Google Shares Research Findings With Scientific World
"Constructing part-of-speech taggers typically requires large amounts of manually annotated data, which is missing in many languages and domains. In this paper, we introduce a method that instead relies on a combination of incomplete annotations projected from English with incomplete crowd-sourced dictionaries in each target language. The result is a 25 percent error reduction compared to the previous state of the art," the post continues. Computer networks are the topic of the paper, "B4: Experience with a Globally Deployed Software Defined WAN," which "presents the motivation, design, and evaluation of B4, a software defined WAN" for data center to data center connectivity, according to the post. The authors of the report present their approach to separating the network's control plane from the data plane to enable rapid deployment of new network control services. The security concerns surrounding data localization and the cloud are the topic in the paper, "When the Cloud Goes Local: The Global Problem With Data Localization," according to the post. "Ongoing efforts to legally define cloud computing and regulate separate parts of the Internet are unlikely to address underlying concerns about data security and privacy," wrote the paper's authors. "Data localization initiatives, led primarily by European countries, could actually bring the cloud to the ground and make the Internet less secure." Statistics research was also covered in Google's top research for 2013. In the report, "Pay by the Bit: An Information-Theoretic Metric for Collective Human Judgment," a researcher looked at the topic of quality control in crowdsourcing. The report found that information theory provides a natural and elegant metric for the value of contributors' work, in the form of the mutual information between their judgments and the questions' answers, each treated as random variables.In May 2014, Google launched a new Quantum Artificial Intelligence Lab to find ways to make computers much smarter so they can help solve some of the world's most challenging problems, from diseases to environmental threats. In February, it announced its first-ever Google App Engine Research Awards to seven projects that will use the App Engine platform's abilities to work with large data sets for academic and scientific research. The new program, which was announced in the spring of 2012, brought in many proposals for a wide variety of scientific research, including in subject areas such as mathematics, computer vision, bioinformatics, climate and computer science. Google created the fledgling App Engine Research Awards program to bolster its support of academic research, while providing academic researchers with access to Google's infrastructure so they can explore innovative ideas in their fields, according to Google. The App Engine platform is designed for managing heavy data loads and running large-scale applications.
Google and its staff are often working on research in many topics in computing.