What Do We Mean by GenAI? A Systematic Mapping of The Evolution, Trends, and Techniques Involved in Generative AI.

Francisco José García Peñalvo; Andrea Vázquez Ingelmo

doi:10.9781/ijimai.2023.07.006

Authors

Francisco José García Peñalvo Universidad de Salamanca
Andrea Vázquez Ingelmo Universidad de Salamanca

DOI:

https://doi.org/10.9781/ijimai.2023.07.006

Keywords:

Artificial Intelligence, Content Generation, Generative AI, Generative Models, Machine Learning, Systematic Literature Mapping

Supporting Agencies

This research was partially funded by the Ministry of Science and Innovation through the AvisSA project grant number (PID2020- 118345RB-I00).

Abstract

Artificial Intelligence has become a focal point of interest across various sectors due to its ability to generate creative and realistic outputs. A specific subset, generative artificial intelligence, has seen significant growth, particularly in late 2022. Tools like ChatGPT, Dall-E, or Midjourney have democratized access to Large Language Models, enabling the creation of human-like content. However, the concept 'Generative Artificial Intelligence lacks a universally accepted definition, leading to potential misunderstandings. While a model that produces any output can be technically seen as generative, the Artificial Intelligent research community often reserves the term for complex models that generate high-quality, human-like material. This paper presents a literature mapping of AI-driven content generation, analyzing 631 solutions published over the last five years to better understand and characterize the Generative Artificial Intelligence landscape. Our findings suggest a dichotomy in the understanding and application of the term "Generative AI". While the broader public often interprets "Generative AI" as AI-driven creation of tangible content, the AI research community mainly discusses generative implementations with an emphasis on the models in use, without explicitly categorizing their work under the term "Generative AI".

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