The panelists discussed the following:

• Prof. Ts. Dr. Sim Yee Wai – shared on the Turing Test, a test to determine whether machines are capable of thinking like humans. He also provided a brief history of Artificial Intelligence (AI); the 1st Wave (Symbolic AI, 1950s – 1960s) and the 2nd Wave (Expert Systems, 1980s – 1990s), which were not really successful at solving real world problems as they were built based on human reasoning and knowledge. This is where the 3rd Wave, which is the Machine Learning (2010s – Present) comes in. Machine learning is based on the idea of how humans accumulate experiences and learning from trials and errors, so when we encounter a similar situation or problem, we can apply the same solution for it. Machine learning can be used to find the correlation between event features and results based on historical data, using data modelling which can help to classify data and contribute predictions for more accurate decision-making. Dr. Sim also advised that the next wave of AI will be a disruptive one and its impact on us will depend on our understanding about the technology and how we react to it.

• Mr Oliver Tian – Highlighted that the need to plan for collaboration between machines and humans for the future. AI & Robotics should be adopted to augment human capabilities and potential and AI projects does not have to be huge. He believed that AI-powered users will emerge soon, and that robotics plug-and-play is also on the rise. On the other hand, he underscored that we should consider the appropriate applications of the technology, and do not focus on the media hype on the fear of machines taking over humans’ jobs. Instead, we should aim to treat AI and machines as evolving digital co-workers that work alongside us and help us do things better. He believes that treating intelligent solutions as co-workers will make them a sustainable and reliable force in the future.

• Mr Soo Ho Hock MENG – Introduced collaborative robots (Cobots) which are the value proposition enabler in the IR4.0 tool kit, especially for SMEs to improve their processes, drive productivity, reduce dependence on labour intensity and provide the foundation for adoption of newer manufacturing technologies. These Cobots are highly cost effective and have successfully been incorporated into manufacturing processes. In one instance, to reduce cost, programming is very much simplified, with no proprietary codes, from Blockly to the common languages such as Lua, C, C++ and Python. This makes it easier to code once and deploy many times in multiple situations. Cobots also provide increased safety, speed and the ability to work 24/7 with minimal human intervention.

• Ts. Dr. Chua Wen-Shyan – Emphasized that successful AI Adoption begins with the first step. He recognises that the first step is always the hardest, but with the right people, skills, continuous development (training) and effort, the learning and adoption curve would be much smoother. There are many low and no-code AI platforms which are user friendly for citizen developers. Low code AI accelerates AI adoption in the community with increased productivity and implementation speed than traditional designs. Having a people-centric strategy would ensure the sustainability of AI adoption and companies would be able to realize the benefits sooner than expected. He highlighted Start Small and Scale Big as the key of transformation in adopting AI as the solutions in the industries.