Written Answer · 2024-01-09 · Parliament 14
National Artificial Intelligence Strategy 2.0 vs Energy and Environmental Sustainability
議員は、国家AI戦略2.0の推進に必要な演算能力の増加とエネルギー持続可能性の目標をいかにバランスさせるかについて政府に質問しました。政府は、データセンター能効の向上、液冷技術の推進、グリーン標準の策定およびグリーンコンピューティング手法の支援を通じて、AI基盤インフラストラクチャの環境保全と持続可能性を確保することを強調しました。中核的な争点は、AI発展の必要性と気候の約束をいかに両立させるかにあります。
重要なポイント
- • Lift data centre efficiency
- • Promote liquid cooling technology
- • Develop green compute methods
国際AI技術の迅速な採用を支援し、人材とイノベーションを重視する
通知遅延と調査進捗に注目します
データ漏洩管理規範を強化します
“The Government is committed to anchoring the necessary compute power and growing the DC sector in a sustainable manner.”
参加者 (2)
英語原文
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.