Intelligence in Humans

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A Brief History of Intelligence
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Abstract

It is believed that animals much like modern humans first appeared about 2.5 million years ago. About 70,000 years ago, the cognitive revolution occurred in a species called Homo sapiens in Africa. The brain structure of sapiens achieved a threshold of sophistication and capacity such that ideas, knowledge and culture were formed. Consequently, biology gave rise to history.

The brain is a three-pound mass you can hold in your hand that can conceive of a universe a hundred billion light years across. — Marian Diamond The brain is the last and grandest biological frontier, the most complex thing we have yet discovered in our universe. — JamesWatson

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References

  1. T. Jackson, The Brain: An Illustrated History of Neuroscience (Shelter Harbor Press, New York, 2015)

    Google Scholar 

  2. R. Kurzweil, How to Create a Mind: The Secret of Human Thought Revealed (Viking Press, New York, 2012)

    Google Scholar 

  3. V. Mountcastle, He Mindful Brain - An organizing Principle for Cerebral Function: The Unit Module and The Distributed System (MIT Press, Cambridge, 1978)

    Google Scholar 

  4. Y.N. Harari, Sapiens: A Brief History of Humankind (Harper, New York, 2014)

    Google Scholar 

  5. D.C. Knill, A. Pouget, The bayesian brain: the role of uncertainty in neural coding and computation. Trends Neurosci. 27(12), 712–719 (2004)

    Article  Google Scholar 

  6. R.L. Gregory, Perceptions as hypotheses. Philos. Trans. R. Soc. Lond. B Biol. Sci. 290(1038), 181–197 (1980)

    Article  Google Scholar 

  7. D. Kersten, P. Mamassian, A. Yuille, Object perception as Bayesian inference. Annu. Rev. Psychol. 55, 271–304 (2004)

    Article  Google Scholar 

  8. R. Linsker, Perceptual neural organization: some approaches based on network models and information theory. Annu. Rev. Neurosci. 13(1), 257–281 (1990)

    Article  Google Scholar 

  9. E.P. Simoncelli, B.A. Olshausen, Natural image statistics and neural representation. Annu. Rev. Neurosci. 24(1), 1193–1216 (2001)

    Article  Google Scholar 

  10. S.B. Laughlin, Efficiency and complexity in neural coding, in Novartis Foundation Symposium (Wiley, Chichester/New York 1999/2001), pp. 177–192

    Google Scholar 

  11. P.R. Montague, P. Dayan, C. Person, T.J. Sejnowski, Bee foraging in uncertain environments using predictive hebbian learning. Nature 377(6551), 725–728 (1995)

    Article  Google Scholar 

  12. W. Schultz, Predictive reward signal of dopamine neurons. J. Neurophysiol. 80(1), 1–27 (1998)

    Article  Google Scholar 

  13. Richard Bellman, On the Theory of Dynamic Programming–A Warehousing Problem, Management Science, Informs, 2(3), 272–275 (1956)

    MathSciNet  MATH  Google Scholar 

  14. R.S. Sutton, A.G. Barto, Toward a modern theory of adaptive networks: expectation and prediction. Psychol. Rev. 88(2), 135 (1981)

    Google Scholar 

  15. K. Friston, J. Kilner, L. Harrison, A free energy principle for the brain. J. Physiol. Paris 100(1–3), 70–87 (2006)

    Article  Google Scholar 

  16. H.B. Callen, Thermodynamics (Wiley, Hoboken, 1966)

    Google Scholar 

  17. K.J. Friston, The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 11, 127–138 (2010)

    Article  Google Scholar 

  18. L. Itti, P. Baldi, Bayesian surprise attracts human attention. Vis. Res. 49(10), 1295–1306 (2009)

    Article  Google Scholar 

  19. K.J. Friston, J. Daunizeau, S.J. Kiebel, Reinforcement learning or active inference? PloS One 4(7), e6421 (2009)

    Google Scholar 

  20. X.S. Zhang, X. Zhang, P. Kaparthi, Combat information overload problem in social networks with intelligent information-sharing and response mechanisms. IEEE Trans. Comput. Soc. Syst. 7(4), 924–939 (2020)

    Article  Google Scholar 

  21. M. Carter, M. Tsikerdekis and S. Zeadally, Approaches for Fake Content Detection: Strengths and Weaknesses to Adversarial Attacks, in IEEE Internet Computing, 25(2), 73–83 (2021)

    Article  Google Scholar 

  22. C.R. Sunstein, Infotopia: How Many Minds Produce Knowledge (Oxford University Press, Oxford, 2006)

    Google Scholar 

  23. N. Negroponte, Being Digital (Knopf, German, New York, 1995)

    Google Scholar 

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Yu, F.R., Yu, A.W. (2023). Intelligence in Humans. In: A Brief History of Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-031-15951-0_6

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  • DOI: https://doi.org/10.1007/978-3-031-15951-0_6

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