AI Singapore (AISG) was launched in June 2017 as an integrated, impact-driven, research and innovation program in artificial intelligence (AI) for the entire country. As a national initiative, AISG brings together the strength of Singaporean research bodies in Singapore's Autonomous Universities (AUs) and research institutes, together with the vibrant ecosystem of AI start-ups and companies developing AI products, to perform use-inspired research, create innovative AI solution, and develop the talent to power Singapore's AI efforts.
To achieve Singapore's national mission, AISG's activities are anchored around four key pillars:
100Experiments (100E) is AISG's flagship program to solve industry business problems through the design and development of AI solutions, translate AI IPs from academia to industry, and help companies build their own AI teams. An organization can propose a problem statement where no commercial-off-the-shelf AI solution exists, but can potentially be solved through AISG's ecosystem of researchers and research IPs within nine to 18 months. AISG will assemble a team of AI researchers and engineers from Singapore's research and development ecosystem to work on an organization's problem statement. Through a collaborative process, a company's existing technical manpower will work alongside a team of AI researchers and engineering assembled by AISG to develop AI solutions while helping the company build up its internal AI capabilities.
100Experiments is AISG's flagship program to solve industry business problems through the design and development of AI solutions, translate AI IPs from academia to industry, and help companies build their own AI teams.
Two examples of successful 100E projects include:
AI Singapore worked together with a local start-up, KroniKare, to develop a Wound Scanner that uses computer vision, image processing, and semantic segmentation on an AI-driven handheld device that mimics the wound analysis by specialists. The KroniKare Wound Scanner is the first AI-based diagnostic tool to be registered in Singapore under the Health Sciences Authority (HAS) Class B medical device. The scanner uses multi-spectral images to automatically analyze and report chronic wound conditions, and therefore allow healthcare institutions to better document wound conditions, triage patients, and allocate resources for wound management. This capability has resulted in improved patient outcomes in terms of early detection and faster interventions for major wound complications and abnormalities. The digitized documentation also produced more accurate records and wound assessment time has been reduced to only 30 seconds, thus significantly reducing nurses' workloads. The tool also helped train and enhance the skills of junior nurses.
The Expedia Group and AI Singapore's project team are working to leverage natural language processing and machine learning to develop an AI-based model to enhance search query understanding and resolution in Japanese before extending the model to other Asian languages to enhance online search efficiency. When completed, the AI solution will enable Expedia Group to deepen its understanding of travel search query patterns and nuances in Asian languages, and equip the travel platform with the ability to better serve the needs of Asian travelers by improving the accuracy and efficiency of search query resolution.
AI Makerspace will help industries jump-start their AI journey by providing access to resources for experimentation, such as curated datasets from industry and government, cutting-edge AI tools, and supercomputing resources specialized for AI workloads.
The AI technologies typically used in the 100E projects are deep learning, computer vision, and natural language processing. The accompanying figure summarizes the spread of AI technology across 100E projects in the various economic sectors.
Over the next few years, AISG will focus on encouraging national and international research collaborations, accelerate the adoption of AI, and grow the AI talent pipeline for Singapore.
©2020 ACM 0001-0782/20/4
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and full citation on the first page. Copyright for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or fee. Request permission to publish from firstname.lastname@example.org or fax (212) 869-0481.
The Digital Library is published by the Association for Computing Machinery. Copyright © 2020 ACM, Inc.
No entries found