Speaker: Paul-Emil Iusztin
Senior ML/AI Engineer, MLOps, Founder @Decoding ML
Paul Iusztin is a senior AI/ML engineer with over seven years of experience building GenAI, Computer Vision and MLOps solutions. His latest contribution was at Metaphysic, where he was one of the core AI engineers who took large GPU-heavy models to production. He previously worked at CoreAI, Everseen, and Continental. In his last university year, he also tried building his first tech company, Dorel.
He is the co-author of the LLM Engineer's Handbook, a bestseller on Amazon, which presents a hands-on framework for building LLM applications.
Paul is the Founder of Decoding ML, an educational channel on production-grade AI that provides code, posts, articles, and courses, inspiring others to build real-world AI systems. Through Decoding ML, he collaborated with companies such as MongoDB, Comet, Qdrant, ZenML and 11 other AI companies. Paul's teaching career started by teaching the foundations of AI laboratory at the Politehnica University of Timisoara.
Connect with him on LinkedIn.
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Session
The Data Backbone of LLM Systems
Any LLM application has four dimensions you must carefully engineer: the code, data, models and prompts. Each dimension influences the other. That's why you must learn how to track and manage each. The trick is that every dimension has particularities requiring unique strategies and tooling.
Date
Wednesday Apr 9 / 02:45PM BST ( 50 minutes )
Location
Fleming (3rd Fl.)
