We will have the privilege of hosting Koo Ping Shung as one of our expert speakers at GITEX 2023. Koo
has traversed through data analytics, data science, and artificial intelligence
in his career for the past 19 years, having co-founded DataScience.Sg (grassroots
community) in Nov 2013, growing it to more than 10,000 members (as of 2020) and Former President of AI Professionals Association, Singapore.
We interviewed Koo on various areas of his expertise and what he's most looking forward to at this years edition of GITEX, in The Year To Imagine AI In Everything.
What do you expect the next 5 years in AI to look like?
AI is definitely here to say the least and we should see more models being
developed, especially cross-medium generative models such as text-images,
text-speech, etc. With this in mind, the media industry will have a huge
shake-up for sure with content generation becoming cheaper.
As for the overall AI industry, given its development
and more talents working on it, it will be difficult to predict its overall
trajectory. However, what I can say for sure is this. With Generative AI
raising the public awareness further on what AI can do, there will definitely
be more emphasis on the AI Professional Ethics and Governance and this is where
regulations and compliance comes into place. We should see more regulations and
compliance going forward, and as for whether it will stifle innovation in AI,
it really depends on individual governments’ literacy level on AI.
With So many new startups in AI, what would your advice be for a startup looking
to differentiate themselves?
My advice will be, focus on collecting good quality
data that allow your startup’s AI products to differentiate it from others. The
data collected at the end of the day can be your differentiating factor that
sets you up on whether you are ahead or behind your competitor. Having said
that, startups should also look at securing the data and ensuring its privacy
3) In the past you
have referred to current AI technology being ‘weak’ due to its limitations
outside of a very specific scope – when do you believe this will improve?
Let me frame the question slightly. The reason why I called the current
technology is weak because at the end of the day, the humans are the one that
provides the scope of it. Current AI technology has not reach a point where the
machine itself can look at a particular challenge and scope a challenge around
it, designing and stating the objective function together with the constraints.
Once AI technology is able to look at real-world problem, scope the challenge
up, determine the objective function and constraint, and converting it to a
mathematical problem, it will be what I considered "strong" AI.
As for when a day will come, I am no oracle and humans are very poor at
predicting the development trajectory of technology. So what I can say for
sure, AI technology will improve as we go along. More importantly right now is
how can we build learning machines, machines that can consistently learn and
improve. This will definitely be a trend I will be monitoring.
4) What are your thoughts on DAI (decentralized artificial intelligence)
– are we ready for this yet?
This is a very new idea from what I observe. Another "combination" of
putting two "hot" technology together, Blockchain and Artificial
Intelligence. However, I am of the opinion that the idea of it is still in
development and will meet with a lot of application challenges, and the first
big challenge is computing power. Given the current geo-political situation,
computing power will get more expensive and with that limited to a few hands.
And training of AI models will need both time and computing power, of which
both are readily available in big corporates, such as Google, Meta, or Amazon.
So are we ready for this yet, the answer is no and the current landscape is
more favorable to have centralized artificial intelligence rather than
What are you most looking forward to at GITEX this year?
few things I am looking forward to:
Meeting Joe Reis, co-author of best-seller “Fundamentals of Data Engineering
because we have been meeting and chatting online but yet to
meet physically. And it will be my privilege to meet an author of a best-seller
- Meeting Andrew Jones from Data Science Infinity again. His business has helped
many to join the data professionals. Always keen to talk to passionate
- Meeting the folks from Women in AI again, as I am very keen to promote diversity
in the AI profession and it ties in with their goals as well
- Of course, all the technical content that GITEX’s team has spend so much effort
to put together!
- Last but not least, I will like to meet more
like-minded professions to discuss about Artificial General Intelligence, Smart
Cities and different AI Applications.
More about Koo Ping Shung
Koo has traversed through data analytics, data
science, and artificial intelligence in his career for the past 19 years.
With an MBA degree and vast relevant
experience, he is able to determine where possible business values are from
data collected. He does it differently by building internal capabilities,
through training, consulting, and mentoring, allowing businesses to continuously
take advantage of their data.
Uniquely, Koo is experienced in the full
process of getting value from data, from data collection, management &
governance to implementation of insights through strategy and business
His research interest is in how an
organization can build Data Science & Artificial Intelligence capabilities,
Artificial General Intelligence, and Smart Cities with a focus on the standard
Co-founded DataScience.Sg (grassroots
community) in Nov 2013, growing it to more than 10,000 members (as at 2020).
Former President of AI Professionals Association, Singapore.