AI Summer School has grown, COVID-19 notwithstanding. More than 250 attendees from 30 countries took part in this year’s event, with leading experts in the field of artificial intelligence (AI) coming together to share their work and foster collaboration amongst the next generation of researchers. The latest edition, which took place from 3 to 7 August, follows the success of the inaugural event last year which attracted 142 attendees from 15 countries.
Held in a virtual setting because of the pandemic, AI Summer School 2020 featured innovative tweaks to the traditional format to enable students, academic researchers and industrial practitioners to explore exciting possibilities surrounding the use of AI in real-world application domains and raise awareness of data innovation challenges and issues.
Unconference Sessions
“The main difficulty this year was in providing opportunities for participants to interact,” said Dr Stefan Winkler, Chair of Organising Committee and Deputy Director of AI Technology, AI Singapore. To address this, “Unconference Sessions” were held to give participants an opportunity to break into small discussion groups with the flexibility of exploring different groups based on their interests.
“The main aim was to facilitate the exchange and cross-pollination of ideas from a ground up rather than a top down approach,” he explained.
A general “Hangout” table was created to help participants navigate to topics they may be interested in, while Individual topic tables gave participants the option to start or join a table with its own Zoom session and Google Doc sharing.
Poster videos
Poster video sessions were also held, where participants shared a video of their AI-related work on Youtube and facilitated discussions on their project by replying to comments posted on the social media platform.
Awards were presented for the three top poster videos. Christian Alvin H. Buhat from the University of the Philippines Los Banos received the nod for his animated agent-based model of COVID-19 infection inside a train wagon. The second award went to Jiafei Duan from the Artificial Intelligence Initiative at the Institute for Infocomm Research, A*STAR, for his video on ActioNet. This is a platform for task-based data collection and augmentation in 3D environment, which has the potential to catalyse research in the field of embodied AI.
The third video poster that caught the judge’s eye was M Ganesh Kumar’s presentation on schemas for few-shot learning, which involves feeding a learning model with a very small amount of training data. Ganesh is from the Graduate School of Integrative Sciences and Engineering at the National University of Singapore (NUS).
DinerDash challenge
Another unique component introduced in AI Summer School 2020 was the DinerDash challenge, which was organised as part of the Reinforcement Learning workshop on Day 2. This is a game where a single waiter makes complex decisions on customer seating arrangements, taking orders, serving food and many others. Participants worked in small groups to test reinforcement learning baselines and competed with one another for the highest score in the DinerDash simulator.
For Ong Chi Wei, a Post-doctoral Research Fellow from the Department of Biomedical Engineering, NUS, this was the best experience he had at the summer camp. “The key takeaway for me was the Reinforcement Learning (RL) Diner Dash challenge. It was well organised and interesting. We were required to submit our proposal on the same day after the question was posted using reinforcement learning. I learnt from my teammates and we managed to solve the problem with different algorithm testing. Overall the challenge made us think creatively and how to work as a team to solve AI problems.”
Distinguished alumni
Adding gravitas to Summer School were presentations by experts in the field of AI.
In a keynote on “AI @ Scale – Trends and Lessons Learnt from Large-scale Machine Learning Projects”, Dr Tok Wee Hyong, Principal Data Science Manager at Microsoft Corporation, shared his insights into key trends in machine learning and deep learning, grounded in practical experience evolving AI ideas from proof of concept to production at some of the world’s largest Fortune 500 companies.
Dr Tok, who is with the AzureCAT team in Redmond, was one of three overseas-based speakers who are alumni of NUS and Nanyang Technological University (NTU) graduate schools, who have gone on to carve out a distinguished career in the field of AI. The others are fellow Singaporean Dr Yi Tay, a research scientist at Google AI, Mountain View, and Dr Trọng-Nghĩa Hoang, a research staff member at the MIT-IBM Watson AI Lab, IBM Research Cambridge.
Personalised learning at scale
The second keynote at the event was delivered by Prof Zhai Chengxiang, Donald Biggar Willett Professor, University of Illinois at Urbana-Champaign. His presentation on “AI for Education: Towards Personalised Learning at Scale” highlighted the exciting opportunities for applying AI techniques to transform education to make it both more affordable and more effective.
In other sessions, speakers shared their work in areas such as federated learning, self-supervised deep learning, multi agent interaction, Gaussian processes and low-resource machine learning, and also covered AI applications in sectors such as healthcare. Additional important aspects of AI such as ethics and governance were discussed too, as were career-related topics such as job hunting and entrepreneurship.
The plus side of a virtual camp
Looking back on AI Summer Camp 2020, Dr Winkler felt the virtual format had its advantages. “We could not hold any social events, such as the buffet dinner and Night Safari outing that we had last year, but on the plus side, we could offer much lower registration fees, and open up the school to a larger number of people with no auditorium size constraints.”
