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Foundations of Artificial Intelligence Frameworks: Notion and Limits of AGI

Within the limited scope of this paper, we argue that artificial general intelligence cannot emerge from current neural network paradigms regardless of scale, nor is such an approach healthy for the field at present. Drawing on various notions, discussions, present-day developments and observations, current debates and critiques, experiments, and so on in between philosophy, including the Chinese Room Argument and G…

Licence
OPEN CC-BY-4.0
Authors
Khanh Gia Bui
Published
2025-11-23 · arXiv
Language
en
Length
36705 words
Type
narrative text

Cites 147 works

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4 Conclusion

In its final form, the paper serves mainly what it is intended of - to critique and analyse the non-trivial yet apparent nature of current existing framework in pursuit of the intelligence question, the lacking knowledge, the implicit and explicit holes in our understanding, and the misguided optimism, plus expectation and progression. Furthermore, it also lays out the foundation of thought, in which of the uncertainty currently presenting, partially formalize the philosophy and approaches that would be taken on, given the school of thought in Section 3. If expanded, of make rigorous in which the substance is not eluded in complication, and the unpolished over-mathification of theoretical works, then potentially speaking, such framework introduced at the end would prove useful to the landscape in which of what we think of, as machine, and the modification of the learning machine on top.

Nevertheless, we do not simply reject, less of our rhetoric in the paper itself, as to criticize current practices and development, the stagnation of theoretical studies, and so on. But rather, the focus is to reach toward those that claims of which overstretched the current ability at present in existing structures. Current systems are good of what it is — more specifically, it is a revolution in which absolved the debate between symbolic or neuronic system, into a more sophisticated and generalized form --- and thus advanced alongside computational development to be as it is. Nevertheless, we should still address the elephant in the room, as for AGI is unattainable because of the opaque nature of such terms, the philosophical gap between treatments and how we view such studies of creating intelligent, or in general, proxical-life[^12] subjects, the overreliance on the LLM mode of operation as potentially universal, in which fallacies from itself have already proven wrong, and the practical, mathematical and theoretical frameworks’ inadequacy that is often not realized, but hidden in plain sight. Such is also why developments and further breakthroughs have stalled — by the lacking of which heuristic cannot cover any more. It is then natural, such as in the paper that future work for us is to recognize such systematic mistakes, identifying the foundation’s weakness, and either fix it, connect it, path it, or reframe entirely under different direction. Said directions realized in this paper might not make it into the future; perhaps being superseded by something much more sophisticated. That said, its end goal should still be conceptually interesting, and the critique would stay, much to the disdain of the deniers, and thus the purpose of this inquiry is completed.