In the two years that Raymond Teh has been leading the Asia-Pacific team at Nvidia, he has seen business grow manifold. Regional revenue rose 150 per cent two years ago and in fiscal 2017, it expanded another 150 per cent.
The enterprise business which sells microprocessors into areas like professional visualisation and data centres, expanded rapidly, accounting for 35 per cent of regional revenue in 2017, up from just 10 per cent two years ago.
Meanwhile the consumer business, providing microprocessors to the gaming hardware makers for which it is better known, dropped to 60 per cent of regional revenue last year, down from 85 per cent two years ago.
It is not a contraction of the consumer business, instead it is a larger business now, explained Teh, because the total regional revenue has grown bigger. While Teh did not disclose Asia-Pacific revenues, observers believe it to be about one-third of Nvidia’s total revenue.
As a company, Nvidia reported record earnings of US$9.71 billion for fiscal 2018, up 41 per cent from a year ago. Expansion in the enterprise business is led by sales of its fast GPU (graphics processing units) which are powering data centres, professional visualisation tools for special cinematic effects and computing systems used in industries like healthcare and autonomous vehicles.
Though it made its a name in PC gaming, Nvidia has become a darling of the AI industry of late. Its muscular GPU microprocessors can crunch complex calculations, allowing the American company to ride the artificial intelligence (AI) wave.
Its GPUs are well-suited for crunching tens of thousands of mathematical calculations simultaneously which makes them a standout for inferencing, simulation and visualisation tasks.
The company based in Santa Clara, California, has evolved into a platform business providing a stack of hardware and software solutions powered by its powerful GPUs.
For Singapore, Teh stressed that the country must move faster if it is to keep ahead of the AI curve. Singapore has expertise in AI and the government like China, is funding key AI initiatives like AI.sg, he said.
“This is a good move because all the AI development is now under one programme, easier for companies like us who want to be work with the government in AI.”
Last year, Nvidia set up a deep learning research lab with Nanyang Technological University where its engineers now work with NTU researchers on leading-edge AI projects.
Set up about a year ago, AI.sg is a five-year S$150 million initiative which seeks to bring together all Singapore-based research institutions and AI start-ups and companies to develop AI products and talent.
Teh now sits on the board of AI.sg where he is now able to share AI best practices gleaned from its business in China and other countries with the local AI research community.
However, he noted that AI is a vast field and Singapore will do better if it specialises, for example, in healthcare. “Singapore can pick a project like diabetes and go deep into it, building expertise that will benefit patients and improve healthcare.”
In the last few months, he had also been hosting foreign AI companies interested in using Singapore as test bed for AI projects. For example, there are companies looking into autonomous vehicles, one area where AI will be used intensively.
He said: “They are looking at insurance claims, liability and reports. If they can do a joint-venture in Singapore, then the technology and business will develop faster, enhancing Singapore in AI industry.”
He has also been talking to local banks and telecom operators in Singapore that have voluminous data which can be mined using AI techniques to get better customer insights.
“Singapore is a service-based economy. It can use AI to enhance this further to give it an improved competitive edge,” he added.
