Episode 24: Beyond Correlation - Teaching AI the Rules of Biology

<p>This week, we sit down with <a href="https://www.linkedin.com/in/jean-baptiste-morlot-45918414a/" target="_blank" rel="noopener noreferer">Jean-Baptiste Morlot</a> of Deep Life, who makes the case that the drug discovery field has been asking the wrong thing of its AI models. Correlation-based machine learning can find patterns, but it can&#39;t tell you why a cell is sick or what it would take to make it healthy again. Jean-Baptiste walks us through how single-cell sequencing unlocked the data volume needed to train something far more ambitious: a causal world model of cellular biology that learns the underlying rules of disease rather than memorizing them.</p><p>We get into how Deep Life&#39;s TwinCell platform works, why most virtual cell benchmarks are quietly inflated by popularity bias, and what it means to build an interpretable AI that a biologist can trust. </p>