To clarify this topic, and understand the difference between Machine Learning (ML) and Artificial Intelligence (AI), it is useful to begin by mentioning some simple definitions.
The AI refers essentially to the ability of a high-tech or computerized device to simulate the human mind. AI software routines and systems provide what appears to be logic, memory and decision making in these devices. As its name implies, artificial intelligence can be interpreted in a general way as the incorporation of human intelligence into machines.
For example, these machines can be used to move and manipulate objects, language recognition and problem solving. Today, the routine of AI is in an increasingly wide range of consumer electronic products, from Bluetooth speakers and smartphones to portable devices of all kinds.
Machine Learning, as the name implies, can be interpreted in a general way as empowering computer systems with the ability to “learn”.
The purpose of ML is to allow machines to learn by themselves using the data provided and make accurate predictions. Then, instead of software routines coded with specific instructions to perform a particular task, Machine Learning is a way to “train” an algorithm so you can learn how to do it. “Training” involves providing enormous amounts of data to the algorithm and allowing the algorithm to adjust and improve.
As an example of ML we can see how the vision of computers has been improved, to recognize an object or image.
At this point, then we can say that ML is a subset of AI, in fact, it is simply a technique within it.
In the industrial aspect, the AI can be applied to predict when the machines will need maintenance or to analyze the manufacturing processes to obtain great efficiency gains, saving millions of dollars.
On the consumer side, instead of having to adapt to technology, technology can adapt to us. Instead of clicking, writing and searching, we can simply ask a machine what we need. We could ask for information such as weather or an action such as preparing the house for bedtime (turning off the thermostat, closing the doors, turning off the lights, etc.).
Finally, it is also true that ML represents currently the most promising path towards artificial intelligence.