Ep. 30: The Potential of Generative A.I. as a Research Assistant for Measurement Science
Update: 2024-11-01
Description
In this episode, podcast co-hosts Dr. Dwight Stoll and Dr. James Grinias talk with Dr. Farooq Wahab, Research Engineering Scientist at the University of Texas at Arlington. Wahab has interests and expertise in chiral separations, improving the green-ness of chromatographic separations, new detectors for chromatography such as microwave rotational spectroscopy, and new techniques for signal processing in chromatography, among other areas. He and several coauthors recently published a paper in Analytical Chemistry discussing their experiences using generative artificial intelligence (i.e. chatGPT) as a research assistant when working on tasks in measurement science ranging from extraction of rotational microwave spectra from free induction decay signals, to baseline removal from chromatographic data.
In the conversation we talk about the origins of this study, strengths and weaknesses of chatGPT as a research assistant in the analytical chemistry space, and the role of generative AI in chemistry teaching and learning. We also touch on tips and tricks also published by Wahab and coworkers for dealing with equations and symbol-heavy text when using generative AI tools. One very interesting application of these tricks is in the translation of relatively old (decades) papers that were published before English became the standard language for much of science publication.
In the conversation we talk about the origins of this study, strengths and weaknesses of chatGPT as a research assistant in the analytical chemistry space, and the role of generative AI in chemistry teaching and learning. We also touch on tips and tricks also published by Wahab and coworkers for dealing with equations and symbol-heavy text when using generative AI tools. One very interesting application of these tricks is in the translation of relatively old (decades) papers that were published before English became the standard language for much of science publication.
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