There exist many misconceptions when it comes to Artificial Intelligence (AI), Machine Learning (ML)and Deep Learning (DL).
Many times these three terminologies are used interchangeably, but actually they don’t refer to the same things.
John McCarthy, commonly known as one of the godfathers of AI, defined it in 1955, as “the science and engineering of making intelligent machines that have the ability to achieve goals like humans do.”
In other words, Artificial Intelligence is human intelligence as displayed by machines. In reality, we haven’t yet been able to create a proper AI till now but we’re very close. Sophia, an AI is the most advanced version present today. We still don’t know many aspects of the human brain like ‘why do we dream ?’ etc., and that’s the reason we are not able to establish proper AI till now.
Arthur Samuel defined Machine Learning (ML) in 1959 as “a large sub-field of AI dealing with the field of study that gives computers the ability to learn without being explicitly programmed”. That is, ML is enabling machines to learn by themselves using the provided data and make accurate predictions by themselves.
So basically, ML is a subset of artificial intelligence; in fact, it’s simply a system or method for realizing AI.
These days, numerous companies use ML to enhance their customer experience. An example is Amazon that uses Machine Learning techniques to give better product recommendations to customers based on their previous preferences. Even Netflix uses ML to offer better suggestions to their viewers of the content that they would like to watch.
Deep learning is also a subset of ML; and just as ML is for AI, Deep Learning is just a technique for realizing Machine Learning. In other words, DL is the further development of ML. Deep Learning algorithms are inspired by the information processing patterns of the human brain. The way we use our brain to identify patterns and organize information, deep learning algorithms can learn to accomplish similar tasks for machines.
If you compare deep learning and machine learning, you’ll realise the subtle differences. For instance, DL can automatically discover the features to be used for classification of information, whereas ML requires these features to be specified manually.
So even though they are all interrelated and interdependent, they refer to completely different things. To summarize, Artificial Intelligence is human intelligence displayed by machines; Machine Learning is an approach to achieve Artificial Intelligence; Deep Learning is a technique for implementing Machine Learning.