A Heideggerian analysis of generative pretrained transformer models

To better understand the emergence of new large language models in the context of future possibilities with regard to developing novel artificial general intelligence, it is essential to analyse and conclude the existential implications of these algorithms. Given the high speed of technological advancements in the field of deep learning, generative pretrained transformers (GPT) are the closest thing related to the invention of highly independent and intelligent programs, because they manifest creativity and convey an accurate formation of a worldview model that was never seen before. Because of these aspects, this article proposes an analysis of the concept of Dasein, defined by Heidegger, in the vast description of advancements added in the field of computational intelligence. The analysis methods described here are meant to bypass the complex problems of cognitive sciences with regard to computational intelligence and to create a highly accurate model of mental representation and hierarchisation of emergent intelligent algorithms.