For citation:
Anikin V. M. Artificial Intelligence from a Physicist’s Perspective and Data by LLM DeepSeek. Izvestiya of Saratov University. Physics , 2026, vol. 26, iss. 2, pp. 233-242. DOI: 10.18500/1817-3020-2026-26-2-233-242, EDN: YOKUKW
Artificial Intelligence from a Physicist’s Perspective and Data by LLM DeepSeek
Background and Objectives. A semantic, etymological, and philosophical analysis of the term “artificial intelligence” is conducted. The semantic inconsistency between the components of this oxymoronic term is demonstrated and is proposed to be figuratively expressed in the form of an aphorism: “Intelligence by name, an imitator by nature”. The term includes as an integral part the fundamental concept of “intelligence”, which in psychology refers to the totality of human abilities to construct representations of reality and to construct target actions based on them. This often leads to the attribution (for various purposes) of mental and emotional properties to AI systems by non-specialists, although these systems, based on computer programs, can be considered merely cognitive tools. Materials and Methods: The theoretical analysis of the problematic was conducted in the context of “dialogues” with the DeepSeek-V.3.2 Large Language Model, which demonstrates the logic and semantic coherence of the generated texts. Based on the content of the generated texts, it was concluded that this language model was trained using a set of texts whose content adequately and accurately reflects the functional role of neural networks. Results: Large language model positively analyzed various aspects of the opinion regarding the inappropriateness of the term “artificial intelligence” and the proposal to replace it in scientific discourse with the more accurate term “imitator of human cognitive functions”. It is noted that the texts generated by DeepSeek reproduce a certain cultural pattern of a “good conversationalist” – the presentation is conducted in an emphatically respectful style, with the presentation of arguments and facts, and the identification of controversial areas. Specific external textual material for the discussion was recent media reports, which distorted the essence of artificial intelligence systems for the sake of false sensationalism. It is substantiated that, in the applied context, the term “AI” remains the “working” term, which has a 70-year history and essentially serves as a brand symbol for the refined concept of “imitator of human cognitive functions”. Conclusion: The study is based on a recursive dialogue with the DeepSeek Large Language Model, which itself becomes an object of methodological reflection.
- Brocman J., ed. What to Think About Machines That Think: Today’s Leading Thinkers on the Age of Machine Intelligence. New York, Harper Perennial, 2015. 576 p.
- Za nauku (MIPT) [For Science]. Available at: https://zanauku.mipt.ru/2022/06/09/tajny-boga-iz-mashiny/ (accessed 14.02.2026 (in Russian).
- Kholodnaya M. A. Cognitive Styles: On the Nature of the Individual Mind. Moscow, PER SE, 2002. 304 p. (in Russian).
- Sloman S., Fernbach P. The Knowledge Illusion: Why We Never Think Alone. New York, Riverhead Books, 2017. 304 p.
- Kobelev N. B. Artificial intelligence and imitation of human functions. Мoscow, KURS, 2026. 112 p. (in Russian).
- Sosnin E. A., Poizner B. N. Results of intellectual activity in creative industries. Мoscow, INFRA-M, 2026. 448 p. (in Russian).
- Sosnin E. A. Characterological concept of artificial intelligence. In: Min’kov S. L., ed. Innovations-2024: Collection of materials from the XX International School-Conference of Students, Postgraduates, and Young Scientists (April 25–27, 2024). Tomsk, STT, 2024. 658 p. (in Russian) (in Russian).
- Lipatova I. I. Machine Learning and Inventions. Patents and Licenses. Intellectual Rights. 2024, no. 8, pp. 2–10 (in Russian). EDN: FPWFHW
- Goodfellow I., Bengio Y., Courville A. Deep Learning. Cambridge, MA, MIT Press, 2017. 800 p.
- Floridi L., Chiriatti M. GPT-3: Its Nature, Scope, Limits, and Consequences. Minds & Machines, 2020, vol. 30, pp. 681–694. https://doi.org/10.1007/s11023-020-09548-1
- Manguel A. Curiosity. New Haven, CT, Yale University Press, 2015. 400 p.
- Broslav M. R., Yablokova O. A., comps. Autobiography of a neural network. Moscow, Izdatel’stvo AST, 2023. 224 p. (in Russian).
- Anikin V. M., Poizner B. N. A provoking for undergraduate to verbalization of scientific judgment in master thesis as a method of knowledge. Tomsk State University Journal of Philosophy, Sociology and Political Science, 2013, no. 2 (22), pp. 15–20 (in Russian). EDN: QBKZMF
- Anikin V. M., Poizner B. N. Dissertantu o dissertatsii: semanticheskiy aspect [To the dissertation candidate about the dissertation: Semantic aspect]. Moscow, INFRA-M, 2024. 225 p. (in Russian). https://doi.org/10.12737/1909143
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