In advanced manufacturing, Mrs Teo highlighted the potential of physical and embodied AI technologies.
She said that Singapore’s industrial robot density is about five times the global average and is consistently among the highest in the world.
As such, physical AI could support simulations for process redesign while digital twins could improve predictive maintenance, reduce material wastage and minimise production downtime.
Still, Mrs Teo cautioned that technologies developed in research labs do not always perform effectively in real factory environments.
“To see real impact, we will need collaborators from the hardware, software and operational domains,” she said. On that note, she welcomed NVIDIA’s new research lab in Singapore, which will focus on embodied AI and efficient AI technologies.
Mrs Teo added that Singapore is also developing the Punggol Digital District as a “frontier testbed”, with integrated data platforms, real-world test scenarios and special permits for robot deployment.
“A growing network of industry partners is using Punggol’s ecosystem for testing and experimentation,” said Mrs Teo.
“These sandboxes and collaborations help to spread acceptance and adoption,” she added.
Mrs Teo said that Singapore’s National AI Missions provide strong reason for leading AI firms to anchor themselves in the country, to develop, test and scale AI solutions that are trusted and globally relevant.
She added that Singapore is also harnessing AI in other areas like healthcare and education for “the public good” and to improve the well-being of citizens.
“We will speak more about them at suitable platforms,” Mrs Teo said.
Mrs Teo on Wednesday also announced an update to Singapore’s National AI Strategy (NAIS). The update builds on the foundations laid by NAIS 2.0, which was launched by Mr Wong in 2023.
She described the refresh as a “‘double-click’ rather than a system reboot”.
The refreshed strategy introduces 10 updated priorities centred around three broad focus areas: deepening sectoral and public sector transformation; mainstreaming AI adoption and strengthening workforce readiness; and building an AI hub.
