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Keywords = praxio-onto-epistemology

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4 pages, 195 KiB  
Proceeding Paper
Large Language Models Cannot Meet Artificial General Intelligence Expectations
by Wolfgang Hofkirchner
Comput. Sci. Math. Forum 2023, 8(1), 67; https://doi.org/10.3390/cmsf2023008067 - 11 Aug 2023
Cited by 1 | Viewed by 1916
Abstract
Large language models (LLMs), in particular, diverse versions of Chat GPT, have been setting the agenda for expectations of artificial general intelligence (AGI) once again. Here, it will be argued that such expectations will not be satisfied by LLMs. The argumentation will not [...] Read more.
Large language models (LLMs), in particular, diverse versions of Chat GPT, have been setting the agenda for expectations of artificial general intelligence (AGI) once again. Here, it will be argued that such expectations will not be satisfied by LLMs. The argumentation will not focus on concrete technical specifics of LLMs that hinder the materialization of AGI. It is rather the AGI itself that lacks the means for being realized. From a techno-social systems perspective, neither LLMs nor AGI can be called intelligent. Only (human) social systems, including techno-social systems, or humans or living systems or other physical systems that self-organize can show the feature of intelligence, but not man-made technological tools. The argumentation will cover praxiological, ontological and epistemological considerations. Full article
(This article belongs to the Proceedings of 2023 International Summit on the Study of Information)
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