Improbable Inspiration: Bayesian Networks (1996)

&gt; Then, in the late 1980s--spurred by the early work of Judea Pearl, a professor of computer science at UCLA, and breakthrough mathematical equations by Danish researchers--AI researchers discovered that Bayesian networks offered an efficient way to deal with the lack or ambiguity of information that has hampered previous systems.<p>The &quot;mathematical equations by Danish researchers&quot;, for those interested, are most likely this paper:<p>Lauritzen, S.L. and Spiegelhalter, D.J. (1988), Local Computations with Probabilities on Graphical Structures and Their Application to Expert Systems. Journal of the Royal Statistical Society: Series B (Methodological), 50: 157-194. <a href="https:&#x2F;&#x2F;doi.org&#x2F;10.1111&#x2F;j.2517-6161.1988.tb01721.x" rel="nofollow">https:&#x2F;&#x2F;doi.org&#x2F;10.1111&#x2F;j.2517-6161.1988.tb01721.x</a><p>Direct PDF Link: <a href="https:&#x2F;&#x2F;www.eecis.udel.edu&#x2F;~shatkay&#x2F;Course&#x2F;papers&#x2F;Lauritzen1988.pdf" rel="nofollow">https:&#x2F;&#x2F;www.eecis.udel.edu&#x2F;~shatkay&#x2F;Course&#x2F;papers&#x2F;Lauritzen1...</a>

I like how in the mid 90s neural networks were almost a write-off. &quot;But the neural nets won&#x27;t help predict the unforeseen. You can&#x27;t train a neural net to identify an incoming missile or plane because you could never get sufficient data to train the system.&quot;

Interesting to see this underpinned the Office Help System one way or another— probably being the infamous paperclip.

Way ahead of their time. They just needed 25 more years of Moore’s law...