ERef Bayreuth

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Unlocking the Power of Generative AI Models and Systems such as GPT-4 and ChatGPT for Higher Education : A Guide for Students and Lecturers

Title data

Gimpel, Henner ; Hall, Kristina ; Decker, Stefan ; Eymann, Torsten ; Lämmermann, Luis ; Mädche, Alexander ; Röglinger, Maximilian ; Ruiner, Caroline ; Schoch, Manfred ; Schoop, Mareike ; Urbach, Nils ; Vandirk, Steffen:
Unlocking the Power of Generative AI Models and Systems such as GPT-4 and ChatGPT for Higher Education : A Guide for Students and Lecturers.
Hohenheim , 2023 . - 46 p. - (Hohenheim Discussion Papers in Business, Economics and Social Sciences ; 2023,02 )

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Project information

Project title:	Project's official title Project's id Projektgruppe WI Digital Society No information

Further data

Item Type:	Working paper, discussion paper
Additional notes:	Whitepaper
Institutions of the University:	Faculties > Faculty of Law, Business and Economics > Department of Business Administration Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration VII - Information Systems Management and Digital Society Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration VII - Information Systems Management and Digital Society > Chair Business Administration VII - Information Systems Management and Digital Society - Univ.-Prof. Dr. Torsten Eymann Research Institutions Research Institutions > Affiliated Institutes Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Result of work at the UBT:	Yes
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics
Date Deposited:	13 Apr 2023 06:46
Last Modified:	13 Apr 2023 06:46
URI:	https://eref.uni-bayreuth.de/id/eprint/75892