Artificial intelligence driven by Softbank’s treasure chest
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. There are also a host of healthcare applications such as patient-specific treatments for diseases and illnesses.
Recently, the popular concept of “Singularity” was perceived by computer scientists. The idea 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. In his original essay, Dr Vinge suggested that the point in time at which machines attained superhuman intelligence would happen sometime between 2005 and 2030. The notion of the “Singularity” is predicated on Moore’s Law, the 1965 observation by Intel cofounder Gordon Moore, that the number of transistors that can be etched onto a sliver of silicon doubles at roughly two year intervals. This has fostered the notion of exponential change, in which technology advances slowly at first and then with increasing rapidity with each succeeding technological generation.
To mention a few examples of the rapid progress made by research and development cofunded by multi-national firms, one can start by mentioning Google. The giant search engine firm is a pioneer in the field of artificial intelligence, developing self-driving automobiles, smartphone assistants and other examples of machine learning. Equally ominous was the prediction four years ago by Prof. 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. “Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”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 the computing power or the ability to develop the algorithms needed to achieve full artificial intelligence. It will not hit us yet for a number of decades.
On the contrary, there is always the fear of what the future may bring since we cannot quite know what will happen if a machine exceeds our own intelligence. We cannot know if we will be infinitely helped by it, or ignored by it or, conceivably, destroyed by it. When it comes to using artificial intelligence to power 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 selfaware machines which unless harnessed, may well be out to do harm to the human race. Mr Musk of Tesla fame said: “If I had to guess 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 a cohort of venture capitalists who are constantly poised to look out for talented people in their ongoing recruiting outreach. It is not uncommon for research firms to seek top-notch university graduates who show leadership potential. Mr Masayoshi Son (see picture) is a Japanese investor who cre- ated SoftBank which he wants to mimic a “virtual Silicon Valley”, meaning a platform on which unicorns (start-ups that turned into a billion dollar marvel) can offer each other contacts and advice, buy goods and services from each other, and even join forces. Mr Son, who founded SoftBank in the 1980s, has grand visions of what technological advancements the future holds. SoftBank’s subsidiaries are pushing the frontiers of technology in areas such as the “Internet of Things”, artificial intelligence and deep learning. It hatched the unique “Vision Fund” with a $100 billion war chest looking to invest in startups with operational experience, and technical background.
For this purpose, the Vision Fund is aggressively competing with traditional technology investors in Silicon Valley in a no-holds-barred fight for talent. Mr Son believes he has a unique ability to predict future technology trends, and states he is ready for the gamble. 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 – having its massive chequebook 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 now backed by one of the country’s four tech giants – Baidu, Alibaba, Tencent or JD.com.
In passing, one may feel that the disruptive path of new technology cannot find a better champion than SoftBank with its aggressive investment appetite to nurture new ventures. Readers appreciate that this disruptive technology has 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. Artificial intelligence in machines can even replicate human judgments 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, as if by magic, the Vision Fund will help humanity get machines able to develop complex algorithms that ‘learn’ from past examples – only then can Mr Son happily claim that he has fulfilled his dream.