appears in a large dataset while using very little memory. It relies on a table and hash functions to map items to specific spots in the table. Adding an item increases the values in those spots, and checking an item’s count returns the smallest value from them. While not exact due to possible collisions, it’s efficient and great for approximate counts when precision isn’t critical.
In this talk, we’ll explore:
• What this data structure is
• How it works internally
• How I used it to build an efficient version of Trending Topics for Bluesky
By the end of this session, you’ll have a clear understanding of Count-Min Sketches, why they’re valuable for handling large-scale data efficiently, and how you can apply them to solve real-world problems.
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