Brown Bag: David A. Yuen
Today we all recognize that scientific machine learning and artificial intelligence are rapidly developing research areas, which scientists must learn to harness effectively in the near future. In this lecture I will give a rundown of the development in Big Data since 2013 in both China and USA and to compare the two systems. I will focus on the challenges confronting educators at universities around the world, which is to train an useful work-force capable of handling big data for the application arena, which encompass not only geosciences but also medical sciences and financial domain. But I will use geosciences as a prime target example, since here we can gather much data from seismology, remote sensing, GPS, INSAR and mineralogical data taken from geological field sites. Examples will be drawn from the geosciences. Finally I will stress that the fundamentals of high-performance computing(HPC) and visualization are still sorely needed and must be employed because of the need to label and to train these numerous data into useful neural networks for eventual applications.