Artificial Intelligence

Stay Ahead Of The Game : What You Need To Know About The Future Of AI

Changi Airport’s new Terminal 4 features an array of “Fast and Seamless Travel” (FAST) transformation to hasten the process of checking in passengers without the need for human supervision. From facial-recognition software to automated bag-tagging and checking, the Google artificial intelligence (AI) technology that is applied across the board is a great example of narrow AI at work.

Of course, many would already have heard of AI. The concept is aged. But with the advancement in technology over the years, we understand now that there are two types of AI – narrow and general AI.

Narrow AI addresses specific applications such as playing strategic games, translations, self-driving vehicles and image recognition – many of which we see and use in our everyday lives.

General AI, or sometimes also known as artificial general intelligence, is based on the principle that machines can be made to think. In general AI, machines is said to potentially have the ability to represent the human mind and function similarly to the human brain. But there is a long way to go with general AI in terms of research and development.

What we have now is plenty of narrow AI. Today, narrow AI is thriving due to the high volume of data available, high performance computing and complex algorithms. In the world of computing, according to Moore’s Law, computing power has been doubling every two years. Take that, and the fact that in 2011, 90% of the data in the world today was created in the last two years alone and continues to grow exponentially and it makes for good infrastructure for narrow AI to be built on.

Machine Learning In Action

All this is called Machine Learning. Machine Learning is one step ahead of computers that are just programmed to execute a specific task over and over again, because it can change and improve its algorithms by itself.

Machine learning algorithms enable computers to communicate with humans, autonomously drive cars, as well as write and publish reports on sports matches.

In an example of how machines can autonomously make decisions on the fly, take Google’s DeepMind AlphaGo programme which recently defeated South Korean Master Lee Sedol in the board game Go (which is recognised to be the world’s most complex board game).

This is thanks to an extension of AI called Deep Learning, which is implemented in Machine Learning. Deep learning uses artificial neural networks and this is inspired by the human brains and the interconnections between the neurons. Deep learning allows for the machines to identify data and make connections through its complex algorithms.

Over the last two decades, AI technology has disrupted our lives, our businesses, and our world.

Narrow AI and the imminent General AI are likely to disrupt even more jobs – jobs that are non-routine and require cognitive abilities, jobs like junior lawyers, analysts, insurance underwriters and more.

All In Present Day

AI is inevitably part of our future. It clearly boasts higher productivity and efficiency with less cost. It is not susceptible to annual leaves, sick leaves, compassionate leaves and all the variables that make hiring humans less desirable in a time that their jobs can be replaced by robots.

But while AI may render certain jobs redundant, AI may also give rise to demand for new jobs and services that did not exist a decade ago. That is why businesses have easily jumped on the AI bandwagon, preparing themselves for the future that is near. Ex-Chief Scientist at Baidu had this to say about AI: “Just as about 100 years ago, electrification changed every single major industry, I think we’re in the phase where AI will change pretty much every major industry.”

Investing In AI

AI is set to also change the investment landscape. As investors, you might be asking then, what does AI mean for the economy and your investment portfolio? What should your next move be as an investor?

Well, it is simple. If you cannot beat them, join them. Some companies have the future in mind, and have already embraced AI, leading in disruption and innovation. These companies include household names like Amazon, Google, Tesla and Facebook.

AI will continue to grow and you should not miss out on its exponential growth – starting now. Picking the next Facebook is tough, even for professionals, so another way is to get exposure to a diversified global portfolio of stocks of various disruptive companies.

Find out more about the LionGlobal Disruptive Innovation Fund, visit

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Comparing the TER cost for 20 years

Here’s the difference a low cost advantage makes to cost savings

Here's how much you pay

Selected TER 1.00% p.a.

LionGlobal All Seasons Fund 0.5% p.a.

By investing a fund with low TER

You may save $90,359.56 over 20 years based on an initial investment of $1,000,000 compared with a TER of 0.5% p.a.

It is enough to provide for a monthly expenditure of $3,000 over the next 2 years and 6 months.

Here's how much you pay

Selected TER 1.50% p.a.

LionGlobal All Seasons Fund 0.5% p.a.

By investing a fund with low TER

You may save $172,038.04 over 20 years based on an initial investment of $1,000,000 compared with a TER of 0.5% p.a.

It is enough to provide for a monthly expenditure of $3,000 over the next 4 years and 9 months.

Here's how much you pay

Selected TER 2.00% p.a.

LionGlobal All Seasons Fund 0.5% p.a.

By investing a fund with low TER

You may save $ 245,831.62 over 20 years based on an initial investment of $1,000,000 compared with a TER of 0.5% p.a.

It is enough to provide for a monthly expenditure of $3,000 over the next 6 years and 9 months.

TER (Total Expense Ratio) is the sum of various identified operating expenses charged on an ongoing basis to the fund’s assets as a percentage of the fund’s average net asset value calculated over a 12-month period at the close of the annual and semi-annual financial statements of the fund for all the p.a. tabs (1.0%, 1.5%, 2.0%).

The above scenarios are for illustration purpose only. Past performance, as well as any prediction, projection or forecast on the economy, securities market or the economic trends of the markets are not necessarily indicative of the future or likely performance of the funds. Calculations based purely on costs with no market movement or investment returns.