From lab breakthroughs to new businesses: How AI is accelerating innovation in Singapore

From lab breakthroughs to new businesses: How AI is accelerating innovation in Singapore Artificial intelligence is speeding up scientific discoveries and product development, but industry leaders say turning innovations into successful businesses remains a challenge. SINGAPORE: Artificial intelligence is accelerating the journey from scientific discoveries to commercially viable products, potentially shortening lengthy research and development processes, industry leaders say. Singapore is seeking to capitalise on these advances through a new initiative aimed at accelerating materials innovation using AI and automation, backed by an initial S$150 million (US$117 million) government investment. Called MARVEL-AI, the initiative was announced on Tuesday (Oct 27) at the Singapore Week of Innovation and Technology (SWITCH) 2026. Led by the Agency for Science, Technology and Research (A*STAR), it will combine advanced AI models with automated laboratories to speed up materials discovery and development. But turning these breakthroughs into commercially viable products and successful businesses remains a challenge. SPEEDING UP SCIENTIFIC DISCOVERIES Traditional materials development can be a lengthy process, involving repeated experiments, validating results and prototyping before a product is ready for commercial use. AI could help researchers shorten these processes, said Professor Loh Xian Jun, executive director of A*STAR’s Institute of Materials Research and Engineering, in an interview with CNA on the sidelines of SWITCH on Wednesday. “We are able to shortcut the discovery time by maybe up to 10 times,” said Prof Loh. “We are able to process validation and characterisation much faster using automation and AI combined, and using these insights, we are able to develop industrially relevant solutions at a very quick time span.” One example is a hydrogel that was developed by Prof Loh and his research team that could potentially be used to treat retinal detachment. “This type of hydrogel is a novel material that is a liquid at room temperature. And when you inject it at body temperatures into the eye, it turns into a hydrogel,” he said. Prof Loh added that the development of the material took a long time to fine tune its composition but advances in AI have helped to speed up the work. “Today, with a very good AI-assisted platform, we are able to create many different combinations of these materials and screen them for properties. This allows us to reduce the time by more than 10 times,” he said. Researchers are also exploring how wood waste can be converted into components typically extracted from fossil fuels, potentially reducing waste and reliance on petroleum-based products. However, developing a promising material in a laboratory is only the first step. “Maybe I can produce five grams of materials today, (but) can I produce a tonne of it?” Prof Loh asked. He explained that scaling up production is far from straightforward, as factors such as heat and mass transfer are difficult to predict. Under the MARVEL-AI initiative, companies can work with researchers to develop solutions for specific industrial problems. “We (can) use AI combined with automation to fast-charge the development process so that we can develop the solutions much faster,” said Prof Loh. “This also results in time and cost savings for the company.” FASTER ENGINEERING, LOWER DEVELOPMENT COSTS Beyond scientific laboratories, AI is also transforming how companies design and manufacture complex industrial equipment. Mr Jacomo Corbo, CEO and co-founder of engineering and deep-tech AI company PhysicsX, said AI could dramatically accelerate simulations used to test and refine designs. “We can increase the speed of doing the same simulations by a factor of 10,000, 100,000, in certain cases, almost a billion times,” he told CNA. “It also means being able to take high-fidelity simulation to parts of the product development lifecycle where it can’t go today,” he said, citing examples of being able to control semiconductor manufacturing equipment to create a chip, or making components in a jet engine. In semiconductor equipment manufacturing, Mr Corbo said PhysicsX’s work had helped reduce the development time for a new machine by almost 20 per cent. But faster simulations do not eliminate the need for accuracy, particularly in industries where design failures could have serious consequences in the real world. “The risk of hallucination with AI models is a very real one,” said Mr Corbo. The term refers to instances when AI systems generate information that sounds plausible but is actually wrong or misleading. He added that AI-generated results should still be validated through methods such as physical testing, while established safety limits remain in place. TURNING INNOVATIONS INTO SUCCESSFUL BUSINESSES While AI is accelerating scientific research and engineering, turning technological advances into commercially successful businesses requires more than faster development. Mr Howard Wright, Nvidia’s vice-president of startup ecosystem, said there is no single formula for startup success, but common factors include the strength of a company’s leadership team, its investors and board members, as well as its ability to protect its intellectual property. His observations were based on Nvidia’s experience working with startups globally through its Inception programme. Mr Wright pointed to how AI has made technical capabilities more accessible to entrepreneurs, reducing the need for specialised expertise. “Years ago … access was really beholden to folks only in certain metropolitan cities,” he said. “Now, as easy as AI is, you don't need a PhD from a world class university in computer science to prompt, to teach, to ask the AI, to teach you how to train it.” For AI start-ups with small teams and limited funding, Mr Wright advised being strategic about when to secure financing. However, he cautioned that some startups limit their growth potential by focusing too narrowly on their domestic markets. “We've noticed in different pockets of the world, they're focused on just servicing that local (area), that city, that state, that government entity,” he said. “In fact they've written code that can traverse boundaries, that could traverse other verticals.” Mr Wright said Nvidia works with more than 1,000 startups in Singapore, pointing to the country’s engineering talent, universities and access to investment capital as strengths. “It's not too ambitious to say maybe the next trillion-dollar market cap startup could come from this very city.”