Asia flexing muscles in the race for AI

Imagine how in the next decade, there will be robots which are efficient and devoid of emotions quietly supervising hundreds of complex factory operations. Ending on this positive note, AI can help humanity develop machines able to code complex algorithms that ‘learn’ from past examples


China has made tremendous strides in many fields, particularly in AI It is a driving force which guided businesses and government agencies to collaborate on a sweeping plan to make China the world’s primary AI innovation centre by 2030, and it’s already making serious progress toward that goal.

In fact, US Air Force General VeraLinn Jamieson says that “We estimate the total spending on artificial intelligence systems in China in 2017 was $12 billion. This is estimated that it will grow to at least $70 billion by next year. One is reminded of the success of China’s biggest digital companies - Baidu, Alibaba, and Tencent - superpowers.

Collectively, known as the BAT, these command a formidable force in the sphere of AI and digital commerce. It is easy to notice how BAT, could soon command what’s perhaps is a most valuable resource--human data. With a clever use of smart algorithms this can harness the power of AI, lifting it to a higher level.

It will soon wield tremendous influence in global digital commerce, autonomous vehicles, the IOT, and a renewed race to outer space. By comparison, one notices that whereas American users’ payment and transportation data are fragmented across various platforms, Chinese AI giants like Tencent have created unified online ecosystems that concentrate all citizen data in one place.

China’s computer vision start-up “SenseTime” has undoubtedly became the most valuable AI startup in the world. Capable of identifying your face, gauging your age and even your potential purchasing habits, “SenseTime” is now a world-class leader in facial recognition technologies. It comes as no surprise that users are applying their AI prowess to everything from traffic surveillance to employee authorization.

Regardless of how artificial intelligence (AI) is defined, there is little doubt that this resource can be of great value, especially in big data applications. Undoubtedly, AI is fast becoming a major technological tool for prescriptive analytics, the step beyond predictive analytics that helps us determine how to implement and/or optimize optimal decisions.

In business applications, it can assess future risks, quantify probabilities and in so doing, give us insights how to improve market penetration, customer satisfaction, security analysis, trade execution, fraud detection and prevention, while proving indispensable in land and air traffic control, national security and defence. That is not to mention, a host of healthcare applications such as patient-specific treatments for diseases and illnesses.

It is appropriate to explain how the popular concept of “Singularity “was formally coined in 1993 by Vernor Vinge, a scientist and science fiction writer, who posited that accelerating technological change would inevitably lead to machine intelligence that would match and then surpass human intelligence.

Equally ominous was the prediction five years ago by the late Prof Stephen Hawking who said the primitive forms of artificial intelligence developed so far have already proved very useful, but he fears the consequences of creating something that can match or surpass humans.

He predicted ....“Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”

Others think this warning is too pessimistic and argue that we are a long way from having Robots with endless computing power or the ability to develop the algorithms needed to achieve full artificial intelligence.

Take a deep breath, as digital war for human supremacy will not hit us, as yet for a number of decades. Understandably, humanity always fears the unknown - what will happen if and when a Robot supersedes our own intelligence. When it comes to use of artificial intelligence in powering complex robotics one cannot ignore the worst fears of prominent technologists and scientists like Elon Musk, Stephen Hawking and Bill Gates, who have all voiced alarm over the possible emergence of self-aware machines which unless harnessed, may well be out to do harm to the human race.

Quoting Mr. Musk of Tesla fame he said that “If I had to guess at what our biggest existential threat is, it’s probably AI”.

In a cautionary mood of admonition, he has said that artificial intelligence would “summon the demon.” One may ask - who is funding such expensive research. China certainly fits the bill - it wants to become a leader in this sector and is investing billions.

Back to US, where the race for AI supports a cohort of venture capitalists who are constantly poised to look out for talented persons in their ongoing quest to recruit outreach. One cannot omit to mention Mr Son who founded Softbank together with a number of sponsors.

This is a mega IT research fund headquartered in Japan. SoftBank is synonymous with its charismatic founder that is reshaping global tech with its colossal treasure box.  The gargantuan fund lures start-ups to cash out away from the clutches of Google, Facebook and Amazon - having its massive war chest, it gives its client entrepreneurs a better shot at competing with the titans. The fund wants to perform a similar function in China.

Readers appreciate that AI albeit a disruptive technology yet with a benign purpose and is helping to link various civilizations, improve crop yields and speed up the progress in complex human Genome classification. Delivery drones, both wheeled and airborne may in the near future compete with couriers while supermarket robots silently stack food items on shelves and move merchandise in warehouses.

Imagine how in the next decade, there will be robots which are efficient and devoid of emotions quietly supervising hundreds of complex factory operations. Ending on this positive note, AI can help humanity develop machines able to code complex algorithms that ‘learn’ from past examples.

Needless to say, businesses that can use machine and deep learning techniques to mine, refine, and make products from data culled from all areas of operation--from customer service to employee productivity - will command a bigger share in market dominance.
Can Malta afford not to join the band wagon?

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