Machine learning is an aspect of artificial intelligence that involves training a neural network (a digital version of the brain) with a specific set of inputs. During that training, the net will determine what factors determine one outcome over another. Here are some of the possible uses of machine learning, should the computation power grow enough to accommodate these use cases:
Medical – The medical field has the most to gain from machine learning. There is already a trial in progress that uses images taken of patient’s retina to determine the potential for cataracts and other issues.
Self-driving cars – Google is already using some form of machine learning for its self-driving car program. We do not know what Waymo uses at this point, but it is not a machine learning algorithm that drives the actions of the car. However, in the future, the car itself could be figuring out what is or isn’t dangerous based on a trained model.
Home automation – At the moment, home automation is a series of connected devices triggered under certain conditions. In a truly smart home environment, the house would know when someone came home if that person is you and what you usually do when you get home. This, in turn, would set the temperature, switch on the lights, open the garage and prepare for your entry into the house.
AR – Augmented Reality could be the next big thing. Google Lens shows us what is already possible and with some development could be the basis for an augmented reality display on glasses or contact lenses.