Imitating the nematode’s nervous system to process information efficiently, this new intelligent system is more robust, more interpretable, and faster to train than current deep neural network architectures with millions of parameters.
Deep Neural Networks And Other Approaches
Researchers are always looking for new ways to build intelligent models. We all know that really deep supervised models work great when we have sufficient data to train them, but one of the hardest things to do is to generalize well and do it efficiently. We can always go deeper, but it has a high computation cost. So as you may already be thinking, there must be another way to make machines intelligent, needing less data or at least fewer layers in our networks.
One of the most complicated tasks that machine learning researchers and engineers are currently working on is self-driving cars. This is a task where every option needs to be covered, and completely stable, to be able to deploy it on our roads. This process of training a self-driving car typically requires many training examples from real humans as well as a really deep neural network able to understand these data and reproduce the human behaviors in any situation ….