Google has announced the that they have awarded about $4 million to about 75 projects “full time faculty pursuing research in a areas of mutual interest” for Q2. In other words, there are people doing things that can help Google who aren’t Google employees. As a result, of course, Google wants in.
While admittedly some of the listed projects are a bit beyond my scope of understanding, it is interesting to see this list from the Official Google Blog to get a glimpse of what is being done with data to help get more mileage from it.
Jeremy Cooperstock, McGill University. A Spatialized Audio Map System for Mobile Blind Users(Geo/maps): A mobile audio system that provides location-based information, primarily for use by the blind and visually impaired communities.
Alexander Pretschner, Karlsruhe Institute of Technology, Germany. Towards Operational Privacy (Security and privacy): Provide a framework for precise semantic definitions in policies for domain-specific applications to give users a way to define the exact behaviour they expect from a system in application-specific contexts.
Erik Brynjolfsson, Massachusetts Institute of Technology. The Future of Prediction – How Google Searches Foreshadow Housing Prices and Quantities (Economics and market algortihms): How data from search engines like Google provide a highly accurate but simple way to predict future business activities.
Stephen Pulman, Oxford University Computing Laboratory. Automatic Generation of Natural Language Descriptions of Visual Scenes (Natural language processing): Develop a system that automatically generates a description of a visual scene.
Jennifer Rexford, Princeton. Rethinking Wide-Area Traffic Management (Software and hardware systems infrastructure): Drawing on mature techniques from optimization theory, design new traffic-management solutions where the hosts, routers, and management system cooperate in a more effective way.
John Quinn, Makerere University, Uganda. Mobile Crop Surveillance in the Developing World(Multimedia search and audio/video processing): A computer vision system using camera-enabled mobile devices to monitor the spread of viral disease among staple crops.
Allison Druin, University of Maryland. Understanding how Children Change as Searchers (Human-computer interaction): Do children change as searchers as they age? How do searchers typically shift between roles over time? If children change, how many of them become Power Searchers? If children don’t change, what roles do they typically demonstrate?
Ronojoy Adhikari, The Institute of Mathematical Sciences, India. Machine Learning of Syntax in Undeciphered Scripts (Machine learning): Devise algorithms that would learn to search for evidence of semantics in datasets such as the Indus script.
We report on what the market has been given but we don’t often think about what is being worked on for the future. Helping the blind with mobility and the prediction of future business activities based on search is interesting stuff for sure.
I wonder what other companies do in these areas? Have you heard of other programs like this?