“The knowledge we learn may not change. The way we learn will change very fast.” Dr. Ge Jin explains how large language models are transforming the way geophysics is taught and learned, particularly by enhancing access to clear explanations and accelerating research. He shares why assessment must evolve and how allowing LLMs in coding classes, while focusing on physics and logic, helps students solve harder problems. The conversation explores prompt engineering, secure AI use in industry, transparent writing practices, and the opportunity to build an SEG library-powered model for cutting-edge knowledge. KEY TAKEAWAYS
> Prompt power: Knowing how to ask AI the right way is becoming as important as knowing where to find the answer - daily practice builds skill and confidence
> Continuous learning boost: LLMs speed up literature research and concept review, letting geophysicists grasp new fields in hours instead of weeks
> Strategy ahead: Training AI on the SEG library could provide reliable, advanced knowledge, alongside company‑specific models that protect data and address language bias. GUEST BIO
Dr. Ge Jin is Associate Professor of Geophysics and co-PI of Reservoir Characterization Project at Colorado School of Mines. His research focuses on Distributed Fiber-Optic Sensing (DFOS) applications in the fields of oil & gas, geothermal, CO2 sequestration, smart city, and earthquake hazard. He is also interested in machine-learning applications and seismic imaging. He obtained his Ph.D. in Geophysics from Columbia University in the City of New York, and dual B.S. in Geophysics and Computer Science from Peking University in Beijing. He worked as a research geophysicist in the oil industry for five years before joining Colorado School of Mines as a faculty member in 2019. LINKS
* Read Ge Jin's article, "President's Page: The transformative role of large language models in geophysics education," at https://doi.org/10.1190/tle44050326.1
* Attend IMAGE '25 - https://www.imageevent.org/
* Learn more about the new podcast series, Inside IMAGE, presented by Seismic Soundoff - https://www.imageevent.org/podcast
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