Bulletin of the American Physical Society
APS March Meeting 2023
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session G51: Autonomous Science
11:30 AM–2:30 PM,
Tuesday, March 7, 2023
Room: Room 321
Sponsoring Unit: FIAP
Chair: Ichiro Takeuchi, University of Maryland, College Park
Abstract: G51.00001 : A Cloud-based AI-driven Autonomous Lab
11:30 AM–12:06 PM
Natural language processing models have emerged as one of the most effective, scalable approaches for capturing human knowledge and modelling chemical processes in organic chemistry. Its use in machine learning tasks demonstrated high quality and ease of use in problems such as predicting chemical reactions [1-2], retrosynthetic routes , digitizing chemical literature , predicting detailed experimental procedures , designing new fingerprints  and yield predictions . In this talk, I'll talk about the impact of language models in chemistry by highlighting the critical role of NLP architectures in implementing the first cloud-based AI-driven autonomous laboratory .
The remote laboratory is made accessible to chemists through the cloud  and is equipped with automation technologies. The AI assists remote chemists with several tasks: designing retrosynthetic trees and suggesting the correct sequence of operational actions (reaction conditions and procedures), or ingesting literature on synthetic procedures to convert them into an executable program. Following supervision by synthetic chemists, the AI self-programs the automation layer and makes decisions on the synthesis execution using feedback loops from analytical chemistry instruments. I will present the platform architecture and its performance across various classes of synthetic tasks.
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