The notion of personalized, contextually aware search is nothing new, but it can put a tremendous strain on servers by asking for a lot of data at once. NC State has developed a search technique that could ease that burden. Its code prioritizes results based solely on the "ambient query context," or the concepts related to a person's recent search history. Look for politicians, for example, and a search for Ford is more likely to bring up Gerald Ford than the car company. By focusing on just a fraction of a user's search habits, the university can customize results using far fewer processor cycles: while a test server could only handle 17 active searchers with an old approach, it can manage 2,900 with the new method. The query engine won't be confined to the lab, either. NC State tells us that a community-driven search beta is due within several months, and there are plans to commercialize the technology in the long run.