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Singapore to invest S$1bn in AI over five years
The funding will go towards compute, talent, and industry development to support Singapore’s national AI strategy
Singapore will invest S$1bn (US$744m) into artificial intelligence (AI) compute, talent and industry development over the next five years to drive the use of the technology across key sectors.
In his Budget 2024 statement on 16 February 2024, Singapore deputy prime minister and finance minister Lawrence Wong said the new funding will support the National AI Strategy 2.0 and further catalyse AI activities in the city-state.
Wong said that AI, which is not just about ChatGPT and large language models, has the potential to transform industries and enhance productivity across existing processes, from drug discovery, to organising warehouses, or driving vehicles.
With Singapore already recognised as a serious player in AI development, he said the country aims to go further “to build new peaks of excellence, and crowd in private sector investments”.
Part of the new funding will be used to ensure Singapore can secure access to the advanced chips that are crucial to AI development and deployment. In December 2023, Nvidia CEO Jensen Huang said the AI chip giant could build an iconic site, along with a new supercomputer, in the city-state.
Industry groups and technology suppliers welcomed the funding boost. Trade association SGTech said the “significant allocation” underscores Singapore’s foresight in recognising the transformative potential of AI across sectors.
“Such a substantial investment demonstrates Singapore’s dedication to remaining at the forefront of technological innovation and also signifies its commitment to foster a robust ecosystem conducive to AI research, development, and adoption,” it said in a statement.
Bee Kheng Tay, president of Cisco ASEAN, is encouraged by the government’s efforts to boost the development and deployment of AI and hopes to see resources channelled into AI governance.
Citing Cisco’s AI readiness index, Tay noted that only 36% of respondents in Singapore said their organisations have comprehensive AI policies and protocols in place. “More support will be required to educate organisations on the importance of adapting internal policies to address data privacy and security and the ethical use of AI,” she said.
Mohan Veloo, vice-president for solutions consulting at Zscaler, noted that recent initiatives such as the AI Verify Foundation and Project Mindforge will help to facilitate the adoption of responsible AI and promote best practices and standards for AI.
Most recently, the Infocomm Media Development Authority has also expanded on the existing framework covering traditional AI to create a new model AI governance framework for generative AI. “This will likely pave the way for future regulations around the National AI Strategy 2.0 and other AI developments, seeking a systematic and balanced approach to address concerns while continuing to facilitate innovation,” he said.
In December 2023, Singapore updated its national AI strategy to focus on driving more widespread adoption of AI; spurring people and businesses to operate with the ambition to be world-leading in AI; and working with stakeholders in and outside Singapore to exchange ideas and administer AI-enabled solutions at scale.
Read more about artificial intelligence in ASEAN
- The Sea-Lion large language model was built to cater to the language and cultural diversity of Southeast Asia, which is currently underserved by existing models that mostly originate from the West.
- Google Cloud has teamed up with the Singapore government on a slew of initiatives to drive AI adoption, build an ecosystem of AI startups and expand the pool of AI talent in the city-state.
- Malaysia’s Aerodyne is running its Dronos platform on AWS to expand its footprint globally and support a variety of drone use cases, from agriculture seeding to cellular tower maintenance.
- Healthcare professionals at Singapore’s National University Health System can now summarise patient case notes and predict patient healthcare journeys using a large language model trained by a supercomputer.