Machine Learning Is Very Different Than Artificial IntelligenceBy Chris Brandt, UniversityHerald Reporter
There are two very popular words in science and technology nowadays - artificial intelligence and machine learning. For a lot of people who might not be aware of the difference, they are just the same. It might come, therefore, as a surprise that these two are different.
In a nutshell, artificial intelligence is the general word or category that is given to describe the idea of machines being able to perform tasks that we label as smart. Machine learning, on the other hand, is a new concept within the big idea of artificial intelligence which maintains that machines can be given data to learn by themselves.
The concept of artificial intelligence existed even before the Industrial Revolution or even before the Enlightenment. The Greeks have already explored the idea in their myths. The most popular of them was about Talos, a giant bronze man forged by Hephaestus, who guard Europa and Crete against pirates. Furthermore, European philosophers during the Middle Ages tried to create analog computer devices they labeled as "logical machines."
As technology progresses, the concept of AI becomes broader and more sophisticate. Now, it is divided into two groups: applied AI and general AI. Applied AI is normally used in automation, like trading stocks and autonomous vehicles. General AI consists of systems that can do almost any task intelligently. This is where machine learning falls.
The idea of machine learning started when Arthur Samuel suggested that instead of teaching machines everything they need to learn, why not teach them to learn for themselves. This became possible with the development of neural networks. Nowadays, some of the most common usage of machine learning is in the use of marketing, Google searches, and natural language processing.
Machine learning has certainly become the buzzword nowadays as a lot of marketers consider AI "old hat" having been around the block for a long time. So, they are repackaging it focusing on machine learning to make it sound fresh and new.