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DTSTART;TZID=America/New_York:20260917T160000
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UID:62246-1789660800-1789664400@astrobiology.com
SUMMARY:NASA Ames AI/ML Seminar: Harnessing Trust: Agentic AI Workflow in Exoplanetary Climate Modeling
DESCRIPTION:JOIN THE AI/ML SEMINAR SERIES \nEveryone 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. \nThe speaker for this event will be Dr. Eric Wolf from the University of Colorado\, Boulder.\nTitle: Harnessing Trust: Agentic AI Workflow in Exoplanetary Climate Modeling \nAbstract: 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 \nfind relevant citations\, write plotting scripts\, perform critical calculations\, act on real file systems\, and \nderive real scientific results? The inherent probabilistic nature of LLM outputs contradicts trained scientific skepticism of anything that cannot be reproduced deterministically. \nIn 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.
URL:https://astrobiology.com/event/nasa-ames-ai-ml-seminar-harnessing-trust-agentic-ai-workflow-in-exoplanetary-climate-modeling/
LOCATION:Online – Webinar
ATTACH;FMTTYPE=image/png:https://astrobiology.com/wp-content/uploads/2026/03/NASA-Ames-AIML-Seminar-Series-Machine-Learning.png
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DTSTART;VALUE=DATE:20260924
DTEND;VALUE=DATE:20260926
DTSTAMP:20260810T182335Z
CREATED:20260810T182335Z
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UID:61037-1790208000-1790380799@astrobiology.com
SUMMARY:SpaceCHI 2026
DESCRIPTION:Space exploration is at the dawn of a new era. Major reductions in launch costs and the rise of the private space industry are rapidly democratizing access to space. Once the exclusive domain of a few large government agencies\, space systems and services are now poised to become increasingly intertwined with everyday life. This transformation is giving rise to entirely new economic sectors and opening the door to novel uncharted research directions. \nHuman-Computer Interaction (HCI) has historically played a vital role in helping to scale emerging technologies and maximize their societal benefits – from the laser printer and the personal computer to groupware and AI. HCI’s tools and methodologies\, honed over decades of refinement\, are uniquely positioned to help drive the current space transformation. \nSpaceCHI seeks to catalyze this potential by providing an interdisciplinary platform for researchers and practitioners worldwide. Hosted at NASA Ames\, one of the most revered bastions of space research\, and located in Silicon Valley\, the beating heart of technological innovation\, this year’s edition of the conference promises an unforgettable experience featuring insights from uniquely qualified experts. SpaceCHI 2026 adopts a hybrid format\, welcoming both on-site and remote participants to present and engage. It is our pleasure inviting you to join us in shaping the future of HCI and space exploration!
URL:https://astrobiology.com/event/spacechi-2026/
LOCATION:NASA Ames Research Center\, https://www.nasa.gov/ames/\, Moffett Field\, CA\, 94035-1000\, United States
ATTACH;FMTTYPE=image/jpeg:https://astrobiology.com/wp-content/uploads/2026/08/SpaceCHI26-scaled-1.jpg
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