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April 10-11, 2018: Training
April 11-13, 2018: Tutorials & Conference
Beijing, CN

Databases: The past, the present, and the future of cognitive computing

This will be presented in English.

Haikal Pribadi (GRAKN.AI)
14:5015:30 Friday, April 13, 2018
模型与方法 (Models and Methods), 英文讲话 (Presented in English)
Location: 多功能厅2(Function Room 2) Level: Intermediate
Secondary topics:  AI应用的硬件、软件栈(Hardware and Software stack for AI applications)

必要预备知识 (Prerequisite Knowledge)

A basic understanding of databases (relational, NoSQL, etc.) and how to work with complex data and AI and cognitive systems

您将学到什么 (What you'll learn)



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

描述 (Description)


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?


Photo of Haikal Pribadi

Haikal Pribadi


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.