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Artificial Intelligence and Exponential Technologies: Business Models Evolution and New Investment Opportunities

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSINTELL))

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Abstract

This chapter deals with the emerging trends in AI: data (non)-necessity; advancements in the learning algorithms; human augmentation; how to fool an AI; what risks it brings; collective intelligence; socio-political implications; impact on privacy, robotics, IoT; the barriers to AI development; and finally, how biology can help creating a better AI.

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References

  • Kurakin, A., Goodfellow, I. J., Bengio, S. (2016). Adversarial Examples in the Physical World. Technical report, Google, Inc. Available at arXiv: 1607.02533.

    Google Scholar 

  • Lake, B. M., Salakhutdinov, R., & Tenenbaum, J. B. (2015). Human-level concept learning through probabilistic program induction. Science, 350(6266), 1332–1338.

    Article  MathSciNet  Google Scholar 

  • Lake, B. M., Ullman, T. D., Tenenbaum, J. B., Gershman, S. J. (2016). Building Machines That Learn and Think Like People. Available at arXiv:1604.00289.

    Google Scholar 

  • Lo, A. W. (2004). The adaptive markets hypothesis: Market efficiency from an evolutionary perspective. Journal of Portfolio Management, 30, 15–29.

    Article  Google Scholar 

  • Papernot, N., McDaniel, P. D., Goodfellow, I. J., Jha, S., Celik, Z. B., Swami, A. (2016). Practical black-box attacks against deep learning systems using adversarial examples. CoRR, abs/1602.02697.

    Google Scholar 

  • Rosenberg, L. B. (2015). Human Swarms, a real-time method for collective intelligence. In Proceedings of the European Conference on Artificial Life (pp. 658–659).

    Google Scholar 

  • Rosenberg, L. B. (2016). Artificial Swarm Intelligence,
a Human-in-the-loop approach to A.I. In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16) (pp. 4381–4382).

    Google Scholar 

  • Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118.

    Article  Google Scholar 

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Authors and Affiliations

  1. Rome, Italy

    Francesco Corea

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  1. Francesco Corea
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Correspondence to Francesco Corea .

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Corea, F. (2017). Discussion. In: Artificial Intelligence and Exponential Technologies: Business Models Evolution and New Investment Opportunities. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-319-51550-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-51550-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51549-6

  • Online ISBN: 978-3-319-51550-2

  • eBook Packages: EngineeringEngineering (R0)

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