MDDI 演講稿 · 2026-04-06

張仁寶部長在AUMOVIO-NTU企業實驗室啟動儀式上的致辭

Josephine Teo · 數碼發展及新聞部長 · AUMOVIO-NTU企業實驗室啟動儀式

要點

  • 新加坡推出覆蓋先進製造、互聯互通、醫療保健與金融服務四大領域的國家AI使命,總理黃循財親自擔任新成立的國家AI理事會主席。
  • AUMOVIO-NTU企業實驗室自2019年成立以來,已發表131篇論文、提交104項專利申請,並獲得10項專利授權。
  • 實驗室開發的AI Pathfinder工具可自動化測試汽車中央儀表盤介面,單次版本釋出最多節省1200人時,目前正在一家區域整車廠試點推廣。
  • 實驗室的AI模糊測試工具經區域整車廠試驗證明,能更快檢測軟體缺陷,並發現了傳統測試完全遺漏的關鍵安全漏洞。
  • 實驗室與AWS簽署支援函以獲取算力資源,並與Origgin簽署諒解備忘錄,通過初創企業、衍生公司及海外網路推動技術商業化。
  • 實驗室計劃吸納逾140名研究人員、工程師與學生,研究方向涵蓋AI、網路安全、新型材料與車聯網通訊。

完整譯文(繁體中文)

MDDI 英文原文譯文 · 翻譯日期: 2026-06-21

林金勇教授,南洋理工大學新加坡(NTU Singapore)副校長(產業)

盧建發先生,AUMOVIO Singapore 總裁兼執行長

各位嘉賓

下午好,感謝各位的邀請。

在今年的財政預算案中,黃總理談到了人工智慧,以及超越個別試點專案的必要性。他表示,我們必須在國家層面進行統籌部署,快速推進、擴大規模。正因如此,他親自主持新成立的國家人工智慧理事會,並在四大關鍵領域啟動國家人工智慧使命:先進製造、互聯互通、醫療衛生和金融服務。

"超越試點"究竟意味著什麼?這意味著設定真正難以實現的目標,迫使我們從根本上重新思考工作方式。這並不是說小問題不值得解決——它們當然值得——但我們不能滿足於對某項技術的淺層應用,而應認真思考如何實現變革性的運用。

比如將從設計到原型的時間縮短一半,或在總裝線上實現近乎零缺陷率。這些都是宏大而富有雄心的目標,值得我們認真對待,絕非靠漸進式改進或區域性自動化就能達到。整個工作流程或許需要徹底重新構想。

我們仍在研究各個領域的具體目標形態,但它們有一個共同特點:都是"延伸目標"。這一點至關重要,因為它迫使我們提出不同的問題,引入不同的專業知識,並探索新的工作方式。

這正引出這個企業實驗室的重要意義。自2019年成立以來,團隊已發表131篇論文,提交104項專利申請,並獲得10項專利授權。這些數字本身令人印象深刻,也反映出這是一個積極進取、力求突破的機構。

在汽車領域,最難攻克的問題往往出乎意料。測試工作繁瑣、不那麼光鮮,卻是可靠性得以建立或崩潰的關鍵環節。作為乘客,你我都知道可靠性至關重要。這個實驗室正是在這類問題上下功夫,涵蓋現代車輛所需的全方位能力。

此外,停留在紙面上的延伸目標走不了多遠。但它能將合適的人聚集到同一張桌子前。

在此次合作之前,AUMOVIO——當時還叫 Continental——正面臨一個熟悉的挑戰。為複雜汽車系統開發可靠軟體耗時費力,且隨著產品日趨精密,難度不斷攀升。他們清楚人工智慧可以提供幫助。

然而,要開發出能在真實汽車條件下穩定執行的解決方案,需要他們自身無法在短期內積累的研究深度。NTU 恰好具備這方面的專業能力。

另一方面,將研究成果轉化為能承受真實產業壓力的解決方案,需要大學所不具備的實際工業部署經驗。但 AUMOVIO 擁有這方面的積累。

NTU 與 AUMOVIO 作為合作伙伴相互補充、相得益彰。除了我此前列舉的成果,這一合作還產生了哪些成效?

實驗室開發了 AI Pathfinder,可自動化測試車輛中央儀表板介面。在單次儀表板版本釋出中,最多節省了1,200個工時,目前正在與一家區域汽車製造商開展試點。

NTU Edwin Teo 教授團隊與 AUMOVIO 合作,開發了新型3D列印材料,可模擬車輛部件中的觸感和振動反饋,為汽車行業長期面臨的難題提供了一套緊湊的解決方案。

實驗室在無線通訊領域的研究也為國際標準的制定作出了貢獻。換言之,源自新加坡的創新正在影響全球車輛之間的通訊方式。

或許最具意義的,是這些成果的實現方式。在大多數合作中,業務部門往往在最後才介入,評估研究人員的產出。而在這裡,AUMOVIO 的業務部門從一開始就直接參與塑造研究議程。未來負責部署解決方案的人,在解決方案設計階段便已深度參與。這種更緊密的迴圈帶來了更好的成果;當然,從大學角度來看,這也有助於避免"死亡之谷"——即研究發現和成果最終未能轉化為產業所需的可用產品和服務。

我們期待在國家人工智慧使命以及"Champions of AI"計劃中看到更多此類合作。

在結束髮言之前,讓我談談為何這類合作的意義超越了這個特定的企業實驗室本身。

當各組織真正全力攻克現實難題時,往往會發生幾件事。

首先,他們向其他人展示了何為可能。許多企業在轉型方面裹足不前,並非因為缺乏興趣,而是不確定能否成功。實驗室的 AI fuzzing 工作就是一個很好的例子。通過與區域內一家汽車製造商開展試驗,AI fuzzing 工具檢測漏洞和安全缺陷的速度遠超以往,還發現了傳統測試完全遺漏的關鍵漏洞。當其他企業看到這樣的成果,他們對可能性的認知便會隨之改變。

其次,此類合作能產生真實的應用案例,吸引更多合作伙伴加入。我很高興今天見證兩項簽署——與 AWS 簽署的支援意向書,以及與 Origgin 簽署的諒解備忘錄(MOU)。

AWS 的支援為實驗室提供了計算資源,將推動人工智慧研究持續前行。

Origgin 將與實驗室合作,通過初創企業、分拆公司及海外網路連線,將技術推向市場。

實驗室還計劃與本地初創企業合作,例如 Squareroot8 Technologies,其量子安全研究與實驗室自身的網路安全研究方向高度契合。

為推進各項雄心勃勃的目標,實驗室將匯聚逾140名研究人員、工程師和學生,涵蓋人工智慧、網路安全、新型材料及車載通訊等領域。

我衷心祝賀團隊全體成員迎來今天的釋出,也祝願大家在未來的歲月中取得更大的成功。非常感謝各位的邀請。

英文原文

MDDI 官網原始記錄 · 抓取日期: 2026-06-21

Prof Lam Khin Yong, Vice President (Industry), NTU Singapore

Mr Lo Kien Foh, President and CEO, AUMOVIO Singapore

Distinguished guests

Good afternoon and thank you for inviting me.

At Budget this year, PM Wong spoke about artificial intelligence and the need to go beyond individual pilots. He said we must, instead, organise at a national level and move with speed and scale. That is why he is personally chairing the new National AI Council, and why we are launching the national AI Missions in four key sectors: advanced manufacturing, connectivity, healthcare and financial services.

What does “going beyond pilots” actually mean? Well, it means setting goals that are genuinely hard to achieve, that compel us to fundamentally rethink how the work is done. It doesn’t mean that small problems are not worth solving – they are, but we cannot be content with shallow applications of a technology but should seriously think about transformative uses.

Like halving the time from design to prototype or achieving near-zero defect rates on a final assembly line. These are big ambitious goals that are worthy of our attention, they are not goals that anyone can reach through incremental improvements or a bit more automation here and there. Entire work processes may need to be re-imagined.

We are still working through what these goals look like in each sector. But they share one characteristic: they are stretch goals. That matters, because they force us to ask different questions, bring in different expertise, and find new ways of working.

This brings me to why this corporate lab matters. Since it was established in 2019, the team has produced 131 publications, filed 104 patent applications, and secured 10 patent awards. These numbers are impressive on their own, and also reflect an active organisation that is keen to make progress.

In the automotive sector, the hardest problems are not always where you expect them. Testing, for instance, is painstaking and unglamorous, but this is where reliability is built or broken. You and I know that as passengers, reliability matters. This lab works on problems like that, across the full range of what a modern vehicle needs to be.

Also, a stretch goal on paper does not go very far. However, it can bring the right people to the table.

Before this collaboration, AUMOVIO – then known as Continental – was grappling with a familiar challenge. Building reliable software for complex automotive systems is slow, expensive, and gets harder as products grow more sophisticated. They knew that AI could help.

However, developing something that works reliably under real automotive conditions required research depth they could not themselves build overnight. NTU had exactly that expertise.

On the other hand, translating research into solutions that work under real industry pressures requires real-world industrial deployment experience that a university does not have. But AUMOVIO does.

NTU and AUMOVIO complement each other well as partners. What has this collaboration produced, besides the achievements that I outlined earlier?

The lab built AI Pathfinder, which automates the testing of vehicle central dashboard interfaces. Up to 1,200 man-hours were saved in a single dashboard release and it is now being piloted with a regional automaker.

Professor Edwin Teo’s team at NTU worked with AUMOVIO to develop new 3-D printed materials that replicate touch sensation and vibration feedback in vehicle components, a compact solution to a problem the automotive industry has long struggled with.

And the lab’s wireless communication research has contributed to the international standard. In other words, innovation from Singapore is shaping how vehicles around the world talk to each other.

What is perhaps most significant is how these outcomes were achieved. In most collaborations, business units are brought in at the end to evaluate what researchers produced. Here, AUMOVIO’s business units directly shape the research agenda from the start. The people who will deploy these solutions are involved as these solutions are being designed. The tighter loop produced better results, and of course, from the university’s perspective, this also helps to avoid the valley of death where research findings and discoveries do not eventually make their way into usable products and services demanded by the industry.

We hope to see more of such collaborations in our National AI Missions and in our Champions of AI programme.

So, let me close with why these collaborations matter beyond this particular corporate lab.

When organisations push genuinely hard at real problems, a few things tend to happen.

First, they show others what is possible. Many companies are holding back on transformation, not because they are uninterested, but because they are not sure it can be done. The lab's AI fuzzing work is a good example. Through a trial with an automaker in the region, the AI fuzzing tool detected bugs and vulnerabilities much faster than before and uncovered critical vulnerabilities that traditional testing had missed entirely. When other companies see results like that, it changes what they think is possible.

Second, such collaborations generate real use cases that bring partners along. I am pleased to witness two signings today - a Letter of Support with AWS, and an MOU with Origgin.

The support of AWS gives the lab access to computing resources that will keep AI research moving.

Origgin will work with the lab to bring technologies to market through startups, spin-offs, and connections to overseas networks.

The lab is also looking to work with local startups like Squareroot8 Technologies, whose quantum security work aligns with its own cybersecurity research.

To pursue its ambitions, the lab will engage over 140 researchers, engineers and students across AI, cybersecurity, novel materials, and vehicular communications.

I congratulate everyone in the team on today’s launch, and wish you more success in the years ahead. Thank you very much for inviting me.