Embracing AI In Singapore

Efficient, accessible and flexible supercomputing resources will play a key role in helping Singapore harness AI technology, says AI Singapore’s Professor Leong Tze Yun.

AsianScientist (Feb. 13, 2019) – Today, there’s no escaping the fact that artificial intelligence (AI) has crept into many aspects of our lives, making communications easier, workflows more effective and research analyses much faster.

Recognizing the productivity gains to be had from the power and pervasiveness of AI, Singapore intends to embrace the technology as part of its Smart Nation initiative. But are businesses and consumers ready to hop onto this AI-adopting journey?

To find out, Supercomputing Asia talked to Professor Leong Tze Yun, director of AI technology at AI Singapore (AISG), a national initiative set up to coordinate the city state’s capabilities in the technology.

What is the state of AI activity in Singapore?

Singapore is no stranger to the adoption of AI and takes pride in having a very active research and development community in AI and its related disciplines. The activity is fueled by highly regarded research work done by universities and research institutions.

A clear sign of adoption is also seen through many successful startup companies that develop or deploy AI technologies. Some of these have even originated from AI research and development in Singapore, for example, companies like [visual search and image recognition startup] ViSenze and [workforce optimization startup] FriarTuck.

What challenges do businesses and end-users face in getting technology-ready for AI?

The most common struggle is the uncertainty of where and how to start with AI. Many people also have doubts and misunderstandings and are often influenced by popular literature and myths. In fact, AI technologies have already been changing our daily lives through the way we work and communicate with others—such as predictive analytics in medical diagnoses and natural language processing in chatbots.

I believe the key to addressing this challenge is in talent development, recruitment and deployment. Apart from public education, a more concerted effort needs to be made in the formal education and training of AI scientists and engineers at the tertiary level, as well as in sectors such as finance, healthcare, education and logistics.

A new model of lifelong learning for the workforce has emerged. For example, industry and institutes of higher learning are working closely together to retrain and upskill employees with specialized skills, and to provide students with more internship opportunities. The government is also providing incentives and establishing policies and guidelines for implementing lifelong learning programs and specialized programs to reach out to targeted sectors, the schools and the public.

How is AISG boosting Singapore’s AI capabilities?

As AISG is a government-driven national program, our goal aligns with the government’s ambitions for AI, which is to catalyze, synergize and boost Singapore’s AI capabilities to power our future digital economy.

AISG will bring together all Singapore-based publicly funded research institutions and the vibrant ecosystem of AI start-ups and companies developing AI products, to perform fundamental and use-inspired research, grow the knowledge, create the tools and develop the talent to power Singapore’s AI efforts.

We support AI innovation by co-funding proof-of value projects in our 100 Experiments (100E) program. To accelerate adoption of AI by industry, the program pairs companies that have a significant industry problem with AI researchers in Singapore to work on their problem statement.

We also support a new approach to research and education in the AI Grand Challenge program, which addresses highly complex issues with significant social and economic impacts in Singapore and beyond. We aim to provide a translation framework and test bed for multidisciplinary teams to work together to devise innovative solutions that can be put into practical use.

What role do supercomputers play in Singapore’s AI strategy?

I would define the future of ‘supercomputing’ for AI as a highly efficient, highly accessible and highly flexible computing and information framework.

In addition to the clusters of high performance processors and data centers, future computing and information platforms for AI research, development, translation and innovation should support rapid prototyping, creative experimentation and effective translation to full-scale production in a fast, secure and adaptable manner.

The platforms and frameworks should facilitate collection, communication, analysis and generation of information from human experts and users as well as from edge and mobile devices. They should also support automated and interactive prototyping, real life experiments and large-scale implementation.

In other words, the underlying computing and information infrastructure should support the whole process of idea generation, knowledge discovery, realtime test-bedding and scaling for deployment.

How can AISG help researchers access supercomputing resources?

We are working closely with the National Supercomputing Centre Singapore to support the work done by researchers and companies participating in our programs. We also provide support for research into the development and deployment of AI technologies, applications and systems.

In fact, we are building an in-house, high performance computing platform to support a range of in-house and funded research and education activities. With our partners, we are also assessing the feasibility of establishing a secure, privacy-preserving and protected access facility to provide relevant real-life data for the teams working on the AI Grand Challenges.

This article was first published in the print version of Supercomputing Asia, January 2019.
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Copyright: Asian Scientist Magazine; Photo: National University of Singapore.
Disclaimer: This article does not necessarily reflect the views of AsianScientist or its staff.

Brenda obtained her MSc in Science Communications from the University of Sheffield, where she studied the possibility of gender bias in written forms of science communication. She is on a lifelong journey to bridge the communications gap between scientists and the public, and hopes to do this as a science and technology writer at Asian Scientist Magazine.

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