Artificial and Biological Intelligence: Hardware vs Wetware

Piero Chiarelli

doi:doi:10.11648/j.ajap.20160506.19

| Peer-Reviewed

Artificial and Biological Intelligence: Hardware vs Wetware

Piero Chiarelli

Published in American Journal of Applied Psychology (Volume 5, Issue 6)

Received: 9 December 2016 Accepted: 22 December 2016 Published: 30 December 2016

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

By starting from physical principles, the paper formulates the basis of the biological intelligence and coscience formation. The work shows that far from equilibrium, the principle of maximum energy dissipation, in a fluid phase, brings the molecules to organize themselves in living systems (ordered stationary states) that sustain energy-matter fluxes that determine the architecture of the dissipative system. The driver of the process is the energy; the matter is the substrate. On this base, and thanks to a “selection rule”, the living systems developed a bi-phasic structure consisting of a solid network permeated by a liquid where fluxes of ions and molecules can be maintained. In this way they realize a “wetware” where the energy and the organization/information are handled, and where a high specialization of functions can be obtained by using the spatial delocalization leading to the development of the complexity of the shape. The outputs of a living system can be divided in two categories: 1) macroscopic outputs: Movements, definition of an organized reaction or plan of action, and 2) microscopic ones: Plastic rearrangement of structures, migration of chemical species and electrochemical dynamics (transportation of matter, rearrangement, sensing, storage and information handling). The biological intelligence is a product of these basic processes where the wetware (matter substrate) is continuously modified by the energy-matter fluxes. On this base, the artificial intelligence of computers can be seen as a subclass of intelligent processes since it owns some limitations due to the invariance of the material substrate (that is not self-modified by the energy fluxes) and by the unique form of the flux of matter that is given by the electron current. Finally, the definition of a bio-inspired artificial intelligence is discussed.

Published in	American Journal of Applied Psychology (Volume 5, Issue 6)
DOI	10.11648/j.ajap.20160506.19
Page(s)	98-103
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Generation of Life, Living Systems, Biological Intelligence, Biological Conscience, Artificial Intelligence, Matter Self-Organization, Maximum Free Energy Dissipation

References

[1]	I. Prigogine, Bulletin de la Classe des Sciences, Academie Royale de Belgique 31: (1945) 600–606.
[2]	I. Prigogine, Étude thermodynamique des Phenomènes Irreversibles, (Desoer, Liege 1947).
[3]	B. H. Lavenda, Thermodynamics of Irreversible Processes, (Macmillan, London, 1978).
[4]	M. Šilhavý, The Mechanics and Thermodynamics of Continuous Media, (Springer, Berlin, 1997) p. 209.
[5]	Y. Sawada, Progr. Theor. Phys. 66, 68-76 (1981).
[6]	W. V. R Malkus, and G. Veronis, J. Fluid Mech. 4 (3), 225–260 (1958).
[7]	L. Onsager, Phys. Rev. 37 (4), 405–426 (1931).
[8]	M. Suzuky and Y. Sawada, Phys. Rew. A, 27-1 (1983).
[9]	W. T. Grandy, Entropy and the Time Evolution of Macroscopic Systems, (Oxford University Press2008).
[10]	E. Madelung, Z. Phys. 40, 322-6, (1926).
[11]	I. Bialynicki-Birula, M. Cieplak and J. Kaminski, Theory of Quanta, (Oxford University Press, Ny 1992).
[12]	J. H. Weiner, Statistical Mechanics of Elasticity (John Wiley & Sons, New York, 1983), p. 316-317.
[13]	Chiarelli, P., “Can fluctuating quantum states acquire the classical behavior on large scale?” J. Adv. Phys. 2013; 2, 139-163; arXiv: 1107.4198 [quantum-phys] 2012.
[14]	Chiarelli, P., “Far from equilibrium maximal principle leading to matter self-organization” submitted to J. Adv. Chem., 5 (3) (2013) pp. 753-83.
[15]	Chiarelli, P., Does life needs water or can be generated other fluids?, O. J. BioPhys., 4,. (2014) pp. 29-38.
[16]	Y. B. Rumer, M. S. Ryvkin, Thermodynamics, Statistical Physics, and Kinetics (Mir Publishers, Moscow, 1980).
[17]	Suzuki, M., Sawada, Y., “Relative stabilities of metastable states of convecting charged-fluid system by computer simulation”, Phys. Rev. A, 1-27, (1982).
[18]	C. P. McKay, H. D. Smith, “Possibilities for methanogenic life in liquid methane on the surface of Titan”, Icarus 178 (2005) 274–276.
[19]	Committee on the Limits of Organic Life in Planetary Systems, Committee on the Origins and Evolution of Life, National Research Council; The Limits of Organic Life in Planetary Systems; The National Academies Press, 2007; page 74.
[20]	De Rossi, D., C. Domenici, Chiarelli, P.,: Analog of Biological Tissue for Mechanoelectrical Transduction: Tactile sensor and muscle-like actuators, in Sensors and Sensory Systems for Advanced robots, P. Dario Ed., 210-18, Nato ASi series, Springer Verlag, Berlin, 1988.
[21]	Chiarelli, P., The pro-elastic behavior of a gel thin tube Materials Science and Engineering C 24 (4): 463-471•June 2004.
[22]	Chiarelli, P., De Rossi, D., Modelling and Mechanical Characterization of Thin Fibres of Contractile Polymer Hydrogels, J. Int. Mat. Syst. & Struc., 3, 396-417, 1992.
[23]	Chiarelli, P., De Rossi, Polyelectrolyte Intelligent Gels: design and Applications, Ionic Interactions in Natural and Synthetic Macromolecules, First Edition. Edited by Alberto Ciferri and Angelo Perico. 2012 John Wiley & Sons, Inc DOI: 10.1002/9781118165850. ch15
[24]	Chiarelli, P., De Rossi, D., Basser, P.,: Hydrogel Stress-Relaxation, J. Int. Mat. Syst. & Struc., 4, 176-83, 1993.
[25]	Grimby, L., Hannerz, J., Hedman, B., Contraction time and voluntary discharge properties of individual short toe extensor motor units in man. J. Pysiol. 1979 Apr; 289: 191–201.
[26]	Chiarelli, P., Eng, J., Basser, P.,: "A Polymer-based method to measure contact stress", Proc. Symposium on Polymer Gels, Tsukuba, Japan, 1989
[27]	A. J. Grodzinsky and N. A. Shoenfeld., Polymer, 18, 5 (1977).
[28]	Clegg, J., Walker; J., A., Miller, J., F., et. al., Genetic Programming for prevention of cyber terrorism through dynamic and evolving intrusion, Decision Support Systems, 43 (4): (2007). 1362–1374.
[29]	Jamil El-Ali1, Peter K., et al., Cells on chips, NATURE 442, 27 (2006).
[30]	Huh, D., Matthews, B., D., Mammoto, A., et al., Reconstituting Organ-Level Lung Functions on a Chip, Science, 328 (5986) (2010) pp. 1662-1668.

Cite This Article

Plain Text BibTeX RIS

APA Style

Piero Chiarelli. (2016). Artificial and Biological Intelligence: Hardware vs Wetware. American Journal of Applied Psychology, 5(6), 98-103. https://doi.org/10.11648/j.ajap.20160506.19

Copy | Download

ACS Style

Piero Chiarelli. Artificial and Biological Intelligence: Hardware vs Wetware. Am. J. Appl. Psychol. 2016, 5(6), 98-103. doi: 10.11648/j.ajap.20160506.19

Copy | Download

AMA Style

Piero Chiarelli. Artificial and Biological Intelligence: Hardware vs Wetware. Am J Appl Psychol. 2016;5(6):98-103. doi: 10.11648/j.ajap.20160506.19

Copy | Download

@article{10.11648/j.ajap.20160506.19,
  author = {Piero Chiarelli},
  title = {Artificial and Biological Intelligence: Hardware vs Wetware},
  journal = {American Journal of Applied Psychology},
  volume = {5},
  number = {6},
  pages = {98-103},
  doi = {10.11648/j.ajap.20160506.19},
  url = {https://doi.org/10.11648/j.ajap.20160506.19},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajap.20160506.19},
  abstract = {By starting from physical principles, the paper formulates the basis of the biological intelligence and coscience formation. The work shows that far from equilibrium, the principle of maximum energy dissipation, in a fluid phase, brings the molecules to organize themselves in living systems (ordered stationary states) that sustain energy-matter fluxes that determine the architecture of the dissipative system. The driver of the process is the energy; the matter is the substrate. On this base, and thanks to a “selection rule”, the living systems developed a bi-phasic structure consisting of a solid network permeated by a liquid where fluxes of ions and molecules can be maintained. In this way they realize a “wetware” where the energy and the organization/information are handled, and where a high specialization of functions can be obtained by using the spatial delocalization leading to the development of the complexity of the shape. The outputs of a living system can be divided in two categories: 1) macroscopic outputs: Movements, definition of an organized reaction or plan of action, and 2) microscopic ones: Plastic rearrangement of structures, migration of chemical species and electrochemical dynamics (transportation of matter, rearrangement, sensing, storage and information handling). The biological intelligence is a product of these basic processes where the wetware (matter substrate) is continuously modified by the energy-matter fluxes. On this base, the artificial intelligence of computers can be seen as a subclass of intelligent processes since it owns some limitations due to the invariance of the material substrate (that is not self-modified by the energy fluxes) and by the unique form of the flux of matter that is given by the electron current. Finally, the definition of a bio-inspired artificial intelligence is discussed.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Artificial and Biological Intelligence: Hardware vs Wetware
AU  - Piero Chiarelli
Y1  - 2016/12/30
PY  - 2016
N1  - https://doi.org/10.11648/j.ajap.20160506.19
DO  - 10.11648/j.ajap.20160506.19
T2  - American Journal of Applied Psychology
JF  - American Journal of Applied Psychology
JO  - American Journal of Applied Psychology
SP  - 98
EP  - 103
PB  - Science Publishing Group
SN  - 2328-5672
UR  - https://doi.org/10.11648/j.ajap.20160506.19
AB  - By starting from physical principles, the paper formulates the basis of the biological intelligence and coscience formation. The work shows that far from equilibrium, the principle of maximum energy dissipation, in a fluid phase, brings the molecules to organize themselves in living systems (ordered stationary states) that sustain energy-matter fluxes that determine the architecture of the dissipative system. The driver of the process is the energy; the matter is the substrate. On this base, and thanks to a “selection rule”, the living systems developed a bi-phasic structure consisting of a solid network permeated by a liquid where fluxes of ions and molecules can be maintained. In this way they realize a “wetware” where the energy and the organization/information are handled, and where a high specialization of functions can be obtained by using the spatial delocalization leading to the development of the complexity of the shape. The outputs of a living system can be divided in two categories: 1) macroscopic outputs: Movements, definition of an organized reaction or plan of action, and 2) microscopic ones: Plastic rearrangement of structures, migration of chemical species and electrochemical dynamics (transportation of matter, rearrangement, sensing, storage and information handling). The biological intelligence is a product of these basic processes where the wetware (matter substrate) is continuously modified by the energy-matter fluxes. On this base, the artificial intelligence of computers can be seen as a subclass of intelligent processes since it owns some limitations due to the invariance of the material substrate (that is not self-modified by the energy fluxes) and by the unique form of the flux of matter that is given by the electron current. Finally, the definition of a bio-inspired artificial intelligence is discussed.
VL  - 5
IS  - 6
ER  -

Copy | Download

Author Information

Piero Chiarelli

National Council of Research of Italy, Pisa, Italy

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Piero Chiarelli. (2016). Artificial and Biological Intelligence: Hardware vs Wetware. American Journal of Applied Psychology, 5(6), 98-103. https://doi.org/10.11648/j.ajap.20160506.19

Copy | Download

ACS Style

Piero Chiarelli. Artificial and Biological Intelligence: Hardware vs Wetware. Am. J. Appl. Psychol. 2016, 5(6), 98-103. doi: 10.11648/j.ajap.20160506.19

Copy | Download

AMA Style

Piero Chiarelli. Artificial and Biological Intelligence: Hardware vs Wetware. Am J Appl Psychol. 2016;5(6):98-103. doi: 10.11648/j.ajap.20160506.19

Copy | Download

@article{10.11648/j.ajap.20160506.19,
  author = {Piero Chiarelli},
  title = {Artificial and Biological Intelligence: Hardware vs Wetware},
  journal = {American Journal of Applied Psychology},
  volume = {5},
  number = {6},
  pages = {98-103},
  doi = {10.11648/j.ajap.20160506.19},
  url = {https://doi.org/10.11648/j.ajap.20160506.19},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajap.20160506.19},
  abstract = {By starting from physical principles, the paper formulates the basis of the biological intelligence and coscience formation. The work shows that far from equilibrium, the principle of maximum energy dissipation, in a fluid phase, brings the molecules to organize themselves in living systems (ordered stationary states) that sustain energy-matter fluxes that determine the architecture of the dissipative system. The driver of the process is the energy; the matter is the substrate. On this base, and thanks to a “selection rule”, the living systems developed a bi-phasic structure consisting of a solid network permeated by a liquid where fluxes of ions and molecules can be maintained. In this way they realize a “wetware” where the energy and the organization/information are handled, and where a high specialization of functions can be obtained by using the spatial delocalization leading to the development of the complexity of the shape. The outputs of a living system can be divided in two categories: 1) macroscopic outputs: Movements, definition of an organized reaction or plan of action, and 2) microscopic ones: Plastic rearrangement of structures, migration of chemical species and electrochemical dynamics (transportation of matter, rearrangement, sensing, storage and information handling). The biological intelligence is a product of these basic processes where the wetware (matter substrate) is continuously modified by the energy-matter fluxes. On this base, the artificial intelligence of computers can be seen as a subclass of intelligent processes since it owns some limitations due to the invariance of the material substrate (that is not self-modified by the energy fluxes) and by the unique form of the flux of matter that is given by the electron current. Finally, the definition of a bio-inspired artificial intelligence is discussed.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Artificial and Biological Intelligence: Hardware vs Wetware
AU  - Piero Chiarelli
Y1  - 2016/12/30
PY  - 2016
N1  - https://doi.org/10.11648/j.ajap.20160506.19
DO  - 10.11648/j.ajap.20160506.19
T2  - American Journal of Applied Psychology
JF  - American Journal of Applied Psychology
JO  - American Journal of Applied Psychology
SP  - 98
EP  - 103
PB  - Science Publishing Group
SN  - 2328-5672
UR  - https://doi.org/10.11648/j.ajap.20160506.19
AB  - By starting from physical principles, the paper formulates the basis of the biological intelligence and coscience formation. The work shows that far from equilibrium, the principle of maximum energy dissipation, in a fluid phase, brings the molecules to organize themselves in living systems (ordered stationary states) that sustain energy-matter fluxes that determine the architecture of the dissipative system. The driver of the process is the energy; the matter is the substrate. On this base, and thanks to a “selection rule”, the living systems developed a bi-phasic structure consisting of a solid network permeated by a liquid where fluxes of ions and molecules can be maintained. In this way they realize a “wetware” where the energy and the organization/information are handled, and where a high specialization of functions can be obtained by using the spatial delocalization leading to the development of the complexity of the shape. The outputs of a living system can be divided in two categories: 1) macroscopic outputs: Movements, definition of an organized reaction or plan of action, and 2) microscopic ones: Plastic rearrangement of structures, migration of chemical species and electrochemical dynamics (transportation of matter, rearrangement, sensing, storage and information handling). The biological intelligence is a product of these basic processes where the wetware (matter substrate) is continuously modified by the energy-matter fluxes. On this base, the artificial intelligence of computers can be seen as a subclass of intelligent processes since it owns some limitations due to the invariance of the material substrate (that is not self-modified by the energy fluxes) and by the unique form of the flux of matter that is given by the electron current. Finally, the definition of a bio-inspired artificial intelligence is discussed.
VL  - 5
IS  - 6
ER  -

Copy | Download