Machine learning is an ever-present and often misunderstood technological concept. The practice, which is the science of using complex processing and mathematical techniques to enable computers to find correlations between large swaths of inputs and output data has been in our collective consciousness of technologies for decades.
Neural-network training seems fairly straightforward. When we’re working with a simple network (such as the single-layer Perceptron shown below), the math required for training is certainly not overwhelming, the network itself can be implemented in a relatively short program written in common languages such as C or Python, and the training process doesn’t require excessive amounts of computational time.
5G, the next (fifth) generation in wireless smartphone communications, has been heavily promoted in the consumer world as a level up for mobile devices. But what does 5G entail in the eyes of the engineers who develop these devices? In this article, we will dive deeper into 5G NR and explore the multiple-use models and multiple frequency bands covered by this emerging standard. We will also take a look at some of the advanced technologies associated with 5G NR.
