Reading a great research paper is a joy. A team of experts deftly guides you, the reader, through the often complicated research landscape, noting the prior art, the current trends, the pressing issues at hand—and then, sometimes artfully, sometimes through seeming sheer force of will, expands the body of knowledge in a fell swoop of 12 or so pages of prose. A great paper contains a puzzle and a solution; these can be useful, enlightening, or both. A great paper is a small, structured quantum of human ingenuity, creativity, and labor, in service of a growing understanding of our world and the future worlds we may inhabit.
Unfortunately, information overload is a defining problem of our time, and computer science research is no exception. The volume of research produced each year in computer science is heartening, but it can be difficult to determine which papers are most deserving of our scarce time. This volume of papers is also at odds with many of the best elements of paper reading: distillation of work to its critical essence, thoughtful consideration of its nuances and the context in which the research was performed, and application of concepts to one's own technical problems and experiences.
Google’s focus on innovation, its services model, its large user community, its talented team, and the evolutionary nature of CS research has led Google to a “Hybrid Research Model.” In this model, we blur the line between
research and engineering activities and encourage teams to pursue the right balance of each, knowing that this
balance varies greatly.
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