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Harald Sack

Iteratively adjusting the weights of a neuron according to the errors created by comparing expected output with actual output is the basis of Frank Rosenblatt's perceptron (1957), the first artificial neural network.

F. Rosenblatt (1958), The perceptron: a probabilistic model for information storage and organization in the brain. Psyc. Review, 65(6), 386–408.
doi.org/10.1037/h0042519

@sourisnumerique @enorouzi @fizise

Slide from the Information Service Engineering 2024 lecture, Basic Machine Learning01, Excursion: A very brief history of AI, The Perceptron. The graphics shows an artificial neuron where the output of the neuron is fed back to the input weights for error adaption. The text says: 1957 The Perceptron algorithm was invented by Frank Rosenblatt at Cornell University. The perceptron is an algorithm for supervised learning of binary classifiers. A binary classifier is a function which can decide whether or not an input, represented by a vector of numbers, belongs to some specific class.
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Harald Sack

@bobdc ...and this will be shown in the next slide on the Mark I Perceptron ;-)

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