Every LLM Is a Neural Network From 1958: Tracing 70 Years From Perceptron to Transformers
blaizedsouza · x · 2026-09-17
An educational thread argues that every LLM is an extension of the 1958 perceptron: a network of simple units that multiply inputs by weights, sum them, and pass the result through a small function—first built by Frank Rosenblatt in 1958.
Key milestones covered:
- Feedforward networks (1958): data flows one way from input to output layer
- Convolutional networks (1998): learn spatial patterns for images and video
- Recurrent networks: adding temporal memory
- Backpropagation (1986): training by shrinking error each pass, one of the most important algorithms ever
Stack these units into layers and train at scale, and you arrive at today's large language models.
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