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Zenodo
2026
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| Online Access: | https://doi.org/10.5281/zenodo.19105951 |
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| _version_ | 1866901932130435072 |
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| author | Xiao, Dongsheng |
| author_facet | Xiao, Dongsheng |
| contents | <p><span>Intelligence, in its most elemental definitions in physics and computer science, exhibits an exceptionally elegant form of structural realism. It is manifested in the precise modelling of causal structure in the universe, the efficient compression of vast quantities of disordered information, the asymptotic optimization of survival or computational objectives, and the capacity to preserve system convergence within complex feedback loops. Precisely because intelligence is, at its core, a relational structure and an algorithmic topology, it is inherently formalizable, reproducible, and portable, and can therefore be reconstructed across substrates—from carbon-based synapses to silicon-based semiconductor transistors.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19105951 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Consciousness as an Efficient Dimensionality-Reduction Algorithm for Intelligence Xiao, Dongsheng <p><span>Intelligence, in its most elemental definitions in physics and computer science, exhibits an exceptionally elegant form of structural realism. It is manifested in the precise modelling of causal structure in the universe, the efficient compression of vast quantities of disordered information, the asymptotic optimization of survival or computational objectives, and the capacity to preserve system convergence within complex feedback loops. Precisely because intelligence is, at its core, a relational structure and an algorithmic topology, it is inherently formalizable, reproducible, and portable, and can therefore be reconstructed across substrates—from carbon-based synapses to silicon-based semiconductor transistors.</span></p> |
| title | Consciousness as an Efficient Dimensionality-Reduction Algorithm for Intelligence |
| url | https://doi.org/10.5281/zenodo.19105951 |