Deep Neural Nets: 33 years ago and 33 years from now
Analysis
This article by Andrej Karpathy discusses the historical significance of the 1989 Yann LeCun paper on handwritten zip code recognition, highlighting its early application of backpropagation in a real-world scenario. Karpathy emphasizes the paper's surprisingly modern structure, including dataset description, architecture, loss function, and experimental results. He then describes his efforts to reproduce the paper using PyTorch, viewing this as a case study on the evolution of deep learning. The article underscores the enduring relevance of foundational research in the field.
Key Takeaways
- •The 1989 LeCun paper represents an early application of backpropagation for real-world image recognition.
- •The paper's structure and methodology are surprisingly modern, resembling contemporary deep learning research.
- •Reproducing the paper provides insights into the progress and evolution of deep learning techniques.
“The Yann LeCun et al. (1989) paper Backpropagation Applied to Handwritten Zip Code Recognition is I believe of some historical significance because it is, to my knowledge, the earliest real-world application of a neural net trained end-to-end with backpropagation.”