SINGAPORE - Students will have to "learn how to learn" instead of focusing on skills and specific tools, as most content will become obsolete within two years, said Dr Simon See, head of computing giant NVIDIA's artificial intelligence (AI) technology centre.
"Technology is moving so fast, you have to keep adopting new skills. What you have to learn is the methodology of learning new things. You must learn how to learn new things," he said.
Dr See was speaking in a panel discussion at the launch of Nanyang Technological University's (NTU) Deep Deep Learning Week on Monday (Oct 12) evening.
Minister-in-Charge of the Smart Nation Initiative Vivian Balakrishnan was the guest of honour.
In a video call to students, staff, alumni and members of the public, Dr Balakrishnan emphasised the need for university students to develop "deep technical skills" in areas such as data analytics, machine learning, and artificial intelligence (AI).
"You are the dynamos that will drive our transformation and push the boundaries of how we can leverage technology to transform our economy and make a real difference," he said.
This is the second edition of NTU's Deep Learning Week, which is organised by the Machine Learning and Data Analytics Lab at the NTU School of Electrical and Electronic Engineering (EEE).
Running from Monday to Sunday (Oct 12 to 18), there will be AI-related workshops as well as a virtual AI career fair for students, ending with a machine learning hackathon, themed "AI in business and economics", said NTU in a statement on Monday.
Along with Dr See, the other panellists included Mr Sim Kai, deputy director of the national AI office, Mr Laurence Liew, director for AI industry innovation at AI Singapore, Ms Jane Shen, chief scientist and managing director at Pensees, Dr Pan Yaozhang, head of data science at Shopee, and Dr Yap Kim Hui, associate professor at NTU's School of EEE.
Moderated by Dr Wesley Tan, senior lecturer at NTU's School of EEE, the panel discussed the impacts of the Covid-19 pandemic on the economy and digital transformation.
Panel members concurred that while Covid-19 had forced companies to speed up digital transformation, most trends were already in motion since last year.
The panel also believed that passion was more important than academic background when pursuing a career in AI.
Mr Liew said that computer scientists were a minority among the applicants in his organisation's AI apprenticeship programme, with social scientists and many from other disciplines who had also applied and were doing well.
"A lot of the most successful tech people in the world do not come from a computer science background," he noted.
"It doesn't really matter what your first degree is in, as long as you are passionate you can get into AI."
This article has been edited for clarity.