Differences between AI and ML

Artificial Intelligence (AI) and Machine Learning (ML) are not interchangeable terms although they are often used as such. AI refers to the idea of machines being capable of acting in smart ways. ML is an application of AI, which works under the assumption that we should just give machines data and that they should learn for themselves.

Applied and General AI

There are two different types of AI, applied and general, each of which has a different purpose. Applied AI is commonly used in trading stocks and shares or in self-driving cars. Generalized AI is a little more complex, this type of AI is present in devices or systems that could theoretically complete any task.

Machine Learning

It is the area of generalized AI which brings us Machine Learning, an exciting new avenue for the field. Instead of teaching computers large amounts of information, ML seeks to teach computers how to learn on their own. The internet has been a driving force in the development of ML because it produces, gathers, and stores incredible amounts of information.

Neural networks – computer systems which group information in the way that human minds do – have been critical to the development of ML. These help computers to think about things and understand the world like a human while staying as accurate, fast, and impartial as a computer. Interestingly, neural networks can help a computer to see images and organize them according to elements they contain.

ML is based on probability. When data is fed into the system, the computer can make predictions, decisions, or statements with some amount of certainty. Feedback is given to the machine about whether the decision it made was correct, and it can learn and revise its answer for the future.

ML systems can do many interesting things. They can read text in the tone the writer was going for, they can listen to music and categorize it by mood, and they might even be able to write their own music to produce a similar feeling.

Natural Language Processing

We should also be able to talk to computers as naturally as we could another person. This is becoming more and more possible with another type of AI, Natural Language Processing (NLP). ML can be used to help computers understand the incredible nuances of language, and to answer in a way that humans can understand.

Many experts have thought that human-like AI is inevitable, and we are currently moving towards that goal very quickly. A great amount of the progress that we have seen in recent years is thanks to ML changing the ways in which we think AI will work.