The Future of Artificial Intelligence

In 2012, Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton published their results on the ImageNet LSVRC2010 contest, a computer vision challenge to classify 1.2 million high-resolution images into 1,000 different classes automatically. Their use of deep neural networks yielded a substantial improvement in error rate and marks the beginning of the recent wave of interest in machine learning and artificial intelligence. In the subsequent years, deep learning has been applied to a considerable number of other problems and used productively in applications such as voice recognition for digital assistants, translation software, and self-driving vehicles. But despite all these impressive success stories, deep learning still suffers from severe limitations. For one thing, enormous amounts of labeled data are required to train the networks.