MDDI 演讲稿 · 2025-06-30

高级政务部长陈杰豪在第12届先进技术材料国际会议上的致辞

高级政务部长陈杰豪在第12届先进技术材料国际会议上的致辞

Tan Kiat How · MDDI 高级政务部长 · How 出席第十二届先进技术材料国际会议

要点

  • 新加坡政府为2021至2025年的研究、创新与企业计划(RIE2025)承诺拨款280亿新元,下一期RIE2030计划目前正在制定中。
  • 总理黄循财宣布为新设「科学人工智能」(AI for Science)计划拨款1.2亿新元,资助人工智能与科学领域的深度合作、共享工具与平台,以及自下而上的研究提案。
  • 首轮「科学人工智能挑战」资助征集所收到的提案中,约三分之一聚焦于材料科学,致力于开发人工智能驱动的平台以加速材料发现与优化。
  • 由新加坡自主研发的深度学习人工智能系统SELENA+,可检测糖尿病患者的威胁性眼部病变,并在本地医疗机构以分钟级速度提供诊断结果。
  • 新加坡海事及港务管理局推出「新加坡海事数字孪生」,借助人工智能仿真与优化技术提升港口安全与运营效率。
  • 美国能源部劳伦斯伯克利国家实验室的A-Lab利用人工智能评估新材料,其每日处理样本量是人类研究员的50至100倍。

完整译文(中文)

MDDI 英文原文译文 · 翻译日期: 2026-06-21

尊贵的嘉宾们,

女士们、先生们,

早上好。很高兴出席第十二届先进技术材料国际会议,简称 ICMAT。

ICMAT 已发展成为材料科学界的顶级平台,汇聚了来自世界各地的顶尖研究人员、行业专家与创新人士。这一点在今天得到了有力印证——本届会议吸引了逾 2,000 名来自全球各地的参与者。

新加坡长期以来积极拥抱并投资于科学、技术与创新,这些领域推动了我国一轮又一轮的经济转型。近年来,这些努力由我国的研究、创新与企业计划(Research, Innovation and Enterprise,简称 RIE)引领推进。政府已为 RIE2025 计划承诺拨款 280 亿新元,覆盖 2021 年至 2025 年。目前,我们正在规划下一阶段的资金安排——RIE2030。

在过去数年的科技与创新历程中,一个关键主题逐渐浮现:以 AI 为代表的数字技术,对于支撑和加速创新至关重要,并由此产生现实世界的影响。AI 尤其对新加坡蕴藏着巨大潜力。它帮助我们突破作为一个没有天然资源的小型开放经济体所面临的局限,让我们得以善用智能工具,提升生产力,并推动创新。

作为通用技术,AI 在广泛应用于经济与社会各领域时,才能真正实现其价值。它改善业务流程,变革运营模式,并通过新产品与新方案创造价值。我们如今已在多个领域亲眼见证了 AI 的影响。

允许我在此分享一些新加坡的实例。

在海事领域,AI 帮助我们应对港口流量增加与海域空间有限的挑战。正是在这一背景下,MPA 推出了新加坡海事数字孪生系统,通过 AI 仿真与优化提升港口安全性和运营效率。

在医疗领域,AI 不仅在改善一线服务的交付,更从根本上改变了我们应对患者护理、疾病诊断与药物研发的方式。以 SELENA+(新加坡眼部病变分析仪)为例,这款在新加坡本土研发的深度学习 AI 软件,能以出色的精准度检测糖尿病患者的危险眼部病变。如今,SELENA+ 已服务于本地医疗机构,在数分钟内即可为患者出具诊断结果,无需数小时乃至数天。

AI 在科学研究中的应用已在加速推动各类发现。去年,我们见证了一个里程碑时刻——诺贝尔化学奖授予了 Demis Hassabis 博士,以表彰他开发出用于预测蛋白质结构的 AI 模型。昔日需要数年才能完成的工作,如今数天甚至数小时即可实现。

正因如此,总理黄循财去年宣布,政府承诺为全新的"AI for Science"计划投入 1.2 亿元。该计划致力于开发 AI 方法与工具,以提升多个科学领域的研究生产力。

让我重点介绍这一计划的三个关键方面。

第一,该计划将资助深度合作项目,汇聚 AI 研究人员与科学领域专家,聚焦对新加坡未来至关重要的领域——例如先进材料研究与生物医学科学。

第二,该计划将支持共享 AI 工具与平台的开发,这些资源将惠及我国整个研究群体。

第三,该计划将资助来自研究群体的自下而上提案。

材料科学尤其蓄势待发,有望被 AI 深度变革。该领域传统的发现与开发方法往往耗时数年乃至数十年。AI 能够大幅加速这一进程——帮助我们发现用于清洁能源的新材料,推动电子技术进步,并实现可持续制造。以美国能源部伯克利国家实验室的 A-Lab 为例,AI 在那里评估潜在新材料的现实可行性,单日处理的样本量是人类的 50 至 100 倍。

因此,我很高兴地注意到,在首轮"AI for Science Challenge"资助征集中,约三分之一的提案聚焦于材料科学。这些提案雄心勃勃、面向未来,旨在开发 AI 驱动的平台与方法论,以加速材料发现与优化进程。许多提案将高通量实验与 AI 相结合,弥合了理论预测与真实材料性能之间的差距。

这反映了我国材料科学研究群体的浓厚兴趣,也展示了他们在应用 AI 方面已有的实力。值得注意的是,许多提案均涉及国际专家,汇聚了来自世界各地的联合研究员与合作者的专业知识。我坚信,这种协作方式至关重要,将使"AI for Science"计划得以成功。我们需要 AI 研究人员与领域专家之间的协作,需要跨研究机构的伙伴关系,需要与产业伙伴的互动。政府机构可以在这一过程中发挥促进与支持作用。

正因如此,新加坡坚持对外开放。我们欢迎思想的全球流动与交叉融合。即便世界进入新的动荡时代,我们仍坚守这一立场。作为小国,我们承担不起与世界隔绝的代价。我们的优势在于融入全球创新网络。我们必须保持作为可信赖枢纽与节点的地位。这使我们能够将科学突破转化为具有现实影响的实用方案——不仅惠及新加坡,更造福世界。

总而言之,ICMAT 持续发挥着催化剂的作用,推动材料科学领域的国际合作。我相信,本周在此举行的讨论将催生突破性的发现与众多新合作。在此,我向今日与会的材料科学研究群体发出邀请:加入我们这段激动人心的旅程,为"AI for Science"计划贡献力量,在新加坡开展研究并与新加坡携手合作,共同推动材料科学创新的前沿。

在此,祝各位第十二届 ICMAT 圆满充实、收获丰硕。

非常感谢。

英文原文

MDDI 官网原始记录 · 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.