Modern AI Explained In 13 Minutes

In 1958 a five-ton computer learned to tell left from right in fifty tries. Nobody wrote the rule. Sixty-eight years later the same arithmetic answers questions for 900 million people a week — and still nobody writes the rules. This is the whole line, end to end: the perceptron that taught itself and the book that buried it, the layers that brought it back, the exam it won in 2012, the move no human would play, the sentence that learned to read itself, and the agents that found each other in 2026. One idea, one thread, sixty-eight years. Chapters: 00:00 The 1958 promise 00:44 The rules do not work 03:02 Stack the layers 04:45 The exam and the card 06:30 Move 37 08:02 Attention 09:40 It gets hands 11:57 Here's my read Sources: The New York Times, 8 July 1958, "New Navy Device Learns by Doing" Frank Rosenblatt, "The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain", Psychological Review, 1958 Minsky and Papert, Perceptrons, MIT Press, 1969 — archive.org/details/perceptronsintro00mins Cornell Chronicle, "Professor's perceptron paved the way for AI - 60 years too soon" Sir James Lighthill, "Artificial Intelligence: A General Survey", Science Research Council, July 1972 Rumelhart, Hinton and Williams, "Learning representations by back-propagating errors", Nature, 9 October 1986 LeCun et al., "Backpropagation Applied to Handwritten Zip Code Recognition", 1989 Deng et al., "ImageNet: A Large-Scale Hierarchical Image Database", CVPR 2009 Krizhevsky, Sutskever and Hinton, "ImageNet Classification with Deep Convolutional Neural Networks", NIPS 2012 Silver et al., "Mastering the game of Go with deep neural networks and tree search", Nature, 2016 Vaswani et al., "Attention Is All You Need", 2017 Brown et al., "Language Models are Few-Shot Learners", 2020 The Nobel Prize in Physics 2024, press release, nobelprize.org OpenAI, METR, Hugging Face and the UK AI Security Institute, 2026 #AI #NeuralNetworks #Perceptron #TechBreaking