NUS has teamed up with Grab, one of Southeast Asia’s most frequently used online-to-offline mobile platforms, to set up an artificial intelligence (AI) laboratory. The Grab-NUS AI Lab — Grab’s first major AI laboratory and NUS’ first AI laboratory with a commercial partner — aims to develop solutions to transform urban transportation, solve complex real-world challenges and pave the way for smarter cities in Southeast Asia.
“Southeast Asia is very unique; it is rapidly growing and developing and there is a huge influx of people coming into the cities. It is also a place where congestion is a big problem for many of the major cities and is probably the best place to study how congestion is formed and how to solve that,” said Professor Ng See-Kiong, Co-Director of the Grab-NUS AI Lab and Director (Translational Research) at the NUS Institute of Data Science. He added that this is an opportunity to leverage on big data and AI to “do something different for our region and with our own people and our own talent”.
Set up with an initial investment of $6 million over two years, the Lab was officially launched on 18 July, graced by Guest-of-Honour Minister for Education Ong Ye Kung. During the event, Mr Ong witnessed the signing of the Research Collaboration Agreement between NUS President Professor Tan Eng Chye and Mr Anthony Tan, Co-Founder and Group CEO of Grab. He also took the opportunity to visit the Lab, housed at the innovation 4.0 building on the Kent Ridge campus.
Since its founding, Grab has facilitated more than 2 billion rides and their vast data can provide deeper insights into how Southeast Asian cities move today. Combining this data with NUS’ AI research expertise, the Grab-NUS AI Lab will map out traffic patterns and identify ways to directly impact mobility and liveability of cities across Southeast Asia.
“The AI Lab will harness the power of Grab’s data and machine learning with research and talent from a world leading institution, to become a valuable tool for governments who are bringing smarter transport to their cities in Southeast Asia,” said Mr Tan.
The Grab-NUS AI Lab will first focus on improving the efficiency and reliability of transportation on the Grab platform in Southeast Asia’s cities, before expanding to research on larger challenges, including congestion and liveability.
The Lab will also develop algorithms to better understand traffic flow and improve passenger and driver experience. These include smarter and more personalised services for passengers based on their needs, intentions and preferences; matching drivers to jobs they prefer and improving safety in driving through better understanding of driver behaviour; real-time detection of traffic events and anomalies which can improve traffic flow; improving the precision and accuracy in the mapping of pick-up points; and localising moving vehicles to increase the ease and efficiency of moving from point to point.
In his speech at the event, Prof Tan said that NUS is very excited to be a partner of Grab’s first major AI Lab and that it is an excellent collaborative effort to create unique AI innovations based on insights relevant to Asia and the world. “This is also a great opportunity for our researchers and students to make a real-world impact through our research in data science and AI. Over time, we hope to build a healthy pipeline of well-trained and experienced data scientists and AI researchers for Singapore and beyond,” he said.
Prof Tan also noted that the Grab-NUS AI Lab is in a position to provide experiential learning for students, a need highlighted at the recent parliamentary debates. “The Grab-NUS AI Lab will be an excellent example of how industry and academic institutions can work together to provide realistic, contextualised learning opportunities for our students. Students will be able to work off real-life data from Grab, and hone their data analytic skills by addressing research questions that have been jointly developed by Grab and NUS,” he elaborated.
Some 28 researchers working on various AI projects are expected to be housed in the new Grab-NUS AI Lab.
See press release.