A Comparative Roundup: Artificial Intelligence vs. Machine Learning vs. Deep Learning
A 1969 McKinsey article claimed that computers were so dumb that they were not capable of making any decisions. In fact they said, it was human intelligence that drives the dumb machine. Alas, this claim has become a bit of a “joke” over the years, as the modern computers are gradually replacing skilled practitioners in fields across many industries such as architecture, medicine, geology, and education. Artificial Intelligence, Machine Learning, Data Science, and Deep Learning are pushing these changes in ways that are only just being understood.
In the current scenario, many buzzwords are being employed in the evolving IT industry, especially in the various research areas around and within Data Science. For many years, the world has known about experiments (with varying degrees of success) in Artificial Intelligence (AI), but recently, rapid strides were made in this field of study, leading to allied research areas of Machine Intelligence, Machine Learning, and now, Deep Learning. So how are these specialized sub-domains under AI similar to or different from each other? This article takes a look.
Artificial Intelligence: This “umbrella” term encompasses all these areas of research. According to field experts, the definition of AI has suffered many detours, thus rendering the term nearly useless over the years. McKinsey’s 2015 Report titled Disruptive technologies: Advances that will transform life, business, and the global economy suggests that about 12 disruptive technologies will create a great global impact 10 years from now. Among these 12, at least five have been determined to be related to AI and Robotics, which includes: automated “knowledge” tasks, Robotics, Internet of Things, 3D Printing technology, and self-driving cars. The total economic impact of these combined technologies has been estimated to reach between $50-99.5 trillion by 2025!
Machine Intelligence (MI): Many Data Scientists believe that Machine Intelligence and Artificial Intelligence are interchangeable terms. The term “Machine Intelligence” has been popular in Europe, while the term “Artificial Intelligence” with its scientific slant has been more popular in the US. MI indicates an involvement of a biological neuron in the research process with a more superior approach than the one usually employed in Sim