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References

Section 1

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[1] Data (n.). (n.d.). Retrieved from https://www.etymonline.com/word/data

[2] http://dmlc.ml/mxnet/2015/10/27/training-deep-net-on-14-million-images.html

[3] Deng, J., Dong, W., Socher, R., Li, L., Li, K., & Fei-Fei, L. (2009). ImageNet: A large-scale hierarchical image database. 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[4] Owens, J. D., Houston, M., Luebke, D., Green, S., Stone, J. E., & Phillips, J. C. (2008). GPU computing

[5] Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., ... & Petersen, S. (2015). Human-level control through deep reinforcement learning. Nature, 518(7540), 529.

[6] Vinyals, O., Babuschkin, I., Chung, J., Mathieu, M., Jaderberg, M., Czarnecki, W. M., . . . Silver, D.(2019).AlphaStar:Mastering the Real-Time Strategy Game StarCraft II.

[7] Jouppi, N. P., Young, C., Patil, N., Patterson, D., Agrawal, G., Bajwa, R., ... & Boyle, R. (2017, June). In-datacenter performance analysis of a tensor processing unit. In 2017 ACM/IEEE 44th Annual International Symposium on Computer Architecture (ISCA) (pp. 1-12). IEEE.

[8] https://developer.nvidia.com/machine-learning

[9] https://filecatalyst.com/a-day-in-data/

[10] http://cocodataset.org/

[11] Deng, L. (2012). The MNIST database of handwritten digit images for machine learning research [best of the web]. IEEE Signal Processing Magazine, 29(6), 141-142.

[12] Sejnowski T. The Deep Learning Revolution (2018)

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[Figure 1] https://www.slideshare.net/IABCHouston/southwest-airlines-nuts-about-online-communications

[Figure 2] http://opening.download/spring-opening.html

[Figure 4] https://www.custom-build-computers.com/Evolution-of-Computers.html

[Figure 5] https://www.slideshare.net/balazskegl/a-historical-introduction-to-deep-learning-hardware-data-and-tricks

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Section 2.1

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[13] Boldrini N. (2018) A.I. for business.

[14] Sejnowsky T.J.,(2018) The Deep Learning Revolution

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[65] Hebb, D. O. (1949), New York: Wiley, The organization of behavior

[66] Hayek, F. A.(1952), Univer. Chicago press, The sensory order.

[18] Awad M., Khanna R. (2015) Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers (pp.127-147), Deep Neural Networks.

[19] Hinton G., Ackley D.H., Sejnowski T.J. (1983) A learning algorithm for Boltzmann machines

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[22] LeCun Y., Boser B., Denker J.S., Henderson D., Howard R.E., Hubbard W., (1989), NIPS 396-404 Handwritten digit recognition with a back propagation network

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[25] Fukushima K. (1980), Biological Cybernetics 193-202, Neocognitron, a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

[26] Krizhevsky A., Sutskever Y., Hinton G. (2012) Imagenet Classification with Deep Convolutional Neural Networks

[27] Yung J. (2017) Explaining Tensorflow Code for a Convolutional Neural Network

[28] Britz D., (2015), WILDML, Understanding Convolutional Neural Networks for NLP

[29] Hinton G., Bartunov S., Santoro A., Richards B., Marris L., Lillicrap T. (2018) Nips Proceedings, Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures

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Section 2.2

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[30] Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., ... & Dieleman, S. (2016). Mastering the game of Go with deep neural networks and tree search. nature, 529(7587), 484.

[31] Noughts And Crosses - The oldest graphical computer game

[32] Minimax theorems. Proceedings of the National Academy of Sciences of the United States of America, 39(1), 42.

[33] Campbell, M., Hoane Jr, A. J., & Hsu, F. H. (2002). Deep blue. Artificial intelligence, 134(1-2), 57-83

[34] Browne, C. B., Powley, E., Whitehouse, D., Lucas, S. M., Cowling, P. I., Rohlfshagen, P., ... & Colton, S. (2012). A survey of monte carlo tree search methods. IEEE Transactions on Computational Intelligence and AI in games, 4(1), 1-43.

[35] Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., ... & Petersen, S. (2015). Human-level control through deep reinforcement learning. Nature, 518(7540), 529. 

[36] Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems (pp. 1097-1105). 

[37] Vinyals, O., Babuschkin, I., Chung, J., Mathieu, M., Jaderberg, M., Czarnecki, W. M., . . . Silver, D.(2019).AlphaStar:Mastering the Real-Time Strategy Game StarCraft II.

[38] Vinyals, O., Ewalds, T., Bartunov, S., Georgiev, P., Vezhnevets, A. S., Yeo, M., ... & Quan, J. (2017). Starcraft ii: A new challenge for reinforcement learning. arXiv preprint arXiv:1708.04782. 

[39] Introduction to reinforcement learning. Cambridge: MIT press, 1998.

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[Figure 1] https://upload.wikimedia.org/wikipedia/commons/thumb/1/1b/Reinforcement_learning_diagram.svg/375px-Reinforcement_learning_diagram.svg.png

[Figure 2] https://www.researchgate.net/publication/262672371/figure/fig1/AS:393455625883662@1470818539933/Game-tree-for-Tic-Tac-Toe-game-using-MiniMax-algorithm.png

[Figure 3] https://media.pri.org/s3fs-public/styles/story_main/public/story/images/DeepBlue.png?itok=N01yMnCK

[Figure 4] [Figure 5] [30]

[Figure 6] https://deepmind.com/blog/alphastar-mastering-real-time-strategy-game-starcraft-ii/

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Section 3.1

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[40] Tesla. Autopilot

[41] Smith, A., Voß, J.‑P. & Grin, J. (2010) Innovation studies and sustainability transitions: The allure of the multi-level perspective and its challenges. Res. Policy 39, 435–448

[42] Barton, J.P.; Infield, D.G. (2004) Energy storage and its use with intermittent renewable energy. IEEE Trans. Energy Convers. 19, 441–448.

[43] Papalexopoulos A., Frowd R., Hansen C., Lannoye E., Tuohy A. (2016). Impact of the transmission grid on the operational system flexibility. Power Systems Computation Conference (PSCC), 2016.

[44] Chong E. K. P., Kreucher C. M., and Hero III A. O. (2009). Partially observable Markov decision process approximations for adaptive sensing. Discrete Event Dynamic Systems, special issue on Optimization of Discrete Event Dynamic Systems, vol. 19, no. 3, pp. 377–422.

[45] Esteva A., Kuprel B., Novoa R., Ko J., Swetter S., Blau H., Thrun S. Dermatologist-level classification of skin cancer with deep neural networks (2017).

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[Figure 1] https://dl.acm.org/citation.cfm?id=3180220

[Figure 2] https://www.dw.com/en/uber-suspends-autonomous-car-testing-after-fatal-crash/a-43042988

[Figure 3] https://adeshpande3.github.io/A-Beginner's-Guide-To-Understanding-Convolutional-Neural-Networks

[Figure 4] https://www.google.com/search?biw=1366&bih=625&tbm=isch&sa=1&ei=x_XPXLyRFsXSkwXd767QCQ&q=medical+imaging&oq=medical+ima&gs_l=img.1.0.0l2j0i30l8.142834.144390..145476...0.0..0.83.864.11......0....1..gws-wiz-img.......35i39j0i67.OY4nVGxRXGE#imgrc=xl-sss-LBo-i6M

[Figure 5] https://www.hydroworld.com/articles/2015/12/northwestern-submits-final-filing-for-194-mw-kerr-hydropower-project.html

[Figure 6] https://www.tdworld.com/overhead-transmission/northern-pass-achieves-major-federal-permitting-milestone

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Section 3.2

 

[46] https://www.quora.com/Why-does-deep-learning-require-a-lot-of-data

[47] https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read/#31f40c4160ba

[48] https://www.theguardian.com/technology/2017/oct/04/robots-artificial-intelligence-machines-us-survey

[49] https://www.theinquirer.net/inquirer/news/3037160/a-quarter-of-brits-fear-they-will-lose-their-job-to-robot-workers

[50] https://www.express.co.uk/news/science/1019342/Artificial-intelligence-AI-danger-UK-robots-take-jobs

[51] https://www.youtube.com/watch?v=WSKi8HfcxEk&t=325s

[52] https://www.forbes.com/sites/forbestechcouncil/2018/12/28/let-the-robots-take-over-how-the-future-of-ai-will-create-more-jobs/#4be59ad73c6d

[53] https://www.mirror.co.uk/news/uk-news/worst-nurse-shortage-ever-nhs-11118667

[54] https://www.theatlantic.com/health/archive/2016/02/nursing-shortage/459741/

[55] http://www.cedefop.europa.eu/en/news-and-press/news/skill-shortages-europe-which-occupations-are-demand-and-why

[56] http://www3.weforum.org/docs/WEF_Future_of_Jobs.pdf

[57] https://www.nvidia.com/object/deep-learning-in-medicine.html

[58] http://fortune.com/2016/10/11/shared-electric-self-driving-cars/

[59] https://www.theatlantic.com/international/archive/2018/02/china-surveillance/552203/

[60] https://shapingtomorrow.com/home/alert/275454-The-Future-of-Intelligence---impacts-on-society

[61] https://www.kdnuggets.com/2016/01/deep-learning-2016-beyond.html

[62] https://cloud.google.com/blog/products/gcp/using-machine-learning-for-insurance-pricing-optimization

[63] https://www.telegraph.co.uk/technology/2016/03/24/microsofts-teen-girl-ai-turns-into-a-hitler-loving-sex-robot-wit/

[64] https://www.nytimes.com/2019/04/21/opinion/computational-inference.html?rref=collection%2Ftimestopic%2FArtificial+Intelligence&fbclid=IwAR09MT9YeIu2xDP9e8a_io-oFz4RN1dCTT4eaqrvWEAP6naRaslp20bHz-o

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[Figure 1] http://www.montereylanguages.com/blog/wp-content/uploads/2014/04/robot-stealing-jobs1.jpg

[Figure 2] https://thecriticalspace.files.wordpress.com/2016/02/mjolner_industrial_revolution_timeline.png

[Figure 3] https://pbs.twimg.com/media/DPcNgztW0AU0KJ5.jpg

[Figure 4] https://reachoutrecovery.com/wp-content/uploads/2017/12/Golf-stick-figure-crossing-a-line.jpg

[Figure 5] https://upload.wikimedia.org/wikipedia/commons/8/8c/Trolley_problem.png

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