Future Computers Will Be Radically Different (Analog Computing) | Veritasium

References: Crevier, D. (1993). AI: The Tumultuous History Of The Search For Artificial Intelligence. Basic Books. – Valiant, L. (2013). Probably Approximately Correct. HarperCollins. – Rosenblatt, F. (1958). The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain. Psychological Review, 65(6), 386-408. – NEW NAVY DEVICE LEARNS BY DOING; Psychologist Shows Embryo of Computer Designed to Read and Grow Wiser (1958). The New York Times, p. 25. – Mason, H., Stewart, D., and Gill, B. (1958). Rival. The New Yorker, p. 45. – Alvinn driving NavLab footage – Pomerleau, D. (1989). ALVINN: An Autonomous Land Vehicle In a Neural Network. NeurIPS, (2)1, 305-313. – ImageNet website – Russakovsky, O., Deng, J. et al. (2015). ImageNet Large Scale Visual Recognition Challenge. – AlexNet Paper: Krizhevsky, A., Sutskever, I., Hinton, G. (2012). ImageNet Classification with Deep Convolutional Neural Networks. NeurIPS, (25)1, 1097-1105. – Karpathy, A. (2014). Blog post: What I learned from competing against a ConvNet on ImageNet. – Fick, D. (2018). Blog post: Mythic @ Hot Chips 2018. – Jin, Y. & Lee, B. (2019). 2.2 Basic operations of flash memory. Advances in Computers, 114, 1-69. – Demler, M. (2018). Mythic Multiplies in a Flash. The Microprocessor Report. – Aspinity (2021). Blog post: 5 Myths About AnalogML. – Wright, L. et al. (2022). Deep physical neural networks trained with backpropagation. Nature, 601, 49–555. – Waldrop, M. M. (2016). The chips are down for Moore’s law. Nature, 530, 144–147. –
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