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Agenda

Discussion of some ways AI/ML can help us

• artifact recognition for QA (supervised/unsupervised learning etc - Sergio Garza has already made some progress in this area for VLASS)
• machine learning approaches to the VLASS imaging problem (and to interferometric imaging in general)
• AI help with pipelines (Brian Kirk/Urvashi working on this)
• RFI detection and excision
• Using AI bots (e.g. ChatGPT) to help with scripting/coding, data cleaning etc.
• Using language models to obtain user science goals from proposal abstracts+titles to inform SRDP pipeline choices (e.g. spectral line/continuum/detection expt/imaging exit) (Adele working on related project for ALMA).

Available software resources to try out (scikit-learn, tensor flow, PyTorch etc)