Heeding Good Advice: Scaling Down and Specializing in the Age of Big AI

Created by W.Langdon from gp-bibliography.bib Revision:1.9101

@InProceedings{Trujillo:2025:GPTP,

• author = "Leonardo Trujillo and Yazmin Maldonado and Jose Manuel Munoz and Cristian Sandoval and Juan Flores-R and Daniel E. Hernandez and Luis Gonzalez",
• title = "Heeding Good Advice: Scaling Down and Specializing in the Age of Big {AI}",
• booktitle = "Genetic Programming Theory and Practice XXII",
• year = "2025",
• editor = "Bogdan Burlacu and Fabricio {Olivetti de Franca} and Alexander Lalejini and Stephen Kelly and Wolfgang Banzhaf",
• series = "Genetic and Evolutionary Computation",
• pages = "405--427",
• address = "Michigan State University, USA",
• month = jun # " 5-7",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-981-95-6397-5",
• DOI = "10.1007/978-981-95-6398-2_20",
• abstract = "In a position paper published last year, Togelius and Yannakakis describe a depressing aspect of the current artificial intelligence(AI) landscape, particularly as it relates to academic research. They outline some of the challenges faced by researchers working in traditional academic institutions, that are finding it increasingly difficult to compete with large transnational companies with comparatively unlimited resources. Togelius and Yannakakis take a proactive stance, providing a series of thoughtful insights and survival strategies for depressed AI academics. we discuss some of the advice offered by Togelius and Yannakakis, from the perspective of research work in genetic programming (GP). Moreover, the chapter describes two research projects we are currently developing that align with two of the survival strategies they put forth: reducing the scale and focusing on specialized domains. We conclude that in the current era of AI research, it is important to heed good advice so that traditional academic spaces, particularly for those working with limited resources, continue to thrive and contribute toward shaping future research in AI, ML, and GP.",
• notes = "published in 2026 after the workshop",

}

Genetic Programming entries for Leonardo Trujillo Yazmin Maldonado Robles Jose Manuel Munoz Cristian Sandoval Juan Flores-R Daniel Eduardo Hernandez Morales Luis Gonzalez

Citations