Artificial Intelligence & Machine Learning, at times, are used interchangeably by users & developers.
Although there is a fair amount of correlation between the two; still the terms & their concepts are not similar to each other. In an actual sense, artificial intelligence is a super-set of machine learning as illustrated in the figure below.
As depicted in the figure above, ‘artificial intelligence is the concept which is aimed at equipping machines & systems with human-like intelligence so that they can self-initiate a response based on the particular input or stimuli.
Machine Language is a subset of Artificial Intelligence that deals in different mathematical and statistical techniques & tools which enable systems & machines to self-learn from data so that they can respond to further stimulus without any extensively coded business logic layer.
1. The emergence of Machine Learning from Artificial Intelligence
As mentioned, machine learning is a subset of artificial intelligence, the figure below shows precisely where does machine learning stands –
Generalizing the different branches of artificial intelligence into more fundamental categorization; artificial intelligence can either be general or applied. In the current world, applied artificial intelligence is more prevalent, and is extensively used in designing smart systems. A few examples of applied AI include intelligent stock trading software, automatic vehicles, etc.
General AI is the current buzzword; aims to equip systems and machines to perform virtually everything that a human does (and even beyond it).
The rise of machine learning is a direct consequence of the interest & investment that has gone in the general AI category.
The onset & emergence of machine learning is primarily due to two major factors:
- The hypothesis or realization (which first happened in the year 1959) that rather than coding every bit of business logic for systems to behave; systems need to be taught how to learn themselves and take self-decisions
- Internet-boom and a lot of focus that businesses have entrusted on the digital domain – all of which leading to a humongous amount of data to be used and leveraged
2. Artificial intelligence vs. Machine Learning – Rationale behind the confusion
As per recent surveys done by The Verge, more than 40% of the start-ups based out of Europe wrongfully claimed that they are using AI technologies. The reason for this confusion could be multi-pronged – starting from a lack of clear understanding of the concepts, or even businesses trying to use these hype words to promote their operations; thereby increases sales & revenues.