Gain an overview of the evolution of databases and its various applications
Explore the applications of knowledge bases and graphs in AI and cognitive systems as well as use cases in AI and cognitive computing and the data infrastructure built to support these systems
In the past 70 years, we have seen databases evolve from punch cards and tapes to globally distributed databases supporting web-scale applications. Each step in this evolution was critical to the enablement of different fields of computing. The relational database enabled the rise of BI systems, and NoSQL databases enabled web scale applications. Now, the future is cognitive computing. However, these systems process data that is more complex than before. Haikal Pribadi reviews the evolution of databases and explains where knowledge graphs and bases sit in this evolution. Could they serve as the next generation of databases?
Haikal Pribadi is the founder and CEO of GRAKN.AI, the database for AI, which uses machine reasoning to handle and interpret complex data. GRAKN.AI was recently awarded Product of the Year 2017 by the University of Cambridge Computer Lab. Haikal’s interest in the field began at the Monash Intelligent Systems Lab, where he built an open source driver for the Parallax Eddie Robot, which was then adopted by NASA. Haikal was also the youngest algorithm expert behind Quintiq’s optimization technology, that supports some of the world’s largest supply chain systems in transportation, retail, and logistics. He holds a master’s degree in AI from the University of Cambridge.
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