from PC Mag.com
Artificial intelligence has recently seen some great developments: better search engines, improved speech recognition programs, IBM’s Watson project, and more.
Underlying all of these advances are models of machine learning. Often, these models are in turn based on mathematical frameworks created by Judea Pearl, professor emeritus at UCLA, that enable algorithms that incorporate real world experiences and human reasoning.
ACM Executive Director John White told me that “Pearl’s research was instrumental in moving machine-based reasoning from the rules-bound expert systems of the 1980s to a calculus that incorporates uncertainty and probabilistic models.” In other words, he has figured out methods for trying to draw the best conclusion, even when there is a degree of uncertainty. It can be applied when trying to answer questions from a large amount of unstructured information, or trying to figure out what someone has said in languages that have lots of similar-sounding words—all things we do a lot today.
Vinton Cerf, an Internet pioneer and a former Turing Award recipient, explained that “Judea Pearl persisted in his deep analysis of Bayesian methods to extract useful information from partial data. In the face of skepticism, he persevered and, ultimately, his work has had enormous impact, not only on the theoretical basis for computational reasoning but in a very real sense, the basis for the successful business models of companies that search the World Wide Web.”…… Report
DCL: Judea’s thinking applies to event processing and decision making based upon event input. BTW, Judea Pearl is one of the nicest guys I’ve ever met.