Infrastructure Requirements for AI Inference vs. Training

Investing in deep learning (DL) is a major decision that requires understanding of each phase of the process, especially if you're considering AI at the edge. Below are practical tips to help you make a more informed decision about DL technology and the composition of your AI cluster. For the purposes of this article, let's define the terms we'll be using: Neural Network: Artificial neural networks are computing systems inspired by the organic neural networks found in human and other animal brains, where nodes (artificial neurons) are connected (artificial synapses) to work together. To enable deep learning of an artificial neural network, your team must curate huge quantities of data into a designated structure, then feed that training dataset into a DL framework. Once the DL framework is trained, it has learned what inputs lead to what logical conclusion.