New Report: Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenge
The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing represents a new data-driven research paradigm poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022.
Approximately 50 scientists with various expertise from academia, industry, and DOE national laboratories met to assess the current and future potential for AI/ML and laboratory automation to advance biological understanding and engineering. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing for a variety of DOE mission needs in energy and the environment.
The report describing the workshop findings is now available.