Speaker
Description
Many grand challenges like climate change and pandemics emerge from complex interactions of millions of individual decisions. While LLMs and AI agents excel at individual behavior, they can't model these intricate societal dynamics.
Enter Large Population Models LPMs: a new AI paradigm simulating millions of interacting agents simultaneously, capturing collective behaviors at societal scale. It's like scaling up AI agents exponentially to understand the ripple effects of countless decisions.
AgentTorch, our open-source platform, makes building and running these massive simulations accessible. It's optimized for GPUs, allowing efficient simulation of entire cities or countries. Think PyTorch, but for large-scale agent-based simulations. LPMs are already making real-world impact. They're being used to help immunize millions of people by optimizing vaccine distribution strategies, and to track billions of dollars in global supply chains, improving efficiency and reducing waste.
In this talk, we'll dive into the underlying technology of LPMs, provide an overview of AgentTorch, and explore how you can contribute to both our research at MIT and the open-source project. We'll also discuss intriguing topics like prompting LPMs versus LLMs, opening up new avenues for AI development. Whether you're interested in complex systems, AI, or tackling global challenges, LPMs offer exciting opportunities for innovation and impact.
Project: github.com/AgentTorch/AgentTorch
Join us: lpm.media.mit.edu/join
Session author's bio
Ayush is a PhD student at MIT, supervised by Prof. Ramesh Raskar. His research is focused on AI and complex systems, with he currently leads the MIT project on Large Population Models (lpm.media.mit.edu). He has published in top-tier AI conferences (CVPR, AAMAS, KDD, etc.) and journals (BMJ, Vaccine), and has won best (student) paper awards at AAMAS, CVPR workshops, and ICML workshops. Ayush's projects have been deployed across multiple countries (reaching over 20 million people), resulted in 25 patents, and have been covered by global press (Reuters, The Weather Channel, VentureBeat, etc.). He has also spent time at the Mayo Clinic and JP Morgan AI Research. Prior to MIT, Ayush did research in in-browser machine learning at Adobe and received the Adobe Outstanding Young Engineer Award in 2020. He earned his MS from MIT in 2022 and his BE from Delhi College of Engineering in 2018.
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