Great article posted yesterday citing MIT and Harvard Researchers using methods to identify optimal interventions for genome regulation. We work on similar operational methods to identify and quantify interventions in education, government and business for portfolio optimization. Causal ML approaches will continue to identify the most effective strategies at lower experimental costs making businesses and public sector enterprise more efficient. “Too often, large-scale experiments are designed empirically. A careful causal framework for sequential experimentation may allow identifying optimal interventions with fewer trials, thereby reducing experimental costs,” Caroline Uhler Caroline Uhler, Themistoklis Sapsis, Jiaqi Yu, Adam Zewe #causalai #causalml https://lnkd.in/gtBRRuEx
