In this exclusive interview with Aik Beng Ng, we explore his journey, reflections, and aspirations in the evolving world of artificial intelligence (AI).
As the Regional Manager for NVIDIA AI Technology Center, Aik’s trajectory in the technology industry representes the transformative power of innovation. From pioneering individualised software deployment solutions to conceptualising the ‘Intellective Exoskeleton’.
Don’t miss Aik’s upcoming session at Big Data & AI World Asia at Marina Bay Sands, Singapore on 11-12 October.
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What pivotal moments in your career led you to where you are today?
Early in my career, I held the role of an IT engineering lead and had the opportunity of being involved in the setup of a new business unit dealing with large scale PC deployment for the region’s corporate customers.
As I soon realised, installing one PC is very different from having to manually install many PCs at production scale. This motivated me to explore how we could use technology to better automate the process. However, no existing solutions were a good fit then.
This spurred me and my team to develop a new solution: ‘methodology of individualised software deployment for hardware-independent personal computer mass development’ that was subsequently patented. Ever since, technology has been central in my career and the roles I have undertaken.
How has your diverse experience influenced your views on AI’s role in different sectors?
As steam and electricity have been key to previous industrial revolutions, so will AI.
When we look across industry verticals, ICT has and continues to be pervasive for productivity and efficiency reasons. Likewise, AI presents a next-level pathway for many existing ICT-enabled use cases.
For example, a vector database could augment existing knowledge bases by storing unstructured data as vectors and enabling natural language queries against such information.
More importantly, particularly in recent years, AI presents an innovation pathway for dramatically accelerating use cases that were previously too costly (i.e. time, compute, etc.) by conventional means or even enabling the previously impossible. Examples include drug discovery, autonomous driving, and more.
Could you explain the concept of ‘Intellective Exoskeleton’ and its potential in changing our AI interactions?
My concept of an ‘Intellective Exoskeleton’ started from my interest in advancements towards Human-AI collaboration.
Just as exoskeletons support and augment our physical abilities, the ‘Intellective Exoskeleton’ is envisioned to be our personalised assistant that harnesses AI for augmenting our cognitive abilities while accounting for bi-directional human-AI communications and feedback, with the nuanced difference from AI assistants such as chatbots that essentially work as natural language interfaces for the products/services we are interacting with.
From an individual viewpoint, during information analysis, it could enable ‘In-character Augmentation’ (i.e. deepening our perspectives) and ‘Out-of-character Augmentation’ (i.e. expanding our perspectives).
From a community viewpoint, our respective ‘Intellective Exoskeletons’ could transcend space to autonomously interact on topics of common interest while bringing our different perspectives into the interaction, just as we would in real life with each other during meetings.
Beyond these illustrations, the ‘Intellective Exoskeleton’ concept goes deeper and broader with many more considerations. Overall, the intent is to help progress our knowledge workforce up the cognitive value chain both individually and as a community.
How can we address issues like data scarcity and privacy in AI development?
Data is a critical component for AI development, and generally, AI model training benefits from more training data which is not always readily available due to reasons such as privacy, rare events, high risk of data acquisition, etc. Hence, synthetic data generation is an important direction towards overcoming data scarcity challenges while preserving data privacy.
Today, generative AI presents a powerful and effective way to generate realistic synthetic data across modalities enabled atop foundation models pretrained on large amounts of data. It is, therefore, an important consideration that data used to pretrain foundation models should also be responsibly and properly sourced.
Why is it vital to partner with educational entities, governments, and other industries for responsible AI growth?
Collaboration and communication are key. No single stakeholder would be sufficiently knowledgeable or capable of managing and influencing the entire AI ecosystem spectrum (e.g. research, engineering, policy & regulation, education & awareness, etc.) needed to foster responsible AI advancements.
Through collaboration, various ecosystem stakeholders are cross-informed across the spectrum, which will better equip everyone involved to design and implement synergistic initiatives towards fostering responsible AI advancements.
For example, schools could include academic modules on responsible AI in addition to technical-oriented modules, policy makers could achieve a more optimal balance on regulations while ensuring room for research and technological innovations, and so on.
How do you envision the future interplay between human cognition and AI?
I believe that both paradigms of autonomous AI and AI augmentation have its relevance and significance moving forward. And in both cases, human cognition is critical. On the front of autonomous AI, human cognition has significantly inspired and informed the design and implementation of AI.
For AI augmentation, as alluded earlier on the ‘Intellective Exoskeleton’, human cognition is potentially augmented by AI while simultaneously informing how the AI could perform better in its design goal to augment us.
Overall, I like to view the balance between human cognition and AI of that in the form of a synergistic co-existence.
What advice would you give to young professionals entering the AI field?
Be curious, be courageous to innovate, be resilient in overcoming challenges, and be humble. As Aristotle said: “The more you know, the more you realise you don’t know.”
What key takeaways do you hope to impart at Big Data & AI World, and why would you encourage fellow leaders to secure their free ticket?
I really love to share some of my thoughts on generative AI and the associated pragmatic considerations in the journey of adopting generative AI (and AI).
In sharing some of the discussion points closer to the ground and hopefully people’s hearts, it is my hope that we will help drive industry adoption to realise improved productivity and efficiency for the workforce today and tomorrow.
On this note, I encourage fellow friends and colleagues in the ecosystem to secure your free admission and join this platform to help drive the AI and technology adoption conversation forward together.