ImageNet’s three million human-labeled images enabled the deep learning breakthrough
Evidence
In 2007, Princeton professor Fei-Fei Li used Amazon Mechanical Turk to recruit human labor, at a scale previously unimaginable, to build a dataset that was previously impossible. It took more than two years to build, and had three million images, each labeled, by human hands, into more than five thousand categories. Li called it ImageNet, and released it in 2009. — Brian Christian, The Alignment Problem, 99
Categorization
- corroborated: 2 independent passages support this claim — Brian Christian, The Alignment Problem, 99
- XREF: connects to: Machine learning divides into unsupervised, supervised, and reinforcement learning — Brian Christian, The Alignment Problem, 58; Fei-Fei Li used Mechanical Turk crowdworkers to build ImageNet’s labeled dataset