Saturday, December 14, 2024
spot_img
HomeTechnologyAI & Machine LearningNew system combines human, artificial intelligence to improve experimentation

New system combines human, artificial intelligence to improve experimentation

The workflow of the human-AI collaborator system developed at ORNL to improve experimentation. Credit: Arpan Biswas and Rama Vasudevan/ORNL, U.S. Dept. of Energy

Though artificial intelligence decreases human error in experimentation, human experts outperform AI when identifying causation or working with small data sets.

To capitalize on AI and researcher strengths, ORNL scientists, in collaboration with National Cheng Kung University, Taiwan, and the University of Tennessee, Knoxville, developed a human-AI collaboration recommender system for improved experimentation performance.

During experiments, the system’s machine learning algorithms, described in npj Computational Materials, display preliminary observations for human review. Researchers vote on data, telling the AI to show similar information or change direction, akin to a streaming service generating suggested content based on users’ activity. After initial guidance, algorithms improve to illuminate relevant data with little human input.

“The foundation of this research is basically not the quantity of the data but the quality of the data that we are aiming for,” ORNL’s Arpan Biswas said.

The experiments and autonomous workflows were supported by the Center for Nanophase Materials Sciences, and algorithm development was supported by the MLExchange project to expand machine learning development at national laboratories.

More information:
Arpan Biswas et al, A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments, npj Computational Materials (2024). DOI: 10.1038/s41524-023-01191-5

Provided by
Oak Ridge National Laboratory

 

Post Disclaimer

The information provided in our posts or blogs are for educational and informative purposes only. We do not guarantee the accuracy, completeness or suitability of the information. We do not provide financial or investment advice. Readers should always seek professional advice before making any financial or investment decisions based on the information provided in our content. We will not be held responsible for any losses, damages or consequences that may arise from relying on the information provided in our content.

RELATED ARTICLES

Most Popular

Recent Comments

error: Content is protected !!