“Technology is moving so fast, and 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 spoke in a panel discussion at the launch of Nanyang Technological University’s (NTU) Deep Learning Week (DLW) recently.
Minister-in-Charge of the Smart Nation Initiative Vivian Balakrishnan was the guest of honor.
In a video call to students, staff, alumni, and members of the public, Dr. Balakrishnan emphasized the need for university students to develop “deep technical skills” in areas such as data analytics, machine learning (ML), 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 DLW, organized by the Machine Learning and Data Analytics Lab at the NTU School of Electrical and Electronic Engineering (EEE).
During the DLW, there were 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.
Along with Dr. See, the other panelists included Mr. Sim Kai, deputy director of the national AI office, Dr. 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.
Distinguished panel members included Ms. Jane Shen, Dr. Laurence Liew, Dr. Pan Yaozhang, NTU EEE chair Tan Yap Peng, Dr. Simon See, NTU EEE student committee president Duan Jiafei, Mr. Sim Kai, Dr. Yap Kim Hui, and moderator Dr. Wesley Tan.
Moderated by Dr. Wesley Tan, senior lecturer at NTU’s School of EEE, the panel discussed the Covid-19 pandemic’s impacts 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.
Dr. Liew said that computer scientists were a minority among the applicants in his organization’s AI apprenticeship program, 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.”