Találati lista | Tudóstér

001-es BibID:	BIBFORM124086
Első szerző:	Héjja Ferenc (PhD. hallgató)
Cím:	Generative AI for Productivity in Industry and Education / Héjja Ferenc, Bartók Tamás, Roy Dakroub, Kocsis Gergely
Dátum:	2024
Megjegyzések:	Generative AI tools are the cutting edge solutions of complex AI related problems. While investigating state-of-the-art results related to the effect of GenAI in the literature, one can note that the trends most likely lead to the expectation of a positive effect on the middle and long run. Based on these findings we define 4 productivity gain related hypotheses that we study using two types of methodologies. Namely we perform a survey research related to university-industry collaboration and quantitative studies mainly based on industrial productivity metrics. We have partnered with a major IT services provider - EPAM Systems - to be able to track, validate and analyze the key productivity metrics of software development projects, with and without using GenAI tools. This evaluation is being performed on various stages of the Software Development Lifecycle (SDLC) and on several project roles. Our goal is to measure the productivity increase provided by GenAI tools. Although this rese arch has just started recently, considering that the area has extremely high attention we present some initial findings.
ISBN:	9789897586989
Tárgyszavak:	Műszaki tudományok Informatikai tudományok könyvfejezet könyvrészlet Generative Artificial Intelligance (GenAI), Large Language Models (LLM), Industry, Education, Productivity.
Megjelenés:	COMPLEXIS 2024 : Proceedings of the 9th International Conference on Complexity, Future Information Systems and Risk / Ali, Emrouznejad; Luigi, Fortuna; Victor, Chang. - p. 128-135. -
További szerzők:	Bartók Tamás Dakroub, Roy Kocsis Gergely (1983-) (programtervező matematikus)
Pályázati támogatás:	TKP 2021 NKTA 34 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon: