Good Old Fashioned AI is dead, long live New-Fangled AI
The "new-fangled" AI, as the article calls it, is often useful when the stakes are low, and you can accept mistakes in outcomes. Examples of such applications are: trying to determine which of your friends occur in a photo, which movies a subscriber <i>may</i> be interested in, or which action <i>could</i> lead to victory in a computer game. Getting a rough translation of a newspaper entry, as mentioned in the article, is also a good example.<p>As soon as you need reliable outcomes, such as certainty <i>whether</i> an erroneous state can arise in a program, <i>whether</i> a proof for a mathematical conjecture exists, or <i>whether</i> a counterexample exists, exhaustive search is often necessary.<p>The question then soon becomes: How can we best delegate this search to a computer, in such a way that we can focus on a clear description of the <i>relations</i> that hold between the concepts we are reasoning about? Which symbolic <i>languages</i> let us best describe the situation so that we can reliably reason about it? How can we be certain that the computed result is itself correct?<p>The article states: <i>"The heart of GOFAI is searching – of trees and, more generally, graphs."</i> I think one could with the same conviction state: "The heart of GOFAI is reasoning – about relations and, more generally, programs."