A machine be capable of learning be built through:

• By building a machine with sufficient computational resources, offering training examples from real-world data, and by designing specific algorithms and tools that define a learning process, rather than specific data manipulations, machines can improve their own performance through learning by doing, inferring patterns, and hypothesis checking.

• By reinforcement learning that uses external feedback to teach the system to change its internal workings in order to guess better next time. This self-change involves identifying the factors that made the biggest difference in the algorithm’s decision, reinforcing accuracy and discouraging wrong decisions.