The reality of the AI revolution

The
reality of the AI revolution

Jason
Bissell, General Manager of Asia Pacific and Japan and Calvin Hoon, Regional VP
for Sales, Asia Pacific,Talend
Inc.

Artificial
intelligence (AI) is one of the most evocative and confusing terms in
technology. In making sense of it, Talend’s Jason Bissell says AI is an
everyday reality today but with plenty more to
deliver in the future…

Based on research
gathered by MIT Technology Review, Asia’s business landscape is poised not only to
benefit greatly from the rise of artificial intelligence
but also (play a major roll in helping?) to
define it. While only a small percentage of respondents are currently investing
in AI development in Asia, 25% of firms have already made investments at a
global level – with another 50% considering doing so.

We have seen a machine master the complex game of Go, previously
thought to be the most difficult challenge of artificial processing. We have
witnessed vehicles operating autonomously, including a caravan of trucks
crossing Europe with only a single operator to monitor systems. We have seen a
proliferation of robotic counterparts and
automated means for accomplishing a variety of tasks and all of this has given
rise to a flurry of people claiming that the AI revolution is already upon us.

However, while there is no doubt that there have been significant
advancements in the field of AI, what we have seen is only a start on the path
to what could be considered full AI.

Understanding the growth of AI capability is crucial for understanding the
advances we have seen. Full AI, that is to say complete, autonomous sentience, involves
the ability for a machine to mimic a human to the point that it would be
indistinguishable from them (the so-called Turing test). This type of true AI is still a long way from reality.
Some would say the major constraint to the future development of AI is no
longer our ability to develop the necessary algorithms, but, rather, having the
computing power to process the volume of data necessary to teach a machine to
interpret complicated things like emotional responses. While it may be
some time yet before we reach full AI, there will be much more practical applications of basic AI in the near term that
hold the potential for significantly enhancing our
lives.

With basic AI, the processing system, embedded within the appliance (local)
or connected to a network (cloud), learns and interprets responses based on
“experience.” That experience comes in the form of training through using data
sets that simulate the situations we want the system to learn from. This is the
confluence of Machine Learning (ML) and AI. The capability to teach machines to
interpret data is the key underpinning technology that will enable more complex forms of AI that can be autonomous in
their responses to input. It is this type of AI that is getting the most
attention. In the next ten years, the use
of this kind of ML-based AI will likely
fall into two categories:

There is no doubt about the commercial prospects for autonomous robotic
systems in the commercial market for
aspects such as online sales conversion, customer satisfaction, and operational efficiency.   We see this
application already being advanced to the
point that it will become commercially viable, which is the first step to it becoming
practical and widespread. Simply put, if revenue can be made from it, it will become self-sustaining and thus continue
to grow. The Amazon Echo, a personal assistant,  has succeeded as a solidly commercial
application of autonomous technology in
the United States. Autonomous vehicle technology is one of the most publicised and one of the most needed
applications of AI. There are an estimated 9000 people injured or killed in
traffic accidents per year in Singapore; autonomous vehicle technology could
almost entirely eliminate this and greatly improve availability and efficiency of
transportation for everyone.

In addition to the automation of transportation and logistics, a wide variety of additional technologies that utilize
autonomous processing techniques are being built.
Currently, the artificial assistant or “chatbot” concept is one of the most
popular. By creating the illusion of a fully sentient remote participant, it
makes interaction with technology more approachable. There have been obvious
failings of this technology (the unfiltered Microsoft chatbot, “Tay,” as a
prime example), but the application of properly developed and managed
artificial systems for interaction is an
important step along the route to full AI. This is also a hugely important application
of AI as it will bring technology to those who previously could not engage with
technology completely for any number of physical or mental reasons. By making
technology simpler and more human to interact with, you remove some of the
barriers to its use that cause difficulty for people with various impairments.

The use of AI for development and discovery is just now beginning to gain
traction, but over the next decade, this
will become an area of significant investment and development. There are so
many repetitive tasks involved in any scientific or research project that using
robotic intelligence engines to manage and perfect the more complex and
repetitive tasks would greatly increase the speed at which new breakthroughs
could be uncovered.

There is also the tantalizing possibility that as we increase the
capability of our AI systems, they could actually
perform research and discover new avenues to explore. While this is still a
long way away, it could greatly
accelerate the discoveries needed for many advancements that could improve and
extend our lives.

The dystopian vision of robots
assuming complete control of society is unlikely; the nuances of perception, intuition, and plain old “gut-check reactions” still elude machines.
Learning from repetition, improving patterns, and developing new processes is
well within reach of current AI models,
and will strengthen in the coming years as advances in AI – specifically
machine learning and neural networking – continue. Rather than being frightened
by the perceived threat of AI, it would be wise to embrace the possibilities
that AI offers.