We describe how new sources of data can be used to better understand the demographic structure of the population of Rwandan mobile phone users. After combining anonymous call data records with follow-up phone interviews, we detect significant differences in phone usage among different social and economic subgroups of the population. However, initial experiments suggest that predicting demographics from call usage, and vice-versa, is quite difficult.
Marvin Minsky, an American scientist working in the field of artificial intelligence (AI) who co-founded vthe Massachusetts Institute of Technology (MIT) AI laboratory, wrote several books on AI and philosophy, and was honored with the ACM A.M. Turing Award, passed away on Sunday, Jan. 24, 2016 at the age of 88. Born in New York City, Minsky attended the Ethical Culture Fieldston School, the Bronx High School of Science, and Phillips Academy, before entering the U.S. Navy in 1944. After leaving the service, he attended Harvard University, where he earned a bachelor's degree in mathematics in 1950. He then went to Princeton University, where he built the first randomly wired neural network learning machine, the Stochastic Neural Analog Reinforcement Calculator (SNARC), before earning his Ph.D in mathematics there in 1954. Doctorate in hand, Minsky was admitted to the group of Junior Fellows at Harvard, where he invented the confocal scanning microscope for thick, light-scattering specimens, decades in advance of the lasers and computer power needed to make it useful; today, it is in wide use in the biological sciences.
StradVision has raised $16.6M in total. We talked with Junhwan Kim, its CEO. How would you describe StradVision in a single tweet? StradVision is a pioneer in deep learning-based vision processing technology, providing the software that will allow Advanced Driver-Assistance Aystems (ADAS) in autonomous vehicles to reach the next level of safety, and usher in the era of the fully autonomous vehicle. How did it all start and why?
Editor's note: The following is an interview with Columbia University Professor Andrew Gelman conducted by Marketing scientist Kevin Gray, in which Gelman spells out the ABCs of Bayesian statistics. Kevin Gray: Most marketing researchers have heard of Bayesian statistics but know little about it. Can you briefly explain in layperson's terms what it is and how it differs from the'ordinary' statistics most of us learned in college? Andrew Gelman: Bayesian statistics uses the mathematical rules of probability to combines data with "prior information" to give inferences which (if the model being used is correct) are more precise than would be obtained by either source of information alone. Classical statistical methods avoid prior distributions.