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One of the most popular terms of today is ‘artificial intelligence’. People have been increasingly talking about how machines might take over their jobs or even bring fundamental changes to societies. But how far have we come to fear these problems now?

The word AI, by itself, actually does not directly relate to a super intelligence which is more powerful than humans, contrary to beliefs. There actually exists three categories of AI:

• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificial Super Intelligence (ASI)

The technical equipments which we use everyday, such as Alexa, Google Translate or your spam folder: They actually work with ANI networks which can only exceed human intelligence in one specific thing.

The second type of AI, namely AGI, is not specified in one subject like ANI, but is as smart as a human being on average. So far, we have not reached such intelligence: Having a system functioning like a human brain requires at least reaching  its computing power, measured by calculations per second (cps).

Urban (2015) mentions scientists’ estimation on an average human brain computing power: It is able to do 10¹⁶ calculations per second (10 quadrillion cps). The writer explains that the fastest computer in the world, Tianhe-2 of China has beaten it with 34 quadrillion cps. However, it also takes a space of 720 m², uses 1,200,000 times as much energy as a human brain uses. It has also cost $390 million to build it, not even mentioning its maintenance. Therefore, my personal opinion is that we probably still have a long way to go until we see an AGI in our daily lives.

Also, even though we manage to cut down the costs for a widespread use in the future, imitating how the brain works is still an issue: In order to do that, scientists are working on ‘artificial neural networks’ which are capable of learning by experience, just like humans. Additionally, breeding computers (their programming) which perform the best to achieve a super-computer, just like what happened in evolution, is a topic considered in this context (Urban, 2015).

The next step is the ASI after that, which can beat any human at any task. Actually, the step from AGI to ASI will be pretty quick: Kurzweil defines ‘Law of Accelerating Returns’ by “human progress moving quicker and quicker as time goes on” (2001).  For instance, in this century, we know much more things compared to a 14^th century man. Same applies for AGI: Once it reaches the human intelligence level, it will be very fast to develop itself to a super intelligence level since its advancement level will help it being even more advanced (Urban, 2015). Then, it would theoretically continue advancing even more: An intelligence explosion, that can know or do anything.

What are we going to do then?

 

References:

Kurzweil, R. (2001). The age of spiritual machines. New York: Texere.

Urban, T. (2015). The Artificial Intelligence Revolution: Part 1 – Wait But Why. [online] Wait But Why. Available at: https://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html [Accessed 15 Oct. 2019].

 

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Ant Financial is one of the most influential fintech companies of today which is shaking up the banking industry (The Economist, 2019).
Valued at $150bn in 2019, which is 50% bigger than Goldman Sachs, the company originates from Alipay. The latter is an online payment service, just like Paypal, founded by Alibaba in 2004 to serve buyers and sellers on the Chinese shopping website Taobao (The Guardian, 2018). Alipay became very successful in China: It reached 700 M active users and a transaction value equivalent to 65% of Chinese GDP in 2017.
In 2011, Alipay was rebranded as ‘Ant Financial’. Through ecosystems, it started to offer “financial services for insurance, credit, loans, credit scoring, and wealth management” (Applico, 2019). This expenditure in the financial services was possible owing to the huge consumer audience the company has. Followingly, Ant Fortune, a product of Ant Financial, has attracted many asset management firms in China since it facilitated them to reach clients and get clearer insights (Finews Asia, 2018). Thereby, they moved their operations to the platform and were able to connect with 180 million users (Applico, 2019).
The amount of ‘big data’ the company manages helped it to offer various products to its consumers, like Yue Bao. The latter makes use of Alipay consumer data and invites consumers to invest even small amounts in their Alipay wallet. By including these over-looked non-corporates, Yue Baeo has became world’s largest money fund worth $251 billion in assets, in 2019.
Another data-driven product is Mybank, which provides credits to small enterprises. Since company can track shopping habits, the amount of time to pay off debts, and numerous other characteristics related to people’s transactions on its platforms, Mybank can calculate a credit score and lend money.
In summary, Ant Financial is actually imitating the banks. Moreover, they facilitate people’s lives by connecting every platform they might need: From restaurants reservations to wealth management. Then, why wouldn’t traditional banks fear being replaced by such powerful player?

 

References:

Applico. (2019). How Ant Financial Became the Largest Fintech in the World. [online] Available at: https://www.applicoinc.com/blog/ant-financial-services-platform-largest-fintech-in-world/ [Accessed 6 Oct. 2019].

Finews.asia. (2019). Ant Financial’s AI Threatens Wealth Managers. [online] Available at: https://www.finews.asia/finance/27092-ant-financial-s-use-of-ai-can-threaten-wealth-division-in-banks [Accessed 6 Oct. 2019].

Kuo, L. (2019). ‘Digital wallet’ of Ant Financial captivates China and beyond. [online] the Guardian. Available at: https://www.theguardian.com/technology/2018/may/28/digital-wallet-of-ant-financial-captivates-china-and-beyond [Accessed 6 Oct. 2019].

The Economist. (2019). Young people and their phones are shaking up banking. [online] Available at: https://www.economist.com/special-report/2019/05/02/young-people-and-their-phones-are-shaking-up-banking [Accessed 6 Oct. 2019].