AT&T Bell Labs

2 milestones · 1989–1995

Explore AT&T Bell Labs's role in AI history across 2 milestones from 1989 to 1995, with the strongest concentration in research breakthroughs.

Quiet Emergence (1)Second AI Winter (1)Research Breakthroughs (2)

Chronology

LeNet-5 convolutional neural network architecture
Research

LeNet: Convolutional Neural Networks

Yann LeCun demonstrated that convolutional neural networks (CNNs) could be trained with backpropagation to recognize handwritten digits. The refined LeNet-5 (1998) achieved 99%+ accuracy on MNIST and was deployed by banks to read checks — running in ATMs for years.

Yann LeCunAT&T Bell Labs
Research

Support Vector Machines

Vapnik and Cortes published their work on Support Vector Machines (SVMs), a method for finding maximum-margin decision boundaries in high-dimensional spaces with unusually strong theoretical guarantees. SVMs quickly became one of the leading approaches for classification problems across text, vision, and bioinformatics.

Vladimir VapnikCorinna CortesAT&T Bell Labs

Related People

Corinna Cortes (1)Vladimir Vapnik (1)Yann LeCun (1)

Frequent Topics

Classification (1)Cnn (1)Commercial (1)Computer Vision (1)Deep Learning (1)Machine Learning (1)Statistical Learning (1)