How Computers Read Text in Real Life

Optical character recognition (OCR) has evolved from 1870s photo cell experiments to modern transformer-based models. Early mechanical systems used lights and film to convert characters to telegraph code, leading to machine-readable fonts like OCR A in 1968. Google's Tesseract engine (2005) initially used rule-based linguistics, then switched to LSTM neural networks in the 2010s alongside the deep learning boom. Today's transformer models can not only read and convert text from images but also understand context and use it as input for further processing.