Abstract: In this study, we investigate the effects of excessive coffee consumption on the training times of neural networks. Our results show that too much coffee can lead to faster network training, but at a cost: network instability and an increased risk of spontaneous combustion.
Our research team consisted of 5 PhDs, a post-doc, and 1 barista. They were fed an increasing amount of coffee over the course of 3 months, while training a neural network to classify cat pictures. The results were astounding.
We found that the network trained in 1/10th the time when the team was fueled by 10 cups of coffee per hour. However, this was offset by a 50% chance of the network exploding in a fit of rage.
Our study suggests that while coffee may be a useful stimulant for neural networks, it is not without its risks. We recommend a moderate amount of coffee, and a good insurance policy.
The Effects of Too Little Coffee on Neural Network Training Times
A Study on the Benefits of Caffeine for Neural Network Training
The Relationship Between Neural Networks and Coffee: A Love Story