Written Answer · 2024-01-09 · Parliament 14
National Artificial Intelligence Strategy 2.0 vs Energy and Environmental Sustainability
MPs asked how the government will balance the compute growth required by NAIS 2.0 with energy sustainability goals. The government replied that it lifts data centre efficiency, promotes liquid cooling, sets green standards, and supports green compute methods to keep AI infrastructure environmentally sustainable. The core debate: reconciling AI development needs with climate commitments.
Key Points
- • Lift data centre efficiency
- • Promote liquid cooling technology
- • Develop green compute methods
Pushes green and efficient AI compute development.
Focuses on the compute-energy balance.
Strengthen green data centre construction.
"The Government is committed to anchoring the necessary compute power and growing the DC sector in a sustainable manner."
Participants (2)
Original Text (English)
SPRS Hansard · Fetched: 2026-05-02
47 Dr Lim Wee Kiak asked the Minister for Communications and Information with regard to the National Artificial Intelligence (AI) Strategy 2.0 (a) how does the Government plan to balance the increased computing power necessary for AI developments with Singapore's energy sustainability goals; and (b) what initiatives or strategies are in place to ensure that the infrastructure and computing power needed for AI growth remain environmentally sustainable.
Mrs Josephine Teo : An important enabler of our National Artificial Intelligence Strategy (NAIS) 2.0 strategy is artificial intelligence (AI) compute power housed in data centres (DCs) in Singapore. The Government is committed to anchoring the necessary compute power and growing the DC sector in a sustainable manner, consistent with our international climate commitments.
One key strategy is to improve the energy efficiency of DCs and facilitate the deployment of efficient cooling solutions. For example, AI compute infrastructure typically relies on liquid cooling, which is more energy-efficient than air cooling for such intensive workloads. Other measures include: (a) supporting DC operators to reduce greenhouse gas emissions through the Economic Development Board's Resource Efficiency Grant for Emissions; (b) developing sustainability standards, such as the Infocomm Media Development Authority's (IMDA)'s Tropical DC Standards that enable DCs to operate safely at higher temperatures and use less energy for cooling; and (c) reviewing Building and Construction Authority (BCA)-IMDA's Green Mark for DCs certification scheme to update the energy-efficiency criteria.
Beyond sustainable AI compute infrastructure, it is important to invest in the development of green computing methods. These methods include (a) coding and algorithm optimisation, (b) software-hardware optimisation, and (c) developing standards for low-data, low-energy AI models. The Government will continue to deepen international and domestic partnerships with the research community and industry partners on this front.