NASA Ames AI/ML Seminar: Harnessing Trust: Agentic AI Workflow in Exoplanetary Climate Modeling
Everyone is invited to the monthly artificial intelligence and machine learning virtual seminar hosted by the AI-Astrobiology Initiative at NASA Ames Research Center. Previously recorded seminars can be found on the AI-ML Astrobiology YouTube channel.
The speaker for this event will be Dr. Eric Wolf from the University of Colorado, Boulder.
Title: Harnessing Trust: Agentic AI Workflow in Exoplanetary Climate Modeling
Abstract: Large language models (LLMs) are now broadly used across society, and their usage amongst research scientists is increasing. On one hand LLMs have helped resolve open problems in mathematics and physics, on the other a hallucinated reference can land you a 1-year ban from arXiv. The top-end capability of high-functioning AI systems is not in question, but trust in everyday workflows is. Should you let an LLM
find relevant citations, write plotting scripts, perform critical calculations, act on real file systems, and
derive real scientific results? The inherent probabilistic nature of LLM outputs contradicts trained scientific skepticism of anything that cannot be reproduced deterministically.
In this talk, Dr. Wolf will discuss how LLMs moved from a hesitant curiosity to the agentic connective tissue linking my entire research workflow. I review real world use cases from my work in exoplanetary climate modeling, in ascending complexity and stakes. I report successes, failures, and lessons learned along the way. Trust in AI-driven agentic workflows is not a vibe, but a property of the harness you build around it. Encouragingly, building agentic workflows is increasing efficiency, reducing technical barriers, and opening new research opportunities.