Maxime Labonne: Designing beyond Transformers | Learning from Machine Learning #12

On this episode of Learning from Machine Learning, I had the privilege of speaking with Maxime Labonne, Head of Post-Training at Liquid AI. We traced his journey from cybersecurity to the cutting edge of model architecture. Maxime shared how the future of AI isn't just about making models bigger—it's about making them smarter and more efficient.

Maxime's work demonstrates that challenging established paradigms requires taking steps backward to leap forward. His framework for data quality—accuracy, diversity, and complexity—offers a blueprint for anyone working with machine learning systems.

Most importantly, Maxime's perspective on learning itself—treating knowledge acquisition like training data exposure—reminds us that growth comes from diverse, high-quality experiences across different contexts. Whether you're trai ...