Machine Learning

Definitions

Artificial intelligence

John McCarthy defined artificial intelligence (in 1956 when preparing the Dartmouth workshop; here, however, we are citing [M07]) as

the science and engineering of making intelligent machines, especially computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.

As explained in [N09], citing this link,

McCarthy has given a couple of reasons for using the term "artificial intelligence." The first was to distinguish the subject matter proposed for the Dartmouth workshop from that of a prior volume of solicited papers, titled Automata Studies, co-edited by McCarthy and Shannon, which (to McCarthy's disappointment) largely concerned the esoteric and rather narrow mathematical subject called "automata theory." The second, according to McCarthy, was "to escape association with 'cybernetics'. Its concentration on analog feedback seemed misguided, and I wished to avoid having either to accept Norbert Wiener as a guru or having to argue with him."

Machine learning

Nidhi Chappell, head of Machine Learning at Intel, in her interview to Wired says

AI is basically the intelligence — how we make machines intelligent, while Machine Learning is the implementation of the compute methods that support it. The way I think of it is: AI is the science and machine learning is the algorithms that make the machines smarter. So the enabler for AI is machine learning.

Bibliography

• [M07] John McCarthy. What Is Artificial Intelligence? Computer Science Department, Stanford University, 2007, http://jmc.stanford.edu/articles/whatisai/whatisai.pdf.
• [N09] Nils J. Nilsson. The Quest for Artificial Intelligence: A History of Ideas and Achievements. Cambridge University Press, 2009.