Citations of Research Papers and Books

Explore the scholarly works and publications referenced throughout this book for further reading and research:

  1. Mitchell, Melanie. “Artificial Intelligence: A Guide for Thinking Humans.” Farrar, Straus and Giroux, 2019.

  2. Goodfellow, Ian, et al. “Deep Learning.” MIT Press, 2016.

  3. Bostrom, Nick. “Superintelligence: Paths, Dangers, Strategies.” Oxford University Press, 2014.

  4. Ng, Andrew. “Machine Learning.” Coursera, Stanford University.

  5. Bengio, Yoshua, et al. “Learning Deep Architectures for AI.” Foundations and Trends® in Machine Learning, 2009.

  6. Silver, David, et al. “Mastering the Game of Go without Human Knowledge.” Nature, vol. 550, no. 7676, 2017, pp. 354-359.

  7. LeCun, Yann, et al. “Deep Learning.” Nature, vol. 521, no. 7553, 2015, pp. 436-444.

  8. Kurzweil, Ray. “The Singularity Is Near: When Humans Transcend Biology.” Penguin Books, 2006.

  9. OpenAI. “GPT-3: Language Models are Few-Shot Learners.” arXiv preprint arXiv:2005.14165, 2020.

  10. Beyer, Kira, et al. “The Imagenet Large Scale Visual Recognition Challenge.” International Journal of Computer Vision, vol. 115, no. 3, 2015, pp. 211-252.

These references provide foundational knowledge and scholarly insights into the field of artificial intelligence (AI) and related topics discussed in this book. Consult these works for in-depth exploration and further understanding of AI’s evolution, applications, and implications in contemporary research and development.

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