MDDI 演講稿 · 2025-06-30

高階政務部長陳杰豪在第12屆先進技術材料國際會議上的致辭

Tan Kiat How · MDDI 高階政務部長 · How 出席第十二屆先進技術材料國際會議

要點

  • 新加坡政府為2021至2025年的研究、創新與企業計劃(RIE2025)承諾撥款280億新元,下一期RIE2030計劃目前正在制定中。
  • 總理黃循財宣佈為新設「科學人工智慧」(AI for Science)計劃撥款1.2億新元,資助人工智慧與科學領域的深度合作、共享工具與平臺,以及自下而上的研究提案。
  • 首輪「科學人工智慧挑戰」資助徵集所收到的提案中,約三分之一聚焦於材料科學,致力於開發人工智慧驅動的平臺以加速材料發現與最佳化。
  • 由新加坡自主研發的深度學習人工智慧系統SELENA+,可檢測糖尿病患者的威脅性眼部病變,並在本地醫療機構以分鐘級速度提供診斷結果。
  • 新加坡海事及港務管理局推出「新加坡海事數字孿生」,藉助人工智慧模擬與最佳化技術提升港口安全與運營效率。
  • 美國能源部勞倫斯伯克利國家實驗室的A-Lab利用人工智慧評估新材料,其每日處理樣本量是人類研究員的50至100倍。

完整譯文(繁體中文)

MDDI 英文原文譯文 · 翻譯日期: 2026-06-21

尊貴的嘉賓們,

女士們、先生們,

早上好。很高興出席第十二屆先進技術材料國際會議,簡稱 ICMAT。

ICMAT 已發展成為材料科學界的頂級平臺,匯聚了來自世界各地的頂尖研究人員、行業專家與創新人士。這一點在今天得到了有力印證——本屆會議吸引了逾 2,000 名來自全球各地的參與者。

新加坡長期以來積極擁抱並投資於科學、技術與創新,這些領域推動了我國一輪又一輪的經濟轉型。近年來,這些努力由我國的研究、創新與企業計劃(Research, Innovation and Enterprise,簡稱 RIE)引領推進。政府已為 RIE2025 計劃承諾撥款 280 億新元,覆蓋 2021 年至 2025 年。目前,我們正在規劃下一階段的資金安排——RIE2030。

在過去數年的科技與創新曆程中,一個關鍵主題逐漸浮現:以 AI 為代表的數字技術,對於支撐和加速創新至關重要,並由此產生現實世界的影響。AI 尤其對新加坡蘊藏著巨大潛力。它幫助我們突破作為一個沒有天然資源的小型開放經濟體所面臨的侷限,讓我們得以善用智慧工具,提升生產力,並推動創新。

作為通用技術,AI 在廣泛應用於經濟與社會各領域時,才能真正實現其價值。它改善業務流程,變革運營模式,並通過新產品與新方案創造價值。我們如今已在多個領域親眼見證了 AI 的影響。

允許我在此分享一些新加坡的例項。

在海事領域,AI 幫助我們應對港口流量增加與海域空間有限的挑戰。正是在這一背景下,MPA 推出了新加坡海事數字孿生系統,通過 AI 模擬與最佳化提升港口安全性和運營效率。

在醫療領域,AI 不僅在改善一線服務的交付,更從根本上改變了我們應對患者護理、疾病診斷與藥物研發的方式。以 SELENA+(新加坡眼部病變分析儀)為例,這款在新加坡本土研發的深度學習 AI 軟體,能以出色的精準度檢測糖尿病患者的危險眼部病變。如今,SELENA+ 已服務於本地醫療機構,在數分鐘內即可為患者出具診斷結果,無需數小時乃至數天。

AI 在科學研究中的應用已在加速推動各類發現。去年,我們見證了一個里程碑時刻——諾貝爾化學獎授予了 Demis Hassabis 博士,以表彰他開發出用於預測蛋白質結構的 AI 模型。昔日需要數年才能完成的工作,如今數天甚至數小時即可實現。

正因如此,總理黃循財去年宣佈,政府承諾為全新的"AI for Science"計劃投入 1.2 億元。該計劃致力於開發 AI 方法與工具,以提升多個科學領域的研究生產力。

讓我重點介紹這一計劃的三個關鍵方面。

第一,該計劃將資助深度合作專案,匯聚 AI 研究人員與科學領域專家,聚焦對新加坡未來至關重要的領域——例如先進材料研究與生物醫學科學。

第二,該計劃將支援共享 AI 工具與平臺的開發,這些資源將惠及我國整個研究群體。

第三,該計劃將資助來自研究群體的自下而上提案。

材料科學尤其蓄勢待發,有望被 AI 深度變革。該領域傳統的發現與開發方法往往耗時數年乃至數十年。AI 能夠大幅加速這一程序——幫助我們發現用於清潔能源的新材料,推動電子技術進步,並實現可持續製造。以美國能源部伯克利國家實驗室的 A-Lab 為例,AI 在那裡評估潛在新材料的現實可行性,單日處理的樣本量是人類的 50 至 100 倍。

因此,我很高興地注意到,在首輪"AI for Science Challenge"資助徵集中,約三分之一的提案聚焦於材料科學。這些提案雄心勃勃、面向未來,旨在開發 AI 驅動的平臺與方法論,以加速材料發現與最佳化程序。許多提案將高通量實驗與 AI 相結合,彌合了理論預測與真實材料效能之間的差距。

這反映了我國材料科學研究群體的濃厚興趣,也展示了他們在應用 AI 方面已有的實力。值得注意的是,許多提案均涉及國際專家,匯聚了來自世界各地的聯合研究員與合作者的專業知識。我堅信,這種協作方式至關重要,將使"AI for Science"計劃得以成功。我們需要 AI 研究人員與領域專家之間的協作,需要跨研究機構的夥伴關係,需要與產業夥伴的互動。政府機構可以在這一過程中發揮促進與支援作用。

正因如此,新加坡堅持對外開放。我們歡迎思想的全球流動與交叉融合。即便世界進入新的動盪時代,我們仍堅守這一立場。作為小國,我們承擔不起與世界隔絕的代價。我們的優勢在於融入全球創新網路。我們必須保持作為可信賴樞紐與節點的地位。這使我們能夠將科學突破轉化為具有現實影響的實用方案——不僅惠及新加坡,更造福世界。

總而言之,ICMAT 持續發揮著催化劑的作用,推動材料科學領域的國際合作。我相信,本週在此舉行的討論將催生突破性的發現與眾多新合作。在此,我向今日與會的材料科學研究群體發出邀請:加入我們這段激動人心的旅程,為"AI for Science"計劃貢獻力量,在新加坡開展研究並與新加坡攜手合作,共同推動材料科學創新的前沿。

在此,祝各位第十二屆 ICMAT 圓滿充實、收穫豐碩。

非常感謝。

英文原文

MDDI 官網原始記錄 · 抓取日期: 2026-06-21

Distinguished guests,

Ladies and gentlemen,

Good morning. I am delighted to join you at the 12th International Conference on Materials for Advanced Technology or ICMAT in short.

ICMAT has established itself as a premier platform for the materials science community. It brings together leading researchers, industry experts, and innovators from around the world. And this is powerfully reflected today – with over 2,000 participants from across the globe joining us at this year's conference.

Singapore has long embraced and invested in science, technology and innovation. These have powered successive waves of our economic transformation. In recent years, these efforts have been guided by our Research, Innovation and Enterprise – or RIE – plans. The Government has committed S$28 billion in funding for our RIE2025 plan from 2021 to 2025. And we are currently shaping the next tranche of funding – RIE2030.

One key theme has emerged in the past few years of our science, technology and innovation journey. It is about how digital technologies, including AI, are critical in underpinning and accelerating innovation. And through this, they enable real-world impact. AI, in particular, holds tremendous potential for Singapore. It allows us to overcome our constraints as a small, open economy with no natural resources. It enables us to leverage smart tools. It helps us improve our productivity. And it drives innovation.

As a general-purpose technology, AI realises its true value when applied across our economy and society. It improves business processes. It transforms operations. And it creates value through new products and solutions. We are already witnessing AI's impact today across multiple domains.

Let me share some examples here in Singapore.

In the maritime sector, AI helps us navigate the challenges of increasing port traffic and constrained sea space. It was against this backdrop that MPA launched Singapore's Maritime Digital Twin – enabling AI simulations and optimisation to enhance port safety and operational efficiency.

In healthcare, AI is not just improving frontline service delivery. It is fundamentally changing how we approach patient care, disease diagnosis, and drug development. Consider SELENA+ – the Singapore Eye Lesion Analyser. This deep-learning AI software, developed right here in Singapore, detects threatening eye conditions in diabetic patients with remarkable precision. Today, SELENA+ serves our local healthcare institutions, delivering patient results in minutes – not hours or days.

The use of AI in scientific research is already accelerating discoveries. Indeed, we witnessed a milestone just last year. The Nobel Prize in Chemistry was awarded to Dr Demis Hassabis for developing AI models to predict protein structures. What once took years can now be accomplished in days – or even hours.

This is why Prime Minister Lawrence Wong announced our commitment of $120 million to the new “AI for Science” initiative last year. This initiative focuses on developing AI methods and tools to enhance research productivity across multiple scientific domains.

Let me highlight three key aspects of this initiative.

First, it will fund deep collaborations. These collaborations will bring together AI researchers and scientific domain experts. They will focus on areas crucial to Singapore's future – such as advanced materials research and biomedical sciences.

Second, it will support the development of shared AI tools and platforms. These resources will benefit our entire research community.

Third, it will fund bottom-up proposals from our research community.

Materials science, in particular, stands ready to be transformed by AI. Traditional methods of discovery and development in this field can take years – even decades. AI can dramatically accelerate this process. It can help us discover new materials for clean energy. It can advance electronics. It can enable sustainable manufacturing. Consider the example of the US Department of Energy's Berkeley National Laboratory's A-Lab. There, AI assesses the real-world viability of potential new materials. It processes 50 to 100 times as many samples as a human in a single day.

I am therefore pleased to note that about one-third of proposals received under the first “AI for Science Challenge” grant call focuses on materials science. These proposals are ambitious and forward-looking. They aim to develop AI-driven platforms and methodologies. They seek to accelerate materials discovery and optimisation. Many combine high-throughput experimentation with AI. They bridge the gap between theoretical predictions and real-world material performance.

This reflects the keen interest of our materials science research community. It demonstrates their existing strength in adopting AI. Notably, many of these proposals involve international experts. They draw on the expertise of co-investigators and collaborators from around the world. And I strongly believe this collaborative approach is essential. It will enable “AI for Science” to succeed. We need collaboration between AI researchers and domain experts. We need partnerships across research institutions. We need engagement with industry partners. Government agencies can facilitate and support this process.

That is why Singapore remains committed to openness. We welcome the global flow and cross-pollination of ideas. We maintain this stance even as the world enters a new era of turbulence. As a small country, we cannot afford to close ourselves off from the world. Our strength lies in being plugged into global innovation networks. We must remain a trusted hub and node. This allows us to translate scientific breakthroughs into practical solutions with real-world impact. Solutions that benefit not just Singapore, but the world.

In conclusion, ICMAT continues to serve as a catalyst. It drives international collaboration in materials science. I am confident that the discussions here this week will lead to breakthrough discoveries and many new collaborations. To the materials science research community here today, I extend an invitation: Join us in this exciting journey. Contribute to the “AI for Science” initiative. Do your research in and with Singapore. Help us push the frontiers of innovation in materials science.

And with that, I wish everyone a meaningful and productive 12th ICMAT.

Thank you very much.