Google’s AlphaGo program recently defeated the world’s second-ranked player of Go — a vastly more complex game than chess — marking an important milestone in the development of artificial intelligence (AI). But equally important was Google's revelation that one of its robots has developed the ability to pick up objects in ways that had previously only been identified in cognitive life forms. Both advances were brought about by the development of computational models based on the human central nervous system, which is particularly well suited to certain aspects of AI, such as pattern recognition and machine and adaptive learning. Research in this area will have significant implications for geopolitics in the future.
Automation and AI are already being applied in nearly every economic sector. Human labor is being redefined, much as it was during earlier technological breakthroughs, at times disrupting employment while revolutionizing how the global economy operates. But not all areas of research and development have the same implications and applications. Robotics has become deeply embedded in manufacturing — most notably the automotive sector — but the tasks performed are generally routine processes, such as moving a car door to a specific spot as a worker attaches it to a frame. These tasks are well suited to conventional computing techniques and algorithms defined by long sequential formulas, rules and computations. Therefore, though highly effective, these machines are confined to performing repeatable tasks. A great deal more programming language will be needed to make them more able to learn and adapt.
To solve complex problems, several different computational techniques are being used. One of the most prevalent methods — and the one used in Google's AlphaGo — has been advanced neural networks (ANNs) modeled after the human brain. This success is partly thanks to Google Brain, a network of 16,000 computers with some 100 billion connections. Unlimited access to Google's cloud computing allows users to obtain programming without hosting the network's computing capacity on their individual devices. While ANNs have a range of applications, particularly in AI, they are far from being truly "intelligent" and currently require substantial investment to operate.
Whichever country leads in these developments will reap the rewards on the world stage as logistics, labor, manufacturing and service sectors change — and with them, the global economy.