I read every major CS paper of the last 100 years...

The video provides a high-level historical narrative of computer science through 10 seminal papers, starting with Alan Turing's 1936 proof that some problems are undecidable by algorithms, which inadvertently defined the universal computer. It progresses through Claude Shannon's 1948 information theory, which defined the bit and entropy, and moves into the dawn of machine learning with Frank Rosenblatt's Perceptron (1958) and its 1969 critique by Minsky and Papert, which led to an AI winter. The narrative then highlights the breakthroughs that ended that winter: the formalization of backpropagation by Rumelhart, Hinton, and Williams (1986); the massive web-indexing innovation of Google's PageRank (1998); the breakthrough success of deep convolutional neural networks with ImageNet (2012); and finally, the transformative power of the transformer architecture (2017) and the scaling laws showcased in OpenAI's GPT-3 (2020). Throughout the history, the video links these abstract papers to the rapid acceleration of AI capabilities today, illustrating that intelligence often emerges simply from sufficient data and computational scale.