Towards Human-like Artificial Intelligence: A Review of Anthropomorphic Computing in AI and Future Trends
Artificial intelligence has brought tremendous convenience to human life in various aspects. However, during its application, there are still instances where AI fails to comprehend certain problems or cannot achieve flawless execution, necessitating more cautious and thoughtful usage. With the advan...
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| Format: | Article |
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MDPI AG
2025-06-01
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| Series: | Mathematics |
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| author | Jiacheng Zhang Haolan Zhang |
| author_facet | Jiacheng Zhang Haolan Zhang |
| author_sort | Jiacheng Zhang |
| collection | DOAJ |
| description | Artificial intelligence has brought tremendous convenience to human life in various aspects. However, during its application, there are still instances where AI fails to comprehend certain problems or cannot achieve flawless execution, necessitating more cautious and thoughtful usage. With the advancements in EEG signal processing technology, its integration with AI has become increasingly close. This idea of interpreting electroencephalogram (EEG) signals illustrates researchers’ desire to explore the deeper relationship between AI and human thought, making human-like thinking a new direction for AI development. Currently, AI faces several core challenges: it struggles to adapt effectively when interacting with an uncertain and unpredictable world. Additionally, the trend of increasing model parameters to enhance accuracy has reached its limits and cannot continue indefinitely. Therefore, this paper proposes revisiting the history of AI development from the perspective of “anthropomorphic computing”, primarily analyzing existing AI technologies that incorporate structures or concepts resembling human brain thinking. Furthermore, regarding the future of AI, we will examine its emerging trends and introduce the concept of “Cyber Brain Intelligence”—a human-like AI system that simulates human thought processes and generates virtual EEG signals. |
| format | Article |
| id | doaj-art-e264f577dfee46688e834f98a4d86b39 |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-e264f577dfee46688e834f98a4d86b392025-08-20T03:50:16ZengMDPI AGMathematics2227-73902025-06-011313208710.3390/math13132087Towards Human-like Artificial Intelligence: A Review of Anthropomorphic Computing in AI and Future TrendsJiacheng Zhang0Haolan Zhang1School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, ChinaNingbo Institute of Technology, Zhejiang University, Ningbo 315104, ChinaArtificial intelligence has brought tremendous convenience to human life in various aspects. However, during its application, there are still instances where AI fails to comprehend certain problems or cannot achieve flawless execution, necessitating more cautious and thoughtful usage. With the advancements in EEG signal processing technology, its integration with AI has become increasingly close. This idea of interpreting electroencephalogram (EEG) signals illustrates researchers’ desire to explore the deeper relationship between AI and human thought, making human-like thinking a new direction for AI development. Currently, AI faces several core challenges: it struggles to adapt effectively when interacting with an uncertain and unpredictable world. Additionally, the trend of increasing model parameters to enhance accuracy has reached its limits and cannot continue indefinitely. Therefore, this paper proposes revisiting the history of AI development from the perspective of “anthropomorphic computing”, primarily analyzing existing AI technologies that incorporate structures or concepts resembling human brain thinking. Furthermore, regarding the future of AI, we will examine its emerging trends and introduce the concept of “Cyber Brain Intelligence”—a human-like AI system that simulates human thought processes and generates virtual EEG signals.https://www.mdpi.com/2227-7390/13/13/2087artificial intelligencehuman-like thinkingelectroencephalogram (EEG)anthropomorphic computationcyber brain intelligenceAI future trends |
| spellingShingle | Jiacheng Zhang Haolan Zhang Towards Human-like Artificial Intelligence: A Review of Anthropomorphic Computing in AI and Future Trends Mathematics artificial intelligence human-like thinking electroencephalogram (EEG) anthropomorphic computation cyber brain intelligence AI future trends |
| title | Towards Human-like Artificial Intelligence: A Review of Anthropomorphic Computing in AI and Future Trends |
| title_full | Towards Human-like Artificial Intelligence: A Review of Anthropomorphic Computing in AI and Future Trends |
| title_fullStr | Towards Human-like Artificial Intelligence: A Review of Anthropomorphic Computing in AI and Future Trends |
| title_full_unstemmed | Towards Human-like Artificial Intelligence: A Review of Anthropomorphic Computing in AI and Future Trends |
| title_short | Towards Human-like Artificial Intelligence: A Review of Anthropomorphic Computing in AI and Future Trends |
| title_sort | towards human like artificial intelligence a review of anthropomorphic computing in ai and future trends |
| topic | artificial intelligence human-like thinking electroencephalogram (EEG) anthropomorphic computation cyber brain intelligence AI future trends |
| url | https://www.mdpi.com/2227-7390/13/13/2087 |
| work_keys_str_mv | AT jiachengzhang towardshumanlikeartificialintelligenceareviewofanthropomorphiccomputinginaiandfuturetrends AT haolanzhang towardshumanlikeartificialintelligenceareviewofanthropomorphiccomputinginaiandfuturetrends |