Review of Lacruz (2023): Translation in Transition: Human and Machine Intelligence

References

1. Carl, Michael, Moritz Schaeffer, and Srinivas Bangalore
   2016 “The CRITT Translation Process Research Database.” InNew Directions in Empirical Translation Process Research, byCarl, Michael, Moritz Schaeffer. and Srinivas Bangalore, –. Cham: Springer Science+Business Media. 10.1007/978‑3‑319‑20358‑4_2
   https://doi.org/10.1007/978-3-319-20358-4_2 [Google Scholar]
2. Clark, Andy, and Toribio, Josefa
   eds. 2012 Language and Meaning in Cognitive Science: Cognitive Issues and Semantic Theory. New York: Taylor & Francis Group. 10.4324/9780203055069
   https://doi.org/10.4324/9780203055069 [Google Scholar]
3. Freiberger, Paul A., and Michael R. Swaine
   2024 “ENIAC.” Encyclopedia Britannica. Last modifiedMay 3, 2024. https://www.britannica.com/technology/ENIAC
   [Google Scholar]
4. Garnelo, Marta, and Murray Shanahan
   2019 “Reconciling deep learning with symbolic artificial intelligence: representing objects and relations.” Current Opinion in Behavioral Sciences: –. 10.1016/j.cobeha.2018.12.010
   https://doi.org/10.1016/j.cobeha.2018.12.010 [Google Scholar]
5. Hutto, Daniel D., and Erik Myin
   2017 Evolving enactivism: Basic minds meet content. Cambridge, MA: MIT press. 10.7551/mitpress/9780262036115.001.0001
   https://doi.org/10.7551/mitpress/9780262036115.001.0001 [Google Scholar]
6. Keskar, Vinaya, Jyoti Yadav, and Ajay H. Kumar
   2020 “5V’s of Big Data Attributes and their Relevance and Importance across Domains.” International Journal of Innovative Technology and Exploring Engineering (IJITEE) (). https://www.ijitee.org/wp-content/uploads/papers/v9i11/K77090991120.pdf. 10.35940/ijitee.K7709.0991120
   https://doi.org/10.35940/ijitee.K7709.0991120 [Google Scholar]
7. Kiefer, Alex B.A Defense of Pure Connectionism
   , “A Defense of Pure Connectionism” (2019) CUNY Academic Works. https://academicworks.cuny.edu/gc_etds/3036
8. Krings, Hans P.
   2001 Repairing texts: Empirical investigations of machine translation post-editing processes. Vol.. Kent, OH: Kent State University Press.
   [Google Scholar]
9. Lacruz, Isabel
   ed. 2023 Translation in Transition: Human and Machine Intelligence. John Benjamins Publishing Company. 10.1075/ata.xx
   https://doi.org/10.1075/ata.xx [Google Scholar]
10. Laney, Doug
    2001 3D Data Management: Controlling Data Volume, Velocity, and Variety. Application Delivery Strategies. META Group Inc.
    [Google Scholar]
11. LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton
    2015 “Deep learning.” Nature: –. 10.1038/nature14539
    https://doi.org/10.1038/nature14539 [Google Scholar]
12. Lieto, Antonio
    2021 Cognitive Design for Artificial Minds. Taylor & Francis Group. 10.4324/9781315460536
    https://doi.org/10.4324/9781315460536 [Google Scholar]
13. Maruyama, Yoshihiro
    2020 “Symbolic and Statistical Theories of Cognition: Towards Integrated Artificial Intelligence.” In: Cleophas, Loek, Massink, Mieke, eds.Software Engineering and Formal Methods. SEFM 2020 Collocated Workshops. SEFM 2020. Lecture Notes in Computer Science(), vol 12524. Cham: Springer. 10.1007/978‑3‑030‑67220‑1_11
    https://doi.org/10.1007/978-3-030-67220-1_11 [Google Scholar]
14. McCarthy, John
    2007 “What is artificial intelligence?” AccessedFebruary 7, 2024. jmc.stanford.edu/articles/whatisai/whatisai.pdf
15. Shannon, Claude E.
    1948 “A Mathematical Theory of Communication.” Bell Systems Technical Journal: –. 10.1002/j.1538‑7305.1948.tb01338.x
    https://doi.org/10.1002/j.1538-7305.1948.tb01338.x [Google Scholar]
16. Tobii Pro Lab
    Tobii Pro Lab 2023 “Understanding Tobii Pro Lab’s eye tracking metrics.” AccessedApril 26, 2024. https://connect.tobii.com/s/article/understanding-tobii-pro-lab-eye-tracking-metrics?language=en_US
17. Turing, Alan
    1950 “Computing machinery and intelligence.” Mind, (): –. 10.1093/mind/LIX.236.433
    https://doi.org/10.1093/mind/LIX.236.433 [Google Scholar]