But in the mid seventies, when it became apparent that A.I. was not delivering on its promise, the industry bubble burst and the funding dried up. In the 1980s, as computers became more popular, another A.I. boom emerged with similar levels of mind-boggling investment being poured into various enterprises. But, again, the sector failed to deliver and the inevitable bust followed.
To understand why these booms failed to stick, you first need to understand what artificial intelligence actually is. The short answer to that (and believe me, there are very very long answers out there) is that A.I. is a number of different overlapping technologies which broadly deal with the challenge of how to use data to make a decision about something. It incorporates a lot of different disciplines and technologies (Big Data or Internet of Things, anyone?) but the most important one is a concept called machine learning.