🗺️ Singapore AI Ecosystem Map
The seven pillars of AI Singapore and their key participants — a full-system view of Singapore's AI landscape.
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🇸🇬 Core Hub
The core institution coordinating execution of Singapore’s national AI strategy
🔬 Foundational Research
World-class research institutions powering foundational AI breakthroughs
A*STAR
Singapore Agency for Science, Technology and Research; primary engine for foundational and applied AI research
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NUS
National University of Singapore; among Asia's top AI research universities. Launched the NUS AI Institute in March 2024, bringing together foundational AI, applied AI and societal impact research
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SUTD
Singapore University of Technology and Design; innovation at the intersection of AI and design
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AISG Research Collaborative Project with US-NSF Researchers
This collaborative project, led by Professor Jie Zhang (NTU) in partnership with MIT researchers including Associate Professor Jacob Andreas, focuses on developing trustworthy and interpretable human-AI collaborative systems for combinatorial optimization. The research establishes natural language as a robust interface for human-AI interaction, enabling systems to formulate complex optimization problems from imprecise input, perform robust AI-assisted solving, and provide explainable feedback. The outcomes aim to serve industries like logistics, manufacturing, and finance with intelligent decision-making tools, while advancing the theoretical foundations of trustworthy AI collaboration.
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PINNACLE: PINN Adaptive ColLocation and Experimental Points Selection
PINNACLE is an adaptive point selection method that improves Physics Informed Neural Networks (PINNs) training efficiency by automatically optimizing the selection of all training point types using empirical Neural Tangent Kernel theory. The method outperforms existing benchmarks across multiple problem types including forward problems, inverse problems, and transfer learning applications.
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BadEdit: Backdooring Large Language Models By Model Editing
AI Singapore researchers present BadEdit, a novel framework for backdoor injection into pre-trained large language models through direct parameter manipulation. The method requires only 15 poisoned samples and 120 seconds to successfully inject backdoors with near 100% attack success rate while minimizing side effects on clean data. BadEdit addresses limitations of traditional weight poisoning methods by significantly reducing data requirements and computational overhead, while demonstrating versatility across diverse task domains including text classification, fact-checking, and conversational sentiment generation.
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Utilizing Symbolic Regression to discover a larger class of splits for Decision Trees
This research introduces Symbolic Regression Enhanced Decision Tree (SREDT), which leverages symbolic regression to discover non-linear and multivariate splitting rules for decision trees. Compared to conventional decision trees, SREDT demonstrates superior prediction performance, more compact tree structures, faster inference time, and robustness to noise. The method uses genetic programming to search for closed-form analytical expressions, significantly outperforming standard decision trees on classification tasks.
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⚖️ Governance Framework
Layered AI governance frameworks and regulators
🧠 Core Technology
AI Singapore's in-house technology platforms and tools
Towards Robust and Expressive Whole-body Human Pose and Shape Estimation
AI Singapore presents research on robust and expressive whole-body human pose and shape estimation. A robustness study evaluates state-of-the-art models across three categories of controlled augmentations, revealing high sensitivity to location-variant changes. To address identified limitations, the team developed RoboSMPLX with three specialized components: a localization module for accurate subject positioning, a contrastive feature extraction module for robust generalization, and a pixel alignment module for precise parameter recovery. The approach demonstrates improved consistency and reduced errors under location-variant augmentations, with results published in NeurIPS.
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🚀 Innovation & Incubation
From experiment to product — accelerating AI innovation
📦 AI Products
AI Singapore's open-source products and tools
AI in Finance Global Challenge Startup Grant Awardee
Pints AI is a Singapore-based startup that won the 8th Global FinTech Hackcelerator's "AI in Finance Global Challenge" organized by the Monetary Authority of Singapore and AI Singapore in June 2023. The company develops privacy-first, enterprise-grade Gen AI solutions using compact language models optimized for on-premise deployment, addressing cost and privacy concerns in the financial services industry. Founded by Partha Rao (CEO) and Calvin Tan (CTO), Pints AI provides customizable AI tools that allow financial institutions to leverage their proprietary data securely while collaborating with Singapore University of Technology and Design.
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🎓 Talent Development
A full pipeline for AI talent development
🌏 International Cooperation
An active hand in global AI governance and cooperation
Breaking Barriers, Building Bridges: Increasing Language Representation in Southeast Asia
AI Singapore co-hosted the third Languages Summit in Bangkok with Google and VISTEC, the first time held outside Singapore, bringing together AI experts and researchers from across Southeast Asia. The summit announced SEA-LION v2, Project SEALD, SEACrowd, and the upcoming Project Aquarium community data platform designed to address gaps in regional high-quality data accessibility. Participants engaged in roundtable discussions on LLM development, data challenges, copyright concerns, and regional collaboration, while sharing progress on language models for Indonesian, Filipino, Thai, and Vietnamese systems.
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🏥 Health Technology
National-level platforms for medical AI and health technology
🤝 Industry Partners
Deep partnerships with global technology leaders
Sources: AI Singapore and other public information. The ecosystem evolves continuously — additions welcome.