Only a few years ago, "intelligent" technologies for speech recognition and internet-supplied recommendations (e.g. via Amazon) were so ineffective that their use was rare and by only a few. Since then, these technologies have enjoyed a very active period of innovation, and are now relied upon daily by millions of people around the world. In this lecture, intended for a general audience, I will describe how intelligent systems of this kind are built through the clever use of optimization algorithms and vast amounts of data. In particular, two live interactive demos will be given to illustrate the challenges ahead. The lecture will conclude with the interesting observation that these same optimization algorithms are also leading to important advances in other spheres, including Formula-1 auto racing and weather prediction.
Jorge Nocedal is a Professor in the Industrial Engineering Department at Northwestern University. His research interests are in optimization algorithms and their application in areas such as machine learning. Much of his current research is being drive by a close collaboration with Google Research. Jorge is passionate about undergraduate education; he was one of the developers of the "Engineering First" Curriculum at Northwestern that exposes students to engineering design in their freshman year. He is currently the Editor in Chief for the SIAM Journal on Optimization, is a SIAM Fellow, and was awarded the 2012 George B. Dantzig Prize.