MDDI 演讲稿 · 2025-09-25
杨莉明部长在 Semafor「下一个 30 亿人」峰会「利用 AI 推动发展」专题讨论上的发言
Remarks by Minister Josephine Teo at the panel discussion "Harnessing AI To Advance Development" at Semafor's The Next 3 Billion Summit
要点
- • 新加坡 AI 实验已 7 年——但生成式 AI 把它真正推开了门——让技能没那么高的人也能用上。
- • 「算力」其实没成为最大的拦路虎。当前最有意思的是「按行业纵深落地」——制造业的预测性维护(半导体停一台机器损失巨大)等。
- • AI 团队最值钱的人是「AI 双语者」——同时拥有领域功能专长 + 数据科学/ML 能力。
- • 对中美技术张力——Josephine 立场:新加坡不容忍违法行为;维持开放经济,让公司自由按性能、安全韧性、成本来组合选择。
- • Manus AI 等公司迁来新加坡——不只是「中立」标签,更是基础设施、技能型劳动力、知识产权尊重等内在基本面。
完整译文(中文)
MDDI 英文原文译文 · 翻译日期:2026-05-02
问:新加坡其实是较早采用 AI 自动化的国家之一。能否谈谈——AI 现在哪些有效、更重要的是哪些没那么有效?为我们把炒作与现实分一分。
部长:AI 并不是全新的事物。我们大约 7 年前就开始认真实验它——同时也把治理框架就位。但更确切地说——这件事真正起飞是在过去 3 年——尤其是生成式 AI——让技能水平没那么高的人也能用上它。这是一个非常显著的变化。
回到你问的「哪些有效、哪些无效」——一开始大家很担心算力的可获得性,但事实证明那并不是最大的拦路虎。算力可获得了——雄心也在变大。当前我们看到的——是「企业层面的采用」呈现非常健康的兴趣水平。它从「用生成式 AI 提升办公生产力」(如转写与摘要)开始——但真正有意思的,是我们现在在各行业垂直领域里看到的应用。
比如制造业——我们看到对 AI 用法的浓厚兴趣。所有制造业公司都需要做运营计划、缺陷检测、维护。比如半导体制造——任何一台生产线上的工具一旦停机,损失就非常大。所以——如果我们能用 AI 做预测性维护,就有可能省下大量金钱。这类应用获得了很大势能。
另一件非常有意思的事——是「需要怎样的 AI 专才」。我们不只需要懂数据科学、机器学习的人——还需要懂真实领域的人——「功能专家」。把「领域功能专家」与「数据科学家+机器学习专家」结合起来——就组成了一支强大的队伍。事实上——同时拥有两套技能的人——我们称为「AI 双语者」(AI bilingualist)——他们是公司更看重的人。
问:Teo 部长——我想听听您的看法。新加坡一直处在中间位置——比如所谓「芯片转运到中国」的事情;而美国的政策又在「技术扩散」上来回摆动。您如何应对美国政策这种鞭打效应?
部长:我们不容忍任何在新加坡境内、或经新加坡进行的违法活动。我们的立场非常清楚。如果有需要跟进的证据——我们会跟进。我相信美国同行知道这一点。对国际社会而言——新加坡一直保持一致。
我也要说——我们维持开放经济。组织在「采用 AI」上确实有选择。他们必须选最契合自身利益的模型。他们的决定可以是「性能 + 技术的安全韧性 + 成本」之间的组合。这些是任何技术项目落地中常青的考量。他们应当能在不同权衡之间做出一个慎重的决定。这就是我们的立场。
话虽如此——地缘政治议题确实会压在组织身上——他们会思考:某个技术栈对自己用户是否不安全?是否带来安全问题?是否有「不可靠或不可用」的风险?落地这项技术的组织必须权衡这些——评估风险是否大到不该推进。
对新加坡而言——我们希望尽可能支持各国各自的努力。Bosun Tijani 博士提到的新加坡大语言模型——是为了反映东南亚语言环境的丰富性与多样性而开发的。假以时日——若其他地区也开发类似模型——我们可以一起合作,去克服「AI 模型如何反映我们的文化与价值」这一挑战。这是一项重要的努力——我们都希望看到 AI 模型反映各自的身份认同。
问:你认为「保持中立」也对你们是优势吗?我注意到 Manus AI 这样的公司搬到了新加坡——因为他们不想再被打上「中国基地」的标签。
部长:组织必须评估——新加坡是否提供了让他们做「最好工作」的环境。这意味着:基础设施是否到位?技能型劳动力是否充足?非常重要——是否尊重知识产权?
这不只是「中立」一个因素——一家公司决定把最重要的活动落地在哪里时,要考虑许多因素。所以我们更愿意相信——不仅是地缘政治考量,更是那些「内在的基本面」让新加坡对企业落子有吸引力。
英文原文
MDDI 官网原始记录 · 抓取日期:2026-05-02
Q: Singapore was really one of the earlier adopters of AI automation. I was wondering if you could take us through what’s working with AI now but more importantly, what's not working? Trying to separate the hype from reality a little for us.
Minister: Well, AI isn't entirely new. We've been experimenting with it in earnest, from about seven years ago. Along with that effort, we also put in place a governance framework. But I should say that the efforts have really taken off in the last three years, particularly with generative AI, making access available to people whose skill levels are not as advanced. So that has been a very significant change.
Now to your question of what is working or what is not working, I think, in the initial stages, there was a real concern about the availability of compute. That has turned out to be not the biggest showstopper. Compute has been made available, and ambitions are growing. Right now, there is a very healthy level of interest in enterprise adoption. While it started with the idea of using generative AI for workplace productivity improvements, such as transcribing and summarising, what has been really interesting are the applications we are now seeing in specific verticals.
For example, in manufacturing, we have seen deep interest in how AI can be used. In all manufacturing companies, there is a need for operations planning, defect detection and maintenance. For example, in semiconductor manufacturing, wherever a tool in the production process is put out of action, a lot of money is lost. So, if we can use AI to do predictive maintenance, that can potentially save a lot of money. Therefore, those kinds of applications are gaining a lot of traction.
What's really interesting is also the kind of AI specialists that are needed. We need not only people who are skilled in data science and machine learning, but also those who understand the actual domain – the functional experts. So, the marriage of domain functional experts together with data scientists and machine-learning experts make a formidable team. In fact, a person who has both sets of skills is what we call an “AI bilingualist”, and they are even more valued by companies.
Q: Minister Teo, I’d love to get your point of view. I think Singapore has been right in the middle of this, with the chip issue allegedly being diverted to China. But then the US policies are going back and forth right on technology diffusion. How are you navigating that sort of whipsaw effect in US policies?
Minister: We do not condone illegal activities taking place either within Singapore or through Singapore. Our position is very clear. If there is any evidence that we should follow up, we will. I think our US colleagues know it. To the international community, Singapore has been very consistent.
I should also say that we maintain an open economy. Organisations do have a choice in the way AI is being adopted. They will have to go with the models that best serve their interests. The decision they make could be a combination of performance, as well as the security and resilience of the technology, balanced against cost considerations. These are evergreen issues that companies implementing all kinds of technology projects will always have to consider. They should be able to make a considered decision, balancing the different trade-offs. That's the position we take.
But having said that, I think it is fair to say that geopolitical issues do weigh on organisations – they will be thinking if a technology stack is unsafe for their users, presents security issues, or risks becoming unreliable or unavailable. Organisations implementing the technology will have to weigh these considerations and assess if the risk is too big for them to proceed.
For Singapore, we would like as best as possible to support countries in each of our endeavours. So Singapore’s Large Language Model, which Dr (Bosun) Tijani talked about, is developed to reflect the richness and diversity of the language environment in Southeast Asia, In time to come, if other regions were to develop similar models, there will be scope for us to work together to overcome the challenges of AI models in reflecting our cultures and values. This is an important endeavour, and we all want to see AI models reflecting our identity.
Q: Do you think you'll also benefit from being sort of neutral? I noticed like it was interesting to see Manus AI move to Singapore. Because they didn't want to be “Chinese-based” anymore.
Minister: Well, organisations have to assess whether Singapore provides the kind of environment that enables them to do their best work. This means whether the infrastructure is available, whether the skilled workforce is available, and very importantly, whether there is respect for intellectual property.
It is not just a case of neutrality but there are many factors that a company must consider before deciding where to locate their most important activities. So, we would like to believe that it is not just geopolitical considerations, but the inherent fundamentals that make Singapore attractive for companies to locate their key activities where we are.