“Simple models and a lot of data trump more elaborate models based on less data.”
With that line, the 2009 paper “The Unreasonable Effectiveness of Data” (co-authored by Google co-workers Alon Halevy and Fernando Pereira), Google (s goog) Director of Research Peter Norvig all but guaranteed his status as one of most-quoted — or at least most-paraphrased — people in the world of big data. Last week, Norvig — as well as Google VP of Energy Arun Majumdar — was bestowed a slightly more-formal honor, as he was inducted into the American Academy of Arts and Sciences.
Norvig, who previously led Google’s search algorithms team and was head of computational sciences at the NASA Ames Research Center, is best known for his work in the realm of artificial intelligence. In fact, the above quote and the paper in which it appears are essentially a testament to the advances Google has been able to make in AI and machine learning thanks to the massive web page and search dataset that Google has amassed. The more examples it has of words and phrases used together in natural language, the better it can perform semantic analysis to determine what’s related to what.
Norvig and Majumdar are among 198 new inductees into the American Academy of Arts and Sciences’ latest class. According to a blog post from Google, they also join six other Google employees as members: Sergey Brin, Larry Page, Eric Schmidt, Vint Cerf, Alfred Spector, Hal Varian and Ray Kurzweil.