Language models in the lab: moving towards a robot chemist
Nov 10, 2023
2:30PM to 3:30PM
Date(s) - 10/11/2023
2:30 pm - 3:30 pm
Computer Science PhD student, University of Toronto
Automating chemistry experiments in self-driving labs is an exciting area but there remain many challenging problems we need to solve. While adding natural language interfaces to autonomous chemistry experiment systems lowers the barrier to using complicated robotics systems and increases utility for non-expert users, translating natural language experiment descriptions from users into low-level robotics languages is nontrivial. Furthermore, while recent advances have used large language models to generate task plans, reliably executing those plans in the real world by an embodied agent remains challenging. To enable autonomous chemistry experiments, robots must interpret natural language commands, perceive the workspace, autonomously plan multi-step actions and motions, consider safety precautions, and interact with various laboratory equipment. In this talk, I will describe our progress towards creating a robot chemist, including a framework that can verifiably plan experiments from natural language inputs and execute them on a real robot.
Marta is a Computer Science PhD student at the University of Toronto working with Alán Aspuru-Guzik. Her research lies at the interaction of AI, natural language processing, and automation of chemistry experiments using self-driving labs. Previously, she completed her MSc in Computer Science at the University of Toronto and HBSc in Chemical Biology at McMaster University.
In-Person: ABB 102