The hardest problem in computing

Big data serving, a complex challenge in applied computing, involves computing over large data sets in real-time, requiring solutions for distributed state management, low latency, high availability, and distributed computation. Traditional methods, like using databases with stateless middle-tier applications, fall short due to network and latency constraints, prompting the need for systems that compute locally where data is stored. Web search, a classic example of big data serving, has driven the development of advanced systems capable of handling the required computational demands. Vespa.ai, an open-source engine developed from the late 1990s web search engine alltheweb.com and later supported by Yahoo!, addresses these challenges by enabling real-time machine-learned model inferences and data organization. With approximately 700 man-years of development, Vespa has become a viable option for various applications beyond search, including recommendation and personalization, offering new possibilities for low latency data computation.