Artificial intelligence - a red moon rising

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 to grow to at least $70 billion by 2020. One is reminded of the three of China’s biggest 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 our most valuable resource – human data. A clever use of smart algorithms can harness the power of AI, lifting it to a higher level.

It will soon wield tremendous influence in global digital commerce, autonomous vehicles, 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 become the most valuable AI start-up in the world.

Artificial intelligence in machines can even replicate human judgements previously considered to be too complex

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. Users are applying their AI prowess to everything from traffic surveillance to employee authorisation.

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 optimise 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. 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 feared the consequences of creating something that can match or surpass humans.

“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 computing power or the ability to develop the algorithms needed to achieve full artificial intelligence. Take a deep breath, as it 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 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. The answer is: China wants to become a leader in this sector and is investing billions. In the US, there is a cohort of venture capitalists who are constantly poised to look out for talented persons in their ongoing recruiting outreach.

It isn’t uncommon for research firms to seek topnotch university graduates who show early leadership potential. One cannot omit Mr Son who created Softbank, 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.

It is shaking up the cosy world of Silicon Valley venture capital. The gargantuan fund lures start-ups to cash out from the clutches of Google, Facebook and Amazon – and with its massive war chest, it gives entrepreneurs a better shot at competing with the titans.

The fund wants to perform a similar function in China, where nearly half of all unicorns are by now backed by one of the country’s three BAT giants. Readers appreciate that this disruptive technology has a benign purpose and is helping to link various civilisations, 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.

Artificial intelligence in machines can even replicate human judgements previously considered to be too complex. Imagine how in the next decade, there will be robots which are efficient and devoid of emotions quietly supervising hundreds of complex factory operations.

In conclusion, ask any mystic about this week’s rare apparition at night of a Red Moon rising. Surely this is a friendly omen which can be interpreted to prognosticate the growing potential of AI. Ending on this positive note, it can help humanity develop machines able to code complex algorithms that ‘learn’ from past examples.

Needless to say, businesses that can use machines 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.

George M. Mangion is a partner in PKF, an audit and business advisory firm