Dec 3, 2024
8:30am - 9:00am
Hynes, Level 2, Room 204
Neil Gershenfeld1
Massachusetts Institute of Technology1
For AI to have an impact in materials science it's necessary to close a feedback loop from measurement to modeling to training to prediction to validation. Each of these steps can introduce barriers to access. I will survey work on lowering them, including open designs of materials science instrumentation, merging offline measurements with online processing, machine architectures for rapid-prototyping of rapid-prototyping, and computational metrology to effectively measure predictive models.