Zoom Recording Passcode: t7^u=4b!

In this talk, I will show how combining large ensembles of cosmological simulations with machine learning opens up new possibilities for advancing our understanding of cosmology, galaxy formation, and dark matter. I will introduce the Backlight, CAMELS, and DREAMS projects—each involving thousands of state-of-the-art N-body or hydrodynamic simulations. While their goals differ, they share a common philosophy: simulate a diverse set of universes and use machine learning to uncover complex patterns in the data. In the final part of the talk, I will explore the challenges of managing petabytes of data and navigating the growing body of scientific papers generated from these simulations. I will then discuss how AI agents can assist with these challenges and potentially transform how we conduct research.