Skip to main content
SpringerLink
Log in

Whether Be New “Winter” of Artificial Intelligence?

  • Conference paper
  • First Online:
Integrated Science in Digital Age (ICIS 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 78))

Included in the following conference series:

Abstract

The article analyzes the formation and development of artificial intelligence as scientific industry, identifies cycles of leaps and drops of its popularity. It’s concluded that the decline in the popularity of artificial intelligence in the near future is inevitable.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Yasnitsky, L.N.: Introduction to Artificial Intelligence. Academy, Moscow (2005)

    Google Scholar 

  2. Andrew, A.M.: Artificial Intelligence. Abacus Press, Turnbull Wells (1983)

    Google Scholar 

  3. Nikolenko, S., Kadurin, A., Arkhangelsk, E.: Deep Learning. Peter, St. Petersburg (2018)

    Google Scholar 

  4. Yasnitsky, L.N.: On the priority of Soviet science in the field of Neuroinformatics. Neurocomput. Dev. Appl. 21(1), 6–8 (2019)

    Google Scholar 

  5. Widrow, B., Hoff, M.E.: Adaptive switching circuits. 1960 IRE WESTCON Conferenction Record, New York (1960)

    Google Scholar 

  6. Galushkin, A.I., Zak, A.S., Tyukhov, B.P.: Comparison of criteria for optimization of adaptive pattern recognition systems. Cybernetics 5, 122–130 (1970)

    MATH  Google Scholar 

  7. Werbos, P.: Beyond regression: new tools for prediction and analysis in the behavioral sciences. Ph.D. thesis. Department of Applied Mathematics, Harvard University, Cambridge, Mass (1974)

    Google Scholar 

  8. Rummelhart, D.E., Hilton, G.E., Williams, R.J.: Learning internal representations by error propagation (1986). McClelland et al.

    Google Scholar 

  9. Fukushima, K.: Neocognitron: a self-organizing neural network for a mechanism of pattern recognition unaffected by shift in position. Biol. Cybern. 36(4), 193–202 (1980)

    Article  Google Scholar 

  10. Osovsky, S.: Neural Networks for Information Processing. Finance and Statistics, Moscow (2002)

    Google Scholar 

  11. Yasnitskii, L.N.: Superposition of base solutions in methods of Trefftz type. Mech. Solids 24(2), 90–96 (1989)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Perm State University, 15, Bukirev Street, 614600, Perm, Russia

    Leonid N. Yasnitsky

  2. Higher School of Economics, National Research University, 38, Studencheskaya Street, 614070, Perm, Russia

    Leonid N. Yasnitsky

Authors
  1. Leonid N. Yasnitsky
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Leonid N. Yasnitsky .

Editor information

Editors and Affiliations

  1. Institute of Certified Specialists (ICS), Perm, Russia

    Tatiana Antipova

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yasnitsky, L.N. (2020). Whether Be New “Winter” of Artificial Intelligence?. In: Antipova, T. (eds) Integrated Science in Digital Age. ICIS 2019. Lecture Notes in Networks and Systems, vol 78. Springer, Cham. https://doi.org/10.1007/978-3-030-22493-6_2

Download citation

Publish with us

Policies and ethics

Search

Navigation