With faster processing power, training data can be larger and neural networks more complex. The rise of improved processing power and its availability through cloud services allows artificial intelligence to become more advanced. Artificial intelligence needs large sets of data, called training data, to learn and become accurate. Depending on the level of complexity, these data sets may need millions or even billions of data points. With the rise of the internet, smartphones, and digitization, large scale user data is captured and now available to "train." Datafication is a modern technological trend turning many previously analogue aspects of our lives into computerized, measurable data. Smartphones, laptops, tablets, and wearable devices capture previously undocumented data points to allow for more sophisticated predictive analytics. Such data points include heart rate, eye movements, tone of voice, location, facial expressions, speed, exercise habits, nutrition levels, and more.